html_url
stringlengths 48
51
| title
stringlengths 5
268
| comments
stringlengths 70
51.8k
| body
stringlengths 0
29.8k
| comment_length
int64 16
1.52k
| text
stringlengths 164
54.1k
| embeddings
sequence |
---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/228 | Not able to access the XNLI dataset | Thanks for reporting this bug !
As it seems to be just a cache problem, I closed your PR.
I think we might just need to clear and reload the `xnli` cache @srush ? | When I try to access the XNLI dataset, I get the following error. The option of plain_text get selected automatically and then I get the following error.
```
FileNotFoundError: [Errno 2] No such file or directory: '/home/sasha/.cache/huggingface/datasets/xnli/plain_text/1.0.0/dataset_info.json'
Traceback:
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
exec(code, module.__dict__)
File "/home/sasha/nlp_viewer/run.py", line 86, in <module>
dts, fail = get(str(option.id), str(conf_option.name) if conf_option else None)
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/caching.py", line 591, in wrapped_func
return get_or_create_cached_value()
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/caching.py", line 575, in get_or_create_cached_value
return_value = func(*args, **kwargs)
File "/home/sasha/nlp_viewer/run.py", line 72, in get
builder_instance = builder_cls(name=conf)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/builder.py", line 610, in __init__
super(GeneratorBasedBuilder, self).__init__(*args, **kwargs)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/builder.py", line 152, in __init__
self.info = DatasetInfo.from_directory(self._cache_dir)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/info.py", line 157, in from_directory
with open(os.path.join(dataset_info_dir, DATASET_INFO_FILENAME), "r") as f:
```
Is it possible to see if the dataset_info.json is correctly placed? | 34 | Not able to access the XNLI dataset
When I try to access the XNLI dataset, I get the following error. The option of plain_text get selected automatically and then I get the following error.
```
FileNotFoundError: [Errno 2] No such file or directory: '/home/sasha/.cache/huggingface/datasets/xnli/plain_text/1.0.0/dataset_info.json'
Traceback:
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
exec(code, module.__dict__)
File "/home/sasha/nlp_viewer/run.py", line 86, in <module>
dts, fail = get(str(option.id), str(conf_option.name) if conf_option else None)
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/caching.py", line 591, in wrapped_func
return get_or_create_cached_value()
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/caching.py", line 575, in get_or_create_cached_value
return_value = func(*args, **kwargs)
File "/home/sasha/nlp_viewer/run.py", line 72, in get
builder_instance = builder_cls(name=conf)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/builder.py", line 610, in __init__
super(GeneratorBasedBuilder, self).__init__(*args, **kwargs)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/builder.py", line 152, in __init__
self.info = DatasetInfo.from_directory(self._cache_dir)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/info.py", line 157, in from_directory
with open(os.path.join(dataset_info_dir, DATASET_INFO_FILENAME), "r") as f:
```
Is it possible to see if the dataset_info.json is correctly placed?
Thanks for reporting this bug !
As it seems to be just a cache problem, I closed your PR.
I think we might just need to clear and reload the `xnli` cache @srush ? | [
-0.1408686488866806,
-0.18925881385803223,
-0.03353646397590637,
0.4693673253059387,
0.40544581413269043,
0.11200030893087387,
0.056036077439785004,
0.35449865460395813,
-0.10948893427848816,
0.2927756607532501,
-0.14041008055210114,
0.16212110221385956,
0.05022745206952095,
-0.02804567478597164,
0.05054093897342682,
-0.03532540053129196,
-0.169126957654953,
0.15102019906044006,
0.1320728361606598,
0.005323596298694611,
-0.1707707643508911,
0.045582592487335205,
-0.26906365156173706,
0.25874191522598267,
-0.28670650720596313,
-0.08528319746255875,
0.0914461761713028,
0.38597795367240906,
-0.30817025899887085,
-0.5349300503730774,
0.045082367956638336,
-0.14433495700359344,
0.24077430367469788,
0.19576658308506012,
-0.0001110580051317811,
0.04933277517557144,
0.26291391253471375,
-0.0573488250374794,
-0.5286889672279358,
-0.14541836082935333,
-0.3568848669528961,
-0.12314407527446747,
-0.014699378982186317,
-0.3132312595844269,
-0.1287817358970642,
-0.22096048295497894,
0.40224409103393555,
-0.3689234256744385,
0.2718048691749573,
0.31527629494667053,
0.20390821993350983,
0.20004351437091827,
0.12182684242725372,
-0.05471378192305565,
0.04933743178844452,
0.13519372045993805,
-0.1314477175474167,
-0.013969961553812027,
0.23928481340408325,
0.1932622492313385,
0.16366678476333618,
0.45788297057151794,
-0.1711953580379486,
-0.11164624989032745,
0.25520727038383484,
0.243842214345932,
-0.030298396944999695,
-0.16049769520759583,
0.32099449634552,
0.23313367366790771,
0.4437568187713623,
-0.4332887530326843,
-0.43349897861480713,
-0.11148454993963242,
-0.0038183475844562054,
-0.26497241854667664,
0.24886426329612732,
0.10019523650407791,
-0.31770798563957214,
0.15545983612537384,
-0.11993886530399323,
-0.36654940247535706,
-0.36813732981681824,
0.1454017460346222,
0.2627983093261719,
0.3802306354045868,
-0.059689246118068695,
0.06708643585443497,
-0.061199504882097244,
-0.19583767652511597,
0.05281435325741768,
-0.08949437737464905,
-0.16413260996341705,
0.3026691973209381,
-0.22698481380939484,
0.12764689326286316,
0.13528817892074585,
0.05715329945087433,
0.11984620243310928,
0.36280232667922974,
0.2032434493303299,
-0.1840134859085083,
-0.37553951144218445,
0.0625774934887886,
-0.2645849287509918,
0.4228106737136841,
0.2957010865211487,
0.14088551700115204,
0.38271546363830566,
-0.008944224566221237,
0.2218949794769287,
-0.36490070819854736,
-0.2945745587348938,
-0.16017666459083557,
-0.11438265442848206,
0.2509685754776001,
0.3615801930427551,
-0.1595371812582016,
-0.2476469874382019,
-0.0595758855342865,
-0.1263955533504486,
0.01934809982776642,
0.20292793214321136,
0.564559280872345,
0.05364493280649185,
0.18948319554328918,
0.03513288497924805,
0.3217781186103821,
0.05370338261127472,
-0.5332468748092651,
-0.17430879175662994,
0.21654155850410461,
-0.3087959587574005,
0.14569512009620667,
0.3105257749557495,
-0.33132481575012207,
0.30016353726387024,
-0.11575452983379364,
-0.3032854199409485,
0.003235284239053726,
0.12947288155555725,
-0.17491813004016876,
0.1020323857665062,
0.07796085625886917,
0.09318621456623077,
0.10305051505565643,
0.19042691588401794,
-0.07996858656406403,
0.06550367921590805,
-0.03327682614326477,
-0.0471925213932991,
-0.4852258861064911,
0.025506744161248207,
0.1306857317686081,
0.07165280729532242,
-0.009505707770586014,
-0.08786729723215103,
-0.05430324003100395,
0.19623038172721863,
-0.22172144055366516,
-0.11173627525568008,
0.11289937049150467,
-0.02556486427783966,
-0.27134576439857483,
0.21264249086380005,
0.5540770292282104,
-0.3136104345321655,
0.20926660299301147,
-0.19852595031261444,
-0.13489246368408203,
0.16316398978233337,
0.3628429174423218,
-0.11672976613044739,
0.07758884876966476,
-0.3848821818828583,
0.32663196325302124,
0.6447769403457642,
-0.5202509164810181,
-0.5076894164085388,
0.2816503047943115,
-0.22235773503780365,
-0.07156785577535629,
0.5067175030708313,
0.24071186780929565,
-0.06453140825033188,
-0.11318308115005493,
0.047000452876091,
0.11700893193483353,
0.04672098159790039,
-0.08850011229515076,
-0.11148910969495773,
-0.2450886219739914,
0.34023767709732056,
0.11302006244659424,
-0.030680183321237564,
0.132091224193573,
-0.029109269380569458,
0.16131937503814697,
0.3716829717159271,
-0.29108256101608276,
0.15118561685085297,
0.28406065702438354,
0.30056604743003845,
0.03720933198928833,
-0.14257794618606567,
-0.11960314959287643,
-0.2946610152721405,
0.23998597264289856,
-0.09203151613473892,
-0.020116493105888367,
-0.3088812828063965,
0.00025285035371780396,
-0.11309009790420532,
-0.04091973975300789,
-0.3876267373561859,
-0.2783125340938568,
0.19049659371376038,
0.4527055025100708,
0.22734439373016357,
-0.019652556627988815,
-0.2899417579174042,
0.3173922300338745,
-0.4826750159263611,
0.0027163736522197723,
-0.6354678273200989,
0.12806381285190582,
-0.09318923950195312,
-0.14903524518013,
-0.16396383941173553,
0.16392536461353302,
0.023550454527139664,
-0.002848624950274825,
-0.09274837374687195,
0.2124704122543335,
-0.2380763739347458,
0.08131269365549088,
0.26387062668800354,
0.10236126184463501,
0.03820338845252991,
-0.5709119439125061,
0.3375822603702545,
0.4717596769332886,
0.22842147946357727,
0.08941132575273514,
-0.2693713903427124,
0.11830680072307587,
-0.08254849910736084,
0.09030067175626755,
0.043727852404117584,
0.01720271445810795,
0.4666250944137573,
0.014810655266046524,
0.06998185068368912,
-0.21279391646385193,
0.3003252446651459,
0.21648988127708435,
0.46217799186706543,
-0.08612561970949173,
-0.5364863872528076,
0.086130291223526,
0.2796008586883545,
0.06051979586482048,
-0.09864357858896255,
-0.010936349630355835,
-0.35100460052490234,
-0.04163479432463646,
0.0550631582736969,
0.22897912561893463,
0.28139108419418335,
0.2278088480234146,
-0.06535398960113525,
0.08311121165752411,
0.09837377071380615,
-0.26217979192733765,
0.18072940409183502,
-0.25792741775512695,
0.10123033076524734,
0.269871324300766,
0.19980132579803467,
0.032053712755441666,
-0.03564509004354477,
-0.5033626556396484,
0.07217030227184296,
0.4454902410507202,
-0.27034348249435425,
-0.17282292246818542,
-0.1369045525789261,
-0.6854813694953918,
0.06065024435520172,
0.07638534903526306,
-0.11054055392742157,
-0.34322434663772583,
-0.02222895622253418,
0.18776102364063263,
0.2145620882511139,
-0.07199481129646301,
-0.09505246579647064,
0.07554078102111816,
0.06864779442548752,
-0.10940844565629959,
-0.41933244466781616,
-0.31495964527130127,
-0.20777547359466553,
0.04685630276799202,
0.2707954943180084,
-0.022806549444794655,
0.24694311618804932,
-0.2802799940109253,
0.0639284998178482,
-0.41443806886672974,
-0.025489725172519684,
0.0234772227704525,
0.029297329485416412,
-0.00047362223267555237,
-0.034068748354911804,
0.48188817501068115,
0.4775170087814331,
-0.062324706465005875,
0.3475897014141083,
0.0415470227599144,
-0.17423024773597717,
0.2578030526638031,
-0.21523967385292053,
-0.23448698222637177,
-0.04180895537137985,
-0.5249141454696655,
-0.35637030005455017,
-0.32827454805374146,
0.08275279402732849,
-0.13988062739372253,
0.0803992748260498,
0.318090558052063,
-0.14647728204727173,
0.2062612771987915,
-0.038883764296770096,
0.19586814939975739,
-0.07545912265777588,
-0.22561395168304443,
0.3382496237754822,
-0.16139717400074005,
-0.21599532663822174,
0.23609322309494019,
0.06490501016378403,
0.2100887894630432,
-0.04124322906136513,
-0.23060056567192078,
0.1721261888742447,
-0.22556985914707184,
0.28446367383003235,
-0.13050413131713867,
-0.15192082524299622,
0.34998250007629395,
-0.010504120960831642,
-0.0014594737440347672,
0.004380516707897186,
0.011881504207849503,
0.11780828982591629,
0.010026469826698303,
0.5716208815574646,
0.20394280552864075,
0.41344475746154785,
0.14451958239078522,
0.37235599756240845,
0.44866451621055603,
0.02675904519855976,
0.32839086651802063,
-0.262139230966568,
0.06690724194049835,
-0.0658818855881691,
-0.3156571686267853,
0.11945406347513199,
0.17475613951683044,
-0.17332357168197632,
-0.10797254741191864,
0.13868209719657898,
0.3889438211917877,
-0.33151957392692566,
-0.13302285969257355,
-0.28740715980529785,
-0.08548354357481003,
-0.1463780254125595,
0.020249327644705772,
0.011118672788143158,
0.12911128997802734,
0.20937472581863403,
-0.34255439043045044,
-0.3424656093120575,
-0.11213222146034241,
0.4633781313896179,
0.002335883677005768,
0.15231482684612274,
-0.27443593740463257,
-0.28418031334877014,
-0.5618230700492859,
0.4806254506111145,
0.1180061548948288,
0.21206675469875336,
-0.27588602900505066,
0.12500113248825073,
0.26634669303894043,
0.022575749084353447,
0.32832586765289307,
-0.3004830777645111,
0.2563643455505371,
0.08078660070896149,
-0.09892930090427399,
-0.23587936162948608,
0.1696384996175766,
-0.1501612663269043,
0.19850066304206848,
0.33587101101875305,
0.19395439326763153,
-0.16084104776382446,
-0.11107290536165237,
-0.016944006085395813,
0.10838137567043304,
-0.17496953904628754,
-0.2175944596529007,
-0.017784323543310165,
-0.0037048086524009705,
-0.1634150892496109,
-0.32848215103149414,
-0.1715681403875351,
0.2472757250070572,
0.13296085596084595,
0.335891455411911,
0.04687159135937691,
-0.07427210360765457,
0.17847181856632233,
0.22041521966457367,
0.3392874002456665,
-0.0961354672908783,
-0.15330930054187775,
0.16526304185390472,
0.2498362809419632,
0.07175793498754501,
0.49867454171180725,
0.28984537720680237,
-0.36226436495780945,
-0.014101285487413406,
-0.22840815782546997,
0.12723538279533386,
0.29033511877059937,
-0.2587491273880005,
0.10405394434928894,
0.03436683118343353,
-0.007826589047908783,
0.061695680022239685,
-0.09590508788824081,
0.2513183355331421,
0.031543757766485214,
-0.12594200670719147,
-0.398691326379776,
0.32729804515838623,
0.1011691689491272,
0.003973290324211121,
0.45400190353393555,
-0.14631932973861694,
-0.22761747241020203,
0.023735394701361656,
0.05723189190030098,
0.9369779825210571,
0.12992817163467407,
0.22923724353313446,
0.3930836021900177,
0.16831237077713013,
0.5259998440742493,
-0.3035131096839905,
0.3688012957572937,
-0.3871549367904663,
-0.08039584755897522,
-0.002947915345430374,
-0.11370426416397095,
-0.011663682758808136,
-0.1774902492761612,
-0.0803154706954956,
0.23407773673534393,
-0.15633408725261688,
0.006111137568950653,
-0.09859137237071991,
0.26289814710617065,
-0.33494704961776733,
-0.09046958386898041,
-0.46061474084854126,
0.08475244790315628,
-0.20800413191318512,
0.334980309009552,
-0.10503844916820526,
-0.1498464196920395,
-0.385303258895874,
0.1126156598329544,
-0.420208215713501,
0.3758964240550995,
-0.08597476780414581,
0.12252435088157654,
-0.07361695170402527,
-0.3276987671852112,
-0.05533352494239807,
0.6137100458145142,
0.5807362198829651,
0.05012687295675278,
-0.3391721248626709,
0.007756650447845459,
-0.2113005518913269,
-0.023091383278369904,
-0.0938933789730072,
0.15532897412776947,
0.33820483088493347,
-0.04085526615381241,
-0.30917805433273315,
0.5142857432365417,
-0.11258649826049805,
0.01624208688735962,
-0.23662205040454865,
-0.25668203830718994,
-0.24029575288295746,
-0.04322406277060509,
-0.12301504611968994,
0.01992608606815338,
-0.12974657118320465,
0.025179501622915268,
0.09975022077560425,
0.012665413320064545,
-0.23290427029132843,
-0.24648424983024597,
-0.13393037021160126,
-0.1444866955280304,
0.18300418555736542,
0.32538139820098877,
0.047446150332689285,
0.1761953979730606,
0.6140016317367554,
0.22167591750621796,
-0.050169289112091064,
-0.24814751744270325,
0.06540375202894211,
0.15567605197429657,
-0.25567328929901123,
-0.2123810350894928,
0.10414337366819382,
0.1746923178434372,
0.09654483944177628,
0.27749502658843994,
0.1864689290523529,
-0.006256610155105591,
-0.14283424615859985,
-0.4487021267414093,
-0.542247474193573,
0.1517488956451416,
-0.19254685938358307,
0.13901546597480774,
-0.1516934037208557,
0.2596281170845032,
0.11874733865261078,
-0.26524898409843445,
-0.33702796697616577,
-0.09570232778787613,
-0.323411762714386,
-0.005745381116867065,
0.39344823360443115,
0.059053368866443634,
0.196878120303154,
0.043673038482666016,
0.1371064931154251,
-0.03669913858175278,
-0.2849010229110718,
-0.15982764959335327,
0.04887765273451805,
0.10002413392066956,
0.13717149198055267,
-0.40278685092926025,
-0.11658169329166412,
-0.28826242685317993,
-0.08812689781188965,
-0.16044285893440247,
0.05028693005442619,
0.29853391647338867,
0.03162441775202751,
0.2532195746898651,
-0.31334492564201355,
0.05800839141011238,
-0.21368736028671265,
0.15737824141979218,
-0.1528380811214447,
0.1841050684452057,
0.05986042693257332,
0.12613007426261902,
0.017675742506980896,
0.009883783757686615,
-0.5507248044013977,
-0.06257525831460953,
-0.090798020362854,
0.18297600746154785,
0.1152569130063057,
-0.4182227849960327,
0.22805601358413696,
-0.14199551939964294,
0.17141956090927124,
0.1962626576423645,
-0.03331763669848442,
0.2832372188568115,
0.181142657995224,
0.18628524243831635,
-0.23866689205169678,
0.20860789716243744,
0.21577955782413483,
0.09463845193386078,
-0.09388956427574158,
0.04307936131954193,
-0.04945437237620354,
-0.02566228061914444,
0.26920613646507263,
-0.10244958102703094,
0.3867933452129364,
-0.40722113847732544,
-0.05248976871371269,
0.1194659024477005,
0.0713922530412674,
-0.05252337083220482,
0.11530591547489166,
0.3662636876106262,
0.16459202766418457,
0.782757043838501,
-0.24703267216682434,
0.14657151699066162,
-0.18498504161834717,
0.32810965180397034,
-0.2487824261188507,
-0.33459770679473877,
-0.3359786868095398,
0.11348118633031845,
-0.29427021741867065,
-0.1261742115020752,
-0.1852845549583435,
0.29954174160957336,
-0.1018143743276596,
0.14273476600646973,
-0.23577992618083954,
0.3921544551849365,
-0.148835688829422,
-0.04539507254958153,
-0.5625843405723572,
-0.22663289308547974,
0.10585501790046692,
-0.17970573902130127,
0.025090841576457024,
0.015994630753993988,
-0.009149357676506042,
0.13094379007816315,
-0.2652379870414734,
-0.40185344219207764,
0.30937230587005615,
0.40477633476257324,
-0.016356661915779114,
-0.27932941913604736,
0.41067442297935486,
0.2905891239643097,
0.0659504160284996,
0.20533022284507751,
0.31929323077201843,
0.4276030361652374,
0.4022083282470703,
0.0665070116519928,
0.20000682771205902,
-0.10693976283073425,
-0.25286224484443665,
-0.013881783932447433,
0.052523091435432434,
0.3014645278453827,
0.05845613032579422,
0.31253066658973694,
0.14970752596855164,
-0.006234737113118172,
0.14302192628383636,
0.04569154232740402,
0.3462030589580536,
0.09222429990768433,
-0.01502034068107605,
-0.1465473622083664,
-0.24552851915359497,
-0.18946360051631927,
-0.12856656312942505,
-0.558147132396698,
0.13780371844768524,
0.21281994879245758,
0.2150428146123886,
0.2549576759338379,
-0.0042096273973584175,
0.049009568989276886,
-0.06657010316848755,
0.13284362852573395,
0.5250779986381531,
-0.0340118333697319,
-0.27033567428588867,
-0.32096928358078003,
-0.5026277303695679,
0.16537794470787048,
-0.025284145027399063,
-0.4208657443523407,
-0.24853581190109253,
0.12115363776683807,
-0.1755252182483673,
-0.23555682599544525,
0.2410193681716919,
0.101404570043087,
0.06959471106529236,
0.3392389118671417,
-0.22689945995807648,
-0.33274638652801514,
0.26964038610458374,
0.05312708020210266,
-0.1709013134241104,
-0.17286834120750427,
-0.09464499354362488,
-0.14867743849754333,
0.04900039732456207,
-0.046039119362831116,
0.3904174566268921,
0.00711417943239212,
0.2057296186685562,
0.19779503345489502,
0.19981157779693604,
0.48119598627090454,
0.0680660530924797,
-0.04043828696012497,
-0.3731038272380829,
-0.1117364838719368,
-0.20125921070575714,
-0.041572049260139465,
0.3111209571361542,
0.5081038475036621,
-0.3583824038505554,
-0.00834466889500618,
-0.3815689980983734,
0.12782993912696838,
-0.1665935218334198,
-0.017484026029706,
-0.2955934703350067,
0.3703538477420807,
-0.2835766077041626,
0.2372780591249466,
0.16417348384857178,
-0.045550912618637085,
-0.029033198952674866,
0.10304367542266846,
-0.33316755294799805,
0.003624744713306427,
0.5232219696044922,
-0.21019817888736725,
-0.23654082417488098,
0.09007922559976578,
0.1933175027370453,
0.11350397765636444,
0.010346682742238045,
-0.33786875009536743,
0.17566832900047302,
0.18242181837558746,
-0.005352132022380829,
-0.24062027037143707,
-0.0816912055015564,
0.0652153268456459,
0.11355289816856384,
-0.06532711535692215,
-0.14270718395709991,
0.15939897298812866,
-0.07285131514072418,
-0.013610651716589928,
-0.08653853833675385
] |
https://github.com/huggingface/datasets/issues/228 | Not able to access the XNLI dataset | Update: The dataset_info.json error is gone, but we have a new one instead:
```
ConnectionError: Couldn't reach https://www.nyu.edu/projects/bowman/xnli/XNLI-1.0.zip
```
I am not able to reproduce on my side unfortunately. Any idea @srush ? | When I try to access the XNLI dataset, I get the following error. The option of plain_text get selected automatically and then I get the following error.
```
FileNotFoundError: [Errno 2] No such file or directory: '/home/sasha/.cache/huggingface/datasets/xnli/plain_text/1.0.0/dataset_info.json'
Traceback:
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
exec(code, module.__dict__)
File "/home/sasha/nlp_viewer/run.py", line 86, in <module>
dts, fail = get(str(option.id), str(conf_option.name) if conf_option else None)
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/caching.py", line 591, in wrapped_func
return get_or_create_cached_value()
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/caching.py", line 575, in get_or_create_cached_value
return_value = func(*args, **kwargs)
File "/home/sasha/nlp_viewer/run.py", line 72, in get
builder_instance = builder_cls(name=conf)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/builder.py", line 610, in __init__
super(GeneratorBasedBuilder, self).__init__(*args, **kwargs)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/builder.py", line 152, in __init__
self.info = DatasetInfo.from_directory(self._cache_dir)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/info.py", line 157, in from_directory
with open(os.path.join(dataset_info_dir, DATASET_INFO_FILENAME), "r") as f:
```
Is it possible to see if the dataset_info.json is correctly placed? | 33 | Not able to access the XNLI dataset
When I try to access the XNLI dataset, I get the following error. The option of plain_text get selected automatically and then I get the following error.
```
FileNotFoundError: [Errno 2] No such file or directory: '/home/sasha/.cache/huggingface/datasets/xnli/plain_text/1.0.0/dataset_info.json'
Traceback:
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
exec(code, module.__dict__)
File "/home/sasha/nlp_viewer/run.py", line 86, in <module>
dts, fail = get(str(option.id), str(conf_option.name) if conf_option else None)
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/caching.py", line 591, in wrapped_func
return get_or_create_cached_value()
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/caching.py", line 575, in get_or_create_cached_value
return_value = func(*args, **kwargs)
File "/home/sasha/nlp_viewer/run.py", line 72, in get
builder_instance = builder_cls(name=conf)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/builder.py", line 610, in __init__
super(GeneratorBasedBuilder, self).__init__(*args, **kwargs)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/builder.py", line 152, in __init__
self.info = DatasetInfo.from_directory(self._cache_dir)
File "/home/sasha/.local/lib/python3.7/site-packages/nlp/info.py", line 157, in from_directory
with open(os.path.join(dataset_info_dir, DATASET_INFO_FILENAME), "r") as f:
```
Is it possible to see if the dataset_info.json is correctly placed?
Update: The dataset_info.json error is gone, but we have a new one instead:
```
ConnectionError: Couldn't reach https://www.nyu.edu/projects/bowman/xnli/XNLI-1.0.zip
```
I am not able to reproduce on my side unfortunately. Any idea @srush ? | [
-0.1408686488866806,
-0.18925881385803223,
-0.03353646397590637,
0.4693673253059387,
0.40544581413269043,
0.11200030893087387,
0.056036077439785004,
0.35449865460395813,
-0.10948893427848816,
0.2927756607532501,
-0.14041008055210114,
0.16212110221385956,
0.05022745206952095,
-0.02804567478597164,
0.05054093897342682,
-0.03532540053129196,
-0.169126957654953,
0.15102019906044006,
0.1320728361606598,
0.005323596298694611,
-0.1707707643508911,
0.045582592487335205,
-0.26906365156173706,
0.25874191522598267,
-0.28670650720596313,
-0.08528319746255875,
0.0914461761713028,
0.38597795367240906,
-0.30817025899887085,
-0.5349300503730774,
0.045082367956638336,
-0.14433495700359344,
0.24077430367469788,
0.19576658308506012,
-0.0001110580051317811,
0.04933277517557144,
0.26291391253471375,
-0.0573488250374794,
-0.5286889672279358,
-0.14541836082935333,
-0.3568848669528961,
-0.12314407527446747,
-0.014699378982186317,
-0.3132312595844269,
-0.1287817358970642,
-0.22096048295497894,
0.40224409103393555,
-0.3689234256744385,
0.2718048691749573,
0.31527629494667053,
0.20390821993350983,
0.20004351437091827,
0.12182684242725372,
-0.05471378192305565,
0.04933743178844452,
0.13519372045993805,
-0.1314477175474167,
-0.013969961553812027,
0.23928481340408325,
0.1932622492313385,
0.16366678476333618,
0.45788297057151794,
-0.1711953580379486,
-0.11164624989032745,
0.25520727038383484,
0.243842214345932,
-0.030298396944999695,
-0.16049769520759583,
0.32099449634552,
0.23313367366790771,
0.4437568187713623,
-0.4332887530326843,
-0.43349897861480713,
-0.11148454993963242,
-0.0038183475844562054,
-0.26497241854667664,
0.24886426329612732,
0.10019523650407791,
-0.31770798563957214,
0.15545983612537384,
-0.11993886530399323,
-0.36654940247535706,
-0.36813732981681824,
0.1454017460346222,
0.2627983093261719,
0.3802306354045868,
-0.059689246118068695,
0.06708643585443497,
-0.061199504882097244,
-0.19583767652511597,
0.05281435325741768,
-0.08949437737464905,
-0.16413260996341705,
0.3026691973209381,
-0.22698481380939484,
0.12764689326286316,
0.13528817892074585,
0.05715329945087433,
0.11984620243310928,
0.36280232667922974,
0.2032434493303299,
-0.1840134859085083,
-0.37553951144218445,
0.0625774934887886,
-0.2645849287509918,
0.4228106737136841,
0.2957010865211487,
0.14088551700115204,
0.38271546363830566,
-0.008944224566221237,
0.2218949794769287,
-0.36490070819854736,
-0.2945745587348938,
-0.16017666459083557,
-0.11438265442848206,
0.2509685754776001,
0.3615801930427551,
-0.1595371812582016,
-0.2476469874382019,
-0.0595758855342865,
-0.1263955533504486,
0.01934809982776642,
0.20292793214321136,
0.564559280872345,
0.05364493280649185,
0.18948319554328918,
0.03513288497924805,
0.3217781186103821,
0.05370338261127472,
-0.5332468748092651,
-0.17430879175662994,
0.21654155850410461,
-0.3087959587574005,
0.14569512009620667,
0.3105257749557495,
-0.33132481575012207,
0.30016353726387024,
-0.11575452983379364,
-0.3032854199409485,
0.003235284239053726,
0.12947288155555725,
-0.17491813004016876,
0.1020323857665062,
0.07796085625886917,
0.09318621456623077,
0.10305051505565643,
0.19042691588401794,
-0.07996858656406403,
0.06550367921590805,
-0.03327682614326477,
-0.0471925213932991,
-0.4852258861064911,
0.025506744161248207,
0.1306857317686081,
0.07165280729532242,
-0.009505707770586014,
-0.08786729723215103,
-0.05430324003100395,
0.19623038172721863,
-0.22172144055366516,
-0.11173627525568008,
0.11289937049150467,
-0.02556486427783966,
-0.27134576439857483,
0.21264249086380005,
0.5540770292282104,
-0.3136104345321655,
0.20926660299301147,
-0.19852595031261444,
-0.13489246368408203,
0.16316398978233337,
0.3628429174423218,
-0.11672976613044739,
0.07758884876966476,
-0.3848821818828583,
0.32663196325302124,
0.6447769403457642,
-0.5202509164810181,
-0.5076894164085388,
0.2816503047943115,
-0.22235773503780365,
-0.07156785577535629,
0.5067175030708313,
0.24071186780929565,
-0.06453140825033188,
-0.11318308115005493,
0.047000452876091,
0.11700893193483353,
0.04672098159790039,
-0.08850011229515076,
-0.11148910969495773,
-0.2450886219739914,
0.34023767709732056,
0.11302006244659424,
-0.030680183321237564,
0.132091224193573,
-0.029109269380569458,
0.16131937503814697,
0.3716829717159271,
-0.29108256101608276,
0.15118561685085297,
0.28406065702438354,
0.30056604743003845,
0.03720933198928833,
-0.14257794618606567,
-0.11960314959287643,
-0.2946610152721405,
0.23998597264289856,
-0.09203151613473892,
-0.020116493105888367,
-0.3088812828063965,
0.00025285035371780396,
-0.11309009790420532,
-0.04091973975300789,
-0.3876267373561859,
-0.2783125340938568,
0.19049659371376038,
0.4527055025100708,
0.22734439373016357,
-0.019652556627988815,
-0.2899417579174042,
0.3173922300338745,
-0.4826750159263611,
0.0027163736522197723,
-0.6354678273200989,
0.12806381285190582,
-0.09318923950195312,
-0.14903524518013,
-0.16396383941173553,
0.16392536461353302,
0.023550454527139664,
-0.002848624950274825,
-0.09274837374687195,
0.2124704122543335,
-0.2380763739347458,
0.08131269365549088,
0.26387062668800354,
0.10236126184463501,
0.03820338845252991,
-0.5709119439125061,
0.3375822603702545,
0.4717596769332886,
0.22842147946357727,
0.08941132575273514,
-0.2693713903427124,
0.11830680072307587,
-0.08254849910736084,
0.09030067175626755,
0.043727852404117584,
0.01720271445810795,
0.4666250944137573,
0.014810655266046524,
0.06998185068368912,
-0.21279391646385193,
0.3003252446651459,
0.21648988127708435,
0.46217799186706543,
-0.08612561970949173,
-0.5364863872528076,
0.086130291223526,
0.2796008586883545,
0.06051979586482048,
-0.09864357858896255,
-0.010936349630355835,
-0.35100460052490234,
-0.04163479432463646,
0.0550631582736969,
0.22897912561893463,
0.28139108419418335,
0.2278088480234146,
-0.06535398960113525,
0.08311121165752411,
0.09837377071380615,
-0.26217979192733765,
0.18072940409183502,
-0.25792741775512695,
0.10123033076524734,
0.269871324300766,
0.19980132579803467,
0.032053712755441666,
-0.03564509004354477,
-0.5033626556396484,
0.07217030227184296,
0.4454902410507202,
-0.27034348249435425,
-0.17282292246818542,
-0.1369045525789261,
-0.6854813694953918,
0.06065024435520172,
0.07638534903526306,
-0.11054055392742157,
-0.34322434663772583,
-0.02222895622253418,
0.18776102364063263,
0.2145620882511139,
-0.07199481129646301,
-0.09505246579647064,
0.07554078102111816,
0.06864779442548752,
-0.10940844565629959,
-0.41933244466781616,
-0.31495964527130127,
-0.20777547359466553,
0.04685630276799202,
0.2707954943180084,
-0.022806549444794655,
0.24694311618804932,
-0.2802799940109253,
0.0639284998178482,
-0.41443806886672974,
-0.025489725172519684,
0.0234772227704525,
0.029297329485416412,
-0.00047362223267555237,
-0.034068748354911804,
0.48188817501068115,
0.4775170087814331,
-0.062324706465005875,
0.3475897014141083,
0.0415470227599144,
-0.17423024773597717,
0.2578030526638031,
-0.21523967385292053,
-0.23448698222637177,
-0.04180895537137985,
-0.5249141454696655,
-0.35637030005455017,
-0.32827454805374146,
0.08275279402732849,
-0.13988062739372253,
0.0803992748260498,
0.318090558052063,
-0.14647728204727173,
0.2062612771987915,
-0.038883764296770096,
0.19586814939975739,
-0.07545912265777588,
-0.22561395168304443,
0.3382496237754822,
-0.16139717400074005,
-0.21599532663822174,
0.23609322309494019,
0.06490501016378403,
0.2100887894630432,
-0.04124322906136513,
-0.23060056567192078,
0.1721261888742447,
-0.22556985914707184,
0.28446367383003235,
-0.13050413131713867,
-0.15192082524299622,
0.34998250007629395,
-0.010504120960831642,
-0.0014594737440347672,
0.004380516707897186,
0.011881504207849503,
0.11780828982591629,
0.010026469826698303,
0.5716208815574646,
0.20394280552864075,
0.41344475746154785,
0.14451958239078522,
0.37235599756240845,
0.44866451621055603,
0.02675904519855976,
0.32839086651802063,
-0.262139230966568,
0.06690724194049835,
-0.0658818855881691,
-0.3156571686267853,
0.11945406347513199,
0.17475613951683044,
-0.17332357168197632,
-0.10797254741191864,
0.13868209719657898,
0.3889438211917877,
-0.33151957392692566,
-0.13302285969257355,
-0.28740715980529785,
-0.08548354357481003,
-0.1463780254125595,
0.020249327644705772,
0.011118672788143158,
0.12911128997802734,
0.20937472581863403,
-0.34255439043045044,
-0.3424656093120575,
-0.11213222146034241,
0.4633781313896179,
0.002335883677005768,
0.15231482684612274,
-0.27443593740463257,
-0.28418031334877014,
-0.5618230700492859,
0.4806254506111145,
0.1180061548948288,
0.21206675469875336,
-0.27588602900505066,
0.12500113248825073,
0.26634669303894043,
0.022575749084353447,
0.32832586765289307,
-0.3004830777645111,
0.2563643455505371,
0.08078660070896149,
-0.09892930090427399,
-0.23587936162948608,
0.1696384996175766,
-0.1501612663269043,
0.19850066304206848,
0.33587101101875305,
0.19395439326763153,
-0.16084104776382446,
-0.11107290536165237,
-0.016944006085395813,
0.10838137567043304,
-0.17496953904628754,
-0.2175944596529007,
-0.017784323543310165,
-0.0037048086524009705,
-0.1634150892496109,
-0.32848215103149414,
-0.1715681403875351,
0.2472757250070572,
0.13296085596084595,
0.335891455411911,
0.04687159135937691,
-0.07427210360765457,
0.17847181856632233,
0.22041521966457367,
0.3392874002456665,
-0.0961354672908783,
-0.15330930054187775,
0.16526304185390472,
0.2498362809419632,
0.07175793498754501,
0.49867454171180725,
0.28984537720680237,
-0.36226436495780945,
-0.014101285487413406,
-0.22840815782546997,
0.12723538279533386,
0.29033511877059937,
-0.2587491273880005,
0.10405394434928894,
0.03436683118343353,
-0.007826589047908783,
0.061695680022239685,
-0.09590508788824081,
0.2513183355331421,
0.031543757766485214,
-0.12594200670719147,
-0.398691326379776,
0.32729804515838623,
0.1011691689491272,
0.003973290324211121,
0.45400190353393555,
-0.14631932973861694,
-0.22761747241020203,
0.023735394701361656,
0.05723189190030098,
0.9369779825210571,
0.12992817163467407,
0.22923724353313446,
0.3930836021900177,
0.16831237077713013,
0.5259998440742493,
-0.3035131096839905,
0.3688012957572937,
-0.3871549367904663,
-0.08039584755897522,
-0.002947915345430374,
-0.11370426416397095,
-0.011663682758808136,
-0.1774902492761612,
-0.0803154706954956,
0.23407773673534393,
-0.15633408725261688,
0.006111137568950653,
-0.09859137237071991,
0.26289814710617065,
-0.33494704961776733,
-0.09046958386898041,
-0.46061474084854126,
0.08475244790315628,
-0.20800413191318512,
0.334980309009552,
-0.10503844916820526,
-0.1498464196920395,
-0.385303258895874,
0.1126156598329544,
-0.420208215713501,
0.3758964240550995,
-0.08597476780414581,
0.12252435088157654,
-0.07361695170402527,
-0.3276987671852112,
-0.05533352494239807,
0.6137100458145142,
0.5807362198829651,
0.05012687295675278,
-0.3391721248626709,
0.007756650447845459,
-0.2113005518913269,
-0.023091383278369904,
-0.0938933789730072,
0.15532897412776947,
0.33820483088493347,
-0.04085526615381241,
-0.30917805433273315,
0.5142857432365417,
-0.11258649826049805,
0.01624208688735962,
-0.23662205040454865,
-0.25668203830718994,
-0.24029575288295746,
-0.04322406277060509,
-0.12301504611968994,
0.01992608606815338,
-0.12974657118320465,
0.025179501622915268,
0.09975022077560425,
0.012665413320064545,
-0.23290427029132843,
-0.24648424983024597,
-0.13393037021160126,
-0.1444866955280304,
0.18300418555736542,
0.32538139820098877,
0.047446150332689285,
0.1761953979730606,
0.6140016317367554,
0.22167591750621796,
-0.050169289112091064,
-0.24814751744270325,
0.06540375202894211,
0.15567605197429657,
-0.25567328929901123,
-0.2123810350894928,
0.10414337366819382,
0.1746923178434372,
0.09654483944177628,
0.27749502658843994,
0.1864689290523529,
-0.006256610155105591,
-0.14283424615859985,
-0.4487021267414093,
-0.542247474193573,
0.1517488956451416,
-0.19254685938358307,
0.13901546597480774,
-0.1516934037208557,
0.2596281170845032,
0.11874733865261078,
-0.26524898409843445,
-0.33702796697616577,
-0.09570232778787613,
-0.323411762714386,
-0.005745381116867065,
0.39344823360443115,
0.059053368866443634,
0.196878120303154,
0.043673038482666016,
0.1371064931154251,
-0.03669913858175278,
-0.2849010229110718,
-0.15982764959335327,
0.04887765273451805,
0.10002413392066956,
0.13717149198055267,
-0.40278685092926025,
-0.11658169329166412,
-0.28826242685317993,
-0.08812689781188965,
-0.16044285893440247,
0.05028693005442619,
0.29853391647338867,
0.03162441775202751,
0.2532195746898651,
-0.31334492564201355,
0.05800839141011238,
-0.21368736028671265,
0.15737824141979218,
-0.1528380811214447,
0.1841050684452057,
0.05986042693257332,
0.12613007426261902,
0.017675742506980896,
0.009883783757686615,
-0.5507248044013977,
-0.06257525831460953,
-0.090798020362854,
0.18297600746154785,
0.1152569130063057,
-0.4182227849960327,
0.22805601358413696,
-0.14199551939964294,
0.17141956090927124,
0.1962626576423645,
-0.03331763669848442,
0.2832372188568115,
0.181142657995224,
0.18628524243831635,
-0.23866689205169678,
0.20860789716243744,
0.21577955782413483,
0.09463845193386078,
-0.09388956427574158,
0.04307936131954193,
-0.04945437237620354,
-0.02566228061914444,
0.26920613646507263,
-0.10244958102703094,
0.3867933452129364,
-0.40722113847732544,
-0.05248976871371269,
0.1194659024477005,
0.0713922530412674,
-0.05252337083220482,
0.11530591547489166,
0.3662636876106262,
0.16459202766418457,
0.782757043838501,
-0.24703267216682434,
0.14657151699066162,
-0.18498504161834717,
0.32810965180397034,
-0.2487824261188507,
-0.33459770679473877,
-0.3359786868095398,
0.11348118633031845,
-0.29427021741867065,
-0.1261742115020752,
-0.1852845549583435,
0.29954174160957336,
-0.1018143743276596,
0.14273476600646973,
-0.23577992618083954,
0.3921544551849365,
-0.148835688829422,
-0.04539507254958153,
-0.5625843405723572,
-0.22663289308547974,
0.10585501790046692,
-0.17970573902130127,
0.025090841576457024,
0.015994630753993988,
-0.009149357676506042,
0.13094379007816315,
-0.2652379870414734,
-0.40185344219207764,
0.30937230587005615,
0.40477633476257324,
-0.016356661915779114,
-0.27932941913604736,
0.41067442297935486,
0.2905891239643097,
0.0659504160284996,
0.20533022284507751,
0.31929323077201843,
0.4276030361652374,
0.4022083282470703,
0.0665070116519928,
0.20000682771205902,
-0.10693976283073425,
-0.25286224484443665,
-0.013881783932447433,
0.052523091435432434,
0.3014645278453827,
0.05845613032579422,
0.31253066658973694,
0.14970752596855164,
-0.006234737113118172,
0.14302192628383636,
0.04569154232740402,
0.3462030589580536,
0.09222429990768433,
-0.01502034068107605,
-0.1465473622083664,
-0.24552851915359497,
-0.18946360051631927,
-0.12856656312942505,
-0.558147132396698,
0.13780371844768524,
0.21281994879245758,
0.2150428146123886,
0.2549576759338379,
-0.0042096273973584175,
0.049009568989276886,
-0.06657010316848755,
0.13284362852573395,
0.5250779986381531,
-0.0340118333697319,
-0.27033567428588867,
-0.32096928358078003,
-0.5026277303695679,
0.16537794470787048,
-0.025284145027399063,
-0.4208657443523407,
-0.24853581190109253,
0.12115363776683807,
-0.1755252182483673,
-0.23555682599544525,
0.2410193681716919,
0.101404570043087,
0.06959471106529236,
0.3392389118671417,
-0.22689945995807648,
-0.33274638652801514,
0.26964038610458374,
0.05312708020210266,
-0.1709013134241104,
-0.17286834120750427,
-0.09464499354362488,
-0.14867743849754333,
0.04900039732456207,
-0.046039119362831116,
0.3904174566268921,
0.00711417943239212,
0.2057296186685562,
0.19779503345489502,
0.19981157779693604,
0.48119598627090454,
0.0680660530924797,
-0.04043828696012497,
-0.3731038272380829,
-0.1117364838719368,
-0.20125921070575714,
-0.041572049260139465,
0.3111209571361542,
0.5081038475036621,
-0.3583824038505554,
-0.00834466889500618,
-0.3815689980983734,
0.12782993912696838,
-0.1665935218334198,
-0.017484026029706,
-0.2955934703350067,
0.3703538477420807,
-0.2835766077041626,
0.2372780591249466,
0.16417348384857178,
-0.045550912618637085,
-0.029033198952674866,
0.10304367542266846,
-0.33316755294799805,
0.003624744713306427,
0.5232219696044922,
-0.21019817888736725,
-0.23654082417488098,
0.09007922559976578,
0.1933175027370453,
0.11350397765636444,
0.010346682742238045,
-0.33786875009536743,
0.17566832900047302,
0.18242181837558746,
-0.005352132022380829,
-0.24062027037143707,
-0.0816912055015564,
0.0652153268456459,
0.11355289816856384,
-0.06532711535692215,
-0.14270718395709991,
0.15939897298812866,
-0.07285131514072418,
-0.013610651716589928,
-0.08653853833675385
] |
https://github.com/huggingface/datasets/issues/225 | [ROUGE] Different scores with `files2rouge` | @Colanim unfortunately there are different implementations of the ROUGE metric floating around online which yield different results, and we had to chose one for the package :) We ended up including the one from the google-research repository, which does minimal post-processing before computing the P/R/F scores. If I recall correctly, files2rouge relies on the Perl, script, which among other things normalizes all numbers to a special token: in the case you presented, this should account for a good chunk of the difference.
We may end up adding in more versions of the metric, but probably not for a while (@lhoestq correct me if I'm wrong). However, feel free to take a stab at adding it in yourself and submitting a PR if you're interested! | It seems that the ROUGE score of `nlp` is lower than the one of `files2rouge`.
Here is a self-contained notebook to reproduce both scores : https://colab.research.google.com/drive/14EyAXValB6UzKY9x4rs_T3pyL7alpw_F?usp=sharing
---
`nlp` : (Only mid F-scores)
>rouge1 0.33508031962733364
rouge2 0.14574333776191592
rougeL 0.2321187823256159
`files2rouge` :
>Running ROUGE...
===========================
1 ROUGE-1 Average_R: 0.48873 (95%-conf.int. 0.41192 - 0.56339)
1 ROUGE-1 Average_P: 0.29010 (95%-conf.int. 0.23605 - 0.34445)
1 ROUGE-1 Average_F: 0.34761 (95%-conf.int. 0.29479 - 0.39871)
===========================
1 ROUGE-2 Average_R: 0.20280 (95%-conf.int. 0.14969 - 0.26244)
1 ROUGE-2 Average_P: 0.12772 (95%-conf.int. 0.08603 - 0.17752)
1 ROUGE-2 Average_F: 0.14798 (95%-conf.int. 0.10517 - 0.19240)
===========================
1 ROUGE-L Average_R: 0.32960 (95%-conf.int. 0.26501 - 0.39676)
1 ROUGE-L Average_P: 0.19880 (95%-conf.int. 0.15257 - 0.25136)
1 ROUGE-L Average_F: 0.23619 (95%-conf.int. 0.19073 - 0.28663)
---
When using longer predictions/gold, the difference is bigger.
**How can I reproduce same score as `files2rouge` ?**
@lhoestq
| 124 | [ROUGE] Different scores with `files2rouge`
It seems that the ROUGE score of `nlp` is lower than the one of `files2rouge`.
Here is a self-contained notebook to reproduce both scores : https://colab.research.google.com/drive/14EyAXValB6UzKY9x4rs_T3pyL7alpw_F?usp=sharing
---
`nlp` : (Only mid F-scores)
>rouge1 0.33508031962733364
rouge2 0.14574333776191592
rougeL 0.2321187823256159
`files2rouge` :
>Running ROUGE...
===========================
1 ROUGE-1 Average_R: 0.48873 (95%-conf.int. 0.41192 - 0.56339)
1 ROUGE-1 Average_P: 0.29010 (95%-conf.int. 0.23605 - 0.34445)
1 ROUGE-1 Average_F: 0.34761 (95%-conf.int. 0.29479 - 0.39871)
===========================
1 ROUGE-2 Average_R: 0.20280 (95%-conf.int. 0.14969 - 0.26244)
1 ROUGE-2 Average_P: 0.12772 (95%-conf.int. 0.08603 - 0.17752)
1 ROUGE-2 Average_F: 0.14798 (95%-conf.int. 0.10517 - 0.19240)
===========================
1 ROUGE-L Average_R: 0.32960 (95%-conf.int. 0.26501 - 0.39676)
1 ROUGE-L Average_P: 0.19880 (95%-conf.int. 0.15257 - 0.25136)
1 ROUGE-L Average_F: 0.23619 (95%-conf.int. 0.19073 - 0.28663)
---
When using longer predictions/gold, the difference is bigger.
**How can I reproduce same score as `files2rouge` ?**
@lhoestq
@Colanim unfortunately there are different implementations of the ROUGE metric floating around online which yield different results, and we had to chose one for the package :) We ended up including the one from the google-research repository, which does minimal post-processing before computing the P/R/F scores. If I recall correctly, files2rouge relies on the Perl, script, which among other things normalizes all numbers to a special token: in the case you presented, this should account for a good chunk of the difference.
We may end up adding in more versions of the metric, but probably not for a while (@lhoestq correct me if I'm wrong). However, feel free to take a stab at adding it in yourself and submitting a PR if you're interested! | [
-0.14572681486606598,
-0.16974392533302307,
-0.19722990691661835,
0.33974677324295044,
-0.11949792504310608,
-0.42426010966300964,
-0.42039984464645386,
0.14767369627952576,
-0.2700444161891937,
0.17250652611255646,
-0.08286791294813156,
0.18038815259933472,
0.12033069878816605,
0.008093969896435738,
-0.10038959980010986,
-0.09797526895999908,
0.1656545251607895,
0.03882867097854614,
0.0924806147813797,
-0.3720676898956299,
0.066559337079525,
0.5696004629135132,
-0.03133261203765869,
0.21043483912944794,
0.05402218550443649,
0.2702386677265167,
0.2851133644580841,
0.30352964997291565,
-0.1485796421766281,
0.028436988592147827,
0.12800218164920807,
0.030641354620456696,
-0.02369792014360428,
0.22214922308921814,
-0.00010886789095820859,
-0.2347189486026764,
0.10260987281799316,
-0.00316624715924263,
-0.27572283148765564,
-0.3026086688041687,
-0.0345572903752327,
0.06436429917812347,
-0.12292841076850891,
-0.07039455324411392,
0.08584661036729813,
-0.04489266499876976,
0.04877201467752457,
0.2095426619052887,
0.4293983578681946,
0.14757375419139862,
0.22625458240509033,
-0.3024369776248932,
-0.18534868955612183,
0.024081934243440628,
0.5763345956802368,
0.1626754105091095,
-0.11448337137699127,
0.4472644627094269,
0.005699165165424347,
-0.3526371419429779,
-0.24019041657447815,
-0.008564136922359467,
0.3430408537387848,
-0.17255935072898865,
0.13255922496318817,
0.19315513968467712,
0.1485852599143982,
-0.04594065248966217,
-0.07953556627035141,
0.24472832679748535,
-0.2702813148498535,
0.03221157193183899,
-0.22717098891735077,
-0.2778374254703522,
-0.0763154923915863,
-0.19976060092449188,
0.11689166724681854,
-0.08144556730985641,
0.16428537666797638,
0.012247947975993156,
0.044132381677627563,
0.2954266369342804,
0.04963909834623337,
0.007164034992456436,
-0.054055385291576385,
-0.10784557461738586,
0.05084608495235443,
0.09846597909927368,
0.29527971148490906,
-0.050543226301670074,
-0.5163146257400513,
0.010772094130516052,
-0.2593674659729004,
0.07496051490306854,
-0.3022814691066742,
-0.037855636328458786,
0.31449607014656067,
0.4659731090068817,
-0.20087093114852905,
0.4996267557144165,
0.2691965401172638,
-0.0934176966547966,
-0.13220703601837158,
-0.03944692760705948,
-0.13782444596290588,
0.10813266038894653,
-0.028946541249752045,
0.020693469792604446,
0.08811824768781662,
0.2246808260679245,
-0.13358275592327118,
-0.012008216232061386,
0.398222953081131,
-0.5637694597244263,
-0.47779831290245056,
0.10259105265140533,
-0.2610342502593994,
-0.43239712715148926,
-0.6891927719116211,
-0.06736093759536743,
-0.25543132424354553,
-0.11924251168966293,
0.09890831261873245,
0.22720104455947876,
-0.1748848706483841,
0.29229775071144104,
0.046788617968559265,
0.1833907961845398,
-0.28950414061546326,
0.019662335515022278,
-0.18399952352046967,
0.06357942521572113,
-0.3143925666809082,
0.13452425599098206,
0.17056594789028168,
0.11274605989456177,
0.3180578649044037,
0.2560538947582245,
0.27351248264312744,
0.03864358365535736,
0.3298662602901459,
-0.28395089507102966,
-0.022635363042354584,
-0.21111632883548737,
-0.21139101684093475,
0.19745370745658875,
0.027128886431455612,
0.09184889495372772,
-0.008701689541339874,
-0.07489361613988876,
-0.18084082007408142,
0.14423638582229614,
0.46661776304244995,
0.20658016204833984,
0.1496511995792389,
-0.11055412888526917,
0.0406920462846756,
0.1169372946023941,
-0.24016308784484863,
-0.5936912894248962,
0.20406046509742737,
-0.13655175268650055,
-0.12701159715652466,
-0.05817777290940285,
0.10982012003660202,
-0.03458242118358612,
0.09312103688716888,
-0.11743132770061493,
0.3731987178325653,
0.06358182430267334,
0.26031294465065,
0.4534834623336792,
-0.04083108901977539,
0.01186465471982956,
-0.16285665333271027,
-0.07088559120893478,
0.4665316641330719,
-0.43853095173835754,
-0.22229687869548798,
0.3354998826980591,
-0.16507023572921753,
-0.06518608331680298,
0.2390466332435608,
0.039275988936424255,
-0.3886536955833435,
-0.1660069078207016,
0.17745031416416168,
0.19752462208271027,
0.07779914885759354,
-0.04839682951569557,
-0.2970067858695984,
0.13495878875255585,
0.3166254758834839,
0.0654771476984024,
-0.23182784020900726,
-0.2993497848510742,
-0.11140484362840652,
-0.06439181417226791,
0.514197051525116,
0.13280721008777618,
-0.2751377820968628,
0.10499174892902374,
-0.2721591889858246,
0.2936933636665344,
-0.05169518291950226,
0.1185731515288353,
0.4230370819568634,
-0.02337534911930561,
-0.7951251268386841,
-0.16027691960334778,
0.43703293800354004,
-0.05248725414276123,
-0.2122921645641327,
-0.47140875458717346,
0.24053315818309784,
-0.23946473002433777,
0.22328287363052368,
0.055049411952495575,
0.18732194602489471,
0.03035423904657364,
0.02407148852944374,
0.09660723805427551,
-0.23642680048942566,
-0.15861909091472626,
-0.17153595387935638,
0.20367786288261414,
-0.22109945118427277,
-0.007433035410940647,
-0.010540366172790527,
0.3596077859401703,
0.31164130568504333,
0.08758017420768738,
0.03730412572622299,
0.26341819763183594,
0.050155505537986755,
0.0980498269200325,
0.3672504425048828,
0.1448051631450653,
-0.0007640253752470016,
0.1889611780643463,
-0.12266073375940323,
0.6879806518554688,
0.016462940722703934,
0.03225133568048477,
-0.34003961086273193,
0.42591530084609985,
-0.21703888475894928,
0.20069116353988647,
0.4093107581138611,
-0.07173743844032288,
-0.050097495317459106,
0.05778001621365547,
-0.006799564231187105,
-0.017152976244688034,
0.7467243671417236,
0.1952691674232483,
0.2502555549144745,
0.002956695854663849,
-0.3220258355140686,
0.2596171498298645,
0.3991404175758362,
-0.015342838130891323,
-0.020852625370025635,
-0.11995432525873184,
0.1937142014503479,
-0.09338856488466263,
-0.03672000765800476,
0.25073885917663574,
0.3810698390007019,
0.19513367116451263,
0.15570716559886932,
-0.1311991810798645,
-0.33823680877685547,
-0.3438020944595337,
0.03513295203447342,
-0.18210352957248688,
0.08744704723358154,
0.4963866174221039,
0.10160735994577408,
0.21628685295581818,
-0.3020772635936737,
-0.5422850847244263,
-0.25364819169044495,
-0.22231410443782806,
0.06132550165057182,
0.16164565086364746,
-0.14391349256038666,
-0.3678344488143921,
-0.15366095304489136,
-0.0919032171368599,
-0.2918884754180908,
-0.2732764482498169,
0.2300969362258911,
0.020874908193945885,
-0.07249949127435684,
-0.2189374715089798,
0.02323257550597191,
0.14874732494354248,
-0.37039417028427124,
0.1783812940120697,
-0.017374012619256973,
-0.028042834252119064,
-0.27953851222991943,
0.22281798720359802,
-0.05679866671562195,
-0.01930420473217964,
-0.03147614002227783,
-0.2791869640350342,
-0.45083630084991455,
0.16968809068202972,
-0.3762677013874054,
-0.010960057377815247,
0.06464451551437378,
-0.0032363757491111755,
0.05967199429869652,
-0.2506176233291626,
-0.07057526707649231,
0.14640071988105774,
0.09220800548791885,
-0.1741306185722351,
-0.35074377059936523,
-0.08965122699737549,
0.03678468242287636,
0.014213903807103634,
-0.19140614569187164,
-0.27752187848091125,
0.07937449216842651,
-0.14331994950771332,
0.6197946071624756,
0.3270139694213867,
0.005700867623090744,
0.3858785927295685,
-0.2369554340839386,
0.00001177145168185234,
0.17174258828163147,
0.5837677121162415,
-0.2605840563774109,
-0.04442854970693588,
0.19860902428627014,
-0.2997126579284668,
-0.4421888589859009,
-0.2730613946914673,
0.18830057978630066,
0.03232206031680107,
-0.008429164066910744,
-0.17861716449260712,
0.031004078686237335,
-0.1309441179037094,
-0.04899725317955017,
-0.2130453884601593,
-0.05581780523061752,
0.33782681822776794,
-0.1836601346731186,
-0.2421920895576477,
-0.06447437405586243,
0.21673373878002167,
0.029940642416477203,
0.28654640913009644,
0.4599356949329376,
-0.4840274751186371,
0.1646125614643097,
-0.1400940716266632,
0.12755994498729706,
0.04408307000994682,
0.5117960572242737,
0.1533815860748291,
0.1332312375307083,
0.0008752048015594482,
-0.14067688584327698,
0.09818042814731598,
0.4896940290927887,
0.056188441812992096,
-0.14490284025669098,
0.3308490812778473,
0.20873358845710754,
0.24980415403842926,
-0.11164984852075577,
-0.04191560670733452,
-0.07632186263799667,
-0.00791233777999878,
0.10350729525089264,
0.07728653401136398,
-0.05600050836801529,
0.017135661095380783,
0.07414527982473373,
-0.0036139339208602905,
-0.15379199385643005,
0.21246279776096344,
0.07286881655454636,
0.39130184054374695,
-0.11124485731124878,
-0.25944772362709045,
-0.005773358047008514,
-0.46897637844085693,
-0.005584202706813812,
0.031853336840867996,
-0.021542735397815704,
-0.15841075778007507,
-0.17286941409111023,
0.05907169356942177,
-0.3485898971557617,
0.26234251260757446,
0.16069412231445312,
0.23712927103042603,
0.16907617449760437,
-0.13415351510047913,
-0.5272519588470459,
-0.294148325920105,
-0.3322208523750305,
0.18113453686237335,
0.596076488494873,
0.11514388769865036,
-0.13822150230407715,
-0.17282268404960632,
0.10999258607625961,
-0.05185077711939812,
-0.14824798703193665,
0.10066777467727661,
-0.33127161860466003,
0.20241904258728027,
0.15132899582386017,
-0.2806145250797272,
0.04583745449781418,
0.3753645718097687,
-0.24381005764007568,
0.12480206787586212,
0.06615749001502991,
-0.1499929428100586,
0.2123294323682785,
0.13495224714279175,
0.33930909633636475,
-0.10402191430330276,
-0.24397088587284088,
-0.29319772124290466,
0.30135542154312134,
-0.3514430522918701,
0.3701417148113251,
0.1212446391582489,
0.0003355368971824646,
0.30029138922691345,
-0.09358739852905273,
0.10684163123369217,
0.3101273477077484,
-0.18164154887199402,
0.1664067804813385,
-0.6221522092819214,
0.11270289123058319,
-0.44617894291877747,
-0.2102094292640686,
0.36847415566444397,
-0.07535791397094727,
0.2850716710090637,
-0.1410284787416458,
0.2084536850452423,
0.23064105212688446,
-0.47709769010543823,
-0.07949845492839813,
-0.16209423542022705,
-0.19412687420845032,
0.2774372696876526,
-0.02041754126548767,
0.7596277594566345,
0.4354732036590576,
0.5633991360664368,
0.23021692037582397,
-0.1473512500524521,
0.38939782977104187,
-0.5955854058265686,
0.19127970933914185,
-0.34151583909988403,
-0.37023502588272095,
0.09574323892593384,
0.10443316400051117,
-0.06511325389146805,
0.21454881131649017,
0.20764991641044617,
0.2953759431838989,
0.39312154054641724,
-0.09911176562309265,
-0.10828026384115219,
0.17655311524868011,
0.12343072891235352,
0.18754130601882935,
-0.2870902717113495,
0.1991366744041443,
0.34644365310668945,
0.004576649516820908,
-0.05969361588358879,
0.0959683433175087,
-0.7420675754547119,
0.02251587063074112,
0.04249122738838196,
0.10044645518064499,
-0.09559989720582962,
0.35474252700805664,
0.11958041787147522,
-0.2243277132511139,
-0.04871850088238716,
0.3672390878200531,
0.15987490117549896,
-0.015912584960460663,
0.00719662569463253,
0.21002444624900818,
-0.3194081783294678,
0.32633107900619507,
0.242310032248497,
-0.03880351036787033,
0.031407780945301056,
-0.22021397948265076,
-0.0787142813205719,
-0.07076065987348557,
0.15572455525398254,
-0.16848213970661163,
-0.5484740734100342,
0.18215541541576385,
-0.33470314741134644,
0.007207001093775034,
-0.02991698868572712,
0.10068950057029724,
-0.09960559010505676,
-0.05343038588762283,
0.16725941002368927,
-0.05686335265636444,
-0.06265363842248917,
-0.03488510102033615,
0.09307181090116501,
-0.33285802602767944,
-0.050463635474443436,
0.47442546486854553,
-0.13673809170722961,
-0.04600970447063446,
0.06487441807985306,
-0.3305659294128418,
0.0352669283747673,
-0.24317610263824463,
0.03892479091882706,
-0.08075741678476334,
-0.19715386629104614,
-0.10430090129375458,
-0.007580584846436977,
-0.2291492074728012,
0.25272732973098755,
0.25843656063079834,
0.24956685304641724,
0.21303749084472656,
0.032852623611688614,
-0.36308497190475464,
-0.09832554310560226,
0.0810789093375206,
0.16799978911876678,
-0.03473341092467308,
-0.019618384540081024,
-0.1595887839794159,
0.2588408589363098,
0.23063212633132935,
-0.35463544726371765,
-0.15017247200012207,
-0.08997658640146255,
0.12681715190410614,
-0.22102300822734833,
-0.31873926520347595,
0.022486412897706032,
0.1468534916639328,
0.14308585226535797,
-0.008150145411491394,
-0.05782918632030487,
-0.24771744012832642,
-0.20516616106033325,
0.083225779235363,
-0.04834723472595215,
-0.09744089841842651,
-0.13200169801712036,
0.21839922666549683,
0.1043625921010971,
-0.14063486456871033,
-0.2313222736120224,
-0.13392606377601624,
0.3573988676071167,
0.12174542248249054,
-0.08553825318813324,
0.1825152337551117,
-0.1426304578781128,
0.1086663231253624,
0.01882341504096985,
-0.02538543939590454,
0.07357704639434814,
-0.026512712240219116,
0.10945796221494675,
-0.20184220373630524,
-0.2564111351966858,
-0.07424164563417435,
-0.28038954734802246,
0.14717337489128113,
0.10414642840623856,
-0.05297304689884186,
0.008782848715782166,
-0.18328946828842163,
0.2844215929508209,
0.36497512459754944,
0.11780503392219543,
-0.09963665157556534,
-0.013917770236730576,
0.22528287768363953,
-0.22220194339752197,
0.09425365179777145,
0.4496179521083832,
0.043986815959215164,
0.06563544273376465,
-0.028284482657909393,
0.15857842564582825,
-0.20769783854484558,
-0.018284879624843597,
-0.05924851819872856,
-0.274423748254776,
-0.01816922426223755,
0.17280733585357666,
-0.19119597971439362,
0.2515231966972351,
0.07363121956586838,
0.15538182854652405,
-0.37914836406707764,
0.1871822029352188,
0.35076963901519775,
-0.0025786757469177246,
0.1941520869731903,
-0.2856433689594269,
0.14951317012310028,
-0.02367575466632843,
0.09032042324542999,
-0.2703600227832794,
0.34511232376098633,
0.0853983536362648,
-0.02180592715740204,
0.08363571763038635,
0.16912135481834412,
-0.10833384096622467,
-0.3376132547855377,
-0.004882588982582092,
-0.08809277415275574,
-0.07047510892152786,
-0.544400155544281,
-0.4664246141910553,
-0.22646990418434143,
-0.394583523273468,
0.0710502415895462,
-0.16874070465564728,
0.3817867636680603,
0.02951917052268982,
0.24772146344184875,
-0.09672556817531586,
-0.18267740309238434,
-0.46176448464393616,
0.01024707779288292,
0.4208807945251465,
-0.04675701633095741,
0.17743246257305145,
0.21671605110168457,
0.41431334614753723,
0.35717928409576416,
0.1616116166114807,
0.2387458086013794,
0.1888272762298584,
-0.23361444473266602,
-0.2279309630393982,
0.03246691823005676,
0.08932045102119446,
-0.19615799188613892,
0.17421609163284302,
0.25997745990753174,
0.043390270322561264,
0.3002178966999054,
0.1322067826986313,
-0.2410818189382553,
0.07742059230804443,
0.26498717069625854,
-0.003574555739760399,
-0.21413002908229828,
0.29473719000816345,
-0.03916162997484207,
0.018681995570659637,
-0.3314741849899292,
0.3797486424446106,
-0.5077441334724426,
-0.08658870309591293,
-0.5439391136169434,
0.15140368044376373,
0.17864581942558289,
-0.12435458600521088,
0.10393225401639938,
0.26889368891716003,
0.41731470823287964,
-0.12723563611507416,
0.33877450227737427,
-0.28413742780685425,
-0.4613204002380371,
-0.2653636336326599,
-0.04584982246160507,
0.03950878977775574,
0.27052927017211914,
-0.4309377372264862,
0.28873559832572937,
-0.29741546511650085,
0.051449984312057495,
0.27456027269363403,
0.4283304512500763,
0.24691930413246155,
0.06649784743785858,
-0.33822938799858093,
0.1559208780527115,
0.19840247929096222,
-0.08824513852596283,
-0.11956954002380371,
0.1306329071521759,
-0.17390617728233337,
0.019816752523183823,
0.10971526056528091,
0.0855555534362793,
-0.3465362787246704,
-0.28865334391593933,
0.4207552969455719,
0.3385229706764221,
0.275066614151001,
0.2680865228176117,
-0.37258201837539673,
-0.3853943943977356,
0.031004125252366066,
-0.12375257909297943,
-0.06270965933799744,
0.06228291243314743,
-0.06584185361862183,
0.38764387369155884,
0.02506408654153347,
0.07477395981550217,
0.07386114448308945,
0.5041284561157227,
0.055955611169338226,
0.0017196849221363664,
-0.22702951729297638,
-0.026206813752651215,
0.09364626556634903,
0.0634227991104126,
-0.6129947304725647,
0.407443642616272,
0.0005168020725250244,
0.18714407086372375,
-0.23370829224586487,
-0.25390002131462097,
0.3750455975532532,
-0.35842156410217285,
0.2720431089401245,
-0.0997019112110138,
0.34275418519973755,
0.22176191210746765,
0.29680517315864563,
0.04679156094789505,
-0.10589517652988434,
0.07175469398498535,
0.29574763774871826,
0.1622447669506073,
0.23034629225730896,
-0.2334200143814087,
-0.08380287140607834,
-0.0016767457127571106,
0.29279518127441406,
0.06492644548416138,
-0.29197126626968384,
0.41343367099761963,
-0.18410754203796387
] |
https://github.com/huggingface/datasets/issues/225 | [ROUGE] Different scores with `files2rouge` | Thank you for your kind answer.
As a side question : Isn't it better to have a package that normalize more ?
I understand to idea of having a package that does minimal post-processing for transparency.
But it means that people using different architecture (with different tokenizers for example) will have difference in ROUGE scores even if their predictions are actually similar.
The goal of `nlp` is to have _one package to rule them all_, right ?
I will look into it but I'm not sure I have the required skill for this ^^ | It seems that the ROUGE score of `nlp` is lower than the one of `files2rouge`.
Here is a self-contained notebook to reproduce both scores : https://colab.research.google.com/drive/14EyAXValB6UzKY9x4rs_T3pyL7alpw_F?usp=sharing
---
`nlp` : (Only mid F-scores)
>rouge1 0.33508031962733364
rouge2 0.14574333776191592
rougeL 0.2321187823256159
`files2rouge` :
>Running ROUGE...
===========================
1 ROUGE-1 Average_R: 0.48873 (95%-conf.int. 0.41192 - 0.56339)
1 ROUGE-1 Average_P: 0.29010 (95%-conf.int. 0.23605 - 0.34445)
1 ROUGE-1 Average_F: 0.34761 (95%-conf.int. 0.29479 - 0.39871)
===========================
1 ROUGE-2 Average_R: 0.20280 (95%-conf.int. 0.14969 - 0.26244)
1 ROUGE-2 Average_P: 0.12772 (95%-conf.int. 0.08603 - 0.17752)
1 ROUGE-2 Average_F: 0.14798 (95%-conf.int. 0.10517 - 0.19240)
===========================
1 ROUGE-L Average_R: 0.32960 (95%-conf.int. 0.26501 - 0.39676)
1 ROUGE-L Average_P: 0.19880 (95%-conf.int. 0.15257 - 0.25136)
1 ROUGE-L Average_F: 0.23619 (95%-conf.int. 0.19073 - 0.28663)
---
When using longer predictions/gold, the difference is bigger.
**How can I reproduce same score as `files2rouge` ?**
@lhoestq
| 94 | [ROUGE] Different scores with `files2rouge`
It seems that the ROUGE score of `nlp` is lower than the one of `files2rouge`.
Here is a self-contained notebook to reproduce both scores : https://colab.research.google.com/drive/14EyAXValB6UzKY9x4rs_T3pyL7alpw_F?usp=sharing
---
`nlp` : (Only mid F-scores)
>rouge1 0.33508031962733364
rouge2 0.14574333776191592
rougeL 0.2321187823256159
`files2rouge` :
>Running ROUGE...
===========================
1 ROUGE-1 Average_R: 0.48873 (95%-conf.int. 0.41192 - 0.56339)
1 ROUGE-1 Average_P: 0.29010 (95%-conf.int. 0.23605 - 0.34445)
1 ROUGE-1 Average_F: 0.34761 (95%-conf.int. 0.29479 - 0.39871)
===========================
1 ROUGE-2 Average_R: 0.20280 (95%-conf.int. 0.14969 - 0.26244)
1 ROUGE-2 Average_P: 0.12772 (95%-conf.int. 0.08603 - 0.17752)
1 ROUGE-2 Average_F: 0.14798 (95%-conf.int. 0.10517 - 0.19240)
===========================
1 ROUGE-L Average_R: 0.32960 (95%-conf.int. 0.26501 - 0.39676)
1 ROUGE-L Average_P: 0.19880 (95%-conf.int. 0.15257 - 0.25136)
1 ROUGE-L Average_F: 0.23619 (95%-conf.int. 0.19073 - 0.28663)
---
When using longer predictions/gold, the difference is bigger.
**How can I reproduce same score as `files2rouge` ?**
@lhoestq
Thank you for your kind answer.
As a side question : Isn't it better to have a package that normalize more ?
I understand to idea of having a package that does minimal post-processing for transparency.
But it means that people using different architecture (with different tokenizers for example) will have difference in ROUGE scores even if their predictions are actually similar.
The goal of `nlp` is to have _one package to rule them all_, right ?
I will look into it but I'm not sure I have the required skill for this ^^ | [
-0.14572681486606598,
-0.16974392533302307,
-0.19722990691661835,
0.33974677324295044,
-0.11949792504310608,
-0.42426010966300964,
-0.42039984464645386,
0.14767369627952576,
-0.2700444161891937,
0.17250652611255646,
-0.08286791294813156,
0.18038815259933472,
0.12033069878816605,
0.008093969896435738,
-0.10038959980010986,
-0.09797526895999908,
0.1656545251607895,
0.03882867097854614,
0.0924806147813797,
-0.3720676898956299,
0.066559337079525,
0.5696004629135132,
-0.03133261203765869,
0.21043483912944794,
0.05402218550443649,
0.2702386677265167,
0.2851133644580841,
0.30352964997291565,
-0.1485796421766281,
0.028436988592147827,
0.12800218164920807,
0.030641354620456696,
-0.02369792014360428,
0.22214922308921814,
-0.00010886789095820859,
-0.2347189486026764,
0.10260987281799316,
-0.00316624715924263,
-0.27572283148765564,
-0.3026086688041687,
-0.0345572903752327,
0.06436429917812347,
-0.12292841076850891,
-0.07039455324411392,
0.08584661036729813,
-0.04489266499876976,
0.04877201467752457,
0.2095426619052887,
0.4293983578681946,
0.14757375419139862,
0.22625458240509033,
-0.3024369776248932,
-0.18534868955612183,
0.024081934243440628,
0.5763345956802368,
0.1626754105091095,
-0.11448337137699127,
0.4472644627094269,
0.005699165165424347,
-0.3526371419429779,
-0.24019041657447815,
-0.008564136922359467,
0.3430408537387848,
-0.17255935072898865,
0.13255922496318817,
0.19315513968467712,
0.1485852599143982,
-0.04594065248966217,
-0.07953556627035141,
0.24472832679748535,
-0.2702813148498535,
0.03221157193183899,
-0.22717098891735077,
-0.2778374254703522,
-0.0763154923915863,
-0.19976060092449188,
0.11689166724681854,
-0.08144556730985641,
0.16428537666797638,
0.012247947975993156,
0.044132381677627563,
0.2954266369342804,
0.04963909834623337,
0.007164034992456436,
-0.054055385291576385,
-0.10784557461738586,
0.05084608495235443,
0.09846597909927368,
0.29527971148490906,
-0.050543226301670074,
-0.5163146257400513,
0.010772094130516052,
-0.2593674659729004,
0.07496051490306854,
-0.3022814691066742,
-0.037855636328458786,
0.31449607014656067,
0.4659731090068817,
-0.20087093114852905,
0.4996267557144165,
0.2691965401172638,
-0.0934176966547966,
-0.13220703601837158,
-0.03944692760705948,
-0.13782444596290588,
0.10813266038894653,
-0.028946541249752045,
0.020693469792604446,
0.08811824768781662,
0.2246808260679245,
-0.13358275592327118,
-0.012008216232061386,
0.398222953081131,
-0.5637694597244263,
-0.47779831290245056,
0.10259105265140533,
-0.2610342502593994,
-0.43239712715148926,
-0.6891927719116211,
-0.06736093759536743,
-0.25543132424354553,
-0.11924251168966293,
0.09890831261873245,
0.22720104455947876,
-0.1748848706483841,
0.29229775071144104,
0.046788617968559265,
0.1833907961845398,
-0.28950414061546326,
0.019662335515022278,
-0.18399952352046967,
0.06357942521572113,
-0.3143925666809082,
0.13452425599098206,
0.17056594789028168,
0.11274605989456177,
0.3180578649044037,
0.2560538947582245,
0.27351248264312744,
0.03864358365535736,
0.3298662602901459,
-0.28395089507102966,
-0.022635363042354584,
-0.21111632883548737,
-0.21139101684093475,
0.19745370745658875,
0.027128886431455612,
0.09184889495372772,
-0.008701689541339874,
-0.07489361613988876,
-0.18084082007408142,
0.14423638582229614,
0.46661776304244995,
0.20658016204833984,
0.1496511995792389,
-0.11055412888526917,
0.0406920462846756,
0.1169372946023941,
-0.24016308784484863,
-0.5936912894248962,
0.20406046509742737,
-0.13655175268650055,
-0.12701159715652466,
-0.05817777290940285,
0.10982012003660202,
-0.03458242118358612,
0.09312103688716888,
-0.11743132770061493,
0.3731987178325653,
0.06358182430267334,
0.26031294465065,
0.4534834623336792,
-0.04083108901977539,
0.01186465471982956,
-0.16285665333271027,
-0.07088559120893478,
0.4665316641330719,
-0.43853095173835754,
-0.22229687869548798,
0.3354998826980591,
-0.16507023572921753,
-0.06518608331680298,
0.2390466332435608,
0.039275988936424255,
-0.3886536955833435,
-0.1660069078207016,
0.17745031416416168,
0.19752462208271027,
0.07779914885759354,
-0.04839682951569557,
-0.2970067858695984,
0.13495878875255585,
0.3166254758834839,
0.0654771476984024,
-0.23182784020900726,
-0.2993497848510742,
-0.11140484362840652,
-0.06439181417226791,
0.514197051525116,
0.13280721008777618,
-0.2751377820968628,
0.10499174892902374,
-0.2721591889858246,
0.2936933636665344,
-0.05169518291950226,
0.1185731515288353,
0.4230370819568634,
-0.02337534911930561,
-0.7951251268386841,
-0.16027691960334778,
0.43703293800354004,
-0.05248725414276123,
-0.2122921645641327,
-0.47140875458717346,
0.24053315818309784,
-0.23946473002433777,
0.22328287363052368,
0.055049411952495575,
0.18732194602489471,
0.03035423904657364,
0.02407148852944374,
0.09660723805427551,
-0.23642680048942566,
-0.15861909091472626,
-0.17153595387935638,
0.20367786288261414,
-0.22109945118427277,
-0.007433035410940647,
-0.010540366172790527,
0.3596077859401703,
0.31164130568504333,
0.08758017420768738,
0.03730412572622299,
0.26341819763183594,
0.050155505537986755,
0.0980498269200325,
0.3672504425048828,
0.1448051631450653,
-0.0007640253752470016,
0.1889611780643463,
-0.12266073375940323,
0.6879806518554688,
0.016462940722703934,
0.03225133568048477,
-0.34003961086273193,
0.42591530084609985,
-0.21703888475894928,
0.20069116353988647,
0.4093107581138611,
-0.07173743844032288,
-0.050097495317459106,
0.05778001621365547,
-0.006799564231187105,
-0.017152976244688034,
0.7467243671417236,
0.1952691674232483,
0.2502555549144745,
0.002956695854663849,
-0.3220258355140686,
0.2596171498298645,
0.3991404175758362,
-0.015342838130891323,
-0.020852625370025635,
-0.11995432525873184,
0.1937142014503479,
-0.09338856488466263,
-0.03672000765800476,
0.25073885917663574,
0.3810698390007019,
0.19513367116451263,
0.15570716559886932,
-0.1311991810798645,
-0.33823680877685547,
-0.3438020944595337,
0.03513295203447342,
-0.18210352957248688,
0.08744704723358154,
0.4963866174221039,
0.10160735994577408,
0.21628685295581818,
-0.3020772635936737,
-0.5422850847244263,
-0.25364819169044495,
-0.22231410443782806,
0.06132550165057182,
0.16164565086364746,
-0.14391349256038666,
-0.3678344488143921,
-0.15366095304489136,
-0.0919032171368599,
-0.2918884754180908,
-0.2732764482498169,
0.2300969362258911,
0.020874908193945885,
-0.07249949127435684,
-0.2189374715089798,
0.02323257550597191,
0.14874732494354248,
-0.37039417028427124,
0.1783812940120697,
-0.017374012619256973,
-0.028042834252119064,
-0.27953851222991943,
0.22281798720359802,
-0.05679866671562195,
-0.01930420473217964,
-0.03147614002227783,
-0.2791869640350342,
-0.45083630084991455,
0.16968809068202972,
-0.3762677013874054,
-0.010960057377815247,
0.06464451551437378,
-0.0032363757491111755,
0.05967199429869652,
-0.2506176233291626,
-0.07057526707649231,
0.14640071988105774,
0.09220800548791885,
-0.1741306185722351,
-0.35074377059936523,
-0.08965122699737549,
0.03678468242287636,
0.014213903807103634,
-0.19140614569187164,
-0.27752187848091125,
0.07937449216842651,
-0.14331994950771332,
0.6197946071624756,
0.3270139694213867,
0.005700867623090744,
0.3858785927295685,
-0.2369554340839386,
0.00001177145168185234,
0.17174258828163147,
0.5837677121162415,
-0.2605840563774109,
-0.04442854970693588,
0.19860902428627014,
-0.2997126579284668,
-0.4421888589859009,
-0.2730613946914673,
0.18830057978630066,
0.03232206031680107,
-0.008429164066910744,
-0.17861716449260712,
0.031004078686237335,
-0.1309441179037094,
-0.04899725317955017,
-0.2130453884601593,
-0.05581780523061752,
0.33782681822776794,
-0.1836601346731186,
-0.2421920895576477,
-0.06447437405586243,
0.21673373878002167,
0.029940642416477203,
0.28654640913009644,
0.4599356949329376,
-0.4840274751186371,
0.1646125614643097,
-0.1400940716266632,
0.12755994498729706,
0.04408307000994682,
0.5117960572242737,
0.1533815860748291,
0.1332312375307083,
0.0008752048015594482,
-0.14067688584327698,
0.09818042814731598,
0.4896940290927887,
0.056188441812992096,
-0.14490284025669098,
0.3308490812778473,
0.20873358845710754,
0.24980415403842926,
-0.11164984852075577,
-0.04191560670733452,
-0.07632186263799667,
-0.00791233777999878,
0.10350729525089264,
0.07728653401136398,
-0.05600050836801529,
0.017135661095380783,
0.07414527982473373,
-0.0036139339208602905,
-0.15379199385643005,
0.21246279776096344,
0.07286881655454636,
0.39130184054374695,
-0.11124485731124878,
-0.25944772362709045,
-0.005773358047008514,
-0.46897637844085693,
-0.005584202706813812,
0.031853336840867996,
-0.021542735397815704,
-0.15841075778007507,
-0.17286941409111023,
0.05907169356942177,
-0.3485898971557617,
0.26234251260757446,
0.16069412231445312,
0.23712927103042603,
0.16907617449760437,
-0.13415351510047913,
-0.5272519588470459,
-0.294148325920105,
-0.3322208523750305,
0.18113453686237335,
0.596076488494873,
0.11514388769865036,
-0.13822150230407715,
-0.17282268404960632,
0.10999258607625961,
-0.05185077711939812,
-0.14824798703193665,
0.10066777467727661,
-0.33127161860466003,
0.20241904258728027,
0.15132899582386017,
-0.2806145250797272,
0.04583745449781418,
0.3753645718097687,
-0.24381005764007568,
0.12480206787586212,
0.06615749001502991,
-0.1499929428100586,
0.2123294323682785,
0.13495224714279175,
0.33930909633636475,
-0.10402191430330276,
-0.24397088587284088,
-0.29319772124290466,
0.30135542154312134,
-0.3514430522918701,
0.3701417148113251,
0.1212446391582489,
0.0003355368971824646,
0.30029138922691345,
-0.09358739852905273,
0.10684163123369217,
0.3101273477077484,
-0.18164154887199402,
0.1664067804813385,
-0.6221522092819214,
0.11270289123058319,
-0.44617894291877747,
-0.2102094292640686,
0.36847415566444397,
-0.07535791397094727,
0.2850716710090637,
-0.1410284787416458,
0.2084536850452423,
0.23064105212688446,
-0.47709769010543823,
-0.07949845492839813,
-0.16209423542022705,
-0.19412687420845032,
0.2774372696876526,
-0.02041754126548767,
0.7596277594566345,
0.4354732036590576,
0.5633991360664368,
0.23021692037582397,
-0.1473512500524521,
0.38939782977104187,
-0.5955854058265686,
0.19127970933914185,
-0.34151583909988403,
-0.37023502588272095,
0.09574323892593384,
0.10443316400051117,
-0.06511325389146805,
0.21454881131649017,
0.20764991641044617,
0.2953759431838989,
0.39312154054641724,
-0.09911176562309265,
-0.10828026384115219,
0.17655311524868011,
0.12343072891235352,
0.18754130601882935,
-0.2870902717113495,
0.1991366744041443,
0.34644365310668945,
0.004576649516820908,
-0.05969361588358879,
0.0959683433175087,
-0.7420675754547119,
0.02251587063074112,
0.04249122738838196,
0.10044645518064499,
-0.09559989720582962,
0.35474252700805664,
0.11958041787147522,
-0.2243277132511139,
-0.04871850088238716,
0.3672390878200531,
0.15987490117549896,
-0.015912584960460663,
0.00719662569463253,
0.21002444624900818,
-0.3194081783294678,
0.32633107900619507,
0.242310032248497,
-0.03880351036787033,
0.031407780945301056,
-0.22021397948265076,
-0.0787142813205719,
-0.07076065987348557,
0.15572455525398254,
-0.16848213970661163,
-0.5484740734100342,
0.18215541541576385,
-0.33470314741134644,
0.007207001093775034,
-0.02991698868572712,
0.10068950057029724,
-0.09960559010505676,
-0.05343038588762283,
0.16725941002368927,
-0.05686335265636444,
-0.06265363842248917,
-0.03488510102033615,
0.09307181090116501,
-0.33285802602767944,
-0.050463635474443436,
0.47442546486854553,
-0.13673809170722961,
-0.04600970447063446,
0.06487441807985306,
-0.3305659294128418,
0.0352669283747673,
-0.24317610263824463,
0.03892479091882706,
-0.08075741678476334,
-0.19715386629104614,
-0.10430090129375458,
-0.007580584846436977,
-0.2291492074728012,
0.25272732973098755,
0.25843656063079834,
0.24956685304641724,
0.21303749084472656,
0.032852623611688614,
-0.36308497190475464,
-0.09832554310560226,
0.0810789093375206,
0.16799978911876678,
-0.03473341092467308,
-0.019618384540081024,
-0.1595887839794159,
0.2588408589363098,
0.23063212633132935,
-0.35463544726371765,
-0.15017247200012207,
-0.08997658640146255,
0.12681715190410614,
-0.22102300822734833,
-0.31873926520347595,
0.022486412897706032,
0.1468534916639328,
0.14308585226535797,
-0.008150145411491394,
-0.05782918632030487,
-0.24771744012832642,
-0.20516616106033325,
0.083225779235363,
-0.04834723472595215,
-0.09744089841842651,
-0.13200169801712036,
0.21839922666549683,
0.1043625921010971,
-0.14063486456871033,
-0.2313222736120224,
-0.13392606377601624,
0.3573988676071167,
0.12174542248249054,
-0.08553825318813324,
0.1825152337551117,
-0.1426304578781128,
0.1086663231253624,
0.01882341504096985,
-0.02538543939590454,
0.07357704639434814,
-0.026512712240219116,
0.10945796221494675,
-0.20184220373630524,
-0.2564111351966858,
-0.07424164563417435,
-0.28038954734802246,
0.14717337489128113,
0.10414642840623856,
-0.05297304689884186,
0.008782848715782166,
-0.18328946828842163,
0.2844215929508209,
0.36497512459754944,
0.11780503392219543,
-0.09963665157556534,
-0.013917770236730576,
0.22528287768363953,
-0.22220194339752197,
0.09425365179777145,
0.4496179521083832,
0.043986815959215164,
0.06563544273376465,
-0.028284482657909393,
0.15857842564582825,
-0.20769783854484558,
-0.018284879624843597,
-0.05924851819872856,
-0.274423748254776,
-0.01816922426223755,
0.17280733585357666,
-0.19119597971439362,
0.2515231966972351,
0.07363121956586838,
0.15538182854652405,
-0.37914836406707764,
0.1871822029352188,
0.35076963901519775,
-0.0025786757469177246,
0.1941520869731903,
-0.2856433689594269,
0.14951317012310028,
-0.02367575466632843,
0.09032042324542999,
-0.2703600227832794,
0.34511232376098633,
0.0853983536362648,
-0.02180592715740204,
0.08363571763038635,
0.16912135481834412,
-0.10833384096622467,
-0.3376132547855377,
-0.004882588982582092,
-0.08809277415275574,
-0.07047510892152786,
-0.544400155544281,
-0.4664246141910553,
-0.22646990418434143,
-0.394583523273468,
0.0710502415895462,
-0.16874070465564728,
0.3817867636680603,
0.02951917052268982,
0.24772146344184875,
-0.09672556817531586,
-0.18267740309238434,
-0.46176448464393616,
0.01024707779288292,
0.4208807945251465,
-0.04675701633095741,
0.17743246257305145,
0.21671605110168457,
0.41431334614753723,
0.35717928409576416,
0.1616116166114807,
0.2387458086013794,
0.1888272762298584,
-0.23361444473266602,
-0.2279309630393982,
0.03246691823005676,
0.08932045102119446,
-0.19615799188613892,
0.17421609163284302,
0.25997745990753174,
0.043390270322561264,
0.3002178966999054,
0.1322067826986313,
-0.2410818189382553,
0.07742059230804443,
0.26498717069625854,
-0.003574555739760399,
-0.21413002908229828,
0.29473719000816345,
-0.03916162997484207,
0.018681995570659637,
-0.3314741849899292,
0.3797486424446106,
-0.5077441334724426,
-0.08658870309591293,
-0.5439391136169434,
0.15140368044376373,
0.17864581942558289,
-0.12435458600521088,
0.10393225401639938,
0.26889368891716003,
0.41731470823287964,
-0.12723563611507416,
0.33877450227737427,
-0.28413742780685425,
-0.4613204002380371,
-0.2653636336326599,
-0.04584982246160507,
0.03950878977775574,
0.27052927017211914,
-0.4309377372264862,
0.28873559832572937,
-0.29741546511650085,
0.051449984312057495,
0.27456027269363403,
0.4283304512500763,
0.24691930413246155,
0.06649784743785858,
-0.33822938799858093,
0.1559208780527115,
0.19840247929096222,
-0.08824513852596283,
-0.11956954002380371,
0.1306329071521759,
-0.17390617728233337,
0.019816752523183823,
0.10971526056528091,
0.0855555534362793,
-0.3465362787246704,
-0.28865334391593933,
0.4207552969455719,
0.3385229706764221,
0.275066614151001,
0.2680865228176117,
-0.37258201837539673,
-0.3853943943977356,
0.031004125252366066,
-0.12375257909297943,
-0.06270965933799744,
0.06228291243314743,
-0.06584185361862183,
0.38764387369155884,
0.02506408654153347,
0.07477395981550217,
0.07386114448308945,
0.5041284561157227,
0.055955611169338226,
0.0017196849221363664,
-0.22702951729297638,
-0.026206813752651215,
0.09364626556634903,
0.0634227991104126,
-0.6129947304725647,
0.407443642616272,
0.0005168020725250244,
0.18714407086372375,
-0.23370829224586487,
-0.25390002131462097,
0.3750455975532532,
-0.35842156410217285,
0.2720431089401245,
-0.0997019112110138,
0.34275418519973755,
0.22176191210746765,
0.29680517315864563,
0.04679156094789505,
-0.10589517652988434,
0.07175469398498535,
0.29574763774871826,
0.1622447669506073,
0.23034629225730896,
-0.2334200143814087,
-0.08380287140607834,
-0.0016767457127571106,
0.29279518127441406,
0.06492644548416138,
-0.29197126626968384,
0.41343367099761963,
-0.18410754203796387
] |
https://github.com/huggingface/datasets/issues/225 | [ROUGE] Different scores with `files2rouge` | You're right, there's a pretty interesting trade-off here between robustness and sensitivity :) The flip side of your argument is that we also still want the metric to be sensitive to model mistakes. How we think about number normalization for example has evolved a fair bit since the Perl script was written: at the time, ROUGE was used mostly to evaluate short-medium text summarization systems, where there were only a few numbers in the input and it was assumed that the most popular methods in use at the time would get those right. However, as your example showcases, that assumption does not hold any more, and we do want to be able to penalize a model that generates a wrong numerical value.
Also, we think that abstracting away tokenization differences is the role of the model/tokenizer: if you use the 🤗Tokenizers library for example, it will handle that for you ;)
Finally, there is a lot of active research on developing model-powered metrics that are both more sensitive and more robust than ROUGE. Check out for example BERTscore, which is implemented in this library! | It seems that the ROUGE score of `nlp` is lower than the one of `files2rouge`.
Here is a self-contained notebook to reproduce both scores : https://colab.research.google.com/drive/14EyAXValB6UzKY9x4rs_T3pyL7alpw_F?usp=sharing
---
`nlp` : (Only mid F-scores)
>rouge1 0.33508031962733364
rouge2 0.14574333776191592
rougeL 0.2321187823256159
`files2rouge` :
>Running ROUGE...
===========================
1 ROUGE-1 Average_R: 0.48873 (95%-conf.int. 0.41192 - 0.56339)
1 ROUGE-1 Average_P: 0.29010 (95%-conf.int. 0.23605 - 0.34445)
1 ROUGE-1 Average_F: 0.34761 (95%-conf.int. 0.29479 - 0.39871)
===========================
1 ROUGE-2 Average_R: 0.20280 (95%-conf.int. 0.14969 - 0.26244)
1 ROUGE-2 Average_P: 0.12772 (95%-conf.int. 0.08603 - 0.17752)
1 ROUGE-2 Average_F: 0.14798 (95%-conf.int. 0.10517 - 0.19240)
===========================
1 ROUGE-L Average_R: 0.32960 (95%-conf.int. 0.26501 - 0.39676)
1 ROUGE-L Average_P: 0.19880 (95%-conf.int. 0.15257 - 0.25136)
1 ROUGE-L Average_F: 0.23619 (95%-conf.int. 0.19073 - 0.28663)
---
When using longer predictions/gold, the difference is bigger.
**How can I reproduce same score as `files2rouge` ?**
@lhoestq
| 184 | [ROUGE] Different scores with `files2rouge`
It seems that the ROUGE score of `nlp` is lower than the one of `files2rouge`.
Here is a self-contained notebook to reproduce both scores : https://colab.research.google.com/drive/14EyAXValB6UzKY9x4rs_T3pyL7alpw_F?usp=sharing
---
`nlp` : (Only mid F-scores)
>rouge1 0.33508031962733364
rouge2 0.14574333776191592
rougeL 0.2321187823256159
`files2rouge` :
>Running ROUGE...
===========================
1 ROUGE-1 Average_R: 0.48873 (95%-conf.int. 0.41192 - 0.56339)
1 ROUGE-1 Average_P: 0.29010 (95%-conf.int. 0.23605 - 0.34445)
1 ROUGE-1 Average_F: 0.34761 (95%-conf.int. 0.29479 - 0.39871)
===========================
1 ROUGE-2 Average_R: 0.20280 (95%-conf.int. 0.14969 - 0.26244)
1 ROUGE-2 Average_P: 0.12772 (95%-conf.int. 0.08603 - 0.17752)
1 ROUGE-2 Average_F: 0.14798 (95%-conf.int. 0.10517 - 0.19240)
===========================
1 ROUGE-L Average_R: 0.32960 (95%-conf.int. 0.26501 - 0.39676)
1 ROUGE-L Average_P: 0.19880 (95%-conf.int. 0.15257 - 0.25136)
1 ROUGE-L Average_F: 0.23619 (95%-conf.int. 0.19073 - 0.28663)
---
When using longer predictions/gold, the difference is bigger.
**How can I reproduce same score as `files2rouge` ?**
@lhoestq
You're right, there's a pretty interesting trade-off here between robustness and sensitivity :) The flip side of your argument is that we also still want the metric to be sensitive to model mistakes. How we think about number normalization for example has evolved a fair bit since the Perl script was written: at the time, ROUGE was used mostly to evaluate short-medium text summarization systems, where there were only a few numbers in the input and it was assumed that the most popular methods in use at the time would get those right. However, as your example showcases, that assumption does not hold any more, and we do want to be able to penalize a model that generates a wrong numerical value.
Also, we think that abstracting away tokenization differences is the role of the model/tokenizer: if you use the 🤗Tokenizers library for example, it will handle that for you ;)
Finally, there is a lot of active research on developing model-powered metrics that are both more sensitive and more robust than ROUGE. Check out for example BERTscore, which is implemented in this library! | [
-0.14572681486606598,
-0.16974392533302307,
-0.19722990691661835,
0.33974677324295044,
-0.11949792504310608,
-0.42426010966300964,
-0.42039984464645386,
0.14767369627952576,
-0.2700444161891937,
0.17250652611255646,
-0.08286791294813156,
0.18038815259933472,
0.12033069878816605,
0.008093969896435738,
-0.10038959980010986,
-0.09797526895999908,
0.1656545251607895,
0.03882867097854614,
0.0924806147813797,
-0.3720676898956299,
0.066559337079525,
0.5696004629135132,
-0.03133261203765869,
0.21043483912944794,
0.05402218550443649,
0.2702386677265167,
0.2851133644580841,
0.30352964997291565,
-0.1485796421766281,
0.028436988592147827,
0.12800218164920807,
0.030641354620456696,
-0.02369792014360428,
0.22214922308921814,
-0.00010886789095820859,
-0.2347189486026764,
0.10260987281799316,
-0.00316624715924263,
-0.27572283148765564,
-0.3026086688041687,
-0.0345572903752327,
0.06436429917812347,
-0.12292841076850891,
-0.07039455324411392,
0.08584661036729813,
-0.04489266499876976,
0.04877201467752457,
0.2095426619052887,
0.4293983578681946,
0.14757375419139862,
0.22625458240509033,
-0.3024369776248932,
-0.18534868955612183,
0.024081934243440628,
0.5763345956802368,
0.1626754105091095,
-0.11448337137699127,
0.4472644627094269,
0.005699165165424347,
-0.3526371419429779,
-0.24019041657447815,
-0.008564136922359467,
0.3430408537387848,
-0.17255935072898865,
0.13255922496318817,
0.19315513968467712,
0.1485852599143982,
-0.04594065248966217,
-0.07953556627035141,
0.24472832679748535,
-0.2702813148498535,
0.03221157193183899,
-0.22717098891735077,
-0.2778374254703522,
-0.0763154923915863,
-0.19976060092449188,
0.11689166724681854,
-0.08144556730985641,
0.16428537666797638,
0.012247947975993156,
0.044132381677627563,
0.2954266369342804,
0.04963909834623337,
0.007164034992456436,
-0.054055385291576385,
-0.10784557461738586,
0.05084608495235443,
0.09846597909927368,
0.29527971148490906,
-0.050543226301670074,
-0.5163146257400513,
0.010772094130516052,
-0.2593674659729004,
0.07496051490306854,
-0.3022814691066742,
-0.037855636328458786,
0.31449607014656067,
0.4659731090068817,
-0.20087093114852905,
0.4996267557144165,
0.2691965401172638,
-0.0934176966547966,
-0.13220703601837158,
-0.03944692760705948,
-0.13782444596290588,
0.10813266038894653,
-0.028946541249752045,
0.020693469792604446,
0.08811824768781662,
0.2246808260679245,
-0.13358275592327118,
-0.012008216232061386,
0.398222953081131,
-0.5637694597244263,
-0.47779831290245056,
0.10259105265140533,
-0.2610342502593994,
-0.43239712715148926,
-0.6891927719116211,
-0.06736093759536743,
-0.25543132424354553,
-0.11924251168966293,
0.09890831261873245,
0.22720104455947876,
-0.1748848706483841,
0.29229775071144104,
0.046788617968559265,
0.1833907961845398,
-0.28950414061546326,
0.019662335515022278,
-0.18399952352046967,
0.06357942521572113,
-0.3143925666809082,
0.13452425599098206,
0.17056594789028168,
0.11274605989456177,
0.3180578649044037,
0.2560538947582245,
0.27351248264312744,
0.03864358365535736,
0.3298662602901459,
-0.28395089507102966,
-0.022635363042354584,
-0.21111632883548737,
-0.21139101684093475,
0.19745370745658875,
0.027128886431455612,
0.09184889495372772,
-0.008701689541339874,
-0.07489361613988876,
-0.18084082007408142,
0.14423638582229614,
0.46661776304244995,
0.20658016204833984,
0.1496511995792389,
-0.11055412888526917,
0.0406920462846756,
0.1169372946023941,
-0.24016308784484863,
-0.5936912894248962,
0.20406046509742737,
-0.13655175268650055,
-0.12701159715652466,
-0.05817777290940285,
0.10982012003660202,
-0.03458242118358612,
0.09312103688716888,
-0.11743132770061493,
0.3731987178325653,
0.06358182430267334,
0.26031294465065,
0.4534834623336792,
-0.04083108901977539,
0.01186465471982956,
-0.16285665333271027,
-0.07088559120893478,
0.4665316641330719,
-0.43853095173835754,
-0.22229687869548798,
0.3354998826980591,
-0.16507023572921753,
-0.06518608331680298,
0.2390466332435608,
0.039275988936424255,
-0.3886536955833435,
-0.1660069078207016,
0.17745031416416168,
0.19752462208271027,
0.07779914885759354,
-0.04839682951569557,
-0.2970067858695984,
0.13495878875255585,
0.3166254758834839,
0.0654771476984024,
-0.23182784020900726,
-0.2993497848510742,
-0.11140484362840652,
-0.06439181417226791,
0.514197051525116,
0.13280721008777618,
-0.2751377820968628,
0.10499174892902374,
-0.2721591889858246,
0.2936933636665344,
-0.05169518291950226,
0.1185731515288353,
0.4230370819568634,
-0.02337534911930561,
-0.7951251268386841,
-0.16027691960334778,
0.43703293800354004,
-0.05248725414276123,
-0.2122921645641327,
-0.47140875458717346,
0.24053315818309784,
-0.23946473002433777,
0.22328287363052368,
0.055049411952495575,
0.18732194602489471,
0.03035423904657364,
0.02407148852944374,
0.09660723805427551,
-0.23642680048942566,
-0.15861909091472626,
-0.17153595387935638,
0.20367786288261414,
-0.22109945118427277,
-0.007433035410940647,
-0.010540366172790527,
0.3596077859401703,
0.31164130568504333,
0.08758017420768738,
0.03730412572622299,
0.26341819763183594,
0.050155505537986755,
0.0980498269200325,
0.3672504425048828,
0.1448051631450653,
-0.0007640253752470016,
0.1889611780643463,
-0.12266073375940323,
0.6879806518554688,
0.016462940722703934,
0.03225133568048477,
-0.34003961086273193,
0.42591530084609985,
-0.21703888475894928,
0.20069116353988647,
0.4093107581138611,
-0.07173743844032288,
-0.050097495317459106,
0.05778001621365547,
-0.006799564231187105,
-0.017152976244688034,
0.7467243671417236,
0.1952691674232483,
0.2502555549144745,
0.002956695854663849,
-0.3220258355140686,
0.2596171498298645,
0.3991404175758362,
-0.015342838130891323,
-0.020852625370025635,
-0.11995432525873184,
0.1937142014503479,
-0.09338856488466263,
-0.03672000765800476,
0.25073885917663574,
0.3810698390007019,
0.19513367116451263,
0.15570716559886932,
-0.1311991810798645,
-0.33823680877685547,
-0.3438020944595337,
0.03513295203447342,
-0.18210352957248688,
0.08744704723358154,
0.4963866174221039,
0.10160735994577408,
0.21628685295581818,
-0.3020772635936737,
-0.5422850847244263,
-0.25364819169044495,
-0.22231410443782806,
0.06132550165057182,
0.16164565086364746,
-0.14391349256038666,
-0.3678344488143921,
-0.15366095304489136,
-0.0919032171368599,
-0.2918884754180908,
-0.2732764482498169,
0.2300969362258911,
0.020874908193945885,
-0.07249949127435684,
-0.2189374715089798,
0.02323257550597191,
0.14874732494354248,
-0.37039417028427124,
0.1783812940120697,
-0.017374012619256973,
-0.028042834252119064,
-0.27953851222991943,
0.22281798720359802,
-0.05679866671562195,
-0.01930420473217964,
-0.03147614002227783,
-0.2791869640350342,
-0.45083630084991455,
0.16968809068202972,
-0.3762677013874054,
-0.010960057377815247,
0.06464451551437378,
-0.0032363757491111755,
0.05967199429869652,
-0.2506176233291626,
-0.07057526707649231,
0.14640071988105774,
0.09220800548791885,
-0.1741306185722351,
-0.35074377059936523,
-0.08965122699737549,
0.03678468242287636,
0.014213903807103634,
-0.19140614569187164,
-0.27752187848091125,
0.07937449216842651,
-0.14331994950771332,
0.6197946071624756,
0.3270139694213867,
0.005700867623090744,
0.3858785927295685,
-0.2369554340839386,
0.00001177145168185234,
0.17174258828163147,
0.5837677121162415,
-0.2605840563774109,
-0.04442854970693588,
0.19860902428627014,
-0.2997126579284668,
-0.4421888589859009,
-0.2730613946914673,
0.18830057978630066,
0.03232206031680107,
-0.008429164066910744,
-0.17861716449260712,
0.031004078686237335,
-0.1309441179037094,
-0.04899725317955017,
-0.2130453884601593,
-0.05581780523061752,
0.33782681822776794,
-0.1836601346731186,
-0.2421920895576477,
-0.06447437405586243,
0.21673373878002167,
0.029940642416477203,
0.28654640913009644,
0.4599356949329376,
-0.4840274751186371,
0.1646125614643097,
-0.1400940716266632,
0.12755994498729706,
0.04408307000994682,
0.5117960572242737,
0.1533815860748291,
0.1332312375307083,
0.0008752048015594482,
-0.14067688584327698,
0.09818042814731598,
0.4896940290927887,
0.056188441812992096,
-0.14490284025669098,
0.3308490812778473,
0.20873358845710754,
0.24980415403842926,
-0.11164984852075577,
-0.04191560670733452,
-0.07632186263799667,
-0.00791233777999878,
0.10350729525089264,
0.07728653401136398,
-0.05600050836801529,
0.017135661095380783,
0.07414527982473373,
-0.0036139339208602905,
-0.15379199385643005,
0.21246279776096344,
0.07286881655454636,
0.39130184054374695,
-0.11124485731124878,
-0.25944772362709045,
-0.005773358047008514,
-0.46897637844085693,
-0.005584202706813812,
0.031853336840867996,
-0.021542735397815704,
-0.15841075778007507,
-0.17286941409111023,
0.05907169356942177,
-0.3485898971557617,
0.26234251260757446,
0.16069412231445312,
0.23712927103042603,
0.16907617449760437,
-0.13415351510047913,
-0.5272519588470459,
-0.294148325920105,
-0.3322208523750305,
0.18113453686237335,
0.596076488494873,
0.11514388769865036,
-0.13822150230407715,
-0.17282268404960632,
0.10999258607625961,
-0.05185077711939812,
-0.14824798703193665,
0.10066777467727661,
-0.33127161860466003,
0.20241904258728027,
0.15132899582386017,
-0.2806145250797272,
0.04583745449781418,
0.3753645718097687,
-0.24381005764007568,
0.12480206787586212,
0.06615749001502991,
-0.1499929428100586,
0.2123294323682785,
0.13495224714279175,
0.33930909633636475,
-0.10402191430330276,
-0.24397088587284088,
-0.29319772124290466,
0.30135542154312134,
-0.3514430522918701,
0.3701417148113251,
0.1212446391582489,
0.0003355368971824646,
0.30029138922691345,
-0.09358739852905273,
0.10684163123369217,
0.3101273477077484,
-0.18164154887199402,
0.1664067804813385,
-0.6221522092819214,
0.11270289123058319,
-0.44617894291877747,
-0.2102094292640686,
0.36847415566444397,
-0.07535791397094727,
0.2850716710090637,
-0.1410284787416458,
0.2084536850452423,
0.23064105212688446,
-0.47709769010543823,
-0.07949845492839813,
-0.16209423542022705,
-0.19412687420845032,
0.2774372696876526,
-0.02041754126548767,
0.7596277594566345,
0.4354732036590576,
0.5633991360664368,
0.23021692037582397,
-0.1473512500524521,
0.38939782977104187,
-0.5955854058265686,
0.19127970933914185,
-0.34151583909988403,
-0.37023502588272095,
0.09574323892593384,
0.10443316400051117,
-0.06511325389146805,
0.21454881131649017,
0.20764991641044617,
0.2953759431838989,
0.39312154054641724,
-0.09911176562309265,
-0.10828026384115219,
0.17655311524868011,
0.12343072891235352,
0.18754130601882935,
-0.2870902717113495,
0.1991366744041443,
0.34644365310668945,
0.004576649516820908,
-0.05969361588358879,
0.0959683433175087,
-0.7420675754547119,
0.02251587063074112,
0.04249122738838196,
0.10044645518064499,
-0.09559989720582962,
0.35474252700805664,
0.11958041787147522,
-0.2243277132511139,
-0.04871850088238716,
0.3672390878200531,
0.15987490117549896,
-0.015912584960460663,
0.00719662569463253,
0.21002444624900818,
-0.3194081783294678,
0.32633107900619507,
0.242310032248497,
-0.03880351036787033,
0.031407780945301056,
-0.22021397948265076,
-0.0787142813205719,
-0.07076065987348557,
0.15572455525398254,
-0.16848213970661163,
-0.5484740734100342,
0.18215541541576385,
-0.33470314741134644,
0.007207001093775034,
-0.02991698868572712,
0.10068950057029724,
-0.09960559010505676,
-0.05343038588762283,
0.16725941002368927,
-0.05686335265636444,
-0.06265363842248917,
-0.03488510102033615,
0.09307181090116501,
-0.33285802602767944,
-0.050463635474443436,
0.47442546486854553,
-0.13673809170722961,
-0.04600970447063446,
0.06487441807985306,
-0.3305659294128418,
0.0352669283747673,
-0.24317610263824463,
0.03892479091882706,
-0.08075741678476334,
-0.19715386629104614,
-0.10430090129375458,
-0.007580584846436977,
-0.2291492074728012,
0.25272732973098755,
0.25843656063079834,
0.24956685304641724,
0.21303749084472656,
0.032852623611688614,
-0.36308497190475464,
-0.09832554310560226,
0.0810789093375206,
0.16799978911876678,
-0.03473341092467308,
-0.019618384540081024,
-0.1595887839794159,
0.2588408589363098,
0.23063212633132935,
-0.35463544726371765,
-0.15017247200012207,
-0.08997658640146255,
0.12681715190410614,
-0.22102300822734833,
-0.31873926520347595,
0.022486412897706032,
0.1468534916639328,
0.14308585226535797,
-0.008150145411491394,
-0.05782918632030487,
-0.24771744012832642,
-0.20516616106033325,
0.083225779235363,
-0.04834723472595215,
-0.09744089841842651,
-0.13200169801712036,
0.21839922666549683,
0.1043625921010971,
-0.14063486456871033,
-0.2313222736120224,
-0.13392606377601624,
0.3573988676071167,
0.12174542248249054,
-0.08553825318813324,
0.1825152337551117,
-0.1426304578781128,
0.1086663231253624,
0.01882341504096985,
-0.02538543939590454,
0.07357704639434814,
-0.026512712240219116,
0.10945796221494675,
-0.20184220373630524,
-0.2564111351966858,
-0.07424164563417435,
-0.28038954734802246,
0.14717337489128113,
0.10414642840623856,
-0.05297304689884186,
0.008782848715782166,
-0.18328946828842163,
0.2844215929508209,
0.36497512459754944,
0.11780503392219543,
-0.09963665157556534,
-0.013917770236730576,
0.22528287768363953,
-0.22220194339752197,
0.09425365179777145,
0.4496179521083832,
0.043986815959215164,
0.06563544273376465,
-0.028284482657909393,
0.15857842564582825,
-0.20769783854484558,
-0.018284879624843597,
-0.05924851819872856,
-0.274423748254776,
-0.01816922426223755,
0.17280733585357666,
-0.19119597971439362,
0.2515231966972351,
0.07363121956586838,
0.15538182854652405,
-0.37914836406707764,
0.1871822029352188,
0.35076963901519775,
-0.0025786757469177246,
0.1941520869731903,
-0.2856433689594269,
0.14951317012310028,
-0.02367575466632843,
0.09032042324542999,
-0.2703600227832794,
0.34511232376098633,
0.0853983536362648,
-0.02180592715740204,
0.08363571763038635,
0.16912135481834412,
-0.10833384096622467,
-0.3376132547855377,
-0.004882588982582092,
-0.08809277415275574,
-0.07047510892152786,
-0.544400155544281,
-0.4664246141910553,
-0.22646990418434143,
-0.394583523273468,
0.0710502415895462,
-0.16874070465564728,
0.3817867636680603,
0.02951917052268982,
0.24772146344184875,
-0.09672556817531586,
-0.18267740309238434,
-0.46176448464393616,
0.01024707779288292,
0.4208807945251465,
-0.04675701633095741,
0.17743246257305145,
0.21671605110168457,
0.41431334614753723,
0.35717928409576416,
0.1616116166114807,
0.2387458086013794,
0.1888272762298584,
-0.23361444473266602,
-0.2279309630393982,
0.03246691823005676,
0.08932045102119446,
-0.19615799188613892,
0.17421609163284302,
0.25997745990753174,
0.043390270322561264,
0.3002178966999054,
0.1322067826986313,
-0.2410818189382553,
0.07742059230804443,
0.26498717069625854,
-0.003574555739760399,
-0.21413002908229828,
0.29473719000816345,
-0.03916162997484207,
0.018681995570659637,
-0.3314741849899292,
0.3797486424446106,
-0.5077441334724426,
-0.08658870309591293,
-0.5439391136169434,
0.15140368044376373,
0.17864581942558289,
-0.12435458600521088,
0.10393225401639938,
0.26889368891716003,
0.41731470823287964,
-0.12723563611507416,
0.33877450227737427,
-0.28413742780685425,
-0.4613204002380371,
-0.2653636336326599,
-0.04584982246160507,
0.03950878977775574,
0.27052927017211914,
-0.4309377372264862,
0.28873559832572937,
-0.29741546511650085,
0.051449984312057495,
0.27456027269363403,
0.4283304512500763,
0.24691930413246155,
0.06649784743785858,
-0.33822938799858093,
0.1559208780527115,
0.19840247929096222,
-0.08824513852596283,
-0.11956954002380371,
0.1306329071521759,
-0.17390617728233337,
0.019816752523183823,
0.10971526056528091,
0.0855555534362793,
-0.3465362787246704,
-0.28865334391593933,
0.4207552969455719,
0.3385229706764221,
0.275066614151001,
0.2680865228176117,
-0.37258201837539673,
-0.3853943943977356,
0.031004125252366066,
-0.12375257909297943,
-0.06270965933799744,
0.06228291243314743,
-0.06584185361862183,
0.38764387369155884,
0.02506408654153347,
0.07477395981550217,
0.07386114448308945,
0.5041284561157227,
0.055955611169338226,
0.0017196849221363664,
-0.22702951729297638,
-0.026206813752651215,
0.09364626556634903,
0.0634227991104126,
-0.6129947304725647,
0.407443642616272,
0.0005168020725250244,
0.18714407086372375,
-0.23370829224586487,
-0.25390002131462097,
0.3750455975532532,
-0.35842156410217285,
0.2720431089401245,
-0.0997019112110138,
0.34275418519973755,
0.22176191210746765,
0.29680517315864563,
0.04679156094789505,
-0.10589517652988434,
0.07175469398498535,
0.29574763774871826,
0.1622447669506073,
0.23034629225730896,
-0.2334200143814087,
-0.08380287140607834,
-0.0016767457127571106,
0.29279518127441406,
0.06492644548416138,
-0.29197126626968384,
0.41343367099761963,
-0.18410754203796387
] |
https://github.com/huggingface/datasets/issues/224 | [Feature Request/Help] BLEURT model -> PyTorch | Hitting this error when using bleurt with PyTorch ...
```
UnrecognizedFlagError: Unknown command line flag 'f'
```
... and I'm assuming because it was built for TF specifically. Is there a way to use this metric in PyTorch? | Hi, I am interested in porting google research's new BLEURT learned metric to PyTorch (because I wish to do something experimental with language generation and backpropping through BLEURT). I noticed that you guys don't have it yet so I am partly just asking if you plan to add it (@thomwolf said you want to do so on Twitter).
I had a go of just like manually using the checkpoint that they publish which includes the weights. It seems like the architecture is exactly aligned with the out-of-the-box BertModel in transformers just with a single linear layer on top of the CLS embedding. I loaded all the weights to the PyTorch model but I am not able to get the same numbers as the BLEURT package's python api. Here is my colab notebook where I tried https://colab.research.google.com/drive/1Bfced531EvQP_CpFvxwxNl25Pj6ptylY?usp=sharing . If you have any pointers on what might be going wrong that would be much appreciated!
Thank you muchly! | 38 | [Feature Request/Help] BLEURT model -> PyTorch
Hi, I am interested in porting google research's new BLEURT learned metric to PyTorch (because I wish to do something experimental with language generation and backpropping through BLEURT). I noticed that you guys don't have it yet so I am partly just asking if you plan to add it (@thomwolf said you want to do so on Twitter).
I had a go of just like manually using the checkpoint that they publish which includes the weights. It seems like the architecture is exactly aligned with the out-of-the-box BertModel in transformers just with a single linear layer on top of the CLS embedding. I loaded all the weights to the PyTorch model but I am not able to get the same numbers as the BLEURT package's python api. Here is my colab notebook where I tried https://colab.research.google.com/drive/1Bfced531EvQP_CpFvxwxNl25Pj6ptylY?usp=sharing . If you have any pointers on what might be going wrong that would be much appreciated!
Thank you muchly!
Hitting this error when using bleurt with PyTorch ...
```
UnrecognizedFlagError: Unknown command line flag 'f'
```
... and I'm assuming because it was built for TF specifically. Is there a way to use this metric in PyTorch? | [
0.0004875287413597107,
-0.19439971446990967,
0.0977800041437149,
0.14103549718856812,
0.28600651025772095,
-0.21947556734085083,
0.29816094040870667,
0.17576207220554352,
0.16847142577171326,
0.15842986106872559,
-0.22391526401042938,
0.20470955967903137,
-0.47158321738243103,
0.24365346133708954,
-0.03945283219218254,
-0.09374237060546875,
-0.18991327285766602,
-0.03363172709941864,
0.1052035465836525,
-0.015584971755743027,
-0.09069801867008209,
0.2365892231464386,
0.04565010964870453,
-0.02871144562959671,
-0.31746068596839905,
0.35048094391822815,
0.05521952360868454,
0.055927153676748276,
-0.14533692598342896,
-0.032764554023742676,
0.3463771343231201,
-0.1924692839384079,
0.2557666003704071,
0.7926076650619507,
-0.00012355622311588377,
-0.2130509316921234,
0.06719064712524414,
-0.011289679445326328,
-0.27556076645851135,
-0.30580538511276245,
0.4654071033000946,
-0.2523364722728729,
0.0014711632393300533,
-0.2047473043203354,
-0.027092352509498596,
-0.06222647801041603,
-0.2024286985397339,
-0.08055980503559113,
0.008652262389659882,
0.3162081837654114,
0.040686558932065964,
0.2029191106557846,
0.0005703046917915344,
0.07062731683254242,
0.09595900774002075,
-0.10697981715202332,
-0.11937206983566284,
0.5899260640144348,
0.19050449132919312,
-0.039017993956804276,
-0.19934436678886414,
0.16511176526546478,
0.1557428538799286,
0.22187592089176178,
0.781131386756897,
0.03963211923837662,
-0.10514868050813675,
0.007861129939556122,
0.051743365824222565,
0.35052239894866943,
-0.0570165291428566,
-0.23309963941574097,
-0.24215416610240936,
0.18319877982139587,
0.068288154900074,
-0.2815703749656677,
-0.25224000215530396,
0.052199751138687134,
0.04698941484093666,
-0.27747398614883423,
-0.3826291263103485,
-0.3548019528388977,
-0.25620725750923157,
0.13442924618721008,
-0.26187700033187866,
0.39998865127563477,
-0.0648723617196083,
-0.05895049870014191,
0.18283896148204803,
0.05480562150478363,
0.20971029996871948,
-0.012297403067350388,
0.357552707195282,
0.3185586929321289,
0.045000024139881134,
-0.22733232378959656,
0.15663954615592957,
-0.14627161622047424,
0.0655384361743927,
-0.24303464591503143,
-0.2348577231168747,
0.12916642427444458,
-0.31121769547462463,
0.009082503616809845,
-0.005182210355997086,
0.4701380431652069,
0.038915686309337616,
0.37499338388442993,
0.350391149520874,
0.2842978835105896,
-0.029754575341939926,
-0.07869093120098114,
-0.06778586655855179,
-0.25944027304649353,
0.28838038444519043,
0.16139480471611023,
-0.21710926294326782,
-0.3110698163509369,
-0.1479407250881195,
-0.058148615062236786,
-0.1836259663105011,
-0.21360017359256744,
0.38544076681137085,
0.24474015831947327,
-0.3576725423336029,
-0.11658535152673721,
0.5851033926010132,
0.05813033878803253,
-0.2100522369146347,
0.0859038382768631,
-0.09296082705259323,
-0.09709036350250244,
-0.29787325859069824,
0.08617281913757324,
0.20618440210819244,
-0.1500415951013565,
0.20931978523731232,
-0.10786916315555573,
0.6836860179901123,
0.13581722974777222,
0.18622775375843048,
0.333433598279953,
0.08329427987337112,
-0.1664721518754959,
-0.24997058510780334,
-0.40275388956069946,
0.25848880410194397,
0.09364005923271179,
-0.17199425399303436,
0.06458362936973572,
-0.11431395262479782,
-0.3340190649032593,
-0.2537508010864258,
0.0032773101702332497,
-0.29372066259384155,
-0.13937141001224518,
0.04673631861805916,
0.3141668736934662,
0.0852745771408081,
-0.29998788237571716,
0.021874941885471344,
-0.2990492582321167,
-0.25199851393699646,
0.09707091003656387,
0.2996886968612671,
-0.3436623215675354,
-0.3732588589191437,
-0.4258340895175934,
0.11342962086200714,
0.3820705711841583,
0.22695305943489075,
0.14589886367321014,
-0.15026432275772095,
-0.11249729245901108,
0.180483877658844,
-0.3285110592842102,
0.3918129503726959,
0.03860662505030632,
-0.1812959760427475,
-0.23008078336715698,
0.10167472064495087,
-0.2862394154071808,
-0.21849629282951355,
0.06395968049764633,
-0.1890784204006195,
-0.1219702959060669,
0.32159721851348877,
0.2692631781101227,
-0.15223830938339233,
-0.11927391588687897,
-0.23923271894454956,
-0.2757665812969208,
0.23823878169059753,
0.1066085696220398,
0.3859720230102539,
-0.018501952290534973,
0.15808379650115967,
0.5193025469779968,
0.018723219633102417,
-0.4093892276287079,
-0.04577060043811798,
-0.13258491456508636,
0.3818323016166687,
-0.2926695942878723,
0.39089125394821167,
-0.320676326751709,
-0.12131329625844955,
0.23700359463691711,
-0.22047315537929535,
0.3617454767227173,
0.19992277026176453,
0.11520010232925415,
-0.10204403847455978,
-0.04495716840028763,
0.34095436334609985,
0.03917757049202919,
-0.11112780123949051,
-0.14549946784973145,
-0.23571977019309998,
-0.19972245395183563,
-0.20017972588539124,
-0.33275479078292847,
-0.2919325530529022,
-0.0543326810002327,
0.4235488176345825,
0.2041720747947693,
-0.03850071132183075,
-0.08839352428913116,
-0.08542560786008835,
0.42085832357406616,
0.13108524680137634,
0.21697238087654114,
-0.12121257930994034,
-0.20755881071090698,
0.13657215237617493,
-0.28143829107284546,
0.24335289001464844,
0.2878012955188751,
0.34533360600471497,
-0.08362184464931488,
0.1704852432012558,
0.2630351781845093,
-0.1229206994175911,
-0.0553075447678566,
-0.05954970419406891,
0.23119059205055237,
0.29891395568847656,
0.2667691111564636,
0.2532308101654053,
0.07388072460889816,
-0.28169938921928406,
0.05441199615597725,
0.012851081788539886,
0.012367136776447296,
0.4185680150985718,
-0.2691675126552582,
-0.14407937228679657,
-0.19352592527866364,
0.20795512199401855,
0.065392404794693,
0.3745553493499756,
-0.026033086702227592,
0.042966097593307495,
0.3506179749965668,
-0.29047855734825134,
-0.21643570065498352,
-0.12244248390197754,
-0.023048128932714462,
0.1722012311220169,
0.10130808502435684,
0.4216386377811432,
0.12463176250457764,
-0.10538530349731445,
0.07629331946372986,
-0.05406550318002701,
0.11428824067115784,
-0.1998913437128067,
-0.10426612943410873,
0.04114816337823868,
0.08948369324207306,
0.16858136653900146,
-0.019060129299759865,
0.06301812827587128,
0.1298634260892868,
-0.2475425750017166,
0.368917316198349,
0.033474162220954895,
0.3673948645591736,
-0.1088714599609375,
-0.3008711338043213,
-0.25574710965156555,
-0.18844883143901825,
0.008497297763824463,
0.253911554813385,
0.09166291356086731,
-0.1420186161994934,
0.0540216900408268,
0.46498996019363403,
-0.0766250267624855,
-0.14190179109573364,
-0.029270004481077194,
-0.36523035168647766,
-0.34538906812667847,
0.00930764526128769,
0.04194915294647217,
0.042097557336091995,
0.0964585542678833,
0.08965092897415161,
-0.03133619576692581,
-0.23312805593013763,
-0.7229450941085815,
0.004387848079204559,
-0.006775561720132828,
0.2805350720882416,
0.21111741662025452,
-0.08313450217247009,
-0.33911240100860596,
0.004088832065463066,
0.05235666781663895,
-0.5004477500915527,
-0.005801443941891193,
0.33237186074256897,
-0.3564043939113617,
0.08894755691289902,
-0.0786409080028534,
-0.10567044466733932,
-0.09344393759965897,
-0.07754145562648773,
-0.0709226131439209,
0.1984402984380722,
0.05370702967047691,
-0.058387286961078644,
-0.020465310662984848,
0.4024657607078552,
0.5086860656738281,
-0.048032745718955994,
-0.1685408502817154,
0.24041202664375305,
0.3423587679862976,
-0.3283785879611969,
-0.3037557899951935,
-0.0282772034406662,
0.06588000804185867,
0.02901761792600155,
0.005568805616348982,
-0.3014434576034546,
-0.4165246784687042,
-0.10350775718688965,
-0.07528005540370941,
0.0514252707362175,
0.20570337772369385,
0.024882882833480835,
0.024753913283348083,
0.07889006286859512,
-0.29824864864349365,
-0.20026525855064392,
-0.019337251782417297,
0.14835575222969055,
0.7090576887130737,
-0.15822094678878784,
-0.1775602400302887,
0.14850440621376038,
0.8652079701423645,
0.01294020563364029,
-0.45980194211006165,
0.10806562006473541,
0.17440694570541382,
0.09269344806671143,
0.015705883502960205,
-0.21939322352409363,
0.2692299783229828,
-0.3033927083015442,
-0.17277409136295319,
0.3044235408306122,
0.10612741112709045,
-0.12558645009994507,
-0.27443021535873413,
-0.12407653033733368,
0.5246573686599731,
-0.13078711926937103,
0.0432763397693634,
0.08086720108985901,
0.027793578803539276,
-0.05913827195763588,
-0.13328993320465088,
-0.335997611284256,
-0.11665208637714386,
0.2886207401752472,
0.08492168039083481,
-0.016899973154067993,
0.04680157080292702,
0.4622916579246521,
-0.1196925938129425,
-0.5215777158737183,
0.4779226779937744,
0.14861798286437988,
-0.6269400119781494,
0.03034314140677452,
-0.09077312797307968,
-0.01497764140367508,
-0.004339289385825396,
-0.30573010444641113,
0.08299004286527634,
0.02205529808998108,
-0.02300373651087284,
0.047544971108436584,
-0.2639550566673279,
0.11107394099235535,
-0.13539643585681915,
-0.3203109800815582,
0.4749372601509094,
0.2835904061794281,
-0.3579861521720886,
0.060252055525779724,
0.2661556303501129,
0.3918269872665405,
-0.16820651292800903,
-0.044259700924158096,
-0.38714534044265747,
-0.24752110242843628,
0.05117461085319519,
-0.16052791476249695,
0.05983017385005951,
0.26893991231918335,
0.06399001181125641,
0.15757091343402863,
0.14858344197273254,
-0.05238517373800278,
0.15332116186618805,
0.06338642537593842,
0.06765417754650116,
-0.03543105721473694,
0.036598119884729385,
0.15093505382537842,
-0.05382128059864044,
0.16688156127929688,
0.311791330575943,
-0.4149140417575836,
-0.4968370199203491,
0.13977214694023132,
0.2661862373352051,
0.21740731596946716,
0.03490883857011795,
0.07774905860424042,
-0.10712722688913345,
0.3252790570259094,
0.3136734962463379,
0.17274144291877747,
0.3225984573364258,
0.15361593663692474,
0.31555381417274475,
0.11419904977083206,
-0.1838606595993042,
0.3391721546649933,
-0.11920882761478424,
0.12232592701911926,
0.34898805618286133,
0.029947329312562943,
-0.027535466477274895,
0.06459630280733109,
0.5371322631835938,
0.9507374167442322,
0.07198921591043472,
0.10562898218631744,
0.3453916609287262,
-0.21591255068778992,
0.33187928795814514,
-0.13465917110443115,
-0.054771460592746735,
-0.20902936160564423,
-0.27686482667922974,
-0.028736935928463936,
-0.00940077006816864,
-0.41684117913246155,
-0.30249524116516113,
-0.24513211846351624,
0.17041343450546265,
-0.37227344512939453,
-0.2893790900707245,
0.27391788363456726,
0.2895249128341675,
-0.012750349938869476,
0.026801928877830505,
0.2843709886074066,
0.07212065160274506,
-0.24628673493862152,
0.3137531578540802,
-0.06891941279172897,
-0.13711774349212646,
-0.12174910306930542,
0.11128251254558563,
-0.34428173303604126,
0.18231087923049927,
-0.14361527562141418,
-0.043186455965042114,
-0.1379406601190567,
-0.2727839946746826,
0.04846426472067833,
0.04304114356637001,
0.7600718140602112,
0.019665725529193878,
-0.3796805143356323,
0.2225048840045929,
-0.06933467835187912,
0.18749548494815826,
0.12327985465526581,
-0.11628518253564835,
0.3619278073310852,
-0.21870329976081848,
-0.08358802646398544,
-0.1212911531329155,
0.23607277870178223,
-0.4464300274848938,
0.16874206066131592,
-0.1505315899848938,
-0.16223563253879547,
0.01151440292596817,
0.2456081658601761,
0.23653148114681244,
0.11821115016937256,
-0.1011229157447815,
0.05867795646190643,
0.14740237593650818,
-0.23920926451683044,
0.032710086554288864,
0.04361782222986221,
-0.3119707703590393,
0.029099272564053535,
-0.04143796116113663,
-0.07832875847816467,
-0.009219510480761528,
0.22514592111110687,
0.18119826912879944,
-0.08502624928951263,
0.2331380546092987,
-0.5456886887550354,
0.48003166913986206,
-0.39778536558151245,
0.16316473484039307,
0.08292648196220398,
-0.033607445657253265,
0.08675375580787659,
0.7250291705131531,
0.4419584274291992,
0.13836205005645752,
-0.4551559388637543,
0.10337215662002563,
-0.38534581661224365,
0.05547995865345001,
-0.18755152821540833,
0.3016723394393921,
-0.21308249235153198,
0.16312822699546814,
-0.05166450887918472,
0.19557636976242065,
-0.19422325491905212,
-0.019207777455449104,
0.1287049949169159,
-0.1361647993326187,
0.05789325013756752,
-0.36982864141464233,
0.18015706539154053,
0.07099314033985138,
-0.2820511758327484,
-0.12980441749095917,
0.07917620986700058,
-0.0011406578123569489,
-0.49501511454582214,
0.1621682494878769,
0.23005986213684082,
-0.015350095927715302,
-0.32313966751098633,
-0.4455387592315674,
-0.057451631873846054,
-0.10607446730136871,
0.021053496748209,
0.14171037077903748,
0.04478997737169266,
0.3292349874973297,
-0.05912426486611366,
-0.04719097912311554,
-0.10356050729751587,
-0.05455074459314346,
0.46705278754234314,
0.22028081119060516,
0.11532847583293915,
0.012021519243717194,
0.34375685453414917,
0.0014599710702896118,
0.13209125399589539,
0.02976076677441597,
0.006227478384971619,
0.06046120077371597,
0.2978818416595459,
0.14499559998512268,
0.1928529441356659,
-0.3699391782283783,
0.229014053940773,
0.14820793271064758,
0.12221960723400116,
-0.1619810312986374,
0.17190229892730713,
0.03464827314019203,
-0.2363877147436142,
-0.20888032019138336,
-0.31774207949638367,
0.08207541704177856,
-0.17358574271202087,
0.13484278321266174,
-0.2804161012172699,
0.4191932678222656,
0.3138980269432068,
-0.09825557470321655,
-0.24227765202522278,
-0.22451098263263702,
0.068136066198349,
0.1616407185792923,
-0.18701015412807465,
0.31334683299064636,
0.40764638781547546,
0.11467598378658295,
0.20449267327785492,
-0.4011955261230469,
-0.14249026775360107,
0.06567273288965225,
-0.42258644104003906,
-0.08957509696483612,
0.3227171003818512,
0.11632966995239258,
-0.053208302706480026,
-0.1357431709766388,
0.17436088621616364,
-0.07144565135240555,
-0.19191372394561768,
0.395449161529541,
-0.3155260682106018,
-0.21161703765392303,
-0.08746601641178131,
0.35621920228004456,
0.1253102868795395,
0.09618903696537018,
0.10229560732841492,
-0.08662346750497818,
0.20117151737213135,
-0.05531684309244156,
0.033217210322618484,
0.15262728929519653,
-0.15838593244552612,
0.12446343898773193,
-0.04102522134780884,
0.26512834429740906,
-0.74640291929245,
0.2926129698753357,
0.2878526747226715,
0.14978192746639252,
-0.21726614236831665,
0.11766484379768372,
-0.013434730470180511,
-0.053702328354120255,
0.31686997413635254,
0.03299371153116226,
0.19358165562152863,
-0.37752828001976013,
-0.036859020590782166,
0.21869458258152008,
0.00196247361600399,
0.16003358364105225,
0.16048268973827362,
0.4990955889225006,
-0.18967550992965698,
0.05753704532980919,
-0.10264881700277328,
-0.14954744279384613,
0.4168829023838043,
-0.39484140276908875,
0.16702069342136383,
-0.061144061386585236,
0.872622013092041,
0.28352856636047363,
-0.15029379725456238,
-0.2694929242134094,
-0.08044754713773727,
-0.2182770073413849,
0.0842762440443039,
0.08718106150627136,
-0.12014051526784897,
0.07406158000230789,
-0.05157264694571495,
0.006864530965685844,
0.1870855689048767,
0.18445222079753876,
0.24675045907497406,
0.3651888966560364,
-0.27606475353240967,
0.31659793853759766,
-0.3954797089099884,
0.15575823187828064,
0.17428436875343323,
0.06074602156877518,
-0.04848933592438698,
-0.14108151197433472,
0.023486055433750153,
-0.11504451930522919,
0.2646304965019226,
-0.22524169087409973,
0.051122941076755524,
-0.18277771770954132,
-0.23931050300598145,
-0.34198781847953796,
-0.05003689229488373,
0.038902245461940765,
-0.031736794859170914,
-0.1246156319975853,
-0.06375440955162048,
-0.09632004052400589,
-0.12807002663612366,
-0.050185658037662506,
-0.29143333435058594,
0.39763709902763367,
0.3708544075489044,
0.15045663714408875,
-0.0725288838148117,
0.7684551477432251,
0.20320600271224976,
0.006717095151543617,
0.30119818449020386,
0.20140664279460907,
-0.11478064954280853,
-0.20222163200378418,
-0.037507813423871994,
0.19382283091545105,
-0.25180089473724365,
-0.26196107268333435,
-0.4261299967765808,
0.6186966896057129,
0.10939067602157593,
-0.47760042548179626,
-0.0888892114162445,
-0.22655119001865387,
-0.22605806589126587,
-0.13082444667816162,
0.2619841396808624,
0.4220671057701111,
0.07908143103122711,
0.032229527831077576,
-0.39357441663742065,
0.07538671791553497,
0.5604331493377686,
-0.42825835943222046,
-0.19135086238384247,
-0.01269717700779438,
0.18095439672470093,
0.239191472530365,
-0.30848655104637146,
-0.767350435256958,
-0.12440449744462967,
0.1188991442322731,
0.1689777672290802,
-0.16665229201316833,
0.23522740602493286,
0.13245025277137756,
0.2679494023323059,
-0.22290945053100586,
0.5535248517990112,
-0.07835764437913895,
-0.13849210739135742,
-0.41262978315353394,
-0.09996578842401505
] |
https://github.com/huggingface/datasets/issues/224 | [Feature Request/Help] BLEURT model -> PyTorch | We currently provide a wrapper on the TensorFlow implementation: https://huggingface.co/metrics/bleurt
We have long term plans to better handle model-based metrics, but they probably won't be implemented right away
@adamwlev it would still be cool to add the BLEURT checkpoints to the transformers repo if you're interested, but that would best be discussed there :)
closing for now | Hi, I am interested in porting google research's new BLEURT learned metric to PyTorch (because I wish to do something experimental with language generation and backpropping through BLEURT). I noticed that you guys don't have it yet so I am partly just asking if you plan to add it (@thomwolf said you want to do so on Twitter).
I had a go of just like manually using the checkpoint that they publish which includes the weights. It seems like the architecture is exactly aligned with the out-of-the-box BertModel in transformers just with a single linear layer on top of the CLS embedding. I loaded all the weights to the PyTorch model but I am not able to get the same numbers as the BLEURT package's python api. Here is my colab notebook where I tried https://colab.research.google.com/drive/1Bfced531EvQP_CpFvxwxNl25Pj6ptylY?usp=sharing . If you have any pointers on what might be going wrong that would be much appreciated!
Thank you muchly! | 57 | [Feature Request/Help] BLEURT model -> PyTorch
Hi, I am interested in porting google research's new BLEURT learned metric to PyTorch (because I wish to do something experimental with language generation and backpropping through BLEURT). I noticed that you guys don't have it yet so I am partly just asking if you plan to add it (@thomwolf said you want to do so on Twitter).
I had a go of just like manually using the checkpoint that they publish which includes the weights. It seems like the architecture is exactly aligned with the out-of-the-box BertModel in transformers just with a single linear layer on top of the CLS embedding. I loaded all the weights to the PyTorch model but I am not able to get the same numbers as the BLEURT package's python api. Here is my colab notebook where I tried https://colab.research.google.com/drive/1Bfced531EvQP_CpFvxwxNl25Pj6ptylY?usp=sharing . If you have any pointers on what might be going wrong that would be much appreciated!
Thank you muchly!
We currently provide a wrapper on the TensorFlow implementation: https://huggingface.co/metrics/bleurt
We have long term plans to better handle model-based metrics, but they probably won't be implemented right away
@adamwlev it would still be cool to add the BLEURT checkpoints to the transformers repo if you're interested, but that would best be discussed there :)
closing for now | [
0.03960353508591652,
-0.294548898935318,
0.0695950984954834,
0.16438624262809753,
0.27279844880104065,
-0.281116247177124,
0.3806678056716919,
0.14022669196128845,
0.14548735320568085,
0.1657414734363556,
-0.21056005358695984,
0.2934771180152893,
-0.4552498459815979,
0.22415979206562042,
0.06959349662065506,
-0.10988396406173706,
-0.05097750574350357,
0.03715774416923523,
0.10635839402675629,
-0.13577419519424438,
-0.10876131802797318,
0.16499070823192596,
0.05934944748878479,
-0.1525467485189438,
-0.2916155159473419,
0.3176150619983673,
0.019248859956860542,
0.025706477463245392,
-0.20944362878799438,
-0.05774233117699623,
0.2948092520236969,
-0.06041407212615013,
0.2058347761631012,
0.7945738434791565,
-0.00012249436986166984,
-0.267738401889801,
0.13256409764289856,
-0.025316013023257256,
-0.34068137407302856,
-0.2211291342973709,
0.38395199179649353,
-0.3060538172721863,
0.08232942968606949,
-0.1754467487335205,
0.04278825223445892,
-0.03406541049480438,
-0.24324075877666473,
-0.042656127363443375,
0.18749338388442993,
0.21665847301483154,
0.042248353362083435,
0.23043592274188995,
0.0012255571782588959,
0.1125812828540802,
0.13914158940315247,
-0.10558630526065826,
-0.10437044501304626,
0.5303356647491455,
0.27584004402160645,
-0.06240950524806976,
-0.19226285815238953,
0.23816801607608795,
0.07783679664134979,
0.10142309963703156,
0.6716704368591309,
0.03906027227640152,
-0.05559539049863815,
-0.06814546138048172,
0.0057654231786727905,
0.3251340687274933,
-0.1148088201880455,
-0.21514946222305298,
-0.3067004680633545,
0.08728203922510147,
0.07104206085205078,
-0.2673068046569824,
-0.21797055006027222,
0.1069883331656456,
0.10014531016349792,
-0.2690121829509735,
-0.41902437806129456,
-0.36483168601989746,
-0.19585199654102325,
0.07973796874284744,
-0.2726512551307678,
0.3813120126724243,
0.009816615842282772,
-0.15502551198005676,
0.13104580342769623,
0.1450662612915039,
0.3880736231803894,
-0.07437723129987717,
0.347133994102478,
0.27463987469673157,
-0.016507018357515335,
-0.30216899514198303,
0.2685924470424652,
-0.136091411113739,
-0.0050390176475048065,
-0.22477178275585175,
-0.16654254496097565,
0.20244866609573364,
-0.26308172941207886,
0.0775960311293602,
-0.04299274459481239,
0.4014994204044342,
-0.0002394840121269226,
0.37281325459480286,
0.32136309146881104,
0.40310484170913696,
0.10458315908908844,
-0.019626177847385406,
-0.07396245747804642,
-0.0863814577460289,
0.258507639169693,
0.19309937953948975,
-0.22396455705165863,
-0.2521964907646179,
-0.06776197999715805,
-0.020372584462165833,
-0.22098663449287415,
-0.24022755026817322,
0.33338066935539246,
0.19345812499523163,
-0.4989130198955536,
-0.023181702941656113,
0.5008065700531006,
0.0060212500393390656,
-0.16556993126869202,
0.10502782464027405,
-0.1418714076280594,
-0.12604521214962006,
-0.30947235226631165,
0.07590886950492859,
0.2528243064880371,
-0.16018125414848328,
0.2812947630882263,
-0.07687214016914368,
0.49812597036361694,
0.04750313609838486,
0.30355268716812134,
0.3707237243652344,
0.096248097717762,
-0.1441243588924408,
-0.20200631022453308,
-0.3485706150531769,
0.1855834424495697,
0.0507267490029335,
-0.1315109133720398,
-0.030971579253673553,
-0.11490444093942642,
-0.27944108843803406,
-0.07502098381519318,
0.050973307341337204,
-0.25767451524734497,
-0.05764269828796387,
0.02539883553981781,
0.3534553349018097,
0.09787649661302567,
-0.2471977025270462,
0.0006358996033668518,
-0.24852745234966278,
-0.1676691323518753,
0.06729397177696228,
0.39564600586891174,
-0.1806042641401291,
-0.3170182406902313,
-0.5069208145141602,
0.16817256808280945,
0.43953606486320496,
0.18799075484275818,
0.16617606580257416,
-0.24754562973976135,
-0.032942190766334534,
0.2556147575378418,
-0.34265583753585815,
0.27378490567207336,
0.11720743775367737,
-0.305671751499176,
-0.23019136488437653,
0.08945822715759277,
-0.3044486939907074,
-0.21890729665756226,
0.08569763600826263,
-0.14614686369895935,
-0.06445053219795227,
0.2756136953830719,
0.26867708563804626,
-0.17650912702083588,
-0.012937309220433235,
-0.2883862555027008,
-0.25624534487724304,
0.2462271749973297,
0.17889517545700073,
0.37698835134506226,
-0.037900738418102264,
0.15235093235969543,
0.538781464099884,
0.06697943806648254,
-0.38386017084121704,
-0.03002522699534893,
-0.156999871134758,
0.5144122242927551,
-0.46003031730651855,
0.38163986802101135,
-0.21484914422035217,
-0.11701158434152603,
0.17491978406906128,
-0.38291752338409424,
0.3466678559780121,
0.15802478790283203,
0.05973019450902939,
-0.08232412487268448,
0.00481763482093811,
0.3204120099544525,
-0.044858139008283615,
-0.07983560860157013,
-0.1922534704208374,
-0.2519010901451111,
-0.15173843502998352,
-0.23149123787879944,
-0.2959873676300049,
-0.18502183258533478,
-0.040659449994564056,
0.22060538828372955,
0.36955732107162476,
-0.021372562274336815,
-0.14678031206130981,
-0.08496762812137604,
0.3680126368999481,
0.1280679851770401,
0.16879601776599884,
-0.036535318940877914,
-0.20773816108703613,
0.1696757972240448,
-0.18458296358585358,
0.2581161558628082,
0.27523720264434814,
0.40712791681289673,
0.02619856223464012,
0.2872464954853058,
0.2546694576740265,
-0.10023227334022522,
-0.10496433079242706,
-0.2070123255252838,
0.2988642752170563,
0.30754148960113525,
0.23850303888320923,
0.29118162393569946,
0.09369339048862457,
-0.27139928936958313,
0.09760597348213196,
-0.060411788523197174,
0.17113259434700012,
0.39449170231819153,
-0.13852442800998688,
-0.08198687434196472,
-0.1640886515378952,
0.14725808799266815,
0.1415473222732544,
0.36072492599487305,
-0.052627794444561005,
0.017791762948036194,
0.23726016283035278,
-0.4145682156085968,
-0.28494346141815186,
-0.08580277115106583,
0.05542195960879326,
0.14266939461231232,
0.06415874511003494,
0.4149327576160431,
0.05140446126461029,
-0.0188014954328537,
0.0447479709982872,
-0.12116052955389023,
0.15478205680847168,
-0.2346334159374237,
-0.04626794904470444,
0.08961528539657593,
0.09873834997415543,
0.0901554748415947,
0.025140583515167236,
0.07456117868423462,
0.1143125370144844,
-0.14357632398605347,
0.3518413007259369,
0.13265903294086456,
0.42570608854293823,
-0.23266732692718506,
-0.3643445670604706,
-0.2572852075099945,
-0.2122786045074463,
0.03864738345146179,
0.3008294105529785,
0.07326662540435791,
-0.08552314341068268,
0.2842051386833191,
0.5591573119163513,
-0.0492175817489624,
-0.10149649530649185,
-0.063578300178051,
-0.29799944162368774,
-0.2619438171386719,
0.013049319386482239,
-0.047071781009435654,
0.021043960005044937,
-0.01213170401751995,
0.12732505798339844,
-0.07290872931480408,
-0.1648215502500534,
-0.791871964931488,
-0.007138855755329132,
0.06195426732301712,
0.2949560582637787,
0.12773045897483826,
-0.13784661889076233,
-0.3270549774169922,
-0.001270536333322525,
0.01725994236767292,
-0.40893107652664185,
-0.023082325235009193,
0.333400696516037,
-0.24032647907733917,
0.020099468529224396,
-0.03319774568080902,
-0.19501295685768127,
-0.12176128476858139,
-0.0371471643447876,
0.035057950764894485,
0.17747166752815247,
0.037284571677446365,
-0.12759655714035034,
0.11328987032175064,
0.32145223021507263,
0.42720887064933777,
-0.1533857136964798,
-0.03843604773283005,
0.1742308884859085,
0.4179564118385315,
-0.2875511050224304,
-0.3364487290382385,
-0.11314113438129425,
-0.04294079542160034,
0.09721885621547699,
0.02003619447350502,
-0.33385950326919556,
-0.3707353472709656,
-0.13501015305519104,
-0.15471312403678894,
0.16762450337409973,
0.21132662892341614,
0.08064785599708557,
0.13571622967720032,
0.08123931288719177,
-0.1643407940864563,
-0.11949416995048523,
-0.051210664212703705,
0.16528776288032532,
0.6772114634513855,
-0.2268790602684021,
-0.1361590325832367,
0.09984970092773438,
0.8651848435401917,
0.14755195379257202,
-0.45604637265205383,
0.036251723766326904,
0.3171021640300751,
0.025822825729846954,
-0.03095582127571106,
-0.291069895029068,
0.18813374638557434,
-0.24658456444740295,
-0.2843208312988281,
0.2827780842781067,
0.10243097692728043,
-0.29742860794067383,
-0.3031907081604004,
-0.20264632999897003,
0.506892204284668,
-0.12234582006931305,
0.07363028824329376,
0.11307651549577713,
0.0693340077996254,
-0.004519810900092125,
-0.06540961563587189,
-0.2938372790813446,
-0.12536656856536865,
0.24079278111457825,
-0.007610015571117401,
0.09480364620685577,
-0.037457797676324844,
0.44763636589050293,
0.003257923061028123,
-0.5484259128570557,
0.3487659692764282,
0.05293440446257591,
-0.5662438869476318,
0.14763320982456207,
-0.07294204831123352,
-0.039310112595558167,
-0.04653788357973099,
-0.3226349353790283,
0.07470069080591202,
0.036167632788419724,
-0.14837059378623962,
-0.06120404973626137,
-0.25290030241012573,
0.09232476353645325,
-0.22582730650901794,
-0.47378313541412354,
0.5314682126045227,
0.33735042810440063,
-0.38272061944007874,
0.09321527183055878,
0.22271139919757843,
0.31544360518455505,
-0.20287923514842987,
-0.01469384878873825,
-0.2976093292236328,
-0.2209089994430542,
0.07640571147203445,
-0.07465633004903793,
-0.026433972641825676,
0.22570650279521942,
-0.051201701164245605,
-0.027302740141749382,
0.1271093636751175,
-0.10163205116987228,
0.18122626841068268,
0.07489539682865143,
0.008387213572859764,
-0.02671448513865471,
0.15502208471298218,
0.11128585040569305,
-0.07816717028617859,
0.19248150289058685,
0.3351227343082428,
-0.41935256123542786,
-0.5140181183815002,
0.11239588260650635,
0.15022076666355133,
0.1733611822128296,
0.09620565921068192,
0.0997607633471489,
-0.010332837700843811,
0.40235763788223267,
0.28301751613616943,
0.16237877309322357,
0.26863452792167664,
0.13129714131355286,
0.4590049982070923,
0.06577195227146149,
-0.14670036733150482,
0.3369627296924591,
-0.1843062937259674,
0.029224611818790436,
0.3064761459827423,
-0.09339839220046997,
-0.026042615994811058,
0.17510423064231873,
0.45825260877609253,
0.9547624588012695,
0.11388440430164337,
0.07662218809127808,
0.2924111783504486,
-0.12001800537109375,
0.3372717797756195,
-0.2470250129699707,
0.05289619788527489,
-0.31194964051246643,
-0.37743079662323,
-0.03756645694375038,
-0.08929362893104553,
-0.4033791720867157,
-0.27996718883514404,
-0.20358093082904816,
0.11634592711925507,
-0.34473085403442383,
-0.22656014561653137,
0.3043632507324219,
0.32432472705841064,
0.07537992298603058,
0.021569836884737015,
0.287003755569458,
0.06190452724695206,
-0.20935119688510895,
0.31468191742897034,
-0.0779997855424881,
-0.23030854761600494,
-0.23614338040351868,
0.10131241381168365,
-0.187404602766037,
0.26554423570632935,
-0.057189591228961945,
-0.006722116842865944,
0.010055450722575188,
-0.3199191093444824,
0.07066012918949127,
0.06933721899986267,
0.7521310448646545,
0.11961214244365692,
-0.37206533551216125,
0.148244708776474,
-0.17030683159828186,
0.13719098269939423,
0.1343541443347931,
-0.16840770840644836,
0.36602407693862915,
-0.14322543144226074,
-0.16689930856227875,
-0.0825682207942009,
0.2166527807712555,
-0.2843283414840698,
0.16792216897010803,
-0.173920139670372,
-0.1123281717300415,
-0.07144229859113693,
0.4080495536327362,
0.32134342193603516,
0.07981818914413452,
-0.20158815383911133,
0.09625990688800812,
0.2228284776210785,
-0.2782500684261322,
0.08793088793754578,
0.13651295006275177,
-0.23687361180782318,
-0.00305919349193573,
0.021061338484287262,
-0.04544374346733093,
-0.07609303295612335,
0.20994733273983002,
0.18963415920734406,
-0.12245554476976395,
0.20275983214378357,
-0.5506261587142944,
0.5572553277015686,
-0.4292539358139038,
0.11070036888122559,
-0.13716785609722137,
-0.022318467497825623,
0.03415050730109215,
0.614263117313385,
0.46294867992401123,
0.17757567763328552,
-0.4233265221118927,
0.1225862205028534,
-0.42704424262046814,
0.10487539321184158,
-0.18003784120082855,
0.3510757386684418,
-0.2739526927471161,
-0.00676131434738636,
0.006709648296236992,
0.38980719447135925,
-0.2270161658525467,
-0.026360461488366127,
0.12607695162296295,
-0.07171663641929626,
-0.02165127918124199,
-0.4830068051815033,
0.11179284006357193,
0.04559263586997986,
-0.2318335324525833,
-0.10764293372631073,
0.08288025110960007,
-0.042953141033649445,
-0.46715980768203735,
0.15198089182376862,
0.1879013180732727,
0.05123550444841385,
-0.2913530170917511,
-0.34454625844955444,
-0.09238672256469727,
-0.1816118210554123,
-0.0012826751917600632,
-0.035988446325063705,
0.07129773497581482,
0.37686648964881897,
0.16384737193584442,
0.03225523978471756,
-0.2014034390449524,
-0.058261938393116,
0.38416942954063416,
0.11524109542369843,
0.06221017614006996,
-0.08224429190158844,
0.39128321409225464,
-0.023472528904676437,
0.02685277909040451,
0.0503184050321579,
0.027712710201740265,
0.08725352585315704,
0.425647109746933,
0.0977625846862793,
0.15738634765148163,
-0.4112390875816345,
0.28078633546829224,
0.1774875968694687,
0.11828821897506714,
-0.13777074217796326,
0.18009963631629944,
0.10431303083896637,
-0.224992036819458,
-0.23325394093990326,
-0.19721508026123047,
0.12463855743408203,
-0.1126864105463028,
0.16435353457927704,
-0.11488209664821625,
0.3551517426967621,
0.3632742762565613,
-0.009765916503965855,
-0.24801523983478546,
-0.3071395754814148,
0.04222584888339043,
0.05488782376050949,
-0.1848628669977188,
0.27694782614707947,
0.4547150433063507,
0.06889287382364273,
0.10064513981342316,
-0.44657522439956665,
-0.09266727417707443,
0.08696957677602768,
-0.3843233585357666,
-0.08820292353630066,
0.34193098545074463,
0.19567814469337463,
-0.15060898661613464,
-0.20592045783996582,
0.15797919034957886,
-0.11409712582826614,
-0.13242556154727936,
0.36024948954582214,
-0.24125291407108307,
-0.14182516932487488,
-0.054071806371212006,
0.3252495527267456,
0.02627585642039776,
0.0775642842054367,
0.05787578970193863,
-0.10660601407289505,
0.06521810591220856,
-0.006445923820137978,
0.10747767239809036,
0.06735964119434357,
-0.01296483725309372,
0.12857083976268768,
-0.11017973721027374,
0.2070382535457611,
-0.6235056519508362,
0.35154885053634644,
0.3406658172607422,
0.04048712179064751,
-0.2386520653963089,
0.1311081200838089,
-0.06537596881389618,
-0.26793164014816284,
0.33320534229278564,
-0.07992002367973328,
0.20084738731384277,
-0.3434513807296753,
0.08213335275650024,
0.28266215324401855,
-0.054147496819496155,
0.06991564482450485,
0.20671403408050537,
0.4017025828361511,
-0.08867113292217255,
-0.05176244676113129,
-0.05980346351861954,
-0.17698337137699127,
0.3869963586330414,
-0.4427589178085327,
0.16624006628990173,
-0.09579436480998993,
0.9571192860603333,
0.3474618196487427,
-0.24923890829086304,
-0.24940219521522522,
-0.14705103635787964,
-0.34628552198410034,
0.1076839417219162,
0.17763426899909973,
-0.03834070265293121,
-0.0039489297196269035,
-0.06391055136919022,
0.0028831809759140015,
0.05237804725766182,
0.15503710508346558,
0.22364646196365356,
0.5317481160163879,
-0.35456860065460205,
0.299388587474823,
-0.22832512855529785,
0.10329064726829529,
0.2751069962978363,
0.13227303326129913,
-0.127249613404274,
-0.01768401637673378,
-0.009352385997772217,
-0.04927118867635727,
0.026652716100215912,
-0.32910609245300293,
0.06418018043041229,
-0.14669649302959442,
-0.2652188837528229,
-0.21753938496112823,
-0.04903087019920349,
0.03659139573574066,
0.04084458202123642,
-0.06513194739818573,
0.032620396465063095,
-0.12107520550489426,
-0.10738211870193481,
-0.052252963185310364,
-0.3160066604614258,
0.348541796207428,
0.3667259216308594,
0.08986833691596985,
-0.02784176729619503,
0.6427887678146362,
0.15500786900520325,
-0.1114484965801239,
0.2014165222644806,
0.14983777701854706,
-0.11773532629013062,
-0.2359752655029297,
0.022950423881411552,
0.30525529384613037,
-0.11438214033842087,
-0.3438956141471863,
-0.49479174613952637,
0.6355993747711182,
0.17985564470291138,
-0.5693952441215515,
-0.17015691101551056,
-0.24646635353565216,
-0.17225560545921326,
-0.11563274264335632,
0.3047388195991516,
0.3367745876312256,
0.10700065642595291,
-0.017186086624860764,
-0.36785197257995605,
0.06726876646280289,
0.4848315119743347,
-0.4563571512699127,
-0.07332669198513031,
-0.11960713565349579,
0.1667352020740509,
0.2647434175014496,
-0.19481265544891357,
-0.9240175485610962,
-0.1374061107635498,
0.14410820603370667,
-0.01407289132475853,
-0.17872872948646545,
0.298997163772583,
0.24600133299827576,
0.2937111258506775,
-0.2554592192173004,
0.5315841436386108,
-0.049537889659404755,
-0.09967632591724396,
-0.4590686857700348,
-0.21204854547977448
] |
https://github.com/huggingface/datasets/issues/224 | [Feature Request/Help] BLEURT model -> PyTorch | Hi there. We ran into the same problem this year (converting BLEURT to PyTorch) and thanks to @adamwlev found his colab notebook which didn't work but served as a good starting point. Finally, we **made it work** by doing just two simple conceptual fixes:
1. Transposing 'kernel' layers instead of 'dense' ones when copying params from the original model;
2. Taking pooler_output as a cls_state in forward function of the BleurtModel class.
Plus few minor syntactical fixes for the outdated parts. The result is still not exactly the same, but is very close to the expected one (1.0483 vs 1.0474).
Find the fixed version here (fixes are commented): https://colab.research.google.com/drive/1KsCUkFW45d5_ROSv2aHtXgeBa2Z98r03?usp=sharing
| Hi, I am interested in porting google research's new BLEURT learned metric to PyTorch (because I wish to do something experimental with language generation and backpropping through BLEURT). I noticed that you guys don't have it yet so I am partly just asking if you plan to add it (@thomwolf said you want to do so on Twitter).
I had a go of just like manually using the checkpoint that they publish which includes the weights. It seems like the architecture is exactly aligned with the out-of-the-box BertModel in transformers just with a single linear layer on top of the CLS embedding. I loaded all the weights to the PyTorch model but I am not able to get the same numbers as the BLEURT package's python api. Here is my colab notebook where I tried https://colab.research.google.com/drive/1Bfced531EvQP_CpFvxwxNl25Pj6ptylY?usp=sharing . If you have any pointers on what might be going wrong that would be much appreciated!
Thank you muchly! | 109 | [Feature Request/Help] BLEURT model -> PyTorch
Hi, I am interested in porting google research's new BLEURT learned metric to PyTorch (because I wish to do something experimental with language generation and backpropping through BLEURT). I noticed that you guys don't have it yet so I am partly just asking if you plan to add it (@thomwolf said you want to do so on Twitter).
I had a go of just like manually using the checkpoint that they publish which includes the weights. It seems like the architecture is exactly aligned with the out-of-the-box BertModel in transformers just with a single linear layer on top of the CLS embedding. I loaded all the weights to the PyTorch model but I am not able to get the same numbers as the BLEURT package's python api. Here is my colab notebook where I tried https://colab.research.google.com/drive/1Bfced531EvQP_CpFvxwxNl25Pj6ptylY?usp=sharing . If you have any pointers on what might be going wrong that would be much appreciated!
Thank you muchly!
Hi there. We ran into the same problem this year (converting BLEURT to PyTorch) and thanks to @adamwlev found his colab notebook which didn't work but served as a good starting point. Finally, we **made it work** by doing just two simple conceptual fixes:
1. Transposing 'kernel' layers instead of 'dense' ones when copying params from the original model;
2. Taking pooler_output as a cls_state in forward function of the BleurtModel class.
Plus few minor syntactical fixes for the outdated parts. The result is still not exactly the same, but is very close to the expected one (1.0483 vs 1.0474).
Find the fixed version here (fixes are commented): https://colab.research.google.com/drive/1KsCUkFW45d5_ROSv2aHtXgeBa2Z98r03?usp=sharing
| [
0.03105197474360466,
-0.2103957235813141,
0.11031089723110199,
0.24948230385780334,
0.28502875566482544,
-0.33688661456108093,
0.2980252504348755,
0.14864566922187805,
0.09188990294933319,
0.16699329018592834,
-0.30923908948898315,
0.3939817249774933,
-0.48465636372566223,
0.25464630126953125,
0.0468795970082283,
-0.08954024314880371,
-0.06799928098917007,
0.05894642695784569,
0.10282014310359955,
-0.17925673723220825,
-0.11254642903804779,
0.1559169441461563,
0.11106309294700623,
-0.10564196109771729,
-0.19486533105373383,
0.3722075819969177,
-0.06696510314941406,
0.11051197350025177,
-0.2348370999097824,
-0.05581817403435707,
0.23994289338588715,
-0.09313477575778961,
0.19716298580169678,
0.7407883405685425,
-0.00012301238893996924,
-0.29678821563720703,
0.10562047362327576,
-0.013817953877151012,
-0.39566442370414734,
-0.22906653583049774,
0.39341676235198975,
-0.3064042925834656,
0.14753983914852142,
-0.18821850419044495,
-0.023235976696014404,
-0.04682978242635727,
-0.2829231023788452,
-0.11125530302524567,
0.13092002272605896,
0.24891841411590576,
0.03568290174007416,
0.12069830298423767,
-0.04003624618053436,
0.10717988759279251,
0.1736428290605545,
-0.19217033684253693,
-0.025240492075681686,
0.5683524012565613,
0.3351752460002899,
-0.019421137869358063,
-0.22494250535964966,
0.1777404099702835,
0.01149292103946209,
0.10073009133338928,
0.661795973777771,
0.04060619696974754,
-0.050766654312610626,
-0.0463242381811142,
0.04265300929546356,
0.3301611840724945,
-0.11374533921480179,
-0.1908949315547943,
-0.25507664680480957,
0.12239804118871689,
0.07248985022306442,
-0.24157071113586426,
-0.23092666268348694,
0.16072112321853638,
0.10856536030769348,
-0.24158066511154175,
-0.3910423517227173,
-0.3491133749485016,
-0.14091533422470093,
0.13794507086277008,
-0.2982495427131653,
0.3092898726463318,
-0.06806907057762146,
-0.12711897492408752,
0.15347877144813538,
0.0853552371263504,
0.34188732504844666,
-0.0955546572804451,
0.35434016585350037,
0.19703879952430725,
0.08634331077337265,
-0.18238544464111328,
0.22257307171821594,
0.04210386052727699,
-0.062443435192108154,
-0.3093153238296509,
-0.12535421550273895,
0.20691800117492676,
-0.2814028859138489,
0.011797267943620682,
-0.027306731790304184,
0.3203352689743042,
0.040419403463602066,
0.35977381467819214,
0.28627586364746094,
0.37072044610977173,
0.07752560079097748,
-0.04536345601081848,
-0.08907102048397064,
-0.15487778186798096,
0.24097369611263275,
0.19222837686538696,
-0.2800595164299011,
-0.3287021517753601,
-0.033770088106393814,
-0.05419699102640152,
-0.21769770979881287,
-0.10590723901987076,
0.34869498014450073,
0.13636153936386108,
-0.49230244755744934,
-0.06439290940761566,
0.6397177577018738,
0.046870630234479904,
-0.18193814158439636,
0.07984868437051773,
-0.14149247109889984,
-0.09508395195007324,
-0.3073860704898834,
0.06758337467908859,
0.21250422298908234,
-0.19385336339473724,
0.27882277965545654,
0.03200087696313858,
0.5187743306159973,
0.12528753280639648,
0.16171284019947052,
0.4335992932319641,
0.16154703497886658,
-0.19240939617156982,
-0.2416660487651825,
-0.2961934506893158,
0.22628909349441528,
0.026455819606781006,
-0.11240114271640778,
0.08938474953174591,
-0.12872382998466492,
-0.3263464570045471,
-0.1520967185497284,
0.023959849029779434,
-0.28712815046310425,
-0.019190020859241486,
-0.010954417288303375,
0.27803778648376465,
0.10987874120473862,
-0.2487732321023941,
-0.03219764679670334,
-0.3951016068458557,
-0.12442648410797119,
0.09461551159620285,
0.4095954895019531,
-0.20389004051685333,
-0.40325531363487244,
-0.42737653851509094,
0.10449196398258209,
0.4528105556964874,
0.33462104201316833,
0.09447555243968964,
-0.22268010675907135,
-0.20602339506149292,
0.182228684425354,
-0.35699212551116943,
0.24966296553611755,
0.1920621693134308,
-0.27465391159057617,
-0.22991600632667542,
0.13340473175048828,
-0.25309333205223083,
-0.21538230776786804,
0.025944694876670837,
-0.1508408635854721,
-0.06364277750253677,
0.3645898699760437,
0.11044356226921082,
-0.18229268491268158,
-0.02314547449350357,
-0.3769245743751526,
-0.1707116812467575,
0.24087752401828766,
0.14524507522583008,
0.3112166225910187,
0.04421839118003845,
0.13978596031665802,
0.545229434967041,
0.10949307680130005,
-0.37678149342536926,
0.03864999860525131,
-0.20870767533779144,
0.4394534230232239,
-0.38880056142807007,
0.36291447281837463,
-0.13229471445083618,
-0.04362037777900696,
0.2286229431629181,
-0.32526838779449463,
0.4498295783996582,
0.15172049403190613,
0.13739268481731415,
-0.11641093343496323,
-0.11465416103601456,
0.2857360541820526,
-0.0415586419403553,
-0.09858444333076477,
-0.175385981798172,
-0.28409701585769653,
-0.22045296430587769,
-0.147940993309021,
-0.2546970546245575,
-0.23914557695388794,
-0.05173944681882858,
0.1921086609363556,
0.32608386874198914,
-0.06349757313728333,
-0.16392400860786438,
-0.038680702447891235,
0.3862399756908417,
0.1850813329219818,
0.21768535673618317,
-0.07578517496585846,
-0.2285490334033966,
0.11393851041793823,
-0.20823408663272858,
0.14065778255462646,
0.1960555911064148,
0.3851838707923889,
0.031623486429452896,
0.40312522649765015,
0.21448063850402832,
-0.11146409064531326,
-0.09128458797931671,
-0.12201724201440811,
0.2812281847000122,
0.324666291475296,
0.2669116258621216,
0.2754969000816345,
0.12106325477361679,
-0.24934867024421692,
0.10694250464439392,
-0.04537442699074745,
0.10155414044857025,
0.35155966877937317,
-0.16831736266613007,
0.06461989879608154,
-0.16824544966220856,
0.1615699678659439,
0.29566341638565063,
0.2568989396095276,
-0.059767477214336395,
-0.0450265035033226,
0.21921998262405396,
-0.46931278705596924,
-0.27227386832237244,
0.011140124872326851,
0.07040084898471832,
0.08245272934436798,
0.07317212224006653,
0.4600592255592346,
0.14472335577011108,
-0.01683230698108673,
0.02773122489452362,
-0.08601688593626022,
0.14787472784519196,
-0.11266074329614639,
-0.06314841657876968,
0.12503033876419067,
0.06865347176790237,
0.07814255356788635,
0.10393920540809631,
0.05523441731929779,
0.1424945890903473,
-0.18085737526416779,
0.33856457471847534,
-0.006266901269555092,
0.4345984160900116,
-0.249354749917984,
-0.3888390064239502,
-0.22619426250457764,
-0.24832506477832794,
-0.034891463816165924,
0.32378798723220825,
-0.01339777372777462,
-0.13628649711608887,
0.19925041496753693,
0.40451356768608093,
-0.08564773201942444,
-0.05584080517292023,
-0.11347314715385437,
-0.26379668712615967,
-0.36608439683914185,
-0.0012674015015363693,
-0.06414400041103363,
0.06512763351202011,
-0.08705278486013412,
0.03587926924228668,
-0.15460710227489471,
-0.1930072158575058,
-0.7795090675354004,
0.06021347641944885,
0.03927228972315788,
0.30001893639564514,
0.20597079396247864,
-0.1349009871482849,
-0.31092119216918945,
0.044446591287851334,
0.10181473940610886,
-0.37420210242271423,
-0.026990581303834915,
0.417681485414505,
-0.23497293889522552,
0.07670997828245163,
-0.03322906792163849,
-0.22106102108955383,
-0.12886755168437958,
-0.02256774716079235,
-0.05517931282520294,
0.12109814584255219,
0.0652790516614914,
-0.20432519912719727,
0.13932447135448456,
0.3219204246997833,
0.41521957516670227,
-0.09877263754606247,
-0.06713970005512238,
0.22492268681526184,
0.42780059576034546,
-0.25694626569747925,
-0.301351934671402,
-0.18492011725902557,
-0.0005777478218078613,
0.017254244536161423,
0.0003764871507883072,
-0.3237825036048889,
-0.36015433073043823,
-0.11460591852664948,
-0.15125621855258942,
0.20219986140727997,
0.16915762424468994,
0.06157908961176872,
0.224295973777771,
0.06467749178409576,
-0.21677854657173157,
-0.16279278695583344,
-0.07023169845342636,
0.24304130673408508,
0.6987829208374023,
-0.23153802752494812,
-0.09995263069868088,
0.0897039920091629,
0.752469003200531,
0.13057518005371094,
-0.423186719417572,
0.06254187226295471,
0.26073333621025085,
0.06086135655641556,
-0.11394082754850388,
-0.26714572310447693,
0.15565060079097748,
-0.3145396411418915,
-0.27640247344970703,
0.3156626224517822,
0.11460062116384506,
-0.28042182326316833,
-0.26113060116767883,
-0.2004973441362381,
0.49796172976493835,
-0.17563274502754211,
0.06963612884283066,
0.03468531370162964,
-0.04997820407152176,
0.02282186597585678,
-0.1170809417963028,
-0.27406227588653564,
-0.11454538255929947,
0.2060009241104126,
0.02208690345287323,
0.0904163047671318,
0.03668069466948509,
0.45275968313217163,
0.015573451295495033,
-0.7020947933197021,
0.4291396141052246,
0.09122688323259354,
-0.6415270566940308,
0.20079074800014496,
-0.15091948211193085,
-0.08306723833084106,
-0.05323367193341255,
-0.3633190393447876,
0.11488113552331924,
0.0365847684442997,
-0.06340625137090683,
-0.024901432916522026,
-0.28089118003845215,
0.019936252385377884,
-0.26069605350494385,
-0.3109963834285736,
0.6108319163322449,
0.30939918756484985,
-0.3783528208732605,
0.05132340267300606,
0.23827819526195526,
0.4477608799934387,
-0.1608956903219223,
0.03582214191555977,
-0.3568879961967468,
-0.21575215458869934,
0.09272745251655579,
-0.11704526096582413,
-0.03972261771559715,
0.2884737551212311,
-0.12854893505573273,
-0.07872042804956436,
0.24400566518306732,
-0.08774784207344055,
0.1997191160917282,
0.049700599163770676,
0.10960305482149124,
-0.09483009576797485,
0.17061875760555267,
0.05049663782119751,
0.06471322476863861,
0.24659648537635803,
0.41444963216781616,
-0.5077788233757019,
-0.47134923934936523,
0.21681636571884155,
0.16121608018875122,
0.17137649655342102,
0.1093549132347107,
0.10491938143968582,
-0.13601121306419373,
0.43549782037734985,
0.27228671312332153,
0.18568487465381622,
0.23380330204963684,
0.039173658937215805,
0.36824843287467957,
0.11878341436386108,
-0.19488810002803802,
0.3924102485179901,
-0.170674130320549,
0.014420703053474426,
0.2270651012659073,
0.06649242341518402,
-0.012271774932742119,
0.12193980813026428,
0.4338003396987915,
0.9371415972709656,
0.14221984148025513,
0.09444331377744675,
0.2991996705532074,
-0.13560274243354797,
0.3273821175098419,
-0.045953571796417236,
0.02885357476770878,
-0.3419894278049469,
-0.2665644884109497,
0.043637558817863464,
-0.04958975315093994,
-0.44529539346694946,
-0.16226740181446075,
-0.19859670102596283,
0.14733000099658966,
-0.3593901991844177,
-0.25683680176734924,
0.2827572226524353,
0.2808370292186737,
0.10884825885295868,
0.030932091176509857,
0.2770262658596039,
0.08055364340543747,
-0.17511048913002014,
0.26924458146095276,
-0.08487468957901001,
-0.1843993365764618,
-0.26210451126098633,
0.13207873702049255,
-0.18024921417236328,
0.37191352248191833,
-0.10059570521116257,
-0.044855475425720215,
-0.060901377350091934,
-0.3492479920387268,
0.0737575888633728,
0.0327632874250412,
0.7054666876792908,
0.09231684356927872,
-0.3070915639400482,
0.08027985692024231,
-0.062137700617313385,
0.17744171619415283,
0.19616656005382538,
-0.14955508708953857,
0.35956045985221863,
-0.13380126655101776,
-0.1622401773929596,
-0.16799667477607727,
0.14697028696537018,
-0.3749425411224365,
0.22124546766281128,
-0.16459882259368896,
-0.045548535883426666,
-0.11824847757816315,
0.40338510274887085,
0.33453625440597534,
0.1593393236398697,
-0.2553209662437439,
0.07714979350566864,
0.20327964425086975,
-0.2602023780345917,
0.045820098370313644,
0.11606155335903168,
-0.2364221066236496,
0.0402362160384655,
-0.009904071688652039,
0.021524876356124878,
-0.0013384893536567688,
0.23494352400302887,
0.17420583963394165,
-0.11456694453954697,
0.23590180277824402,
-0.6396331787109375,
0.5488191246986389,
-0.3684130609035492,
0.1757143884897232,
-0.1360732764005661,
-0.055178992450237274,
0.12224508821964264,
0.5733035206794739,
0.4357832074165344,
0.21459415555000305,
-0.3986991345882416,
0.18546873331069946,
-0.3889482319355011,
0.08772922307252884,
-0.18641024827957153,
0.3603321313858032,
-0.17637723684310913,
0.0029720868915319443,
-0.11693356931209564,
0.23120135068893433,
-0.20673413574695587,
0.03993794322013855,
0.19829165935516357,
-0.03068380430340767,
0.009558885358273983,
-0.4418536424636841,
0.02748611569404602,
0.03583340346813202,
-0.23903554677963257,
-0.0639573484659195,
0.11508999019861221,
-0.02289605140686035,
-0.4367915391921997,
0.1588520109653473,
0.2320312261581421,
0.009140817448496819,
-0.32059186697006226,
-0.38937908411026,
-0.1304398477077484,
-0.1896282583475113,
0.06611350178718567,
0.027370154857635498,
0.0649438351392746,
0.21625937521457672,
0.2079448103904724,
0.020306043326854706,
-0.16019943356513977,
-0.04887603968381882,
0.41021987795829773,
0.16648009419441223,
0.009113239124417305,
-0.034340761601924896,
0.42611533403396606,
-0.02806224673986435,
0.19161036610603333,
0.024117454886436462,
-0.025749370455741882,
0.16406989097595215,
0.4158223867416382,
0.13150396943092346,
0.15301206707954407,
-0.39151960611343384,
0.31367525458335876,
0.2520207464694977,
0.20041455328464508,
-0.20123547315597534,
0.2113136351108551,
0.08531980961561203,
-0.24712762236595154,
-0.1780570149421692,
-0.20906847715377808,
0.050173066556453705,
-0.1371205747127533,
0.17602597177028656,
-0.11124125123023987,
0.36048269271850586,
0.3827468752861023,
-0.061240192502737045,
-0.23618574440479279,
-0.26754826307296753,
0.05084863677620888,
0.044831614941358566,
-0.2170989215373993,
0.31279855966567993,
0.5844203233718872,
0.04400472342967987,
0.05221609026193619,
-0.3825650215148926,
-0.11984279006719589,
0.008465098217129707,
-0.2900795638561249,
-0.10884629189968109,
0.3588649034500122,
0.20460045337677002,
-0.10920138657093048,
-0.09902498126029968,
0.15128180384635925,
-0.0717029795050621,
-0.12134341895580292,
0.39471155405044556,
-0.40146973729133606,
-0.16225993633270264,
-0.03691476956009865,
0.3568076491355896,
-0.02662954106926918,
0.06826359033584595,
0.10880716145038605,
-0.21613872051239014,
0.07733315229415894,
-0.015025246888399124,
-0.01827465370297432,
0.09222211688756943,
0.07474467158317566,
0.10134054720401764,
-0.09447591006755829,
0.1506623923778534,
-0.7600218653678894,
0.3500680923461914,
0.2666798233985901,
0.07755827903747559,
-0.1919763684272766,
0.1510920524597168,
-0.11532817780971527,
-0.23615196347236633,
0.3830995559692383,
-0.016696017235517502,
0.25774872303009033,
-0.3252435624599457,
-0.041428934782743454,
0.4066010117530823,
-0.02356446161866188,
0.043433502316474915,
0.1191042810678482,
0.4557110667228699,
-0.13713541626930237,
-0.08016903698444366,
-0.08495017886161804,
-0.17106102406978607,
0.334772527217865,
-0.3921130895614624,
0.2219248265028,
0.057305265218019485,
0.8864078521728516,
0.3305407762527466,
-0.20438870787620544,
-0.27269217371940613,
-0.09083288162946701,
-0.29800689220428467,
0.04675421491265297,
0.1034170389175415,
-0.08217354118824005,
0.027585923671722412,
-0.027783703058958054,
0.006058171391487122,
0.12412020564079285,
0.1421758532524109,
0.26756611466407776,
0.29824957251548767,
-0.3599909842014313,
0.2530735731124878,
-0.2842276692390442,
0.15552237629890442,
0.1820707768201828,
0.06622336804866791,
-0.23234081268310547,
-0.0077626658603549,
0.0711766928434372,
-0.10512158274650574,
0.057173073291778564,
-0.23002056777477264,
0.07925764471292496,
-0.21019110083580017,
-0.234105184674263,
-0.2609882652759552,
0.06782655417919159,
-0.014428498223423958,
0.004517506808042526,
-0.08634749054908752,
0.02315201237797737,
-0.11450622975826263,
-0.09457816183567047,
0.021241137757897377,
-0.2878338098526001,
0.3728131353855133,
0.3003571629524231,
0.12165670096874237,
0.05715637654066086,
0.5850411653518677,
0.12948980927467346,
-0.17101655900478363,
0.26426154375076294,
0.13617144525051117,
-0.10343565791845322,
-0.18146252632141113,
-0.043379973620176315,
0.2637508809566498,
-0.050897277891635895,
-0.2635940611362457,
-0.5351039171218872,
0.550689160823822,
0.11400303244590759,
-0.5117972493171692,
-0.2289525866508484,
-0.16178415715694427,
-0.18558961153030396,
-0.10991455614566803,
0.24824468791484833,
0.3811723589897156,
0.13884267210960388,
-0.02862614206969738,
-0.4515787363052368,
0.00406445749104023,
0.465069979429245,
-0.4754205346107483,
-0.12336903810501099,
-0.1212315633893013,
0.18406851589679718,
0.29907095432281494,
-0.12919802963733673,
-0.8295280337333679,
-0.1543295979499817,
0.09583029896020889,
-0.038087889552116394,
-0.13884219527244568,
0.2332545816898346,
0.11724242568016052,
0.2540249228477478,
-0.29439660906791687,
0.5520853400230408,
0.04639887809753418,
-0.16173940896987915,
-0.4791439175605774,
-0.1919277459383011
] |
https://github.com/huggingface/datasets/issues/223 | [Feature request] Add FLUE dataset | @mariamabarham
I put all the datasets on this drive: https://1drv.ms/u/s!Ao2Rcpiny7RFinDypq7w-LbXcsx9?e=iVsEDh
Some information :
• For FLUE, the quote used is
> @misc{le2019flaubert,
> title={FlauBERT: Unsupervised Language Model Pre-training for French},
> author={Hang Le and Loïc Vial and Jibril Frej and Vincent Segonne and Maximin Coavoux and Benjamin Lecouteux and Alexandre Allauzen and Benoît Crabbé and Laurent Besacier and Didier Schwab},
> year={2019},
> eprint={1912.05372},
> archivePrefix={arXiv},
> primaryClass={cs.CL}
> }
• The Github repo of FLUE is avaible here : https://github.com/getalp/Flaubert/tree/master/flue
Information related to the different tasks of FLUE :
**1. Classification**
Three dataframes are available:
- Book
- DVD
- Music
For each of these dataframes is available a set of training and test data, and a third one containing unlabelled data.
Citation :
>@dataset{prettenhofer_peter_2010_3251672,
author = {Prettenhofer, Peter and
Stein, Benno},
title = {{Webis Cross-Lingual Sentiment Dataset 2010 (Webis-
CLS-10)}},
month = jul,
year = 2010,
publisher = {Zenodo},
doi = {10.5281/zenodo.3251672},
url = {https://doi.org/10.5281/zenodo.3251672}
}
**2. Paraphrasing**
French part of the PAWS-X dataset (https://github.com/google-research-datasets/paws).
Three dataframes are available:
- train
- dev
- test
Citation :
> @InProceedings{pawsx2019emnlp,
> title = {{PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification}},
> author = {Yang, Yinfei and Zhang, Yuan and Tar, Chris and Baldridge, Jason},
> booktitle = {Proc. of EMNLP},
> year = {2019}
> }
**3. Natural Language Inference**
French part of the XNLI dataset (https://github.com/facebookresearch/XNLI).
Three dataframes are available:
- train
- dev
- test
For the dev and test datasets, extra columns compared to the train dataset were available so I left them in the dataframe (I didn't know if these columns could be useful for other tasks or not).
In the context of the FLUE benchmark, only the columns gold_label, sentence1 and sentence2 are useful.
Citation :
> @InProceedings{conneau2018xnli,
> author = "Conneau, Alexis
> and Rinott, Ruty
> and Lample, Guillaume
> and Williams, Adina
> and Bowman, Samuel R.
> and Schwenk, Holger
> and Stoyanov, Veselin",
> title = "XNLI: Evaluating Cross-lingual Sentence Representations",
> booktitle = "Proceedings of the 2018 Conference on Empirical Methods
> in Natural Language Processing",
> year = "2018",
> publisher = "Association for Computational Linguistics",
> location = "Brussels, Belgium",
**4. Parsing**
The dataset used by the FLUE authors for this task is not freely available.
Users of your library will therefore not be able to access it.
Nevertheless, I think maybe it is useful to add a link to the site where to request this dataframe: http://ftb.linguist.univ-paris-diderot.fr/telecharger.php?langue=en
(personally it was sent to me less than 48 hours after I requested it).
**5. Word Sense Disambiguation Tasks**
5.1 Verb Sense Disambiguation
Two dataframes are available: train and test
For both dataframes, 4 columns are available: document, sentence, lemma and word.
I created the document column thinking that there were several documents in the dataset but afterwards it turns out that there were not: several sentences but only one document. It's up to you to keep it or not when importing these two dataframes.
The sentence column is used to determine to which sentence the word in the word column belongs. It is in the form of a dictionary {'id': 'd000.s001', 'idx': '1'}. I thought for a while to keep only the idx because the id doesn't matter any more information. Nevertheless for the test dataset, the dictionary has an extra value indicating the source of the sentence. I don't know if it's useful or not, that's why I left the dictionary just in case. The user is free to do what he wants with it.
Citation :
> Segonne, V., Candito, M., and Crabb ́e, B. (2019). Usingwiktionary as a resource for wsd: the case of frenchverbs. InProceedings of the 13th International Confer-ence on Computational Semantics-Long Papers, pages259–270
5.2 Noun Sense Disambiguation
Two dataframes are available: 2 train and 1 test
I confess I didn't fully understand the procedure for this task.
Citation :
> @dataset{loic_vial_2019_3549806,
> author = {Loïc Vial},
> title = {{French Word Sense Disambiguation with Princeton
> WordNet Identifiers}},
> month = nov,
> year = 2019,
> publisher = {Zenodo},
> version = {1.0},
> doi = {10.5281/zenodo.3549806},
> url = {https://doi.org/10.5281/zenodo.3549806}
> }
Finally, additional information about FLUE is available in the FlauBERT publication :
https://arxiv.org/abs/1912.05372 (p. 4).
Hoping to have provided you with everything you need to add this benchmark :)
| Hi,
I think it would be interesting to add the FLUE dataset for francophones or anyone wishing to work on French.
In other requests, I read that you are already working on some datasets, and I was wondering if FLUE was planned.
If it is not the case, I can provide each of the cleaned FLUE datasets (in the form of a directly exploitable dataset rather than in the original xml formats which require additional processing, with the French part for cases where the dataset is based on a multilingual dataframe, etc.). | 723 | [Feature request] Add FLUE dataset
Hi,
I think it would be interesting to add the FLUE dataset for francophones or anyone wishing to work on French.
In other requests, I read that you are already working on some datasets, and I was wondering if FLUE was planned.
If it is not the case, I can provide each of the cleaned FLUE datasets (in the form of a directly exploitable dataset rather than in the original xml formats which require additional processing, with the French part for cases where the dataset is based on a multilingual dataframe, etc.).
@mariamabarham
I put all the datasets on this drive: https://1drv.ms/u/s!Ao2Rcpiny7RFinDypq7w-LbXcsx9?e=iVsEDh
Some information :
• For FLUE, the quote used is
> @misc{le2019flaubert,
> title={FlauBERT: Unsupervised Language Model Pre-training for French},
> author={Hang Le and Loïc Vial and Jibril Frej and Vincent Segonne and Maximin Coavoux and Benjamin Lecouteux and Alexandre Allauzen and Benoît Crabbé and Laurent Besacier and Didier Schwab},
> year={2019},
> eprint={1912.05372},
> archivePrefix={arXiv},
> primaryClass={cs.CL}
> }
• The Github repo of FLUE is avaible here : https://github.com/getalp/Flaubert/tree/master/flue
Information related to the different tasks of FLUE :
**1. Classification**
Three dataframes are available:
- Book
- DVD
- Music
For each of these dataframes is available a set of training and test data, and a third one containing unlabelled data.
Citation :
>@dataset{prettenhofer_peter_2010_3251672,
author = {Prettenhofer, Peter and
Stein, Benno},
title = {{Webis Cross-Lingual Sentiment Dataset 2010 (Webis-
CLS-10)}},
month = jul,
year = 2010,
publisher = {Zenodo},
doi = {10.5281/zenodo.3251672},
url = {https://doi.org/10.5281/zenodo.3251672}
}
**2. Paraphrasing**
French part of the PAWS-X dataset (https://github.com/google-research-datasets/paws).
Three dataframes are available:
- train
- dev
- test
Citation :
> @InProceedings{pawsx2019emnlp,
> title = {{PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification}},
> author = {Yang, Yinfei and Zhang, Yuan and Tar, Chris and Baldridge, Jason},
> booktitle = {Proc. of EMNLP},
> year = {2019}
> }
**3. Natural Language Inference**
French part of the XNLI dataset (https://github.com/facebookresearch/XNLI).
Three dataframes are available:
- train
- dev
- test
For the dev and test datasets, extra columns compared to the train dataset were available so I left them in the dataframe (I didn't know if these columns could be useful for other tasks or not).
In the context of the FLUE benchmark, only the columns gold_label, sentence1 and sentence2 are useful.
Citation :
> @InProceedings{conneau2018xnli,
> author = "Conneau, Alexis
> and Rinott, Ruty
> and Lample, Guillaume
> and Williams, Adina
> and Bowman, Samuel R.
> and Schwenk, Holger
> and Stoyanov, Veselin",
> title = "XNLI: Evaluating Cross-lingual Sentence Representations",
> booktitle = "Proceedings of the 2018 Conference on Empirical Methods
> in Natural Language Processing",
> year = "2018",
> publisher = "Association for Computational Linguistics",
> location = "Brussels, Belgium",
**4. Parsing**
The dataset used by the FLUE authors for this task is not freely available.
Users of your library will therefore not be able to access it.
Nevertheless, I think maybe it is useful to add a link to the site where to request this dataframe: http://ftb.linguist.univ-paris-diderot.fr/telecharger.php?langue=en
(personally it was sent to me less than 48 hours after I requested it).
**5. Word Sense Disambiguation Tasks**
5.1 Verb Sense Disambiguation
Two dataframes are available: train and test
For both dataframes, 4 columns are available: document, sentence, lemma and word.
I created the document column thinking that there were several documents in the dataset but afterwards it turns out that there were not: several sentences but only one document. It's up to you to keep it or not when importing these two dataframes.
The sentence column is used to determine to which sentence the word in the word column belongs. It is in the form of a dictionary {'id': 'd000.s001', 'idx': '1'}. I thought for a while to keep only the idx because the id doesn't matter any more information. Nevertheless for the test dataset, the dictionary has an extra value indicating the source of the sentence. I don't know if it's useful or not, that's why I left the dictionary just in case. The user is free to do what he wants with it.
Citation :
> Segonne, V., Candito, M., and Crabb ́e, B. (2019). Usingwiktionary as a resource for wsd: the case of frenchverbs. InProceedings of the 13th International Confer-ence on Computational Semantics-Long Papers, pages259–270
5.2 Noun Sense Disambiguation
Two dataframes are available: 2 train and 1 test
I confess I didn't fully understand the procedure for this task.
Citation :
> @dataset{loic_vial_2019_3549806,
> author = {Loïc Vial},
> title = {{French Word Sense Disambiguation with Princeton
> WordNet Identifiers}},
> month = nov,
> year = 2019,
> publisher = {Zenodo},
> version = {1.0},
> doi = {10.5281/zenodo.3549806},
> url = {https://doi.org/10.5281/zenodo.3549806}
> }
Finally, additional information about FLUE is available in the FlauBERT publication :
https://arxiv.org/abs/1912.05372 (p. 4).
Hoping to have provided you with everything you need to add this benchmark :)
| [
-0.09875033795833588,
0.2994914650917053,
-0.1906658262014389,
0.08413086831569672,
-0.09124993532896042,
0.10564102977514267,
0.4507472515106201,
-0.14683814346790314,
-0.21770641207695007,
0.004500426352024078,
-0.20793591439723969,
-0.17496585845947266,
-0.15123486518859863,
0.27440688014030457,
0.07923612743616104,
-0.36933478713035583,
-0.001966707408428192,
0.033536963164806366,
0.0868884027004242,
-0.34479355812072754,
-0.10768920928239822,
0.17830190062522888,
-0.049756813794374466,
0.19358950853347778,
-0.00017957063391804695,
0.09124097973108292,
-0.22928372025489807,
-0.15842890739440918,
-0.1509992629289627,
-0.02232060395181179,
0.13173751533031464,
0.24340614676475525,
0.07313701510429382,
0.38489121198654175,
-0.00010290565842296928,
-0.21261009573936462,
0.12683197855949402,
-0.12616373598575592,
0.029008451849222183,
0.032224707305431366,
0.02200361341238022,
-0.2267683744430542,
-0.3399676978588104,
0.037781842052936554,
-0.1280568689107895,
-0.2536057233810425,
-0.18752998113632202,
-0.5613652467727661,
-0.1343904435634613,
0.5067586302757263,
0.24277807772159576,
-0.17855897545814514,
0.13484226167201996,
0.014460690319538116,
0.1603565514087677,
0.2705265283584595,
-0.32320085167884827,
-0.1657284051179886,
0.6291850805282593,
0.14990399777889252,
0.034464359283447266,
0.299895703792572,
0.22463494539260864,
-0.37106797099113464,
-0.2069711983203888,
-0.13152313232421875,
-0.05224614590406418,
-0.3681877553462982,
0.027923583984375,
0.35658785700798035,
0.6327370405197144,
-0.08151998370885849,
-0.5868775248527527,
-0.09462009370326996,
0.24371466040611267,
-0.07554932683706284,
-0.10097461193799973,
-0.13449391722679138,
0.2280341386795044,
0.19478893280029297,
0.3044319748878479,
-0.40359747409820557,
-0.06974363327026367,
0.0990145206451416,
0.08143571019172668,
0.009418077766895294,
-0.05463429540395737,
-0.017630569636821747,
0.11922620236873627,
-0.16042016446590424,
0.010838668793439865,
0.16477179527282715,
-0.060169246047735214,
0.36071068048477173,
-0.21490664780139923,
-0.3206721246242523,
0.06903428584337234,
-0.05932850390672684,
0.3171025812625885,
0.07181338965892792,
-0.608530580997467,
0.03394018113613129,
-0.4754469394683838,
-0.13653287291526794,
0.23075494170188904,
0.1410786360502243,
0.11318837851285934,
-0.2693191468715668,
0.1695142388343811,
-0.34914854168891907,
0.12838324904441833,
-0.00893649086356163,
-0.006788323167711496,
-0.025769703090190887,
-0.28193041682243347,
0.06205940619111061,
-0.09378920495510101,
-0.3450583219528198,
0.00953446514904499,
0.028470683842897415,
0.19382166862487793,
-0.2102639526128769,
-0.10387542098760605,
0.19578397274017334,
0.0845952033996582,
0.31471413373947144,
-0.18962429463863373,
0.19519789516925812,
-0.1819043904542923,
-0.6139768958091736,
-0.15016724169254303,
0.04668860137462616,
-0.2589320242404938,
0.033653706312179565,
0.1179800033569336,
-0.3058912456035614,
0.04503721743822098,
0.10600259155035019,
-0.03552224487066269,
0.24374499917030334,
0.18960943818092346,
-0.330634206533432,
-0.14126470685005188,
-0.2343374639749527,
-0.2384476661682129,
0.08291614800691605,
0.006255749613046646,
0.29035305976867676,
-0.27429625391960144,
-0.132715106010437,
0.0041040703654289246,
-0.0777202919125557,
-0.549354612827301,
0.25537705421447754,
0.12873254716396332,
-0.2849130630493164,
-0.05030667036771774,
0.7471095323562622,
-0.1838758885860443,
-0.2807391285896301,
0.06724202632904053,
-0.05907435715198517,
-0.09857086837291718,
-0.06438565999269485,
0.035185277462005615,
0.33346879482269287,
-0.5780576467514038,
-0.14078916609287262,
-0.21537350118160248,
-0.3041473925113678,
0.26338276267051697,
0.24018315970897675,
-0.013686489313840866,
0.12782764434814453,
-0.27479541301727295,
-0.02918938174843788,
0.054756857454776764,
-0.05104214698076248,
-0.007746802642941475,
0.19158364832401276,
-0.17146112024784088,
0.25183263421058655,
0.005483254790306091,
0.07924217730760574,
-0.01534961722791195,
-0.07730845361948013,
0.29996687173843384,
0.3543703556060791,
-0.2617481052875519,
-0.07039570063352585,
-0.036199793219566345,
-0.4247276782989502,
0.16641637682914734,
0.1873418539762497,
0.07433468103408813,
-0.0027771443128585815,
0.1444615125656128,
-0.23539042472839355,
0.13004983961582184,
-0.06374673545360565,
0.223867729306221,
0.2670321464538574,
0.13562460243701935,
0.52492356300354,
0.06076273322105408,
0.04892569035291672,
-0.15978315472602844,
-0.015663962811231613,
0.10479092597961426,
0.4020426273345947,
0.31529003381729126,
-0.1573580801486969,
-0.025230739265680313,
-0.12310608476400375,
-0.24866123497486115,
-0.36729195713996887,
0.24655038118362427,
0.2638358175754547,
0.019912991672754288,
0.33392003178596497,
-0.357746422290802,
0.2866944372653961,
-0.22801707684993744,
-0.25668105483055115,
-0.1881212592124939,
0.2682744860649109,
-0.08029606938362122,
0.02375076897442341,
-0.1958562582731247,
0.35900285840034485,
-0.10002193599939346,
-0.0650896430015564,
-0.10964334011077881,
-0.1666446030139923,
0.21401216089725494,
0.1449785828590393,
0.5165335536003113,
0.2998847961425781,
0.2574204206466675,
-0.24572421610355377,
-0.1387699991464615,
0.18689005076885223,
0.06296168267726898,
-0.20906659960746765,
0.14302563667297363,
0.2379070222377777,
0.18251925706863403,
0.051116518676280975,
0.06885787844657898,
-0.024304836988449097,
0.3960515856742859,
0.21396595239639282,
-0.07813738286495209,
-0.1446685492992401,
0.30037227272987366,
-0.06700195372104645,
0.28173166513442993,
-0.07894673198461533,
-0.39791518449783325,
-0.021499350666999817,
0.3684978783130646,
0.022610630840063095,
0.11486069113016129,
0.1395164430141449,
-0.1527702510356903,
-0.10070927441120148,
0.21678513288497925,
-0.48139747977256775,
0.12765121459960938,
0.26268669962882996,
0.22171497344970703,
-0.16540634632110596,
0.25981947779655457,
0.03460785746574402,
0.04588094353675842,
-0.25480198860168457,
-0.10957492142915726,
-0.039888568222522736,
0.1586693376302719,
0.07674157619476318,
-0.34561803936958313,
-0.4028259515762329,
-0.0025885868817567825,
0.08199048042297363,
0.049554575234651566,
-0.19892188906669617,
0.07890412211418152,
-0.05405363813042641,
0.23634327948093414,
-0.3461318910121918,
-0.2608318626880646,
-0.09982599318027496,
0.24856789410114288,
-0.33776822686195374,
-0.006427828222513199,
0.042945168912410736,
-0.1900702714920044,
0.32391369342803955,
-0.03564951941370964,
-0.00315234437584877,
-0.24567316472530365,
0.00588980270549655,
-0.4746783971786499,
0.29337117075920105,
-0.053815145045518875,
-0.31592875719070435,
0.38174858689308167,
-0.07545958459377289,
0.1476750671863556,
-0.33012962341308594,
-0.5107157230377197,
0.1697302758693695,
-0.12999437749385834,
0.575386106967926,
0.12542343139648438,
0.02576528489589691,
0.013467654585838318,
-0.12582723796367645,
0.02396179921925068,
-0.05465292930603027,
-0.1641533523797989,
-0.11448454856872559,
-0.08873169124126434,
0.42236241698265076,
0.0386972539126873,
-0.45314255356788635,
-0.42036664485931396,
-0.1723112016916275,
0.2529330849647522,
-0.16396479308605194,
-0.0030090510845184326,
0.22998592257499695,
-0.1378037929534912,
0.13826453685760498,
0.009906891733407974,
0.13187910616397858,
-0.26472756266593933,
0.027845803648233414,
0.20042890310287476,
-0.3106869161128998,
-0.2774639129638672,
0.061187949031591415,
-0.09069793671369553,
0.0852125734090805,
-0.24416659772396088,
-0.3625800609588623,
0.2580147683620453,
-0.09587226808071136,
0.27385061979293823,
-0.19152070581912994,
0.07490339875221252,
0.1914641261100769,
0.16966593265533447,
-0.06745731085538864,
0.11042968183755875,
0.007872123271226883,
-0.13218480348587036,
0.010557470843195915,
0.0869903415441513,
-0.10921663790941238,
-0.0853852927684784,
-0.011631377041339874,
0.2945597767829895,
-0.011589999310672283,
0.06750217825174332,
0.2806149125099182,
0.026751503348350525,
0.23155353963375092,
-0.3706285059452057,
-0.4429999589920044,
0.35534635186195374,
0.040036000311374664,
0.04863486438989639,
0.41959822177886963,
0.21355536580085754,
-0.2142554670572281,
-0.20989453792572021,
0.05257746949791908,
0.18030855059623718,
-0.07134474813938141,
0.040761854499578476,
-0.10820119082927704,
0.16658490896224976,
-0.24493514001369476,
-0.2167084515094757,
-0.17305870354175568,
-0.10115177929401398,
0.25474393367767334,
0.3276863694190979,
0.093620665371418,
-0.07407154887914658,
-0.22788836061954498,
0.23817841708660126,
-0.300315260887146,
-0.044358447194099426,
0.08408119529485703,
0.25461193919181824,
-0.2716078460216522,
0.33530646562576294,
0.030030101537704468,
0.15427611768245697,
0.21860197186470032,
-0.6904956102371216,
-0.4939383268356323,
0.13585558533668518,
0.3060668706893921,
0.1556713879108429,
0.1767359972000122,
-0.1837189644575119,
-0.22654761373996735,
0.30841830372810364,
0.2455105483531952,
-0.16246208548545837,
0.029782280325889587,
0.19417054951190948,
0.42701590061187744,
-0.0171998031437397,
-0.046921733766794205,
0.0955195277929306,
-0.16586410999298096,
-0.09738194942474365,
0.39466896653175354,
-0.02931247651576996,
0.017172763124108315,
0.08575226366519928,
0.137074276804924,
-0.0335642471909523,
0.2016945779323578,
0.2797214388847351,
-0.059396203607320786,
-0.16069501638412476,
0.15213672816753387,
0.0868341326713562,
-0.04038210213184357,
-0.48504725098609924,
0.07861019670963287,
0.19921687245368958,
-0.020880240947008133,
-0.5251501202583313,
0.0876171886920929,
-0.23867137730121613,
0.4695502817630768,
0.16023927927017212,
0.2618004381656647,
0.32919129729270935,
-0.2775520384311676,
-0.21814961731433868,
0.030388478189706802,
0.2831471264362335,
0.4071330428123474,
-0.03894490376114845,
-0.43501928448677063,
-0.776552677154541,
-0.0014821141958236694,
-0.09129558503627777,
0.016643479466438293,
0.41284841299057007,
0.43938320875167847,
-0.13270777463912964,
0.24752633273601532,
0.076760433614254,
0.9190419912338257,
0.23129485547542572,
0.041549693793058395,
0.07719247043132782,
-0.08021663874387741,
0.1929486244916916,
-0.3251569867134094,
-0.13492462038993835,
0.04967120662331581,
-0.23054398596286774,
0.005983946844935417,
0.26198527216911316,
0.34716683626174927,
0.2499637007713318,
-0.23360739648342133,
0.10049983859062195,
0.09623244404792786,
-0.19594307243824005,
0.29610949754714966,
0.3082045912742615,
0.10677415877580643,
-0.4312557280063629,
0.03384609892964363,
0.23043572902679443,
0.043792806565761566,
0.20384739339351654,
-0.07254531979560852,
-0.05668361485004425,
0.10696379840373993,
0.1314014494419098,
-0.45485883951187134,
-0.07609505951404572,
-0.5070959329605103,
0.12641814351081848,
-0.4729512631893158,
0.08941704034805298,
0.2029142826795578,
-0.08584138751029968,
0.42142343521118164,
0.47171857953071594,
0.040915802121162415,
0.022925127297639847,
0.47623881697654724,
0.06283987313508987,
-0.08770649880170822,
-0.23555314540863037,
0.2755262553691864,
-0.050539638847112656,
-0.2636359632015228,
0.32308340072631836,
-0.20167532563209534,
-0.13621468842029572,
-0.38254696130752563,
-0.1163196712732315,
-0.10659092664718628,
-0.04572846740484238,
-0.17525967955589294,
0.41036543250083923,
0.17232657968997955,
-0.19534622132778168,
0.14802269637584686,
0.3497508764266968,
-0.2356005609035492,
-0.19416096806526184,
0.10732913017272949,
-0.09747309982776642,
-0.3136826455593109,
-0.22666007280349731,
0.24906349182128906,
-0.6465165615081787,
0.29450729489326477,
0.4389953315258026,
-0.15036293864250183,
-0.23534393310546875,
0.08640588074922562,
0.44002726674079895,
-0.4701535403728485,
-0.38490724563598633,
0.0059770564548671246,
-0.14805962145328522,
-0.042697399854660034,
0.2869289219379425,
0.06660977005958557,
-0.2061111330986023,
0.1507674604654312,
-0.09458740800619125,
-0.36929062008857727,
-0.028940849006175995,
0.1487242430448532,
0.12537972629070282,
0.27110984921455383,
-0.2238439917564392,
0.03578522801399231,
0.07909592986106873,
-0.3972316384315491,
-0.10924950987100601,
-0.10658740252256393,
0.0030478201806545258,
0.24276475608348846,
0.05568774417042732,
0.014138064347207546,
0.03401078283786774,
0.19847622513771057,
-0.34704339504241943,
-0.07309698313474655,
-0.18337324261665344,
-0.1146322637796402,
0.07452747970819473,
0.13493061065673828,
0.1228223368525505,
-0.077947698533535,
-0.035056471824645996,
-0.10303807258605957,
-0.14566455781459808,
0.11736613512039185,
0.07653297483921051,
-0.07971978187561035,
0.25643283128738403,
-0.09329646825790405,
0.011540405452251434,
-0.16124552488327026,
0.0922037810087204,
0.2833353281021118,
0.04205460846424103,
0.28873109817504883,
0.16807055473327637,
0.18502826988697052,
-0.13068319857120514,
0.08269279450178146,
0.2942376434803009,
-0.004716634750366211,
0.3498418927192688,
-0.1388331651687622,
0.037948597222566605,
0.28711998462677,
0.30442380905151367,
-0.07962283492088318,
0.02395400032401085,
-0.10387270152568817,
-0.038740258663892746,
0.3412598669528961,
0.28051409125328064,
-0.3252316117286682,
0.16337814927101135,
0.10603345930576324,
-0.14815394580364227,
0.19855047762393951,
0.2169756293296814,
0.32979583740234375,
0.29217708110809326,
0.4217357635498047,
-0.15993690490722656,
-0.13561317324638367,
0.010873289778828621,
0.4031975567340851,
0.3240828514099121,
-0.037429079413414,
-0.1339365839958191,
0.09704168140888214,
0.264242559671402,
0.010727807879447937,
0.274061918258667,
-0.13993841409683228,
0.32852232456207275,
0.19472768902778625,
0.2168823778629303,
-0.012067921459674835,
-0.2332325428724289,
0.4450658857822418,
0.3071078658103943,
0.28177204728126526,
0.22357061505317688,
0.10950889438390732,
-0.14016768336296082,
-0.1730029135942459,
-0.22349724173545837,
-0.04635661840438843,
0.0801677256822586,
-0.2020120918750763,
-0.001011483371257782,
0.4020218551158905,
-0.3433103561401367,
-0.18070578575134277,
-0.22531436383724213,
-0.053367067128419876,
-0.0010698288679122925,
-0.2768160402774811,
0.112814761698246,
0.1313040852546692,
-0.3100360333919525,
0.06996661424636841,
0.02971084788441658,
0.026648633182048798,
-0.06110558658838272,
0.2780030071735382,
0.010399229824543,
0.17701563239097595,
0.047720108181238174,
0.4197746217250824,
-0.13973702490329742,
0.08330446481704712,
0.016874466091394424,
0.31802231073379517,
-0.20493702590465546,
-0.01801310107111931,
0.08799592405557632,
0.32789117097854614,
0.06277631223201752,
0.2459595799446106,
0.320583313703537,
0.12034431099891663,
-0.1926158219575882,
-0.015043161809444427,
0.17180296778678894,
-0.19165131449699402,
-0.41362860798835754,
0.012699954211711884,
-0.03840883821249008,
0.08607941120862961,
-0.37970414757728577,
-0.031050771474838257,
-0.12854592502117157,
-0.13488523662090302,
0.3256210684776306,
-0.2585844397544861,
-0.10838155448436737,
-0.07899247854948044,
0.13846108317375183,
0.16617566347122192,
-0.2029038965702057,
0.4855582118034363,
0.23405641317367554,
-0.16686522960662842,
-0.21744246780872345,
-0.4381391108036041,
0.051265373826026917,
0.08015064895153046,
0.1744614839553833,
-0.1245618611574173,
0.06258368492126465,
0.3831964433193207,
0.11679412424564362,
-0.042772114276885986,
-0.06421244889497757,
0.16320037841796875,
0.3232917785644531,
-0.34794703125953674,
0.0629393607378006,
0.2859339714050293,
0.4084406793117523,
-0.030207963660359383,
-0.018503978848457336,
-0.07329057157039642,
0.41259074211120605,
0.1505436897277832,
-0.13348513841629028,
-0.2462119311094284,
0.13039067387580872,
0.12726637721061707,
0.3557191491127014,
0.22650910913944244,
0.5275260210037231,
-0.22152623534202576,
-0.037970881909132004,
-0.2685335576534271,
-0.22323279082775116,
-0.06925410777330399,
0.17556259036064148,
0.02854483760893345,
0.06362191587686539,
-0.11477160453796387,
-0.31324541568756104,
-0.24616079032421112,
0.203011617064476,
0.17591363191604614,
0.2730839252471924,
-0.5236432552337646,
0.21069705486297607,
0.09567048400640488,
-0.37458232045173645,
-0.18295717239379883,
0.14599262177944183,
0.041923414915800095,
-0.036862365901470184,
-0.09746697545051575,
-0.05345077067613602,
0.0436975359916687,
-0.1767207235097885,
-0.23924516141414642,
-0.1110527440905571,
0.13255849480628967,
0.31383413076400757,
0.1159164160490036,
-0.36679232120513916,
0.17310664057731628,
0.2874091863632202,
0.22819122672080994,
0.28344497084617615,
-0.02660796046257019,
-0.020219523459672928,
0.03794587776064873,
-0.2808718681335449,
0.3004860281944275,
0.1155647337436676,
0.09652014821767807,
0.1939515769481659,
-0.22160011529922485
] |
https://github.com/huggingface/datasets/issues/222 | Colab Notebook breaks when downloading the squad dataset | The notebook forces version 0.1.0. If I use the latest, things work, I'll run the whole notebook and create a PR.
But in the meantime, this issue gets fixed by changing:
`!pip install nlp==0.1.0`
to
`!pip install nlp` | When I run the notebook in Colab
https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
![image](https://user-images.githubusercontent.com/338917/83311709-ffd1b800-a1dd-11ea-8394-3a87df0d7f8b.png)
| 38 | Colab Notebook breaks when downloading the squad dataset
When I run the notebook in Colab
https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
![image](https://user-images.githubusercontent.com/338917/83311709-ffd1b800-a1dd-11ea-8394-3a87df0d7f8b.png)
The notebook forces version 0.1.0. If I use the latest, things work, I'll run the whole notebook and create a PR.
But in the meantime, this issue gets fixed by changing:
`!pip install nlp==0.1.0`
to
`!pip install nlp` | [
-0.20377331972122192,
0.10567396879196167,
-0.03363513946533203,
0.06406787782907486,
-0.10075315833091736,
-0.1691393107175827,
0.13653059303760529,
0.10918207466602325,
-0.3450912833213806,
0.1280626356601715,
-0.16435293853282928,
0.5187444686889648,
0.18093863129615784,
0.08213922381401062,
0.16695699095726013,
0.07651332020759583,
0.06449422985315323,
0.46056950092315674,
0.04686892777681351,
0.15668262541294098,
-0.2131081521511078,
0.4624912738800049,
-0.4079589247703552,
0.1537039875984192,
-0.23863652348518372,
-0.16774117946624756,
-0.20612671971321106,
0.27909159660339355,
-0.5138829946517944,
-0.27585065364837646,
0.297965943813324,
0.14172382652759552,
-0.008438993245363235,
0.18113583326339722,
-0.00011696519504766911,
-0.23673871159553528,
0.12079568952322006,
-0.051851581782102585,
-0.3485306203365326,
-0.3542289137840271,
-0.008578561246395111,
-0.4436558187007904,
0.15956906974315643,
-0.34196075797080994,
0.14092859625816345,
0.3921468257904053,
0.3511866331100464,
0.37066900730133057,
0.3492595851421356,
0.3874807357788086,
0.15486444532871246,
0.3137633800506592,
0.21581004559993744,
-0.054475974291563034,
0.16369754076004028,
-0.2806618809700012,
-0.2976788580417633,
0.32439976930618286,
0.5822188258171082,
-0.16857078671455383,
0.0035515576601028442,
0.1059035211801529,
-0.09550733119249344,
0.05590522289276123,
0.12202002853155136,
0.1638885736465454,
-0.25351929664611816,
-0.42911747097969055,
0.2994453012943268,
0.12129329144954681,
0.0607747808098793,
-0.2001691460609436,
-0.01815180666744709,
0.0014596953988075256,
0.2585047483444214,
-0.3444949984550476,
0.21898558735847473,
0.3701314330101013,
-0.34308353066444397,
0.07960154861211777,
0.0347071997821331,
-0.032762810587882996,
-0.217060849070549,
0.230853870511055,
0.056651949882507324,
0.3647039234638214,
-0.06477495282888412,
0.010259903967380524,
0.2563156485557556,
0.07807134091854095,
0.22043833136558533,
0.2324579954147339,
-0.19939710199832916,
-0.01257722731679678,
-0.020614508539438248,
-0.19665183126926422,
-0.15251672267913818,
0.3759249150753021,
0.23538938164710999,
-0.3535800576210022,
0.196884885430336,
-0.06267080456018448,
0.19996103644371033,
0.19693246483802795,
0.02321106567978859,
-0.012032496742904186,
0.35832950472831726,
-0.04169832170009613,
0.39903324842453003,
0.4018419086933136,
-0.02484768256545067,
0.0016648806631565094,
0.04790092259645462,
-0.177496999502182,
-0.2790900468826294,
-0.12938418984413147,
0.06468921899795532,
-0.189718559384346,
-0.2175167053937912,
-0.016829531639814377,
-0.15009905397891998,
0.27821674942970276,
0.03317305073142052,
0.19462904334068298,
-0.06817463040351868,
-0.23874244093894958,
0.10872025787830353,
-0.022551842033863068,
-0.3674684762954712,
-0.17430125176906586,
0.009949443861842155,
-0.0019467584788799286,
-0.1876400262117386,
0.10968397557735443,
0.2619292140007019,
0.18368858098983765,
0.4778350293636322,
-0.15345947444438934,
0.09960543364286423,
-0.11781322956085205,
0.052396245300769806,
-0.2653234302997589,
-0.10134170204401016,
0.3144099712371826,
0.3155171573162079,
-0.22006909549236298,
-0.2717234492301941,
-0.5757358074188232,
0.04511953145265579,
0.1976000964641571,
-0.03203395754098892,
-0.012889672070741653,
-0.12502753734588623,
0.10841798782348633,
-0.2844674587249756,
-0.07026495039463043,
-0.3243393003940582,
0.054984934628009796,
-0.21550452709197998,
-0.25893157720565796,
0.04896059259772301,
-0.1539314091205597,
-0.245650514960289,
-0.0019285448361188173,
-0.058479346334934235,
0.18696627020835876,
-0.0323915034532547,
-0.09881709516048431,
0.16054767370224,
0.00841245986521244,
-0.0025032609701156616,
0.2557321786880493,
-0.14600391685962677,
-0.08713565021753311,
0.06068771332502365,
0.19247467815876007,
0.38259610533714294,
-0.3142409026622772,
-0.7157806158065796,
0.12331622838973999,
-0.07620730251073837,
-0.2864677309989929,
-0.09852322190999985,
0.181364044547081,
0.4203035235404968,
-0.18550926446914673,
0.07004640251398087,
0.4979860186576843,
-0.17399761080741882,
0.1083311215043068,
-0.2697705924510956,
-0.17382073402404785,
-0.12889905273914337,
0.05015195533633232,
0.11421224474906921,
-0.017191380262374878,
-0.03910631686449051,
0.7044433951377869,
0.16681408882141113,
-0.09890884160995483,
-0.20148733258247375,
0.05992184951901436,
0.3261891007423401,
-0.3010638356208801,
-0.0882209837436676,
-0.14634931087493896,
-0.5062057971954346,
0.01004686951637268,
-0.3460908532142639,
0.21325284242630005,
0.0968346819281578,
-0.21113018691539764,
-0.05918348208069801,
-0.06821369379758835,
-0.01218407228589058,
-0.17810165882110596,
0.10006794333457947,
0.020486939698457718,
0.048870284110307693,
-0.04860570281744003,
0.09019947052001953,
0.39791059494018555,
-0.19552581012248993,
0.4248863756656647,
-0.20517784357070923,
0.18992064893245697,
-0.34831029176712036,
-0.36242300271987915,
0.06926039606332779,
0.31324702501296997,
0.0034317485988140106,
-0.1705968677997589,
-0.10006601363420486,
0.2572607696056366,
0.08105379343032837,
-0.07469089329242706,
0.10122917592525482,
-0.36668211221694946,
0.3960619270801544,
0.06066770479083061,
-0.04035735875368118,
-0.06082839146256447,
0.012146678753197193,
-0.03536980599164963,
-0.02880086749792099,
0.2245766669511795,
-0.18602298200130463,
-0.04142371565103531,
0.17305608093738556,
0.20941871404647827,
0.039265647530555725,
-0.11988596618175507,
-0.20445342361927032,
0.1320449560880661,
0.32316601276397705,
0.2368137091398239,
0.04117957130074501,
0.010915195569396019,
-0.36299949884414673,
0.21057859063148499,
0.4938598871231079,
0.027466241270303726,
0.24809953570365906,
0.01987292990088463,
0.04852696508169174,
0.0026454664766788483,
0.34254059195518494,
0.08806069195270538,
0.3751702308654785,
0.11413420736789703,
-0.11013118922710419,
-0.003826858475804329,
-0.18535751104354858,
-0.30785664916038513,
0.1314210295677185,
0.0830453634262085,
0.1299072653055191,
-0.16973936557769775,
0.3030274212360382,
0.014845994301140308,
-0.36467915773391724,
-0.1110706627368927,
-0.07071467489004135,
0.23503398895263672,
0.10903173685073853,
0.3059641122817993,
-0.14340360462665558,
-0.6106245517730713,
-0.2032153457403183,
-0.11518280953168869,
-0.1861463189125061,
-0.18630245327949524,
-0.054775431752204895,
0.39907020330429077,
0.3937791585922241,
0.13219667971134186,
0.3591201603412628,
0.20930393040180206,
-0.11759829521179199,
0.18299829959869385,
0.1719692349433899,
-0.04389527067542076,
-0.42944610118865967,
0.03136976808309555,
0.3862445652484894,
0.29799884557724,
0.10854163765907288,
-0.23654919862747192,
-0.24920272827148438,
0.015471708960831165,
-0.4298044443130493,
0.26033616065979004,
-0.3362565040588379,
0.2794796824455261,
0.09976346790790558,
0.24782228469848633,
-0.5951438546180725,
-0.10310759395360947,
0.16499000787734985,
-0.11449187994003296,
-0.12290894240140915,
-0.09292814135551453,
-0.03688323125243187,
-0.4055462181568146,
-0.26714786887168884,
-0.20519253611564636,
-0.4359728693962097,
-0.2693944275379181,
0.3358285427093506,
0.01575186476111412,
0.21157878637313843,
0.3739762306213379,
0.09294816851615906,
0.31005221605300903,
0.04953598231077194,
-0.2053631693124771,
0.12083633244037628,
0.03579314425587654,
0.0885268971323967,
-0.2505459785461426,
-0.4985419809818268,
0.09977518022060394,
0.05173453688621521,
0.037645094096660614,
-0.24499185383319855,
-0.41610968112945557,
-0.5225145816802979,
0.12612798810005188,
0.1882447749376297,
-0.0012071207165718079,
-0.07886308431625366,
0.20694276690483093,
-0.19732968509197235,
0.1095580905675888,
-0.01307712122797966,
-0.24611112475395203,
-0.12782594561576843,
0.0830916091799736,
0.3247511386871338,
-0.15073630213737488,
0.10587995499372482,
0.14839689433574677,
0.19341638684272766,
0.31456393003463745,
-0.07250475883483887,
0.11436943709850311,
0.12013456970453262,
0.27393531799316406,
-0.21050935983657837,
-0.3405758738517761,
0.3424801826477051,
0.010134965181350708,
-0.009619051590561867,
0.3454561233520508,
-0.05972875654697418,
-0.5129147171974182,
-0.18136189877986908,
0.10224531590938568,
-0.25864046812057495,
-0.35660701990127563,
0.10800474882125854,
0.43654659390449524,
-0.0429634153842926,
0.2192896157503128,
0.176939457654953,
-0.0064318375661969185,
-0.26712295413017273,
-0.39389076828956604,
0.2829705476760864,
-0.23305228352546692,
0.10045421123504639,
0.18662957847118378,
-0.45402929186820984,
-0.6995073556900024,
0.1291135847568512,
0.020111992955207825,
0.29739686846733093,
-0.008754976093769073,
0.2319486141204834,
0.1322501301765442,
-0.028030648827552795,
0.24217189848423004,
0.08653083443641663,
-0.1293119341135025,
0.05553670600056648,
0.02404181659221649,
-0.25207918882369995,
0.14389944076538086,
-0.3590138852596283,
0.5358404517173767,
0.8802664875984192,
0.37709736824035645,
-0.16434848308563232,
0.05778127163648605,
0.5292019844055176,
-0.032791536301374435,
0.1895885169506073,
0.10803986340761185,
-0.30443376302719116,
-0.3213100731372833,
-0.14403459429740906,
0.05696239322423935,
-0.048293691128492355,
-0.0072516086511313915,
0.09713459759950638,
-0.10260340571403503,
0.2945187985897064,
-0.13049399852752686,
-0.1803799420595169,
0.49008429050445557,
-0.04314805567264557,
0.06898368895053864,
0.034631866961717606,
-0.20050598680973053,
-0.14851167798042297,
0.2358812689781189,
0.2782011926174164,
-0.21470855176448822,
-0.2510850429534912,
0.19106850028038025,
-0.2993552088737488,
0.12639901041984558,
0.5574198961257935,
-0.012704958207905293,
-0.08767616003751755,
-0.1413710117340088,
-0.010357685387134552,
0.37668415904045105,
0.008204463869333267,
0.34758469462394714,
0.13797669112682343,
-0.08299775421619415,
0.15213747322559357,
0.2743895649909973,
-0.010234429500997066,
0.060648828744888306,
-0.12669657170772552,
-0.13302627205848694,
-0.26653560996055603,
0.43179649114608765,
0.0313241109251976,
0.8313065767288208,
-0.19805578887462616,
0.18259061872959137,
0.21659579873085022,
0.03458178788423538,
0.700577974319458,
0.09818445146083832,
0.29737430810928345,
-0.1605040431022644,
-0.26129215955734253,
-0.02691712975502014,
0.03417275473475456,
0.2771380543708801,
0.003568492829799652,
-0.6976840496063232,
0.3543376326560974,
0.5069888234138489,
-0.06665970385074615,
0.1408870369195938,
0.20467042922973633,
-0.20412833988666534,
-0.3309398293495178,
-0.6929692029953003,
0.1499154269695282,
-0.24720902740955353,
0.21208223700523376,
-0.23182713985443115,
-0.01660650037229061,
-0.22074241936206818,
-0.055851973593235016,
-0.39808905124664307,
0.09784277528524399,
-0.49289393424987793,
-0.14910347759723663,
0.30979645252227783,
-0.2716407775878906,
-0.015284748747944832,
0.318087100982666,
0.2980523109436035,
0.21503791213035583,
-0.04117577522993088,
0.05580143630504608,
-0.009489171206951141,
-0.4288063049316406,
0.069615438580513,
0.12072674930095673,
0.07078708708286285,
-0.2315792739391327,
-0.011699400842189789,
-0.15616866946220398,
0.19199419021606445,
-0.14730089902877808,
0.3778708577156067,
0.26534610986709595,
0.11379937827587128,
0.15317006409168243,
-0.11881119012832642,
-0.04288323223590851,
-0.18436691164970398,
-0.2605475187301636,
0.1095840334892273,
-0.10283772647380829,
-0.1080937311053276,
0.17686614394187927,
0.17040139436721802,
-0.16747748851776123,
-0.018127765506505966,
0.24444758892059326,
-0.10914572328329086,
0.05315779149532318,
0.21790295839309692,
0.2029287964105606,
-0.04807587340474129,
-0.21867182850837708,
0.1641601324081421,
-0.4710911810398102,
-0.2075665295124054,
0.019297659397125244,
0.004306101240217686,
-0.17338921129703522,
-0.056421104818582535,
0.6419909596443176,
0.29731160402297974,
0.03289363533258438,
-0.1205991804599762,
-0.36713284254074097,
-0.22014771401882172,
0.20411597192287445,
0.2204362004995346,
-0.1217895895242691,
0.3346557915210724,
0.3340521454811096,
0.28580614924430847,
0.0965176597237587,
-0.2278682440519333,
0.2888352870941162,
-0.37428563833236694,
0.1768331676721573,
0.03506293147802353,
-0.2467694878578186,
0.1611359417438507,
-0.13581226766109467,
-0.05651426315307617,
0.547860860824585,
0.06339478492736816,
-0.2198670208454132,
-0.13317617774009705,
0.06871268153190613,
0.11896972358226776,
-0.10746381431818008,
-0.31719645857810974,
-0.06813296675682068,
-0.09852121770381927,
-0.04035230726003647,
0.07765203714370728,
-0.0682106763124466,
0.10933534801006317,
-0.06905272603034973,
0.26677948236465454,
0.2946944832801819,
0.2482583075761795,
0.07181014120578766,
-0.05436810851097107,
0.21100717782974243,
0.12927581369876862,
0.2501763701438904,
0.2140113115310669,
0.03418012708425522,
0.14100198447704315,
-0.00031037628650665283,
-0.07852867245674133,
0.15759477019309998,
0.266745001077652,
-0.4023352265357971,
0.10853855311870575,
-0.06370002031326294,
-0.04671737924218178,
0.38915032148361206,
0.05957898497581482,
-0.1627657562494278,
0.25530385971069336,
0.07318656891584396,
-0.14528286457061768,
0.0629551038146019,
0.5381839275360107,
0.16475962102413177,
0.07420110702514648,
0.48672521114349365,
0.11547712981700897,
-0.048144444823265076,
0.1442146748304367,
0.10595778375864029,
0.23524419963359833,
0.2533341348171234,
0.011607512831687927,
-0.08355844020843506,
0.013890925794839859,
0.11324334144592285,
0.08847473561763763,
0.05775381997227669,
0.1947414129972458,
0.008706476539373398,
-0.00255652517080307,
0.18441610038280487,
-0.13208413124084473,
0.09944799542427063,
0.2976967692375183,
-0.03657403588294983,
-0.21635495126247406,
0.04410649836063385,
0.2792079448699951,
0.062182217836380005,
0.13555821776390076,
0.8394277095794678,
-0.535256028175354,
-0.25631389021873474,
-0.11296945065259933,
0.13962063193321228,
-0.36160191893577576,
-0.006912203039973974,
-0.3097972273826599,
0.15970873832702637,
-0.13192445039749146,
-0.018767990171909332,
-0.15464213490486145,
-0.04683637619018555,
0.30263882875442505,
0.2967252731323242,
-0.1764540821313858,
-0.11941330134868622,
-0.21040698885917664,
0.09632765501737595,
-0.1580304205417633,
-0.04321964830160141,
0.5650871992111206,
-0.4615534543991089,
0.15587055683135986,
-0.11572045087814331,
0.5128489136695862,
0.1959538757801056,
0.23445622622966766,
-0.17214342951774597,
-0.16993466019630432,
-0.040043652057647705,
0.021636465564370155,
-0.09688606858253479,
-0.01911655068397522,
0.4978407621383667,
0.2487410008907318,
0.1886564940214157,
0.030080711469054222,
-0.11569540202617645,
0.19563598930835724,
0.15852324664592743,
-0.2628212869167328,
0.05865900591015816,
-0.10240822285413742,
-0.1074177622795105,
-0.14664116501808167,
-0.2744993567466736,
-0.043056122958660126,
-0.3473239839076996,
0.5429143905639648,
-0.2994093596935272,
-0.1069813072681427,
0.0449775867164135,
-0.09464637190103531,
0.0484454482793808,
-0.004604628309607506,
0.5350642204284668,
0.403215616941452,
0.02547585219144821,
-0.21520183980464935,
-0.4277659058570862,
-0.38895684480667114,
0.2161230444908142,
-0.2563636600971222,
0.011096818372607231,
0.059635311365127563,
0.18237672746181488,
-0.10124049335718155,
0.41397738456726074,
-0.07893024384975433,
0.04184630885720253,
-0.12649881839752197,
-0.06532084196805954,
-0.47243618965148926,
-0.1160053163766861,
0.28529053926467896,
-0.2760682702064514,
-0.06966478377580643,
-0.22366377711296082,
0.15214930474758148,
-0.2058599591255188,
-0.07175612449645996,
-0.007133167237043381,
-0.3104133605957031,
-0.2900140881538391,
-0.10448214411735535,
0.07206257432699203,
0.17017734050750732,
0.10107715427875519,
0.019608356058597565,
-0.32109400629997253,
-0.04657530412077904,
-0.2240411788225174,
-0.271959125995636,
0.07557492703199387,
0.2256832867860794,
0.2975493371486664,
-0.05231298506259918,
0.3451107442378998,
-0.16596199572086334,
0.5020350813865662,
0.10082212090492249,
0.03670166805386543,
-0.012219477444887161,
0.0015544518828392029,
-0.12299051135778427,
0.08524467796087265,
-0.14766019582748413,
0.45889905095100403,
-0.2785676419734955,
0.17531099915504456,
-0.4899505376815796,
-0.3166499733924866,
0.3832274377346039,
-0.4803461730480194,
-0.09981128573417664,
0.0017299461178481579,
0.20958417654037476,
0.13941442966461182,
-0.30026501417160034,
-0.39764609932899475,
-0.02579391747713089,
-0.15764199197292328,
-0.17507284879684448,
-0.4597727954387665,
0.13977783918380737,
-0.20215071737766266,
0.05126635357737541,
-0.0826166495680809,
0.4182423949241638,
0.07982709258794785,
-0.25584203004837036,
0.015247397124767303,
-0.15567579865455627
] |
https://github.com/huggingface/datasets/issues/222 | Colab Notebook breaks when downloading the squad dataset | When you install `nlp` for the first time on a Colab runtime, it updates the `pyarrow` library that was already on colab. This update shows this message on colab:
```
WARNING: The following packages were previously imported in this runtime:
[pyarrow]
You must restart the runtime in order to use newly installed versions.
```
You just have to restart the runtime and it should be fine.
If you don't restart, then it breaks like in your first message | When I run the notebook in Colab
https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
![image](https://user-images.githubusercontent.com/338917/83311709-ffd1b800-a1dd-11ea-8394-3a87df0d7f8b.png)
| 78 | Colab Notebook breaks when downloading the squad dataset
When I run the notebook in Colab
https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
![image](https://user-images.githubusercontent.com/338917/83311709-ffd1b800-a1dd-11ea-8394-3a87df0d7f8b.png)
When you install `nlp` for the first time on a Colab runtime, it updates the `pyarrow` library that was already on colab. This update shows this message on colab:
```
WARNING: The following packages were previously imported in this runtime:
[pyarrow]
You must restart the runtime in order to use newly installed versions.
```
You just have to restart the runtime and it should be fine.
If you don't restart, then it breaks like in your first message | [
-0.16229428350925446,
0.28865036368370056,
-0.016385259106755257,
0.08907576650381088,
-0.09513925015926361,
-0.13527382910251617,
0.24156032502651215,
0.04239333048462868,
-0.4444727599620819,
0.05577059090137482,
-0.3425390422344208,
0.5006805658340454,
0.19029931724071503,
0.05172187089920044,
0.23175173997879028,
0.12949393689632416,
0.05272127315402031,
0.45624175667762756,
-0.005170382559299469,
0.15157285332679749,
-0.1371893286705017,
0.4322417974472046,
-0.3422397971153259,
0.19298404455184937,
-0.2837298512458801,
-0.20665043592453003,
-0.3387557864189148,
0.33662930130958557,
-0.3838270604610443,
-0.36793971061706543,
0.30076923966407776,
0.11652305722236633,
-0.010650593787431717,
0.24211174249649048,
-0.00011587276821956038,
-0.26339447498321533,
0.07170158624649048,
0.05097352713346481,
-0.32355111837387085,
-0.18543969094753265,
0.1579289734363556,
-0.2767643332481384,
0.3587702810764313,
-0.36968278884887695,
0.23197349905967712,
0.2630351483821869,
0.19682085514068604,
0.41317909955978394,
0.378421425819397,
0.25508973002433777,
0.15432633459568024,
0.36232462525367737,
0.15149959921836853,
-0.049903079867362976,
0.3280055522918701,
-0.240153506398201,
-0.24223308265209198,
0.5541877746582031,
0.5191040635108948,
-0.17601542174816132,
-0.0643187090754509,
-0.023654695600271225,
-0.15008221566677094,
0.10818663239479065,
0.09065616130828857,
0.2510840594768524,
-0.30428019165992737,
-0.35956698656082153,
0.14779290556907654,
0.07521237432956696,
0.01005680114030838,
-0.25509873032569885,
0.08777572959661484,
-0.08877255767583847,
0.2548277676105499,
-0.4677804410457611,
0.22016599774360657,
0.29525285959243774,
-0.3333255648612976,
0.047399066388607025,
0.06930747628211975,
-0.09359443932771683,
-0.15576386451721191,
0.1831720769405365,
0.11445970833301544,
0.3580797016620636,
-0.0566365122795105,
0.01170644536614418,
0.25798267126083374,
0.11046642810106277,
0.2554870843887329,
0.26135581731796265,
-0.12736041843891144,
-0.12093034386634827,
-0.048167597502470016,
-0.10802482068538666,
-0.11227396875619888,
0.353577584028244,
0.17000266909599304,
-0.2848018407821655,
0.18919840455055237,
-0.08284571766853333,
0.180411696434021,
0.1894938349723816,
-0.025866255164146423,
0.011831950396299362,
0.17808930575847626,
-0.227344810962677,
0.4025893807411194,
0.26510074734687805,
-0.1325012743473053,
-0.019606098532676697,
0.06968577951192856,
-0.08283194899559021,
-0.18123900890350342,
-0.2002732753753662,
0.11146120727062225,
-0.17330406606197357,
-0.21198901534080505,
-0.06052526831626892,
-0.21012082695960999,
0.10313369333744049,
0.030671827495098114,
0.22637057304382324,
-0.04862555116415024,
-0.3248879611492157,
-0.008808787912130356,
0.009723534807562828,
-0.3067668378353119,
-0.1658761203289032,
-0.02070273831486702,
-0.015813101083040237,
-0.3158724009990692,
0.2927926778793335,
0.25611111521720886,
0.01416999101638794,
0.4369167387485504,
-0.0667463019490242,
0.11256466805934906,
-0.06157010793685913,
-0.03654201328754425,
-0.25050827860832214,
-0.1376703977584839,
0.19454526901245117,
0.28504160046577454,
-0.13704144954681396,
-0.274625688791275,
-0.5182225108146667,
-0.029475823044776917,
0.13417834043502808,
-0.09137134999036789,
-0.10038185119628906,
-0.14188069105148315,
0.11342830955982208,
-0.28249549865722656,
-0.0845005214214325,
-0.24448567628860474,
-0.011239003390073776,
-0.27759864926338196,
-0.32704615592956543,
0.06488142162561417,
-0.11334045231342316,
-0.11958074569702148,
-0.17336557805538177,
-0.0513911210000515,
0.22777405381202698,
-0.1550368368625641,
-0.060792289674282074,
0.12664705514907837,
0.08688856661319733,
0.05646301433444023,
0.36917534470558167,
-0.22387832403182983,
0.05881846696138382,
-0.030297335237264633,
0.27381205558776855,
0.4754830300807953,
-0.13133665919303894,
-0.5511143803596497,
0.02224794775247574,
-0.09273926168680191,
-0.2200123369693756,
-0.17768478393554688,
0.1853412687778473,
0.43592777848243713,
-0.1713544875383377,
0.12053315341472626,
0.47766441106796265,
-0.12799139320850372,
0.08927568793296814,
-0.25258973240852356,
-0.2019869089126587,
0.021061614155769348,
0.0683601051568985,
0.10308273136615753,
-0.04792409390211105,
0.010847516357898712,
0.6572158336639404,
0.15238052606582642,
-0.1279432773590088,
-0.2924891412258148,
0.012023558840155602,
0.2637319266796112,
-0.15930792689323425,
-0.08614962548017502,
-0.10207740217447281,
-0.49761849641799927,
-0.01891493611037731,
-0.38266482949256897,
0.22172364592552185,
0.11234728246927261,
-0.126118466258049,
-0.019689809530973434,
-0.02919624000787735,
0.013085011392831802,
-0.10262607038021088,
0.11551791429519653,
0.09121492505073547,
0.03127623721957207,
0.03552217409014702,
0.011038664728403091,
0.3079177439212799,
-0.2108154445886612,
0.40704068541526794,
-0.16428785026073456,
0.3394855260848999,
-0.37261924147605896,
-0.45434367656707764,
0.03883136063814163,
0.3175657093524933,
-0.005407072603702545,
-0.18586820363998413,
-0.0847700759768486,
0.30383995175361633,
-0.03310529887676239,
-0.0015199631452560425,
-0.0419730544090271,
-0.21679885685443878,
0.41755738854408264,
-0.03388039767742157,
0.040236301720142365,
-0.15333695709705353,
0.011028864420950413,
-0.11775416135787964,
0.12128815799951553,
0.15278573334217072,
-0.27263888716697693,
-0.0467425212264061,
0.11932708323001862,
0.08081527799367905,
0.0008184816688299179,
-0.12340371310710907,
-0.12160488963127136,
0.20139914751052856,
0.25048884749412537,
0.23211517930030823,
0.05561453476548195,
0.003987550735473633,
-0.3448365330696106,
0.16886049509048462,
0.6388943791389465,
0.009611144661903381,
0.1933998167514801,
0.00266338512301445,
-0.05535616725683212,
-0.09187646955251694,
0.36545637249946594,
-0.1382659524679184,
0.4473469853401184,
0.08535989373922348,
-0.11062639951705933,
0.046115897595882416,
-0.20016111433506012,
-0.3595981001853943,
0.08434490114450455,
0.1504209339618683,
0.3393532633781433,
-0.16112473607063293,
0.32813283801078796,
0.18927931785583496,
-0.4165051579475403,
-0.1966778188943863,
-0.11323972791433334,
0.16031938791275024,
0.046376269310712814,
0.31053587794303894,
-0.22582700848579407,
-0.636313796043396,
-0.2138478010892868,
-0.2246876358985901,
-0.1736542284488678,
-0.21213839948177338,
-0.06543605029582977,
0.41710567474365234,
0.37957391142845154,
0.10483014583587646,
0.390836626291275,
0.2919412851333618,
-0.1407936066389084,
0.1514676809310913,
0.07684770226478577,
-0.11653365194797516,
-0.4451969861984253,
0.03559618815779686,
0.440340518951416,
0.30272260308265686,
0.1866854727268219,
-0.18262280523777008,
-0.14730453491210938,
0.041650332510471344,
-0.47399434447288513,
0.25526338815689087,
-0.28294235467910767,
0.250566691160202,
0.005636274814605713,
0.2146396040916443,
-0.5915750861167908,
-0.2966306507587433,
0.17837530374526978,
-0.19174475967884064,
-0.06382707506418228,
-0.07141566276550293,
-0.09075494855642319,
-0.36869990825653076,
-0.23214147984981537,
-0.19074279069900513,
-0.3892240822315216,
-0.251996248960495,
0.30632466077804565,
0.04709013178944588,
0.1246849074959755,
0.3451833128929138,
-0.05784675106406212,
0.4203663170337677,
-0.006661331746727228,
-0.04496560990810394,
0.0683775469660759,
0.032240767031908035,
0.06294314563274384,
-0.2506498694419861,
-0.3901831805706024,
0.08632995188236237,
0.08140083402395248,
0.07147687673568726,
-0.32992255687713623,
-0.4478316903114319,
-0.4516489505767822,
0.10525127500295639,
0.2513579726219177,
0.009099237620830536,
-0.09579459577798843,
0.20816729962825775,
-0.1809079349040985,
0.05214749276638031,
0.12245678156614304,
-0.35239288210868835,
-0.2072189748287201,
0.15541231632232666,
0.3015429377555847,
-0.15515083074569702,
0.14002060890197754,
-0.03658069670200348,
0.2472066581249237,
0.12030628323554993,
-0.16269686818122864,
0.2434939742088318,
0.0470380038022995,
0.2754899859428406,
-0.2692047357559204,
-0.3264658451080322,
0.3509717881679535,
-0.13879045844078064,
-0.07192058861255646,
0.35272228717803955,
-0.17399722337722778,
-0.543537974357605,
-0.17621366679668427,
0.08835037052631378,
-0.3520292341709137,
-0.35120058059692383,
0.14087727665901184,
0.4890918731689453,
-0.12838980555534363,
0.16154582798480988,
0.10040249675512314,
0.13662998378276825,
-0.3128577470779419,
-0.28019729256629944,
0.14688032865524292,
-0.31283360719680786,
0.015016519464552402,
0.0840366780757904,
-0.5422759652137756,
-0.6152955293655396,
0.09041263908147812,
0.02460484765470028,
0.16473181545734406,
0.010636936873197556,
0.16953417658805847,
0.1697925478219986,
-0.07759535312652588,
0.18881714344024658,
0.239374041557312,
-0.21169348061084747,
0.10137900710105896,
0.10286170244216919,
-0.24931302666664124,
0.004477288573980331,
-0.4466741681098938,
0.4395610988140106,
0.8527019023895264,
0.21628931164741516,
-0.16088272631168365,
0.1470588594675064,
0.49671170115470886,
0.08200763911008835,
0.1896102875471115,
0.13085351884365082,
-0.27469202876091003,
-0.3481546640396118,
-0.20279721915721893,
0.02792271226644516,
-0.20913085341453552,
0.03567733243107796,
-0.04792370647192001,
-0.05737582594156265,
0.33631300926208496,
-0.05814089626073837,
-0.11765992641448975,
0.5659452676773071,
-0.05071742832660675,
0.1383465975522995,
-0.0365656279027462,
-0.16751006245613098,
-0.05538645386695862,
0.20562489330768585,
0.31446439027786255,
-0.14917083084583282,
-0.11714661121368408,
0.25812581181526184,
-0.17916470766067505,
0.1546858251094818,
0.5725120306015015,
0.03370543196797371,
-0.01572665572166443,
-0.25497832894325256,
-0.027280151844024658,
0.3534432649612427,
0.03846055269241333,
0.3919437825679779,
0.02410222217440605,
-0.09691464155912399,
0.22327588498592377,
0.36032718420028687,
0.006348045542836189,
0.005739316344261169,
-0.05591969192028046,
-0.13157901167869568,
-0.16340459883213043,
0.5269417762756348,
0.09646141529083252,
0.9199798107147217,
-0.13518962264060974,
0.2328004240989685,
0.39558547735214233,
0.005457688122987747,
0.8213492035865784,
0.036442771553993225,
0.29021501541137695,
-0.2200111299753189,
-0.10888098925352097,
0.038619667291641235,
-0.027458976954221725,
0.14550791680812836,
-0.15644913911819458,
-0.6769137978553772,
0.24205626547336578,
0.45106345415115356,
0.08140227198600769,
0.05928388983011246,
0.22673889994621277,
-0.040526434779167175,
-0.2793492078781128,
-0.6700121760368347,
0.16516238451004028,
-0.23910804092884064,
0.25718143582344055,
-0.3153548538684845,
0.006179021671414375,
-0.12149988114833832,
-0.01944376714527607,
-0.41948968172073364,
0.1596042513847351,
-0.3940163552761078,
-0.10973115265369415,
0.25963613390922546,
-0.24909450113773346,
-0.003667149692773819,
0.19052889943122864,
0.323668897151947,
0.18673259019851685,
-0.0359213650226593,
-0.02719733491539955,
-0.07232923060655594,
-0.34440359473228455,
0.1388995498418808,
0.07803389430046082,
0.13850179314613342,
-0.23670151829719543,
-0.086870476603508,
0.028653942048549652,
0.24055737257003784,
-0.17888350784778595,
0.2510043978691101,
0.26750999689102173,
0.09652285277843475,
0.03877583518624306,
0.021772412583231926,
0.049311600625514984,
-0.12440276145935059,
-0.25639116764068604,
0.08975756168365479,
-0.10483016073703766,
-0.04636775329709053,
0.25974172353744507,
0.16537608206272125,
-0.15297949314117432,
-0.09329453110694885,
0.16011497378349304,
-0.12814617156982422,
0.09165763854980469,
0.18983621895313263,
0.2613019049167633,
-0.07720856368541718,
-0.17520993947982788,
0.045474305748939514,
-0.5221548676490784,
-0.3000226616859436,
-0.07522928714752197,
0.02601168490946293,
-0.05449220538139343,
0.07419305294752121,
0.6213568449020386,
0.3452058434486389,
0.1389111578464508,
-0.09827123582363129,
-0.30082517862319946,
-0.1382514238357544,
0.22200584411621094,
0.31040114164352417,
-0.10538050532341003,
0.43308311700820923,
0.4210222363471985,
0.2333647608757019,
0.170184925198555,
-0.23408553004264832,
0.3082627058029175,
-0.34560006856918335,
0.1343725323677063,
-0.04723048955202103,
-0.2782139182090759,
0.1894894689321518,
-0.06866849958896637,
-0.05093331262469292,
0.5490370988845825,
0.13024351000785828,
-0.19484561681747437,
-0.0554991252720356,
0.06485946476459503,
0.08955325931310654,
-0.10635159909725189,
-0.355571985244751,
-0.08047802746295929,
0.07174202799797058,
0.00746369082480669,
0.11996142566204071,
-0.13209018111228943,
0.15138033032417297,
-0.06826154887676239,
0.37282606959342957,
0.24534690380096436,
0.13897669315338135,
0.11990594863891602,
0.018168345093727112,
0.23148804903030396,
0.16493651270866394,
0.26410728693008423,
0.11129942536354065,
-0.008376307785511017,
0.10891096293926239,
0.01216726005077362,
-0.04408532381057739,
0.0655946359038353,
0.1964225471019745,
-0.38780468702316284,
0.07796412706375122,
-0.23517318069934845,
-0.037391506135463715,
0.48941290378570557,
0.13260655105113983,
-0.18248435854911804,
0.2481166124343872,
0.06972344219684601,
-0.11593437194824219,
0.022276239469647408,
0.4485892355442047,
0.18295283615589142,
-0.019731197506189346,
0.4950128495693207,
0.1573648303747177,
-0.003334715962409973,
0.12629817426204681,
0.04812316596508026,
0.2687561810016632,
0.36889469623565674,
0.0004860414192080498,
-0.06775552034378052,
-0.06217379868030548,
0.03523818403482437,
0.17615734040737152,
0.060218654572963715,
0.15215088427066803,
-0.06740161776542664,
-0.12788814306259155,
0.15209059417247772,
-0.289011150598526,
0.06382182240486145,
0.3066234290599823,
-0.05420027673244476,
-0.2557840645313263,
0.11049554497003555,
0.3738560676574707,
-0.02909044921398163,
0.08440802246332169,
0.8333595395088196,
-0.35441017150878906,
-0.3209327161312103,
-0.1020396426320076,
0.2567328214645386,
-0.345008909702301,
0.09901490807533264,
-0.27242404222488403,
0.10394691675901413,
-0.08362768590450287,
0.08783477544784546,
-0.17857876420021057,
-0.13201038539409637,
0.3258436918258667,
0.2735811173915863,
-0.2538757920265198,
-0.15999843180179596,
-0.16739705204963684,
0.05449536442756653,
-0.1816900074481964,
0.07494211196899414,
0.5572719573974609,
-0.33135414123535156,
0.09935422241687775,
-0.23304104804992676,
0.528035581111908,
0.289602667093277,
0.2048736810684204,
-0.19099849462509155,
-0.1523382067680359,
-0.040742866694927216,
0.04505090415477753,
-0.014735380187630653,
-0.06881915777921677,
0.4951958954334259,
0.10088448226451874,
0.18965791165828705,
0.049777351319789886,
-0.13975872099399567,
0.28492471575737,
0.13173896074295044,
-0.21514549851417542,
0.037306033074855804,
-0.10045898705720901,
0.0037534888833761215,
-0.17565684020519257,
-0.3053843677043915,
-0.050677500665187836,
-0.31464946269989014,
0.5148182511329651,
-0.14559148252010345,
-0.11733540147542953,
-0.04240352660417557,
-0.13935600221157074,
0.05286145955324173,
0.09525205194950104,
0.6466183066368103,
0.5057283639907837,
0.15907415747642517,
-0.19428105652332306,
-0.4506126046180725,
-0.41047388315200806,
0.2689817547798157,
-0.30991464853286743,
0.11366626620292664,
0.05045691505074501,
0.1924663633108139,
-0.16570335626602173,
0.4790000915527344,
-0.026662632822990417,
0.11698726564645767,
-0.24810901284217834,
-0.15506228804588318,
-0.5336962342262268,
-0.015051908791065216,
0.11213739216327667,
-0.3295289874076843,
-0.1642407327890396,
-0.043305810540914536,
0.21823453903198242,
-0.3421745002269745,
-0.07783357799053192,
-0.06188158690929413,
-0.30674275755882263,
-0.2668483257293701,
-0.07545420527458191,
0.25476449728012085,
0.10352201759815216,
0.13317328691482544,
0.07666158676147461,
-0.3111726939678192,
0.02930312603712082,
-0.38363757729530334,
-0.1451123058795929,
0.04734295606613159,
0.17323514819145203,
0.19779308140277863,
0.0003887750208377838,
0.36838898062705994,
-0.19359779357910156,
0.504595160484314,
0.09660807251930237,
0.06460712105035782,
-0.002981509082019329,
-0.09048981219530106,
-0.07207770645618439,
0.08612068742513657,
-0.0878099799156189,
0.42042770981788635,
-0.23913711309432983,
0.2577548027038574,
-0.547700047492981,
-0.26309603452682495,
0.4129125475883484,
-0.4527483284473419,
-0.04186302050948143,
-0.00435636006295681,
0.19462785124778748,
0.11911725997924805,
-0.19335907697677612,
-0.4065576493740082,
-0.09077239036560059,
-0.10226772725582123,
-0.12823066115379333,
-0.44656145572662354,
0.18074040114879608,
-0.12650536000728607,
-0.009618472307920456,
-0.11334371566772461,
0.2060469388961792,
0.044330112636089325,
-0.275480717420578,
-0.0735137015581131,
-0.18137381970882416
] |
https://github.com/huggingface/datasets/issues/222 | Colab Notebook breaks when downloading the squad dataset | Thanks for reporting the second one ! We'll update the notebook to fix this one :) | When I run the notebook in Colab
https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
![image](https://user-images.githubusercontent.com/338917/83311709-ffd1b800-a1dd-11ea-8394-3a87df0d7f8b.png)
| 16 | Colab Notebook breaks when downloading the squad dataset
When I run the notebook in Colab
https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
![image](https://user-images.githubusercontent.com/338917/83311709-ffd1b800-a1dd-11ea-8394-3a87df0d7f8b.png)
Thanks for reporting the second one ! We'll update the notebook to fix this one :) | [
-0.20812611281871796,
0.08529740571975708,
-0.08818325400352478,
0.16447675228118896,
-0.023115716874599457,
-0.10333463549613953,
0.3287059962749481,
0.08260271698236465,
-0.3126956820487976,
0.21142813563346863,
-0.39940762519836426,
0.33623337745666504,
0.2900557816028595,
0.16409508883953094,
0.15483728051185608,
0.164514422416687,
0.09830836951732635,
0.37275904417037964,
-0.06697463989257812,
0.14713607728481293,
-0.22851459681987762,
0.4517594575881958,
-0.3685060143470764,
0.06003374978899956,
-0.27340254187583923,
-0.20931918919086456,
-0.23765408992767334,
0.273295134305954,
-0.4236902594566345,
-0.2180948704481125,
0.2879370152950287,
0.18390336632728577,
-0.11174572259187698,
0.2599034309387207,
-0.00011433531471993774,
-0.24122940003871918,
-0.020322293043136597,
-0.06533646583557129,
-0.3073402941226959,
-0.16067226231098175,
-0.08061999082565308,
-0.23325759172439575,
0.2200169563293457,
-0.4098558723926544,
0.1319078803062439,
0.41221514344215393,
0.2227526307106018,
0.286211758852005,
0.2939855456352234,
0.29529327154159546,
0.18044836819171906,
0.4040350914001465,
0.12714536488056183,
-0.17765109241008759,
0.32549697160720825,
-0.2722628116607666,
-0.24315336346626282,
0.410020112991333,
0.627405047416687,
-0.08831330388784409,
-0.06562700122594833,
0.13427631556987762,
-0.12808924913406372,
0.12494772672653198,
0.08908423036336899,
0.24771210551261902,
-0.2894337773323059,
-0.4838736951351166,
0.34367427229881287,
0.11621173471212387,
0.15104791522026062,
-0.12315120548009872,
0.058925919234752655,
0.05899590253829956,
0.1713838130235672,
-0.29327523708343506,
0.26158592104911804,
0.3350571095943451,
-0.22270549833774567,
0.13434647023677826,
0.006289578974246979,
0.08987294882535934,
-0.1818217933177948,
0.13155537843704224,
-0.027878839522600174,
0.16018429398536682,
-0.14802968502044678,
-0.09576212614774704,
0.22563056647777557,
0.011602772399783134,
0.2465774267911911,
0.09906674921512604,
-0.16215816140174866,
-0.09483564645051956,
-0.1089966893196106,
-0.24236761033535004,
-0.2443491518497467,
0.24999386072158813,
0.23728668689727783,
-0.24156509339809418,
0.3187462091445923,
-0.029161054641008377,
0.2450110912322998,
0.1847766935825348,
-0.031999439001083374,
-0.14745502173900604,
0.25958141684532166,
-0.1022157296538353,
0.4240211844444275,
0.41627928614616394,
-0.1882748007774353,
-0.09184844046831131,
-0.02441922202706337,
-0.17939020693302155,
-0.22493113577365875,
-0.09151172637939453,
0.04073415696620941,
-0.24053452908992767,
-0.2889053225517273,
0.07782167941331863,
-0.1368495523929596,
0.2789806127548218,
0.06914238631725311,
0.2426397204399109,
-0.001409911666996777,
-0.4101417362689972,
0.03285718709230423,
-0.010167215019464493,
-0.2695293724536896,
-0.22026358544826508,
-0.030173445120453835,
-0.09110906720161438,
-0.1644534468650818,
0.26104265451431274,
0.24966920912265778,
0.136254221200943,
0.5002055764198303,
-0.09450667351484299,
0.23768068850040436,
-0.2036779224872589,
0.03617642819881439,
-0.42523881793022156,
-0.09555710107088089,
0.3575984239578247,
0.3498214781284332,
-0.203954815864563,
-0.22149424254894257,
-0.5597000122070312,
0.10842228680849075,
0.07068213075399399,
-0.03556116670370102,
-0.022771235555410385,
-0.037245579063892365,
0.1511412113904953,
-0.20522908866405487,
0.02430899254977703,
-0.31279516220092773,
0.04790033400058746,
-0.28003260493278503,
-0.1421736478805542,
0.01360168308019638,
-0.03400634229183197,
-0.2153872549533844,
-0.03196972608566284,
-0.016684822738170624,
0.2605353593826294,
-0.10019350796937943,
0.00802689790725708,
0.20574261248111725,
-0.04610013589262962,
-0.040377043187618256,
0.31282347440719604,
-0.15650902688503265,
-0.009523682296276093,
-0.010019519366323948,
0.2053345888853073,
0.3080560863018036,
-0.2581486999988556,
-0.7119432687759399,
0.05824534222483635,
0.005247361958026886,
-0.26256269216537476,
-0.13132771849632263,
0.23769718408584595,
0.5601800680160522,
-0.1987905353307724,
0.11458456516265869,
0.4635341167449951,
-0.18903322517871857,
0.09863816946744919,
-0.15008224546909332,
-0.1512318104505539,
-0.1275019496679306,
0.12364053726196289,
0.20790448784828186,
-0.006194032728672028,
0.07666581869125366,
0.5572872161865234,
0.16624769568443298,
-0.1265098601579666,
-0.3530396819114685,
0.07210428267717361,
0.27843502163887024,
-0.3214608430862427,
-0.09803193807601929,
-0.10858356207609177,
-0.5646517872810364,
0.06257221847772598,
-0.28644707798957825,
0.08351267129182816,
0.13649031519889832,
-0.23094579577445984,
-0.0580952987074852,
-0.0626564472913742,
-0.07724547386169434,
-0.03654152527451515,
0.1337592601776123,
-0.09502677619457245,
-0.033458929508924484,
0.020008746534585953,
0.11398935317993164,
0.3453357517719269,
-0.2902800738811493,
0.5099153518676758,
0.008631348609924316,
0.32485464215278625,
-0.27559128403663635,
-0.30001163482666016,
0.1337188333272934,
0.09635904431343079,
0.08106764405965805,
-0.1677875816822052,
-0.14541804790496826,
0.29110416769981384,
0.19663825631141663,
0.031059160828590393,
0.14562588930130005,
-0.27314692735671997,
0.4598880112171173,
0.058973077684640884,
-0.035778917372226715,
-0.13375794887542725,
0.08443674445152283,
-0.19134965538978577,
-0.04629848897457123,
0.2320573627948761,
-0.24288012087345123,
-0.04818817228078842,
0.11958301067352295,
0.1858396679162979,
0.04129054397344589,
-0.13352656364440918,
-0.15656763315200806,
0.09857840836048126,
0.23880954086780548,
0.20704035460948944,
-0.0013627633452415466,
-0.04337596893310547,
-0.34334397315979004,
0.19563522934913635,
0.46204400062561035,
-0.005481511354446411,
0.20487985014915466,
-0.06295571476221085,
-0.06925413757562637,
0.0003483295440673828,
0.42172321677207947,
0.04121627286076546,
0.4216998815536499,
0.08651918917894363,
-0.090688556432724,
0.0007988698780536652,
-0.03490293025970459,
-0.3570866584777832,
0.16904473304748535,
0.14286863803863525,
0.2106134444475174,
-0.1635541021823883,
0.22982488572597504,
-0.036555614322423935,
-0.3995290696620941,
-0.10759542882442474,
-0.08823565393686295,
0.13155025243759155,
0.13491052389144897,
0.3200078308582306,
-0.11699086427688599,
-0.5118411779403687,
-0.07171622663736343,
-0.1881691813468933,
-0.09109161794185638,
-0.2565024793148041,
-0.047091953456401825,
0.506132960319519,
0.3253307044506073,
0.013789152726531029,
0.3485431671142578,
0.34163233637809753,
-0.002122672274708748,
0.3129968047142029,
0.11849890649318695,
-0.04346625134348869,
-0.28942447900772095,
0.07920357584953308,
0.42273062467575073,
0.24148361384868622,
0.21288280189037323,
-0.30292388796806335,
-0.15141017735004425,
-0.14659321308135986,
-0.28685131669044495,
0.29411792755126953,
-0.19982564449310303,
0.23458154499530792,
-0.02369757741689682,
0.1992698311805725,
-0.5368194580078125,
-0.12628576159477234,
0.1590675413608551,
-0.010400773026049137,
-0.08413989841938019,
-0.05235573649406433,
-0.01666244864463806,
-0.4458804428577423,
-0.20343223214149475,
-0.1740431785583496,
-0.3917514979839325,
-0.24149511754512787,
0.18787041306495667,
-0.11721916496753693,
0.1827543079853058,
0.2395993322134018,
0.065528005361557,
0.40171733498573303,
-0.03590880334377289,
-0.24859121441841125,
0.018446635454893112,
-0.1290372908115387,
0.2076355516910553,
-0.32397735118865967,
-0.5115103721618652,
0.10641662776470184,
0.18794181942939758,
0.0032007023692131042,
-0.26909077167510986,
-0.43559908866882324,
-0.3778632879257202,
0.049906257539987564,
0.119134321808815,
0.023840852081775665,
-0.2214813530445099,
0.005934268236160278,
-0.26215100288391113,
0.04465475678443909,
-0.010199185460805893,
-0.2739880084991455,
-0.11105111986398697,
0.07669292390346527,
0.30780330300331116,
-0.19712606072425842,
0.11028680205345154,
0.03152870759367943,
0.25294387340545654,
0.3045100271701813,
-0.11898021399974823,
0.18053938448429108,
0.1001780778169632,
0.217914417386055,
-0.2815532982349396,
-0.44954508543014526,
0.3379516899585724,
-0.1619504988193512,
-0.06860882043838501,
0.35916173458099365,
-0.09100829809904099,
-0.5044240951538086,
-0.17165996134281158,
0.072667196393013,
-0.26782113313674927,
-0.42276081442832947,
0.07086481899023056,
0.44430238008499146,
-0.14769354462623596,
0.11258593201637268,
0.21931472420692444,
0.019851818680763245,
-0.2291976511478424,
-0.3125329911708832,
0.33609849214553833,
-0.28678032755851746,
0.001498315017670393,
0.15573740005493164,
-0.41713234782218933,
-0.6907585859298706,
0.16188699007034302,
-0.0503639280796051,
0.1151643842458725,
-0.11067374050617218,
0.29069948196411133,
0.10505314916372299,
0.03925466164946556,
0.3141642212867737,
0.11675354838371277,
-0.15859441459178925,
0.04357834532856941,
-0.07495133578777313,
-0.19444707036018372,
0.03445034846663475,
-0.46410566568374634,
0.5842931270599365,
0.791657030582428,
0.39100512862205505,
-0.04272051155567169,
0.14425702393054962,
0.5085097551345825,
-0.03295799344778061,
0.15193405747413635,
0.08288567513227463,
-0.14068740606307983,
-0.3031001091003418,
-0.1240249052643776,
0.05947873368859291,
-0.027399515733122826,
-0.060650307685136795,
0.033765941858291626,
-0.20056183636188507,
0.30888551473617554,
-0.07161420583724976,
-0.0267878919839859,
0.5213572382926941,
-0.019524237141013145,
0.08624415844678879,
0.10341477394104004,
-0.10577695071697235,
-0.11154292523860931,
0.4208713471889496,
0.30464044213294983,
-0.20926691591739655,
-0.2674808204174042,
0.2845478951931,
-0.49008119106292725,
0.09635571390390396,
0.5848199725151062,
-0.010691358707845211,
-0.031013168394565582,
-0.1739792674779892,
0.0050660669803619385,
0.3778679072856903,
0.05310952290892601,
0.40148672461509705,
0.17706425487995148,
-0.02953927032649517,
0.17760561406612396,
0.257417768239975,
-0.09426917135715485,
0.01887008547782898,
0.014035731554031372,
-0.1412169188261032,
-0.23207984864711761,
0.44888657331466675,
0.07712198048830032,
0.8232882618904114,
-0.1511876881122589,
0.06643524020910263,
0.17773103713989258,
0.005393411964178085,
0.5558375716209412,
-0.015879733487963676,
0.22724460065364838,
-0.1396792232990265,
-0.4450140595436096,
-0.022555772215127945,
-0.10461308807134628,
0.28905585408210754,
-0.026632964611053467,
-0.7058284878730774,
0.2149587869644165,
0.2657940983772278,
0.15262751281261444,
0.02041568234562874,
0.05576954782009125,
-0.14507755637168884,
-0.24285975098609924,
-0.5719939470291138,
0.22100290656089783,
-0.17519983649253845,
0.2350521981716156,
-0.28548693656921387,
0.03061573952436447,
-0.25519639253616333,
0.043435677886009216,
-0.45206600427627563,
0.06690526008605957,
-0.4822937846183777,
0.013023794628679752,
0.14497774839401245,
-0.25090157985687256,
0.04381660744547844,
0.3447955846786499,
0.38753020763397217,
0.17426258325576782,
-0.04343307018280029,
-0.01864882931113243,
-0.03557267785072327,
-0.30341026186943054,
-0.0630999282002449,
-0.01694113202393055,
0.005117092281579971,
-0.2645796239376068,
-0.06806783378124237,
-0.07059996575117111,
0.30341193079948425,
-0.14938153326511383,
0.3579692840576172,
0.1762150526046753,
0.12822237610816956,
-0.06678523123264313,
-0.05379936099052429,
-0.11600913107395172,
-0.1748107224702835,
-0.29133135080337524,
0.1321408748626709,
-0.1205013245344162,
-0.005070164799690247,
0.29780736565589905,
0.18357326090335846,
-0.12276741117238998,
-0.035556141287088394,
0.2913229167461395,
-0.2046390175819397,
0.10926903784275055,
0.21874366700649261,
0.25724437832832336,
-0.12845025956630707,
-0.2801276445388794,
0.30033043026924133,
-0.4932372570037842,
-0.17429225146770477,
0.11607924103736877,
-0.17401978373527527,
-0.12756580114364624,
-0.13076527416706085,
0.6403630971908569,
0.41495847702026367,
-0.010212138295173645,
-0.06361081451177597,
-0.36319300532341003,
-0.20702557265758514,
0.20271044969558716,
0.25006306171417236,
0.02594696916639805,
0.22087985277175903,
0.19487769901752472,
0.21906661987304688,
0.06693298369646072,
-0.270333468914032,
0.373213529586792,
-0.4460946023464203,
0.05523914471268654,
-0.03002113476395607,
-0.24697262048721313,
0.23904503881931305,
-0.15189622342586517,
-0.03373747318983078,
0.502168595790863,
0.06566665321588516,
-0.26115095615386963,
-0.06453022360801697,
0.06806580722332001,
0.00853058323264122,
-0.12818123400211334,
-0.2609414756298065,
0.004728136584162712,
-0.03035365790128708,
-0.06656614691019058,
0.17197631299495697,
-0.058868810534477234,
0.2700216770172119,
-0.12606224417686462,
0.33104389905929565,
0.20877617597579956,
0.15549926459789276,
0.0846952572464943,
0.013366863131523132,
0.20232270658016205,
0.12882864475250244,
0.12136552482843399,
0.1580013632774353,
-0.07078966498374939,
0.25705859065055847,
0.02487761527299881,
-0.07617715001106262,
-0.007841411978006363,
0.33350980281829834,
-0.33863329887390137,
0.15942130982875824,
0.0026581971906125546,
-0.16646437346935272,
0.3518216907978058,
-0.0122822942212224,
-0.12231290340423584,
0.10254073888063431,
0.13919846713542938,
-0.10381705313920975,
-0.05152583494782448,
0.5680357813835144,
0.20062626898288727,
0.030121412128210068,
0.5001777410507202,
0.08568538725376129,
-0.04003031924366951,
0.2109011858701706,
0.044015124440193176,
0.3199205994606018,
0.477145254611969,
0.07485055923461914,
-0.11321045458316803,
0.025738749653100967,
0.23483610153198242,
0.11907745152711868,
0.05644068866968155,
0.16241036355495453,
-0.04504361003637314,
-0.050260014832019806,
0.11100438237190247,
-0.17791956663131714,
0.08935988694429398,
0.49929049611091614,
-0.10340704023838043,
-0.22849802672863007,
0.042944394052028656,
0.10159806907176971,
0.027173761278390884,
0.12443164736032486,
0.738997757434845,
-0.48798197507858276,
-0.26755407452583313,
-0.19579683244228363,
0.1438283771276474,
-0.4215511977672577,
0.08674022555351257,
-0.31011244654655457,
0.06441142410039902,
-0.09468194842338562,
-0.0019607506692409515,
-0.16727225482463837,
-0.05734232813119888,
0.3959067165851593,
0.2621211111545563,
-0.19068606197834015,
0.03612062335014343,
-0.12258759886026382,
0.10783541947603226,
-0.13998591899871826,
-0.012021541595458984,
0.4424281716346741,
-0.30636030435562134,
0.2628045082092285,
0.014340197667479515,
0.6072162389755249,
0.18633612990379333,
0.20774537324905396,
-0.10181604325771332,
-0.2245771735906601,
0.06042516231536865,
-0.08757299929857254,
0.012050177901983261,
-0.055068016052246094,
0.4431183338165283,
0.08779536187648773,
0.26832982897758484,
0.08101987838745117,
-0.14020629227161407,
0.22144773602485657,
0.1270507127046585,
-0.18602310121059418,
0.034433431923389435,
-0.29817187786102295,
-0.0920553207397461,
-0.14600978791713715,
-0.29239657521247864,
-0.17628207802772522,
-0.3040122985839844,
0.4630802571773529,
-0.23748037219047546,
-0.15882517397403717,
0.09287767112255096,
0.026172105222940445,
0.07179025560617447,
0.00036934204399585724,
0.5908597111701965,
0.3205854296684265,
-0.0013034939765930176,
-0.2988016605377197,
-0.5059593915939331,
-0.3325135409832001,
0.1911904215812683,
-0.16133569180965424,
0.13938629627227783,
0.08501014113426208,
0.1867828071117401,
-0.02311478555202484,
0.45860767364501953,
0.1640261709690094,
-0.08083482086658478,
-0.2100592404603958,
-0.06281013786792755,
-0.5517159700393677,
-0.13538366556167603,
0.26514410972595215,
-0.26066315174102783,
-0.16066502034664154,
-0.16178691387176514,
0.28976377844810486,
-0.1578645408153534,
0.008336901664733887,
-0.04479454457759857,
-0.27315443754196167,
-0.33197638392448425,
-0.24862372875213623,
0.15242043137550354,
0.12959279119968414,
0.12297084927558899,
0.007584661245346069,
-0.33314165472984314,
0.12094786763191223,
-0.2889213562011719,
-0.10682777315378189,
0.011426374316215515,
0.21625448763370514,
0.250301331281662,
0.02853419817984104,
0.26356276869773865,
-0.09871037304401398,
0.4951654374599457,
0.1588352471590042,
0.02855980396270752,
-0.16628402471542358,
-0.08736930787563324,
-0.07266160845756531,
0.059975218027830124,
-0.04567209258675575,
0.40819433331489563,
-0.32333117723464966,
0.2676665186882019,
-0.4084075689315796,
-0.2796306312084198,
0.392464816570282,
-0.37216269969940186,
-0.07345762848854065,
-0.01743394136428833,
0.2117195427417755,
0.13282813131809235,
-0.13608139753341675,
-0.32911065220832825,
-0.07494746148586273,
-0.11623641848564148,
-0.2900269031524658,
-0.45486074686050415,
0.2603672742843628,
-0.07690216600894928,
0.06409212946891785,
-0.10680924355983734,
0.34088853001594543,
0.1294020712375641,
-0.2829594314098358,
-0.16729773581027985,
-0.21795813739299774
] |
https://github.com/huggingface/datasets/issues/222 | Colab Notebook breaks when downloading the squad dataset | This trick from @thomwolf seems to be the most reliable solution to fix this colab notebook issue:
```python
# install nlp
!pip install -qq nlp==0.2.0
# Make sure that we have a recent version of pyarrow in the session before we continue - otherwise reboot Colab to activate it
import pyarrow
if int(pyarrow.__version__.split('.')[1]) < 16:
import os
os.kill(os.getpid(), 9)
``` | When I run the notebook in Colab
https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
![image](https://user-images.githubusercontent.com/338917/83311709-ffd1b800-a1dd-11ea-8394-3a87df0d7f8b.png)
| 60 | Colab Notebook breaks when downloading the squad dataset
When I run the notebook in Colab
https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
![image](https://user-images.githubusercontent.com/338917/83311709-ffd1b800-a1dd-11ea-8394-3a87df0d7f8b.png)
This trick from @thomwolf seems to be the most reliable solution to fix this colab notebook issue:
```python
# install nlp
!pip install -qq nlp==0.2.0
# Make sure that we have a recent version of pyarrow in the session before we continue - otherwise reboot Colab to activate it
import pyarrow
if int(pyarrow.__version__.split('.')[1]) < 16:
import os
os.kill(os.getpid(), 9)
``` | [
-0.2108590304851532,
0.31305992603302,
-0.049380332231521606,
0.03972186520695686,
-0.08726876974105835,
-0.18556517362594604,
0.2631244361400604,
0.15955516695976257,
-0.44758912920951843,
0.10873610526323318,
-0.3607417941093445,
0.5732998847961426,
0.19588486850261688,
0.08197712898254395,
0.17324364185333252,
0.19502784311771393,
-0.008884638547897339,
0.3963029682636261,
-0.057467564940452576,
0.16443295776844025,
-0.22316746413707733,
0.3445679247379303,
-0.3933257460594177,
0.1032145544886589,
-0.22195595502853394,
-0.19702430069446564,
-0.15914304554462433,
0.29760801792144775,
-0.39194461703300476,
-0.2167634516954422,
0.27606332302093506,
0.1715928465127945,
-0.059993281960487366,
0.17929421365261078,
-0.00011473386257421225,
-0.20161773264408112,
-0.030263230204582214,
-0.07803517580032349,
-0.3729619085788727,
-0.23220182955265045,
0.03527386486530304,
-0.33603227138519287,
0.3040671646595001,
-0.4480282664299011,
0.13219532370567322,
0.4575706422328949,
0.2886238396167755,
0.35761699080467224,
0.29694077372550964,
0.2759973108768463,
0.1642184555530548,
0.3264271020889282,
0.13450878858566284,
0.005115261767059565,
0.23249945044517517,
-0.2531128525733948,
-0.2693357467651367,
0.42635324597358704,
0.5949572324752808,
-0.26348480582237244,
-0.13266947865486145,
0.10558639466762543,
-0.1691100001335144,
0.15007247030735016,
0.11090759932994843,
0.22836950421333313,
-0.344156950712204,
-0.4259018003940582,
0.22296041250228882,
0.060683850198984146,
0.02652881294488907,
-0.26247644424438477,
0.054827980697155,
0.005878575146198273,
0.27631425857543945,
-0.3067043721675873,
0.15786680579185486,
0.35337457060813904,
-0.3750433027744293,
0.11998167634010315,
0.02427566424012184,
0.033813994377851486,
-0.19935107231140137,
0.1858348846435547,
0.05883972346782684,
0.343229204416275,
-0.02436065301299095,
-0.013873949646949768,
0.21716883778572083,
0.08212460577487946,
0.3446105122566223,
0.21561802923679352,
-0.03924686834216118,
-0.0030005155131220818,
-0.1363031566143036,
-0.20195722579956055,
-0.14123904705047607,
0.23442456126213074,
0.23353010416030884,
-0.3234664797782898,
0.28888267278671265,
0.006387138739228249,
0.2911266088485718,
0.19484877586364746,
-0.05898584797978401,
-0.11289198696613312,
0.21247822046279907,
-0.13682159781455994,
0.39696359634399414,
0.3778129816055298,
-0.10544446110725403,
0.002824101597070694,
-0.044340867549180984,
-0.1690581887960434,
-0.15089067816734314,
-0.10000819712877274,
0.12246547639369965,
-0.17493733763694763,
-0.2805670201778412,
0.023782603442668915,
-0.22518011927604675,
0.29884639382362366,
0.04263242706656456,
0.24172699451446533,
-0.06156925484538078,
-0.37630218267440796,
0.06695341318845749,
-0.02502242848277092,
-0.34266865253448486,
-0.2041155844926834,
-0.0023026647977530956,
-0.019037291407585144,
-0.16797615587711334,
0.09720903635025024,
0.30007511377334595,
0.1617031842470169,
0.4099462628364563,
-0.11885754019021988,
0.1719551980495453,
-0.10903345793485641,
0.03236810863018036,
-0.2970982789993286,
-0.09300362318754196,
0.27639320492744446,
0.38804447650909424,
-0.24145792424678802,
-0.2290213257074356,
-0.5571017265319824,
0.045669712126255035,
0.16808468103408813,
-0.012525200843811035,
-0.008397631347179413,
-0.15670877695083618,
0.1424696296453476,
-0.2702634930610657,
-0.04810602217912674,
-0.30732473731040955,
0.010949742048978806,
-0.2560478746891022,
-0.18128329515457153,
0.03165686875581741,
-0.07667209953069687,
-0.17649976909160614,
-0.07915295660495758,
0.0010234005749225616,
0.1980469524860382,
-0.16310574114322662,
-0.03464559465646744,
0.12622477114200592,
0.03138294070959091,
0.04735119640827179,
0.23515060544013977,
-0.1826513558626175,
0.054192714393138885,
0.028838926926255226,
0.22627674043178558,
0.4111819863319397,
-0.20428423583507538,
-0.6995334029197693,
-0.007170290220528841,
-0.08847233653068542,
-0.2417573630809784,
-0.13286659121513367,
0.24760931730270386,
0.44656020402908325,
-0.1435137689113617,
0.21046529710292816,
0.5739884376525879,
-0.16754485666751862,
0.1404290497303009,
-0.22272250056266785,
-0.17239852249622345,
-0.06703240424394608,
0.18465368449687958,
0.14324384927749634,
-0.10967373102903366,
0.011932075023651123,
0.637118935585022,
0.23053854703903198,
-0.1181582510471344,
-0.232115238904953,
-0.004396114498376846,
0.2663671672344208,
-0.307822585105896,
-0.10001197457313538,
-0.05420035496354103,
-0.5955290794372559,
0.030195817351341248,
-0.27251386642456055,
0.19959959387779236,
-0.01254892349243164,
-0.19998201727867126,
-0.03226301074028015,
0.002767818048596382,
-0.021475505083799362,
-0.041503820568323135,
0.14903368055820465,
-0.10393498837947845,
0.03776175156235695,
0.01641112193465233,
0.13712643086910248,
0.3391304612159729,
-0.2325786054134369,
0.4468236565589905,
-0.003963744267821312,
0.2574148178100586,
-0.2883979082107544,
-0.3253239393234253,
0.15580134093761444,
0.24388766288757324,
0.03058543987572193,
-0.1248806044459343,
-0.06957944482564926,
0.2165549397468567,
0.10290727764368057,
-0.08505699038505554,
0.06705203652381897,
-0.3381919860839844,
0.3775499761104584,
0.08620890974998474,
-0.05293312668800354,
-0.07910649478435516,
0.07668915390968323,
-0.0767320841550827,
0.018533185124397278,
0.22335022687911987,
-0.31230801343917847,
-0.07031091302633286,
0.10400648415088654,
0.21962209045886993,
0.06820762902498245,
-0.13731427490711212,
-0.1277414709329605,
0.21088209748268127,
0.22927658259868622,
0.244489386677742,
0.015720881521701813,
0.038441531360149384,
-0.3653057813644409,
0.27148914337158203,
0.4710398018360138,
0.009044945240020752,
0.2805316746234894,
-0.027613885700702667,
-0.06783580034971237,
-0.017648398876190186,
0.3719351887702942,
0.023189764469861984,
0.32941877841949463,
0.11665686219930649,
-0.11657072603702545,
0.01113898679614067,
-0.10210777819156647,
-0.29719579219818115,
0.11165915429592133,
0.1278635412454605,
0.3178746700286865,
-0.10101091116666794,
0.3305141031742096,
-0.034372154623270035,
-0.3430921733379364,
-0.20008860528469086,
-0.09329666942358017,
0.2421555519104004,
0.12846019864082336,
0.25913605093955994,
-0.13541017472743988,
-0.6098312735557556,
-0.05507991462945938,
-0.16726814210414886,
-0.090360626578331,
-0.22800885140895844,
-0.023899409919977188,
0.45616281032562256,
0.276153564453125,
0.07358154654502869,
0.2938823103904724,
0.21407930552959442,
0.0367489755153656,
0.08619954437017441,
0.15598152577877045,
-0.11963637173175812,
-0.31850939989089966,
0.0718802958726883,
0.39522674679756165,
0.24352465569972992,
0.08686231076717377,
-0.24151507019996643,
-0.18731874227523804,
-0.09849104285240173,
-0.3265635371208191,
0.2032727152109146,
-0.23567236959934235,
0.30599111318588257,
-0.017747044563293457,
0.2388731837272644,
-0.6264257431030273,
-0.21012380719184875,
0.10280880331993103,
-0.12800614535808563,
-0.11295357346534729,
-0.03887312859296799,
-0.005858607590198517,
-0.3610164523124695,
-0.24185693264007568,
-0.14751112461090088,
-0.5018797516822815,
-0.24258753657341003,
0.2574930191040039,
-0.0037882179021835327,
0.19984561204910278,
0.2799195349216461,
0.07124128937721252,
0.3175303339958191,
0.09950865805149078,
-0.2388117015361786,
0.06216571480035782,
0.02206607535481453,
0.23596256971359253,
-0.24667274951934814,
-0.5061877965927124,
0.06595106422901154,
0.05682873725891113,
0.032461293041706085,
-0.2706143260002136,
-0.4002765417098999,
-0.465181440114975,
0.14091917872428894,
0.23564434051513672,
-0.04908043146133423,
-0.13650193810462952,
0.13784277439117432,
-0.18993277847766876,
0.07168592512607574,
0.01500818133354187,
-0.2303987443447113,
-0.17598643898963928,
0.13017922639846802,
0.2832840383052826,
-0.25433680415153503,
0.04595976695418358,
0.15705351531505585,
0.22293870151042938,
0.11176830530166626,
-0.083133265376091,
0.15639086067676544,
0.0955338254570961,
0.1974157691001892,
-0.18021884560585022,
-0.42029011249542236,
0.33444952964782715,
-0.11916840076446533,
-0.09323754161596298,
0.34363552927970886,
-0.15984144806861877,
-0.604213535785675,
-0.12987607717514038,
0.06717176735401154,
-0.38668757677078247,
-0.46388745307922363,
0.16150718927383423,
0.5007524490356445,
-0.1398274004459381,
0.2503450810909271,
0.18707329034805298,
0.008182933554053307,
-0.34842953085899353,
-0.3713095784187317,
0.2292095273733139,
-0.26665523648262024,
0.04256106913089752,
0.20368073880672455,
-0.42458483576774597,
-0.6710546612739563,
0.18562442064285278,
0.07730090618133545,
0.12946704030036926,
0.03373346105217934,
0.16176483035087585,
0.14359444379806519,
0.01068422943353653,
0.2023099660873413,
0.23272587358951569,
-0.043824389576911926,
0.0860024243593216,
0.05781089514493942,
-0.284172922372818,
0.02707858756184578,
-0.39344486594200134,
0.5534502863883972,
0.82149738073349,
0.21728666126728058,
-0.12233014404773712,
0.161693274974823,
0.512523353099823,
-0.02566528506577015,
0.16802293062210083,
0.13292090594768524,
-0.22827960550785065,
-0.37134337425231934,
-0.14193890988826752,
0.10894770175218582,
-0.05841958522796631,
0.07994873821735382,
0.09687226265668869,
-0.06940171867609024,
0.2451850324869156,
-0.07987070083618164,
-0.05815878510475159,
0.5733697414398193,
-0.04309689998626709,
0.17280890047550201,
0.07421660423278809,
-0.18566349148750305,
-0.13516639173030853,
0.305774986743927,
0.2549997568130493,
-0.048399049788713455,
-0.2348625659942627,
0.2255319058895111,
-0.31759583950042725,
0.16910533607006073,
0.5100562572479248,
-0.028746042400598526,
-0.008707329630851746,
-0.2693237364292145,
0.009692050516605377,
0.3701845109462738,
0.0820201113820076,
0.256671279668808,
0.07617249339818954,
-0.08871469646692276,
0.2006741166114807,
0.2374025583267212,
-0.12386049330234528,
0.02468188852071762,
-0.15152502059936523,
-0.19545288383960724,
-0.20539426803588867,
0.4353124499320984,
0.09283722192049026,
0.7878344655036926,
-0.23235715925693512,
0.16138100624084473,
0.27821919322013855,
0.02919618785381317,
0.6408751010894775,
-0.03151513263583183,
0.33673012256622314,
-0.18474218249320984,
-0.2963073253631592,
0.053685300052165985,
-0.02115555852651596,
0.1532127559185028,
0.014196395874023438,
-0.6053224802017212,
0.23526014387607574,
0.3834209442138672,
0.02982737310230732,
0.08889052271842957,
0.13620389997959137,
-0.11280248314142227,
-0.32899385690689087,
-0.6385902166366577,
0.17903026938438416,
-0.31387943029403687,
0.19821517169475555,
-0.30542829632759094,
0.003389583434909582,
-0.2572369873523712,
0.05614405870437622,
-0.36994582414627075,
0.15100428462028503,
-0.5142830610275269,
-0.048113904893398285,
0.2063174694776535,
-0.30066657066345215,
-0.10240314900875092,
0.300640344619751,
0.17832377552986145,
0.20467081665992737,
0.06039530038833618,
0.06155680865049362,
-0.058590881526470184,
-0.30445829033851624,
0.08371365070343018,
0.03717843443155289,
0.07622479647397995,
-0.2088422179222107,
-0.08287840336561203,
-0.07315363734960556,
0.27861690521240234,
-0.23776978254318237,
0.3863203525543213,
0.2796516418457031,
0.18206268548965454,
0.020238172262907028,
-0.06534850597381592,
-0.037681981921195984,
-0.1724327802658081,
-0.28082188963890076,
0.10838428139686584,
-0.10882590711116791,
-0.06522068381309509,
0.28962716460227966,
0.1406569480895996,
-0.17361317574977875,
-0.0035924874246120453,
0.2703544497489929,
-0.1790098249912262,
0.1063862144947052,
0.20714975893497467,
0.2732166349887848,
-0.11991051584482193,
-0.21892857551574707,
0.19247543811798096,
-0.5636967420578003,
-0.17945496737957,
0.02946116402745247,
-0.07871925085783005,
-0.026361390948295593,
-0.08183688670396805,
0.631582498550415,
0.3025014400482178,
0.02565683051943779,
-0.07841385900974274,
-0.4058826267719269,
-0.18444348871707916,
0.2054409384727478,
0.1786111444234848,
-0.1519635021686554,
0.37673142552375793,
0.3331974148750305,
0.193341925740242,
0.04874858260154724,
-0.23890846967697144,
0.2942793071269989,
-0.40905633568763733,
0.16265268623828888,
-0.057454802095890045,
-0.3167046904563904,
0.1807573288679123,
-0.16345810890197754,
-0.006830867379903793,
0.5193843245506287,
0.12761372327804565,
-0.237626314163208,
-0.08323725312948227,
0.06300914287567139,
0.02087610960006714,
-0.10651836544275284,
-0.3156396448612213,
-0.07924634218215942,
-0.03797822818160057,
-0.030868735164403915,
0.09227944910526276,
-0.11090949177742004,
0.2121518850326538,
-0.045085735619068146,
0.2560538947582245,
0.2237636148929596,
0.18538793921470642,
0.03360719978809357,
-0.02662503719329834,
0.2571994364261627,
0.103535957634449,
0.208764910697937,
0.17264524102210999,
0.038589365780353546,
0.22618544101715088,
-0.04137689620256424,
-0.16636626422405243,
0.07988855242729187,
0.3123323917388916,
-0.36842775344848633,
0.06631982326507568,
-0.12071607261896133,
-0.08334916085004807,
0.3914593756198883,
0.0945458635687828,
-0.22146737575531006,
0.2422187626361847,
0.12057972699403763,
-0.2034115493297577,
0.05944051593542099,
0.5620882511138916,
0.1985337734222412,
0.11759072542190552,
0.5118353962898254,
0.003311287611722946,
-0.0001255124807357788,
0.14947068691253662,
0.1118350401520729,
0.29032543301582336,
0.40054959058761597,
-0.05944668874144554,
-0.1089259535074234,
-0.040777262300252914,
0.1046377420425415,
0.12247244268655777,
0.104865163564682,
0.1897202730178833,
-0.003135383129119873,
-0.08938490599393845,
0.09117859601974487,
-0.21281325817108154,
0.07399358600378036,
0.3456506133079529,
-0.0707034021615982,
-0.2760521471500397,
0.061199285089969635,
0.22912639379501343,
0.0624624565243721,
0.07917775958776474,
0.7251800298690796,
-0.34647998213768005,
-0.2281430959701538,
-0.02409774251282215,
0.16770753264427185,
-0.39005348086357117,
0.1112295538187027,
-0.2578761577606201,
0.10365492850542068,
-0.07326438277959824,
0.06669114530086517,
-0.15407678484916687,
-0.13330844044685364,
0.3501731753349304,
0.2939985692501068,
-0.1731889396905899,
-0.024732721969485283,
-0.10646162182092667,
0.1602122187614441,
-0.10827084630727768,
-0.023033855482935905,
0.3853769898414612,
-0.34098494052886963,
0.19518744945526123,
-0.184858500957489,
0.5654686093330383,
0.17510512471199036,
0.18691007792949677,
-0.2589702606201172,
-0.19222979247570038,
-0.04654514417052269,
-0.009189987555146217,
-0.12912294268608093,
-0.10915717482566833,
0.4811045229434967,
0.1795612871646881,
0.2597264051437378,
0.07102728635072708,
-0.13908211886882782,
0.2577846646308899,
0.19828620553016663,
-0.2809126675128937,
0.14965423941612244,
-0.2773096561431885,
0.04808777570724487,
-0.17036616802215576,
-0.25108009576797485,
-0.10992150753736496,
-0.26709216833114624,
0.41964513063430786,
-0.26302942633628845,
-0.08880849182605743,
0.0830579325556755,
-0.06837192177772522,
0.06529147922992706,
0.036942094564437866,
0.5547948479652405,
0.33888235688209534,
0.017961259931325912,
-0.25608697533607483,
-0.40430766344070435,
-0.3963000774383545,
0.22965607047080994,
-0.2289820909500122,
-0.07774485647678375,
0.08669283241033554,
0.2964426577091217,
-0.050080738961696625,
0.49343276023864746,
0.014594167470932007,
0.044201672077178955,
-0.18333584070205688,
-0.009463541209697723,
-0.5380403995513916,
-0.06271453201770782,
0.21355772018432617,
-0.33248093724250793,
-0.07470738142728806,
-0.2555917799472809,
0.22630353271961212,
-0.3445778489112854,
0.011229854077100754,
-0.022472016513347626,
-0.370181679725647,
-0.24126386642456055,
-0.08208002150058746,
0.17296934127807617,
0.07968718558549881,
0.06808533519506454,
0.01229977235198021,
-0.23334704339504242,
0.03424596041440964,
-0.2586531341075897,
-0.20849581062793732,
0.040847696363925934,
0.20121587812900543,
0.22902452945709229,
0.08602142333984375,
0.36334502696990967,
-0.09533359110355377,
0.5152747631072998,
0.09685724973678589,
0.04516313597559929,
-0.04169933870434761,
-0.024246975779533386,
-0.12852951884269714,
0.13830913603305817,
-0.22996149957180023,
0.44079622626304626,
-0.3113741874694824,
0.2767087519168854,
-0.4855022430419922,
-0.3400691747665405,
0.36335206031799316,
-0.5322354435920715,
-0.1876487284898758,
0.04002277925610542,
0.22818812727928162,
0.08981306105852127,
-0.17658741772174835,
-0.29772669076919556,
-0.02463051676750183,
-0.11291200667619705,
-0.23598924279212952,
-0.41634872555732727,
0.23685230314731598,
-0.1849517822265625,
0.04134880378842354,
-0.09677921235561371,
0.28482678532600403,
0.03882337361574173,
-0.244221493601799,
-0.21315842866897583,
-0.21907676756381989
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | I like this feature! I think the first question we should decide on is how to convert all datasets into the same format. In T5, the authors decided to format every dataset into a text-to-text format. If the dataset had "multiple" inputs like MNLI, the inputs were concatenated. So in MNLI the input:
> - **Hypothesis**: The St. Louis Cardinals have always won.
>
> - **Premise**: yeah well losing is i mean i’m i’m originally from Saint Louis and Saint Louis Cardinals when they were there were uh a mostly a losing team but
was flattened to a single input:
> mnli hypothesis: The St. Louis Cardinals have always won. premise:
> yeah well losing is i mean i’m i’m originally from Saint Louis and Saint Louis Cardinals
> when they were there were uh a mostly a losing team but.
This flattening is actually a very simple operation in `nlp` already. You would just need to do the following:
```python
def flatten_inputs(example):
return {"input": "mnli hypothesis: " + example['hypothesis'] + " premise: " + example['premise']}
t5_ready_mnli_ds = mnli_ds.map(flatten_inputs, remove_columns=[<all columns except output>])
```
So I guess converting the datasets into the same format can be left to the user for now.
Then the question is how we can merge the datasets. I would probably be in favor of a simple
```python
dataset.add()
```
function that checks if the dataset is of the same format and if yes merges the two datasets. Finally, how should the sampling be implemented? **Examples-proportional mixing** corresponds to just merging the datasets and shuffling. For the other two sampling approaches we would need some higher-level features, maybe even a `dataset.sample()` function for merged datasets.
What are your thoughts on this @thomwolf @lhoestq @ghomasHudson @enzoampil ? | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 291 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
I like this feature! I think the first question we should decide on is how to convert all datasets into the same format. In T5, the authors decided to format every dataset into a text-to-text format. If the dataset had "multiple" inputs like MNLI, the inputs were concatenated. So in MNLI the input:
> - **Hypothesis**: The St. Louis Cardinals have always won.
>
> - **Premise**: yeah well losing is i mean i’m i’m originally from Saint Louis and Saint Louis Cardinals when they were there were uh a mostly a losing team but
was flattened to a single input:
> mnli hypothesis: The St. Louis Cardinals have always won. premise:
> yeah well losing is i mean i’m i’m originally from Saint Louis and Saint Louis Cardinals
> when they were there were uh a mostly a losing team but.
This flattening is actually a very simple operation in `nlp` already. You would just need to do the following:
```python
def flatten_inputs(example):
return {"input": "mnli hypothesis: " + example['hypothesis'] + " premise: " + example['premise']}
t5_ready_mnli_ds = mnli_ds.map(flatten_inputs, remove_columns=[<all columns except output>])
```
So I guess converting the datasets into the same format can be left to the user for now.
Then the question is how we can merge the datasets. I would probably be in favor of a simple
```python
dataset.add()
```
function that checks if the dataset is of the same format and if yes merges the two datasets. Finally, how should the sampling be implemented? **Examples-proportional mixing** corresponds to just merging the datasets and shuffling. For the other two sampling approaches we would need some higher-level features, maybe even a `dataset.sample()` function for merged datasets.
What are your thoughts on this @thomwolf @lhoestq @ghomasHudson @enzoampil ? | [
-0.06062939018011093,
-0.43357160687446594,
-0.05662921816110611,
-0.015485309064388275,
-0.16559098660945892,
0.04524776339530945,
0.18558672070503235,
0.18404962122440338,
0.20415988564491272,
-0.14907832443714142,
-0.24861812591552734,
0.2844125032424927,
-0.1800074279308319,
0.47155213356018066,
0.3802827000617981,
-0.4318718910217285,
0.07262524217367172,
-0.14835751056671143,
-0.3279542624950409,
0.3465222120285034,
0.043432027101516724,
0.12348020076751709,
-0.18072369694709778,
0.029902007430791855,
-0.35131070017814636,
-0.16163277626037598,
-0.3850715458393097,
0.07486452162265778,
0.014117991551756859,
0.031469352543354034,
0.06988038122653961,
0.3947067856788635,
-0.04164344444870949,
0.18248435854911804,
-0.00011498481762828305,
-0.10626955330371857,
0.11025393009185791,
-0.1087462455034256,
0.09373389184474945,
-0.03407789766788483,
0.13381794095039368,
-0.3790649175643921,
0.058088354766368866,
-0.16541621088981628,
0.20267626643180847,
0.14574658870697021,
0.1934349536895752,
0.05130394548177719,
0.3670564889907837,
-0.2185332477092743,
0.08402933180332184,
0.26443198323249817,
-0.13484972715377808,
0.3218310475349426,
-0.0651739165186882,
0.02047070860862732,
0.044885843992233276,
0.23994137346744537,
0.6195873022079468,
-0.47857508063316345,
-0.027776941657066345,
0.22522087395191193,
-0.011841628700494766,
-0.012316416949033737,
0.12501248717308044,
-0.06387162208557129,
-0.2911246716976166,
-0.2389596402645111,
-0.3664330244064331,
0.24455338716506958,
-0.04346802085638046,
-0.21901509165763855,
-0.22686205804347992,
-0.5487809777259827,
-0.025223106145858765,
-0.01662977784872055,
-0.326879620552063,
0.06366682797670364,
-0.16956283152103424,
-0.05313921347260475,
-0.1652791053056717,
-0.0777100995182991,
-0.06440579891204834,
0.1307315230369568,
0.29616230726242065,
0.5442551374435425,
0.0387100987136364,
0.053566258400678635,
0.2903417646884918,
0.036765966564416885,
-0.11274214088916779,
-0.2751785218715668,
0.3076981008052826,
0.07872704416513443,
-0.32095393538475037,
-0.34821999073028564,
0.0695447325706482,
-0.31259289383888245,
0.32180315256118774,
0.08210974186658859,
0.13770149648189545,
0.06355192512273788,
-0.13061709702014923,
0.21757471561431885,
0.38325244188308716,
0.008566847071051598,
-0.0750824585556984,
-0.16860586404800415,
0.007640670984983444,
-0.14267084002494812,
0.1661435067653656,
0.1513281613588333,
0.11848486959934235,
-0.004000247921794653,
-0.4497514069080353,
-0.06211620569229126,
-0.0710141658782959,
0.05218597874045372,
-0.12578356266021729,
-0.5080181360244751,
-0.11419260501861572,
-0.09674488008022308,
-0.11398350447416306,
-0.17604142427444458,
-0.26717716455459595,
0.17692387104034424,
0.003627914935350418,
0.27180927991867065,
-0.1638910472393036,
0.03908424824476242,
-0.03798029571771622,
0.01682923547923565,
-0.4351593852043152,
-0.08235833048820496,
0.2814764380455017,
0.08760927617549896,
0.05325385928153992,
0.16166581213474274,
-0.04158489406108856,
0.06549911201000214,
0.332254022359848,
0.028684310615062714,
0.13818120956420898,
-0.04580060765147209,
0.17860060930252075,
-0.26701080799102783,
-0.010549895465373993,
0.15709362924098969,
-0.3184623420238495,
-0.12240960448980331,
-0.15247127413749695,
-0.20893260836601257,
0.05303369462490082,
0.010931023396551609,
-0.17490319907665253,
-0.28919920325279236,
-0.4556143581867218,
0.7248806357383728,
0.015414074063301086,
-0.08319571614265442,
-0.19418630003929138,
0.13860708475112915,
-0.1514989137649536,
-0.09328716993331909,
0.22360345721244812,
0.11550799012184143,
-0.07817286252975464,
-0.27755212783813477,
0.019101375713944435,
-0.08028481900691986,
0.012738101184368134,
0.304551899433136,
-0.06466139107942581,
0.2548964023590088,
0.06150007247924805,
0.2096283882856369,
0.30092281103134155,
-0.39963531494140625,
-0.0024379361420869827,
0.34459465742111206,
-0.05548939108848572,
0.3846750855445862,
0.10268242657184601,
0.12903325259685516,
0.00221403781324625,
-0.19203858077526093,
0.2654207944869995,
0.9147472977638245,
-0.38112103939056396,
0.06711127609014511,
-0.19821713864803314,
-0.3537558317184448,
0.5127946138381958,
0.2841840982437134,
0.011132195591926575,
-0.3445623815059662,
-0.13308793306350708,
-0.0049951025284826756,
0.07843337953090668,
0.0030071884393692017,
0.03737063705921173,
-0.02651938796043396,
-0.3109757602214813,
0.07546744495630264,
-0.19495409727096558,
-0.115241140127182,
-0.4247463643550873,
-0.1003587543964386,
0.04577895998954773,
0.3210233747959137,
0.26057329773902893,
-0.15339195728302002,
0.22681349515914917,
-0.3086334466934204,
-0.15567214787006378,
-0.2565402388572693,
0.13309957087039948,
-0.026752278208732605,
-0.014473576098680496,
-0.20608532428741455,
-0.09645234048366547,
0.32367751002311707,
0.0577915757894516,
-0.07589920610189438,
-0.4959026575088501,
0.24824412167072296,
-0.077762171626091,
0.020057471469044685,
0.07954811304807663,
0.6802391409873962,
-0.18799707293510437,
-0.07588966190814972,
0.1854725182056427,
0.2653414309024811,
-0.3162192702293396,
0.25385794043540955,
0.22005969285964966,
0.33087337017059326,
0.2140362411737442,
-0.0697961375117302,
0.10537343472242355,
-0.0637868195772171,
-0.04165664687752724,
-0.22341936826705933,
-0.19158995151519775,
0.43757516145706177,
-0.17595253884792328,
0.463652104139328,
-0.03217608481645584,
0.02915244735777378,
-0.22143886983394623,
-0.01690283790230751,
-0.23426449298858643,
0.38474154472351074,
0.31314295530319214,
-0.20771293342113495,
0.33080944418907166,
-0.046972163021564484,
-0.44120243191719055,
0.2577657401561737,
0.24474388360977173,
0.06818315386772156,
0.09573803842067719,
-0.009551957249641418,
-0.045534223318099976,
-0.3349413573741913,
-0.060299456119537354,
0.34204697608947754,
0.5666442513465881,
0.26995715498924255,
0.19837501645088196,
0.06839533895254135,
-0.2664468288421631,
-0.11241086572408676,
0.0692981630563736,
0.16281472146511078,
0.012806608341634274,
0.2764888405799866,
0.03590695559978485,
0.07019908726215363,
-0.01635851338505745,
-0.09048351645469666,
0.13983921706676483,
-0.18486753106117249,
-0.15955151617527008,
0.013510974124073982,
-0.23286262154579163,
-0.661297082901001,
-0.2655385434627533,
0.05956576392054558,
-0.3062054514884949,
-0.319520503282547,
0.12936243414878845,
0.017231788486242294,
-0.14742322266101837,
0.17125503718852997,
0.23219692707061768,
0.607446551322937,
-0.39070576429367065,
-0.1505921334028244,
-0.06880813837051392,
-0.3318815529346466,
-0.1426524519920349,
0.07787388563156128,
0.549889862537384,
0.3654056191444397,
0.43545612692832947,
0.17507439851760864,
0.0016453061252832413,
0.04031530022621155,
-0.4197556972503662,
0.09459864348173141,
-0.3344561457633972,
0.16005419194698334,
0.06284233927726746,
-0.1625741869211197,
0.14567077159881592,
-0.42311927676200867,
-0.08997100591659546,
0.024390386417508125,
-0.09786457568407059,
0.017521221190690994,
-0.0396757647395134,
0.027871476486325264,
-0.22343939542770386,
-0.3024548888206482,
-0.5716314911842346,
-0.4520237147808075,
0.3431037664413452,
-0.27985459566116333,
0.14475837349891663,
0.0694185420870781,
-0.22567537426948547,
0.14136293530464172,
-0.17480261623859406,
0.07033857703208923,
-0.11356350034475327,
-0.10608261823654175,
0.042191363871097565,
-0.34368401765823364,
-0.2414880245923996,
-0.38526827096939087,
-0.026993216946721077,
0.1701684594154358,
-0.0015302281826734543,
-0.06010874733328819,
-0.2366362065076828,
0.07347780466079712,
-0.21928173303604126,
0.11132682859897614,
0.29573196172714233,
0.1376895308494568,
-0.16666603088378906,
0.13377836346626282,
-0.04997451975941658,
-0.18687541782855988,
0.20780950784683228,
0.32819244265556335,
0.3863658905029297,
0.15270429849624634,
0.0017188973724842072,
0.2775653302669525,
0.6705092191696167,
0.3482150733470917,
0.04389109089970589,
0.09031020104885101,
0.25889748334884644,
0.06046076864004135,
0.1286640763282776,
-0.18067094683647156,
0.26686447858810425,
-0.20002683997154236,
0.5133737325668335,
0.1512202024459839,
0.1806647777557373,
-0.10541103035211563,
-0.2131507396697998,
0.12126965820789337,
-0.3510887920856476,
-0.1996564269065857,
0.3020295798778534,
-0.31928250193595886,
0.021582331508398056,
-0.05449039489030838,
-0.3992007374763489,
-0.2533678114414215,
-0.04955428093671799,
0.017427291721105576,
0.3520650267601013,
-0.05508100241422653,
0.19885984063148499,
-0.4190732538700104,
-0.09170428663492203,
-0.46005338430404663,
0.19697128236293793,
0.08974097669124603,
0.3336322605609894,
-0.06856122612953186,
-0.11177203059196472,
-0.08517734706401825,
0.1311119943857193,
0.5710868835449219,
-0.5576232671737671,
-0.2217063158750534,
0.17702358961105347,
0.1506168097257614,
-0.08356249332427979,
-0.12241517007350922,
-0.38056671619415283,
-0.026714732870459557,
0.46636343002319336,
0.42542821168899536,
-0.4082850515842438,
-0.35964280366897583,
0.2669551968574524,
-0.16865240037441254,
-0.020689569413661957,
-0.13011807203292847,
-0.20354948937892914,
-0.21533101797103882,
-0.17324474453926086,
0.026581868529319763,
0.22452165186405182,
0.16896408796310425,
-0.1544281542301178,
0.15072380006313324,
-0.046022042632102966,
0.23721414804458618,
0.21118459105491638,
-0.012833455577492714,
-0.05038946494460106,
0.26388460397720337,
0.0650329738855362,
0.07246600836515427,
-0.03061072528362274,
-0.2702557444572449,
0.10697230696678162,
-0.13292673230171204,
0.06653112173080444,
0.2735390067100525,
-0.07887067645788193,
0.7340445518493652,
0.15070095658302307,
0.3863653838634491,
0.17446628212928772,
-0.1042366474866867,
0.020268280059099197,
-0.2474546730518341,
0.21436722576618195,
0.20877262949943542,
0.24122527241706848,
-0.1877690851688385,
-0.19011326134204865,
0.5577906370162964,
0.33030593395233154,
-0.015693001449108124,
0.41446152329444885,
-0.4715427756309509,
-0.2955447733402252,
0.3173159956932068,
0.037461526691913605,
0.7747876644134521,
-0.0559433251619339,
0.3117319345474243,
0.08896906673908234,
-0.4208648204803467,
0.5706254839897156,
-0.43463313579559326,
0.15796628594398499,
-0.09969194233417511,
-0.18400435149669647,
0.030260616913437843,
-0.10041100531816483,
-0.026499107480049133,
0.2533981204032898,
-0.38214847445487976,
0.3142700791358948,
0.4203941226005554,
-0.25699344277381897,
-0.03189202398061752,
0.5367090106010437,
-0.05316828936338425,
-0.3928298056125641,
-0.05631323903799057,
0.04181140661239624,
-0.32738596200942993,
0.08863338828086853,
-0.12786144018173218,
-0.3133983016014099,
0.23929113149642944,
0.1586398184299469,
-0.3130236864089966,
0.10464895516633987,
-0.06307268142700195,
0.14268921315670013,
0.22421951591968536,
-0.035015303641557693,
0.24764713644981384,
-0.13931328058242798,
0.0429934561252594,
-0.1307624876499176,
-0.06671702861785889,
0.03300987556576729,
-0.10206114500761032,
0.07684885710477829,
0.09859734773635864,
-0.16361364722251892,
0.5141545534133911,
-0.0033410824835300446,
0.008826300501823425,
-0.29763033986091614,
0.2612650990486145,
-0.3895629644393921,
-0.276950865983963,
-0.024676434695720673,
0.18370632827281952,
0.09997154027223587,
-0.29114770889282227,
0.6143852472305298,
0.0873115211725235,
0.0357685349881649,
0.04025207459926605,
0.1385815590620041,
-0.23400579392910004,
0.5710294842720032,
-0.24325956404209137,
-0.01429014652967453,
0.08371679484844208,
-0.013701401650905609,
-0.11303932219743729,
-0.4529513716697693,
-0.0207376591861248,
0.38573089241981506,
0.07245340943336487,
-0.022204995155334473,
0.06766734272241592,
0.1305583119392395,
-0.06083385646343231,
-0.017283156514167786,
-0.2517119348049164,
-0.29927992820739746,
0.10248804837465286,
0.24880841374397278,
0.24665340781211853,
0.15516209602355957,
-0.041943833231925964,
-0.24314746260643005,
-0.13975267112255096,
0.5461680889129639,
-0.03090217337012291,
0.26203492283821106,
-0.051449257880449295,
0.3808257579803467,
0.3815823495388031,
0.5050756931304932,
-0.2507596015930176,
0.07350698858499527,
0.06648766249418259,
0.1924353688955307,
0.44197627902030945,
-0.26780688762664795,
-0.032334066927433014,
0.24625711143016815,
-0.1350875347852707,
0.10860054194927216,
-0.32450005412101746,
-0.15105046331882477,
-0.20546089112758636,
0.10554122179746628,
0.19726675748825073,
0.02915121428668499,
0.047509338706731796,
-0.033540308475494385,
-0.13116846978664398,
-0.10678388178348541,
0.021674226969480515,
-0.37187138199806213,
-0.12796550989151,
0.23094749450683594,
-0.1180993914604187,
0.0367705412209034,
0.07956629991531372,
0.13500702381134033,
0.004463784396648407,
-0.09252685308456421,
0.31753668189048767,
0.09242818504571915,
0.06634555011987686,
-0.1891518533229828,
-0.18550202250480652,
0.04238702729344368,
0.23217496275901794,
0.1891823709011078,
0.0023199990391731262,
0.08651171624660492,
-0.17059358954429626,
-0.1667363941669464,
0.21267817914485931,
0.2336457073688507,
0.01032559759914875,
-0.09136780351400375,
0.1436552107334137,
0.09549880772829056,
-0.0544309988617897,
-0.005216378252953291,
0.22590729594230652,
0.05995369330048561,
-0.007213480770587921,
0.06645393371582031,
0.19826093316078186,
0.39348655939102173,
-0.18172939121723175,
0.045478835701942444,
0.035260286182165146,
-0.39731937646865845,
0.1519799381494522,
-0.040100280195474625,
0.00020148977637290955,
0.00528678297996521,
0.06006809324026108,
0.0377880223095417,
0.12491361796855927,
-0.32155483961105347,
0.32893696427345276,
0.262973815202713,
0.025910526514053345,
0.035576287657022476,
0.17994658648967743,
-0.028497472405433655,
-0.15546952188014984,
0.27964523434638977,
0.07556164264678955,
0.43249401450157166,
0.0586092472076416,
0.8388553857803345,
-0.2928153872489929,
-0.513799250125885,
0.11348996311426163,
0.424418568611145,
-0.002087157219648361,
-0.19419698417186737,
0.054136864840984344,
0.11889065057039261,
-0.3490162789821625,
0.07172706723213196,
-0.06716296076774597,
-0.1238756775856018,
0.5954532027244568,
-0.0036203712224960327,
0.1662234663963318,
-0.22186864912509918,
-0.17409703135490417,
0.28185030817985535,
0.2393641471862793,
-0.11452360451221466,
0.11490707099437714,
0.08922533690929413,
-0.12978611886501312,
-0.15155154466629028,
0.5569117069244385,
0.25876203179359436,
0.05257067829370499,
-0.4229050278663635,
0.014233014546334743,
0.09556449949741364,
0.10881701111793518,
0.07581400871276855,
0.08942347019910812,
0.45313453674316406,
-0.1393473595380783,
0.27781942486763,
-0.011475536040961742,
-0.011696679517626762,
-0.154131218791008,
0.033524323254823685,
-0.4807209372520447,
-0.3438222110271454,
0.39191505312919617,
0.1465260088443756,
-0.16903084516525269,
0.10381101816892624,
0.26207026839256287,
-0.7270404696464539,
-0.2905240058898926,
0.41981521248817444,
-0.028902582824230194,
-0.03651423752307892,
-0.20693422853946686,
0.06619679182767868,
0.18844348192214966,
0.5728141665458679,
0.27638599276542664,
0.32753732800483704,
-0.38855424523353577,
-0.11769816279411316,
-0.5355229377746582,
-0.17271271347999573,
0.1998899132013321,
-0.04911524057388306,
-0.186818465590477,
0.14797520637512207,
-0.02143321931362152,
0.3246809244155884,
-0.26161473989486694,
0.10892422497272491,
0.16829948127269745,
0.07349081337451935,
-0.5057327151298523,
0.11960236728191376,
0.20687857270240784,
0.04922626540064812,
0.19890852272510529,
-0.057058461010456085,
-0.08498969674110413,
0.13170494139194489,
-0.07632112503051758,
-0.0857621505856514,
0.005865886807441711,
0.2451675534248352,
0.16403938829898834,
-0.026462681591510773,
0.08232583105564117,
0.4630805552005768,
-0.01387227512896061,
-0.19936423003673553,
-0.019803274422883987,
0.04457425698637962,
-0.4071342647075653,
-0.07029031962156296,
-0.09318269789218903,
0.1952255666255951,
-0.39534685015678406,
0.29372358322143555,
0.008449711836874485,
-0.11666037887334824,
0.0764622613787651,
0.02875891514122486,
-0.15167874097824097,
-0.049831509590148926,
0.08785512298345566,
0.1956939697265625,
0.29837992787361145,
0.740128219127655,
-0.0052440352737903595,
0.12361189723014832,
-0.17261390388011932,
-0.06902056932449341,
0.027409732341766357,
-0.053223028779029846,
-0.23431609570980072,
-0.10208185017108917,
0.06130241975188255,
0.16821064054965973,
0.21723411977291107,
-0.6970353126525879,
-0.3775850236415863,
0.03720245510339737,
-0.0556478425860405,
0.013423949480056763,
0.7778046131134033,
0.13142307102680206,
-0.16813664138317108,
-0.16086889803409576,
-0.3078276515007019,
0.011136813089251518,
-0.297132670879364,
0.04810846969485283,
-0.45130521059036255
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | I agree that we should leave the flattening of the dataset to the user for now. Especially because although the T5 framing seems obvious, there are slight variations on how the T5 authors do it in comparison to other approaches such as gpt-3 and decaNLP.
In terms of sampling, Examples-proportional mixing does seem the simplest to implement so would probably be a good starting point.
Temperature-scaled mixing would probably most useful, offering flexibility as it can simulate the other 2 methods by setting the temperature parameter. There is a [relevant part of the T5 repo](https://github.com/google-research/text-to-text-transfer-transformer/blob/03c94165a7d52e4f7230e5944a0541d8c5710788/t5/data/utils.py#L889-L1118) which should help with implementation.
According to the T5 authors, equal-mixing performs worst. Among the other two methods, tuning the K value (the artificial dataset size limit) has a large impact.
| It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 126 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
I agree that we should leave the flattening of the dataset to the user for now. Especially because although the T5 framing seems obvious, there are slight variations on how the T5 authors do it in comparison to other approaches such as gpt-3 and decaNLP.
In terms of sampling, Examples-proportional mixing does seem the simplest to implement so would probably be a good starting point.
Temperature-scaled mixing would probably most useful, offering flexibility as it can simulate the other 2 methods by setting the temperature parameter. There is a [relevant part of the T5 repo](https://github.com/google-research/text-to-text-transfer-transformer/blob/03c94165a7d52e4f7230e5944a0541d8c5710788/t5/data/utils.py#L889-L1118) which should help with implementation.
According to the T5 authors, equal-mixing performs worst. Among the other two methods, tuning the K value (the artificial dataset size limit) has a large impact.
| [
-0.07244556397199631,
-0.467218816280365,
-0.040159933269023895,
-0.055031321942806244,
-0.304560124874115,
0.0747440978884697,
0.1744338721036911,
0.06729500740766525,
0.2653241455554962,
-0.1193469762802124,
-0.2597564160823822,
0.3054881989955902,
-0.16949790716171265,
0.3780532777309418,
0.35094723105430603,
-0.4499828517436981,
-0.021549955010414124,
-0.14634406566619873,
-0.2921192944049835,
0.324207067489624,
0.05431655794382095,
0.11644261330366135,
-0.15435390174388885,
0.06620006263256073,
-0.2752176523208618,
-0.17669454216957092,
-0.34399914741516113,
0.12340910732746124,
0.08483219146728516,
0.07976438105106354,
0.13584452867507935,
0.39544519782066345,
-0.018593134358525276,
0.12798629701137543,
-0.000111412737169303,
-0.09476036578416824,
0.09925207495689392,
-0.09712206572294235,
0.1526375710964203,
0.03999316692352295,
0.1779927909374237,
-0.3429226577281952,
0.0634026750922203,
-0.14008671045303345,
0.13159680366516113,
0.24719160795211792,
0.19724278151988983,
0.08876565098762512,
0.4500899910926819,
-0.3533526659011841,
0.10489170253276825,
0.3131389617919922,
-0.2438289225101471,
0.30103304982185364,
-0.08568572252988815,
-0.1528027057647705,
0.011506261304020882,
0.28885069489479065,
0.6218158006668091,
-0.5280038714408875,
-0.015143148601055145,
0.10488273203372955,
-0.04628778249025345,
0.04999203234910965,
0.13104325532913208,
-0.0666382759809494,
-0.28239738941192627,
-0.25352394580841064,
-0.3627510964870453,
0.2775130569934845,
-0.12239693850278854,
-0.06288975477218628,
-0.192586749792099,
-0.5656943321228027,
-0.003744387999176979,
0.05627430975437164,
-0.3290136158466339,
0.08781717717647552,
-0.2160564512014389,
0.015035653486847878,
-0.12497919052839279,
-0.1268686205148697,
-0.007691536098718643,
0.11148081719875336,
0.30812910199165344,
0.5256880521774292,
0.07436874508857727,
0.13465401530265808,
0.35248714685440063,
0.10151573270559311,
-0.14089272916316986,
-0.26514488458633423,
0.29077792167663574,
0.13547110557556152,
-0.3288780450820923,
-0.37709754705429077,
0.15168583393096924,
-0.2695583701133728,
0.28027063608169556,
0.09671274572610855,
0.14681369066238403,
0.05229128897190094,
-0.08265077322721481,
0.26438283920288086,
0.38912948966026306,
0.012631913647055626,
-0.09676509350538254,
-0.11974359303712845,
0.02395952120423317,
-0.10591056942939758,
0.19155767560005188,
0.13948854804039001,
0.14466069638729095,
0.009004228748381138,
-0.4349183440208435,
-0.11233647912740707,
-0.19096265733242035,
0.09654764831066132,
-0.18051843345165253,
-0.5517171621322632,
-0.08570057153701782,
-0.10183704644441605,
-0.020415570586919785,
-0.12436326593160629,
-0.2886071503162384,
0.1530826836824417,
-0.07474653422832489,
0.15041980147361755,
-0.18044017255306244,
0.02078830450773239,
-0.07014726847410202,
0.06636682152748108,
-0.462980717420578,
-0.03496813774108887,
0.2592128813266754,
0.10559295117855072,
0.07144852727651596,
0.1174030676484108,
-0.020503327250480652,
0.16793939471244812,
0.42610931396484375,
0.030805256217718124,
0.028726674616336823,
-0.03104657307267189,
0.14761847257614136,
-0.3091065287590027,
-0.031393419951200485,
0.23605014383792877,
-0.3518315851688385,
-0.09727918356657028,
-0.14454936981201172,
-0.17756307125091553,
0.13741560280323029,
0.04549838975071907,
-0.2158234715461731,
-0.26927056908607483,
-0.441557377576828,
0.7260332107543945,
-0.013283692300319672,
-0.02393115684390068,
-0.17176997661590576,
0.259479820728302,
-0.20922605693340302,
-0.11802931129932404,
0.18940530717372894,
0.09559951722621918,
-0.021369582042098045,
-0.31907832622528076,
-0.10603727400302887,
-0.06091995909810066,
-0.015615783631801605,
0.3213063180446625,
-0.151783749461174,
0.1992667317390442,
0.1068788468837738,
0.17462219297885895,
0.2618972957134247,
-0.4294564425945282,
-0.05689644813537598,
0.3527347445487976,
-0.061471495777368546,
0.38411834836006165,
0.05087510496377945,
0.17250452935695648,
-0.009615043178200722,
-0.21683649718761444,
0.24459490180015564,
0.983712911605835,
-0.404123991727829,
0.0024759043008089066,
-0.185939759016037,
-0.4244101345539093,
0.5637450218200684,
0.3482625186443329,
0.0648256316781044,
-0.29352274537086487,
-0.18867358565330505,
0.03436806797981262,
0.046717651188373566,
0.0923098772764206,
0.07490967959165573,
-0.08023171126842499,
-0.2644890546798706,
0.010359544306993484,
-0.22413411736488342,
-0.1698399782180786,
-0.42165297269821167,
-0.00873611494898796,
-0.036963459104299545,
0.3787110149860382,
0.37277835607528687,
-0.14035218954086304,
0.237596333026886,
-0.30643683671951294,
-0.11149434745311737,
-0.31171655654907227,
0.14455872774124146,
-0.06806737184524536,
0.012566164135932922,
-0.23941916227340698,
-0.06527689844369888,
0.2053755819797516,
0.09740221500396729,
-0.10502316802740097,
-0.4230077266693115,
0.29147908091545105,
-0.04073402285575867,
0.021507807075977325,
-0.013076692819595337,
0.614617109298706,
-0.2161233127117157,
-0.116585873067379,
0.20798203349113464,
0.291594535112381,
-0.31383368372917175,
0.2109994739294052,
0.30932095646858215,
0.3545565605163574,
0.1958429217338562,
-0.06140464171767235,
0.09926991164684296,
-0.012211006134748459,
-0.08991379290819168,
-0.17108172178268433,
-0.08095481246709824,
0.4797084927558899,
-0.20128488540649414,
0.3575448989868164,
-0.02191038988530636,
0.03489571064710617,
-0.20772439241409302,
-0.05692202225327492,
-0.1906934380531311,
0.3881007730960846,
0.3106745183467865,
-0.22799547016620636,
0.3347799479961395,
-0.0767851322889328,
-0.4003092050552368,
0.2434409260749817,
0.21397249400615692,
0.013479337096214294,
0.09026619046926498,
-0.023068010807037354,
0.0312410369515419,
-0.3101979196071625,
-0.06050332635641098,
0.3375436067581177,
0.5514167547225952,
0.2894958555698395,
0.17737038433551788,
0.016729244962334633,
-0.21758225560188293,
-0.07269231975078583,
0.04261384159326553,
0.1653767228126526,
-0.06318723410367966,
0.14198440313339233,
-0.041099268943071365,
0.09890101104974747,
0.02665790170431137,
-0.10134835541248322,
0.12281974405050278,
-0.14453928172588348,
-0.04268159717321396,
-0.037505075335502625,
-0.15475626289844513,
-0.5833339095115662,
-0.19117631018161774,
0.052576228976249695,
-0.35153090953826904,
-0.2960585355758667,
0.2087559700012207,
0.05685410648584366,
-0.17757241427898407,
0.16798126697540283,
0.19975121319293976,
0.6398568749427795,
-0.39235299825668335,
-0.1751716583967209,
-0.05248171091079712,
-0.29990026354789734,
-0.11523335427045822,
0.1373639702796936,
0.43582555651664734,
0.30238285660743713,
0.49836045503616333,
0.23070229589939117,
-0.03288009762763977,
0.12016383558511734,
-0.3862852454185486,
0.11135131120681763,
-0.3567821979522705,
0.2921696603298187,
0.09976066648960114,
-0.10114516317844391,
0.0970672070980072,
-0.3661125898361206,
-0.07395435869693756,
-0.09430330991744995,
-0.06166940927505493,
-0.04039396345615387,
0.008098820224404335,
0.026680387556552887,
-0.2271045446395874,
-0.2285715937614441,
-0.5969739556312561,
-0.49180614948272705,
0.2876458168029785,
-0.2523242235183716,
0.09606648981571198,
0.043231528252363205,
-0.2876448929309845,
0.20857645571231842,
-0.1413346379995346,
0.03815591707825661,
-0.18621958792209625,
-0.07839317619800568,
-0.02086154744029045,
-0.3604215979576111,
-0.17928363382816315,
-0.422829806804657,
-0.012583755888044834,
0.1930728256702423,
-0.07771419733762741,
-0.06733407080173492,
-0.2891920506954193,
0.032975926995277405,
-0.10656090080738068,
0.08936822414398193,
0.23315834999084473,
0.14413048326969147,
-0.20324985682964325,
0.07360047847032547,
-0.02718188613653183,
-0.1418774425983429,
0.2734167277812958,
0.39811575412750244,
0.36558014154434204,
0.14558780193328857,
-0.02538781240582466,
0.21974122524261475,
0.7495047450065613,
0.28150755167007446,
0.08701758086681366,
0.10910997539758682,
0.29363590478897095,
-0.03916487470269203,
0.09498448669910431,
-0.17914023995399475,
0.25715699791908264,
-0.11236843466758728,
0.4973568916320801,
0.1744980365037918,
0.15857043862342834,
-0.20294521749019623,
-0.27151721715927124,
0.019823230803012848,
-0.2972184121608734,
-0.21401159465312958,
0.2666808068752289,
-0.2744174003601074,
-0.002879694104194641,
-0.10535693168640137,
-0.4169650077819824,
-0.23437228798866272,
-0.08540157228708267,
-0.02018485963344574,
0.28638947010040283,
0.04233963042497635,
0.17477644979953766,
-0.37227681279182434,
-0.024910947307944298,
-0.4501193165779114,
0.13502947986125946,
0.053518146276474,
0.3062891662120819,
-0.12003666162490845,
-0.10522732138633728,
-0.099813312292099,
0.15174566209316254,
0.5571808218955994,
-0.5467590689659119,
-0.15157878398895264,
0.08499222993850708,
0.08082776516675949,
-0.13787327706813812,
-0.07683352380990982,
-0.34837594628334045,
-0.013061403296887875,
0.4500737488269806,
0.3170126676559448,
-0.43303248286247253,
-0.36202460527420044,
0.22607110440731049,
-0.1992088109254837,
-0.07860724627971649,
-0.15291933715343475,
-0.20009441673755646,
-0.18559390306472778,
-0.12708865106105804,
0.014105066657066345,
0.26386529207229614,
0.2031843066215515,
-0.09490790218114853,
0.18410980701446533,
-0.02212667278945446,
0.26804283261299133,
0.22520719468593597,
0.0337846465408802,
-0.08329089730978012,
0.2344714105129242,
0.14794911444187164,
0.07315370440483093,
-0.027881748974323273,
-0.3805592954158783,
0.07879495620727539,
-0.08251582086086273,
0.11951687932014465,
0.30150672793388367,
0.006075269542634487,
0.6325334310531616,
0.08441071212291718,
0.3359811007976532,
0.2805604040622711,
-0.10613861680030823,
0.08464629203081131,
-0.2193402200937271,
0.13918522000312805,
0.15871590375900269,
0.25185441970825195,
-0.09183425456285477,
-0.23387929797172546,
0.5279425978660583,
0.28383785486221313,
-0.050370652228593826,
0.42784854769706726,
-0.48821645975112915,
-0.2839679718017578,
0.2870752811431885,
0.09380435943603516,
0.7551211714744568,
-0.021680839359760284,
0.3053111433982849,
0.11571769416332245,
-0.3540657162666321,
0.6180205345153809,
-0.3570942282676697,
0.10530238598585129,
-0.07974395155906677,
-0.19833479821681976,
0.03314223885536194,
-0.05398918315768242,
-0.12255165725946426,
0.26841914653778076,
-0.34920966625213623,
0.335441529750824,
0.4309313893318176,
-0.2644554376602173,
-0.045098140835762024,
0.5335498452186584,
-0.02422489784657955,
-0.3266540467739105,
-0.020113375037908554,
0.07147333025932312,
-0.30048394203186035,
0.06917276978492737,
-0.14425423741340637,
-0.24988864362239838,
0.21163970232009888,
0.17763064801692963,
-0.25000855326652527,
0.05973845720291138,
-0.03575151786208153,
0.1542450487613678,
0.21908296644687653,
0.02060939371585846,
0.2647174596786499,
-0.2386094629764557,
-0.07471178472042084,
-0.16828171908855438,
-0.1355242282152176,
0.0720594972372055,
-0.19097557663917542,
0.04476761445403099,
0.11568400263786316,
-0.09888505935668945,
0.5525389313697815,
-0.07500897347927094,
-0.10550448298454285,
-0.2602429986000061,
0.25004419684410095,
-0.4098776578903198,
-0.21422843635082245,
0.020000256597995758,
0.1741640418767929,
0.1515708863735199,
-0.35633909702301025,
0.5705783367156982,
0.06015283986926079,
0.05220331624150276,
0.052962057292461395,
0.16527235507965088,
-0.2551437020301819,
0.4723822772502899,
-0.24417735636234283,
0.006947994232177734,
0.05782755836844444,
0.009747333824634552,
-0.102012999355793,
-0.3523838520050049,
-0.06964657455682755,
0.31335726380348206,
0.09305255115032196,
-0.042641185224056244,
0.03194166719913483,
0.13272316753864288,
-0.11251083016395569,
0.019939225167036057,
-0.1706300973892212,
-0.36915016174316406,
0.14089323580265045,
0.24945934116840363,
0.2711485028266907,
0.18250614404678345,
-0.11808463931083679,
-0.20866364240646362,
-0.10900400578975677,
0.5103971362113953,
0.0016739293932914734,
0.2612941861152649,
-0.13015809655189514,
0.3655264973640442,
0.42578956484794617,
0.4940814971923828,
-0.2902446389198303,
0.03717299550771713,
0.037440225481987,
0.09641530364751816,
0.48279711604118347,
-0.2636583149433136,
0.02178003638982773,
0.2817063629627228,
-0.13145862519741058,
0.058572232723236084,
-0.34479525685310364,
-0.1682952344417572,
-0.22006326913833618,
0.11335426568984985,
0.10334259271621704,
-0.020654119551181793,
0.07225695997476578,
-0.04305354505777359,
-0.14204126596450806,
-0.06888562440872192,
0.045750442892313004,
-0.49925723671913147,
-0.08053195476531982,
0.2202770709991455,
-0.1371796429157257,
-0.011609427630901337,
0.02034958079457283,
0.23941396176815033,
-0.008112229406833649,
-0.12586088478565216,
0.29131388664245605,
0.1330929398536682,
0.12393414229154587,
-0.1924992948770523,
-0.16767145693302155,
0.019878968596458435,
0.21255391836166382,
0.17324021458625793,
-0.056935764849185944,
0.19535769522190094,
-0.17024734616279602,
-0.14223472774028778,
0.24023392796516418,
0.12741324305534363,
0.04383229836821556,
-0.17915286123752594,
0.17719945311546326,
0.1416485458612442,
-0.09756141155958176,
0.06519679725170135,
0.22627584636211395,
0.08455795794725418,
0.12077274918556213,
0.09019751846790314,
0.1219424307346344,
0.4357948303222656,
-0.2544054388999939,
-0.017903020605444908,
0.1419234275817871,
-0.351421594619751,
0.1340951770544052,
-0.04542107507586479,
-0.07775237411260605,
0.0030962564051151276,
0.11714660376310349,
-0.07418832182884216,
0.12427617609500885,
-0.3563074469566345,
0.3523235321044922,
0.27313128113746643,
-0.01798110082745552,
0.06044319272041321,
0.1776667684316635,
0.005221795290708542,
-0.13915102183818817,
0.3545141816139221,
0.10290132462978363,
0.40711650252342224,
0.03838269039988518,
0.9214759469032288,
-0.28261417150497437,
-0.4910769760608673,
0.074270099401474,
0.4407668709754944,
0.013904735445976257,
-0.20886003971099854,
0.06338049471378326,
0.0767066553235054,
-0.349092036485672,
0.09109146893024445,
0.02814275398850441,
-0.1617656946182251,
0.6003193855285645,
-0.0926634818315506,
0.19700390100479126,
-0.12050983309745789,
-0.18638822436332703,
0.30416521430015564,
0.2193455994129181,
-0.0848199725151062,
0.03866316005587578,
0.08103355765342712,
-0.09659154713153839,
-0.2082844078540802,
0.539487898349762,
0.1378851681947708,
-0.03067024052143097,
-0.4813683331012726,
0.02654212713241577,
0.1303127110004425,
0.16194486618041992,
-0.042261797934770584,
0.1696631759405136,
0.42150866985321045,
-0.1417672038078308,
0.29074108600616455,
0.0038774237036705017,
-0.09474688023328781,
-0.18484871089458466,
0.07130374759435654,
-0.4407298266887665,
-0.35878968238830566,
0.38067737221717834,
0.14892904460430145,
-0.1816977560520172,
0.12254293262958527,
0.2738814353942871,
-0.6083030104637146,
-0.22651799023151398,
0.28876474499702454,
-0.16612592339515686,
-0.08401194959878922,
-0.22621002793312073,
0.08732544630765915,
0.05002979189157486,
0.6215313673019409,
0.2386113405227661,
0.3424452245235443,
-0.31244197487831116,
-0.11013562232255936,
-0.5452611446380615,
-0.12234259396791458,
0.15473434329032898,
-0.12682385742664337,
-0.16537782549858093,
0.17525804042816162,
-0.025400705635547638,
0.3293079137802124,
-0.26487916707992554,
0.18954189121723175,
0.1383688747882843,
0.08010149747133255,
-0.45095768570899963,
0.1427934616804123,
0.08015468716621399,
0.0685940533876419,
0.27189093828201294,
-0.1098073422908783,
-0.17113739252090454,
0.08312532305717468,
-0.06507846713066101,
-0.06606283038854599,
-0.0689278393983841,
0.2686031460762024,
0.16191941499710083,
0.03138861805200577,
0.07718020677566528,
0.4355566203594208,
0.004979666322469711,
-0.20629256963729858,
0.0015182457864284515,
0.0014965813606977463,
-0.3515438437461853,
-0.19137030839920044,
-0.07274559140205383,
0.1683378964662552,
-0.3356752097606659,
0.2971011996269226,
-0.029855817556381226,
-0.11843480169773102,
0.1227511614561081,
0.06191503256559372,
-0.1948867291212082,
-0.09245669096708298,
0.10430537909269333,
0.15145081281661987,
0.21517954766750336,
0.7912341356277466,
-0.033916689455509186,
0.05124349892139435,
-0.10069805383682251,
-0.010347947478294373,
0.04032726585865021,
-0.09624392539262772,
-0.22648505866527557,
-0.07546033710241318,
0.03443174064159393,
0.0869658961892128,
0.10204719007015228,
-0.6406650543212891,
-0.37819695472717285,
0.03704700991511345,
-0.04062342643737793,
-0.0003268904983997345,
0.7422401905059814,
0.09145697951316833,
-0.1913265585899353,
-0.0755397230386734,
-0.32336387038230896,
0.008202241733670235,
-0.29208534955978394,
0.1692119836807251,
-0.3407365679740906
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | I agree with going with temperature-scaled mixing for its flexibility!
For the function that combines the datasets, I also find `dataset.add()` okay while also considering that users may want it to be easy to combine a list of say 10 data sources in one go.
`dataset.sample()` should also be good. By the looks of it, we're planning to have as main parameters: `temperature`, and `K`.
On converting the datasets to the same format, I agree that we can leave these to the users for now. But, I do imagine it'd be an awesome feature for the future to have this automatically handled, based on a chosen *approach* to formatting :smile:
E.g. T5, GPT-3, decaNLP, original raw formatting, or a contributed way of formatting in text-to-text. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 125 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
I agree with going with temperature-scaled mixing for its flexibility!
For the function that combines the datasets, I also find `dataset.add()` okay while also considering that users may want it to be easy to combine a list of say 10 data sources in one go.
`dataset.sample()` should also be good. By the looks of it, we're planning to have as main parameters: `temperature`, and `K`.
On converting the datasets to the same format, I agree that we can leave these to the users for now. But, I do imagine it'd be an awesome feature for the future to have this automatically handled, based on a chosen *approach* to formatting :smile:
E.g. T5, GPT-3, decaNLP, original raw formatting, or a contributed way of formatting in text-to-text. | [
-0.09163219481706619,
-0.4211600720882416,
-0.04513248801231384,
-0.08009868860244751,
-0.2404671162366867,
0.059044964611530304,
0.1587897539138794,
0.05346059799194336,
0.30978649854660034,
-0.15817712247371674,
-0.23331528902053833,
0.3175208568572998,
-0.1927580088376999,
0.35245880484580994,
0.42011570930480957,
-0.4721607267856598,
0.027789317071437836,
-0.20416474342346191,
-0.3079902231693268,
0.35350745916366577,
0.0078004151582717896,
0.11438114196062088,
-0.17745058238506317,
0.08323551714420319,
-0.29803040623664856,
-0.16597478091716766,
-0.35576871037483215,
0.13368433713912964,
0.09495039284229279,
0.019253242760896683,
0.17773222923278809,
0.3762141764163971,
-0.0357888862490654,
0.0648593083024025,
-0.00011105541489087045,
-0.11337066441774368,
0.21172308921813965,
-0.08244490623474121,
0.09594912827014923,
-0.04149681329727173,
0.14164206385612488,
-0.38433295488357544,
0.0004229896003380418,
-0.0986679345369339,
0.18146944046020508,
0.16644404828548431,
0.19007359445095062,
0.049618855118751526,
0.3385031223297119,
-0.29403936862945557,
0.1220092922449112,
0.3003107011318207,
-0.16042426228523254,
0.25943702459335327,
-0.07904580980539322,
-0.07974834740161896,
0.04912269115447998,
0.22365301847457886,
0.6150230169296265,
-0.5491244196891785,
-0.0011966824531555176,
0.1282312422990799,
-0.0015522688627243042,
-0.024032112210989,
0.1823764443397522,
-0.04576140269637108,
-0.3587004244327545,
-0.24357569217681885,
-0.3750145435333252,
0.23614278435707092,
-0.11858702450990677,
-0.15378594398498535,
-0.2185506522655487,
-0.5235364437103271,
0.02771851420402527,
0.016797097399830818,
-0.2812066078186035,
0.02997349575161934,
-0.16756169497966766,
-0.04844861850142479,
-0.16560259461402893,
-0.12260453402996063,
0.013107195496559143,
0.15340232849121094,
0.3461077809333801,
0.5681386590003967,
0.06152692064642906,
0.16792187094688416,
0.40035420656204224,
0.0016654245555400848,
-0.15272551774978638,
-0.3198026120662689,
0.29201003909111023,
0.09851133823394775,
-0.38790521025657654,
-0.3371363580226898,
0.1489792913198471,
-0.18864706158638,
0.24584227800369263,
0.15510164201259613,
0.10689498484134674,
0.08710213005542755,
-0.11532724648714066,
0.27482134103775024,
0.3207060694694519,
0.0658683329820633,
-0.06847185641527176,
-0.11937612295150757,
0.027747048065066338,
-0.08491230756044388,
0.21637919545173645,
0.12413544207811356,
0.2167028784751892,
-0.02785976231098175,
-0.4467775523662567,
-0.14667266607284546,
-0.17592653632164001,
0.12826527655124664,
-0.17640042304992676,
-0.524179995059967,
-0.05227186158299446,
-0.10353738069534302,
0.08943959325551987,
-0.048955611884593964,
-0.28327587246894836,
0.10214965045452118,
-0.07685297727584839,
0.20829130709171295,
-0.06274810433387756,
0.07493423670530319,
-0.07943785935640335,
0.12596245110034943,
-0.4375801086425781,
-0.01497543416917324,
0.30172044038772583,
0.11206872761249542,
0.11711080372333527,
0.15991513431072235,
-0.02833031862974167,
0.10989698767662048,
0.3795184791088104,
-0.016750697046518326,
0.050976626574993134,
-0.007164042443037033,
0.1398804932832718,
-0.32601621747016907,
-0.0488298200070858,
0.1761285662651062,
-0.34295204281806946,
-0.14655029773712158,
-0.13508251309394836,
-0.20721761882305145,
0.14267075061798096,
0.05246469005942345,
-0.19705796241760254,
-0.27266278862953186,
-0.469783753156662,
0.7273021936416626,
-0.06460843235254288,
-0.043151721358299255,
-0.13948577642440796,
0.27761369943618774,
-0.2422705888748169,
-0.09580087661743164,
0.19651944935321808,
0.09004785120487213,
-0.008326750248670578,
-0.3287340998649597,
-0.09379439800977707,
-0.1102161854505539,
-0.03254228085279465,
0.26917797327041626,
-0.17343416810035706,
0.2014375925064087,
0.048721395432949066,
0.20125935971736908,
0.2725919187068939,
-0.467446893453598,
-0.0660242959856987,
0.3148563504219055,
-0.021598059684038162,
0.37245580554008484,
0.047157011926174164,
0.2215045690536499,
-0.009119553491473198,
-0.19109781086444855,
0.27087265253067017,
0.9994992613792419,
-0.39096599817276,
-0.0052987802773714066,
-0.14486417174339294,
-0.36753806471824646,
0.5181840658187866,
0.34996935725212097,
0.06550046056509018,
-0.3326672911643982,
-0.14244595170021057,
-0.023778382688760757,
0.08096598088741302,
0.0770779699087143,
0.08081132173538208,
-0.023395702242851257,
-0.3496008515357971,
0.02572062239050865,
-0.21601687371730804,
-0.13175401091575623,
-0.39827898144721985,
-0.013193009421229362,
-0.011377250775694847,
0.3362920582294464,
0.2629062533378601,
-0.11397732049226761,
0.23644927144050598,
-0.26847612857818604,
-0.1313517987728119,
-0.3461121916770935,
0.1502704918384552,
-0.06126667559146881,
0.051079463213682175,
-0.2666863799095154,
-0.036756664514541626,
0.3218362331390381,
0.1138492226600647,
-0.11466069519519806,
-0.5048949718475342,
0.2798417806625366,
-0.08512654155492783,
0.032010518014431,
-0.015921875834465027,
0.6123453378677368,
-0.13566911220550537,
-0.09030590206384659,
0.18309861421585083,
0.3067482113838196,
-0.32861700654029846,
0.2714981436729431,
0.3248351514339447,
0.2580251395702362,
0.1833747923374176,
-0.02368352562189102,
0.11495939642190933,
-0.03480041027069092,
-0.03136957809329033,
-0.20113030076026917,
-0.10553111881017685,
0.4779738187789917,
-0.17939849197864532,
0.40344473719596863,
-0.027947911992669106,
0.02752644009888172,
-0.19954337179660797,
-0.036002691835165024,
-0.22701188921928406,
0.367566853761673,
0.3015568256378174,
-0.19315442442893982,
0.3859136998653412,
-0.09095410257577896,
-0.3488398790359497,
0.17814302444458008,
0.20084065198898315,
0.013798952102661133,
0.09303046762943268,
-0.016065359115600586,
-0.0603153333067894,
-0.3105744421482086,
-0.06443570554256439,
0.4159681797027588,
0.6467360854148865,
0.2788432538509369,
0.1465170532464981,
0.05391903221607208,
-0.23704062402248383,
-0.07217651605606079,
0.02709732949733734,
0.17971578240394592,
-0.022057941183447838,
0.13218240439891815,
0.028972607105970383,
0.053669046610593796,
-0.0197980348020792,
-0.14596885442733765,
0.1391361653804779,
-0.18290135264396667,
-0.026788270100951195,
0.0350450798869133,
-0.19006139039993286,
-0.5519410967826843,
-0.2311941236257553,
0.04605114087462425,
-0.375975638628006,
-0.3040531575679779,
0.12783879041671753,
0.025094876065850258,
-0.19186356663703918,
0.1835845559835434,
0.2177857607603073,
0.5667122602462769,
-0.4283854067325592,
-0.25661733746528625,
-0.10000119358301163,
-0.25852108001708984,
-0.10058089345693588,
0.12403920292854309,
0.41809219121932983,
0.30088603496551514,
0.4967927932739258,
0.28931277990341187,
-0.014469848945736885,
0.020839190110564232,
-0.3807588815689087,
0.04763735085725784,
-0.288138210773468,
0.2660779356956482,
0.10908018052577972,
-0.23446260392665863,
0.1544487029314041,
-0.4112611711025238,
-0.02723073586821556,
-0.06777597963809967,
-0.05139286071062088,
-0.049117833375930786,
-0.015199120156466961,
0.0207084771245718,
-0.17686575651168823,
-0.22578808665275574,
-0.6239805221557617,
-0.4909670948982239,
0.28933680057525635,
-0.28130975365638733,
0.0613841712474823,
0.016535308212041855,
-0.26013949513435364,
0.19389955699443817,
-0.15522347390651703,
0.03759928047657013,
-0.17455731332302094,
-0.10408574342727661,
0.04657413065433502,
-0.3616589605808258,
-0.16067299246788025,
-0.41546830534935,
-0.11438252776861191,
0.23246780037879944,
-0.08507470786571503,
-0.0425742045044899,
-0.23878808319568634,
0.048094674944877625,
-0.12757475674152374,
0.09415815770626068,
0.2228919416666031,
0.1751595139503479,
-0.22287091612815857,
0.09907601773738861,
-0.036777425557374954,
-0.26462864875793457,
0.1948915719985962,
0.33807286620140076,
0.42725706100463867,
0.17781081795692444,
0.01658076047897339,
0.17279289662837982,
0.7245492935180664,
0.25919094681739807,
0.05576366186141968,
0.15051709115505219,
0.3070625364780426,
0.03356906771659851,
0.14654755592346191,
-0.23375555872917175,
0.24164286255836487,
-0.16472789645195007,
0.5056428909301758,
0.09843314439058304,
0.1719014048576355,
-0.2043481171131134,
-0.28388190269470215,
-0.012782398611307144,
-0.2579216957092285,
-0.18797719478607178,
0.2683839499950409,
-0.22223517298698425,
0.020278356969356537,
-0.055379871279001236,
-0.3724345564842224,
-0.25288158655166626,
-0.04279504343867302,
0.017948660999536514,
0.31589123606681824,
-0.030992522835731506,
0.15221890807151794,
-0.34515342116355896,
-0.0411997027695179,
-0.4830809235572815,
0.15105335414409637,
0.08815167844295502,
0.27570006251335144,
-0.08164797723293304,
-0.0731469988822937,
-0.1406986564397812,
0.10453666746616364,
0.5943602323532104,
-0.5221483111381531,
-0.16565899550914764,
0.09090529382228851,
0.08042608946561813,
-0.09018901735544205,
-0.08775423467159271,
-0.2720241844654083,
-0.04363056644797325,
0.4483170211315155,
0.36958035826683044,
-0.3692058026790619,
-0.3136216998100281,
0.2565195858478546,
-0.18059846758842468,
-0.03166762739419937,
-0.19901442527770996,
-0.18238741159439087,
-0.18923181295394897,
-0.14206206798553467,
0.03215467929840088,
0.1843511015176773,
0.2113642543554306,
-0.10405097156763077,
0.17735259234905243,
-0.05196564644575119,
0.2529606819152832,
0.20239824056625366,
0.01307758316397667,
-0.040300264954566956,
0.22695446014404297,
0.15439800918102264,
0.031860142946243286,
-0.12105235457420349,
-0.29360511898994446,
0.09633069485425949,
-0.06996095180511475,
0.11004846543073654,
0.271496057510376,
-0.00305559067055583,
0.6472855806350708,
0.05717632919549942,
0.31057435274124146,
0.2889767289161682,
-0.12562023103237152,
0.05900801718235016,
-0.23012974858283997,
0.14177188277244568,
0.22950918972492218,
0.25832289457321167,
-0.13930945098400116,
-0.19662606716156006,
0.5935574173927307,
0.3162984549999237,
-0.07326257973909378,
0.38970157504081726,
-0.46200162172317505,
-0.2712932527065277,
0.2523413896560669,
0.027918927371501923,
0.6917436122894287,
-0.025947771966457367,
0.2671622931957245,
0.06503260135650635,
-0.384538471698761,
0.6288003325462341,
-0.3909117579460144,
0.1575741320848465,
-0.07772613316774368,
-0.23540401458740234,
0.0326017290353775,
-0.09457425773143768,
-0.06971939653158188,
0.26830774545669556,
-0.3717164695262909,
0.34969374537467957,
0.4773365259170532,
-0.20441070199012756,
-0.05118029564619064,
0.5518015027046204,
-0.029192546382546425,
-0.400279700756073,
-0.10723662376403809,
0.08906093239784241,
-0.28121334314346313,
0.10603442788124084,
-0.16336649656295776,
-0.27637630701065063,
0.24864256381988525,
0.11350046098232269,
-0.27409273386001587,
0.11336158961057663,
-0.03516446799039841,
0.1855698674917221,
0.2648400366306305,
0.016313955187797546,
0.25120601058006287,
-0.17889165878295898,
-0.0666220486164093,
-0.1549469530582428,
-0.0886358767747879,
0.1312912553548813,
-0.14661234617233276,
0.05025830119848251,
0.030554739758372307,
-0.2045278698205948,
0.5105484127998352,
-0.07615140080451965,
-0.10789109766483307,
-0.24378013610839844,
0.24476522207260132,
-0.43671631813049316,
-0.1542508751153946,
0.11010661721229553,
0.16822589933872223,
0.2132159322500229,
-0.31623944640159607,
0.6001381874084473,
0.08641384541988373,
-0.009584203362464905,
0.055802345275878906,
0.1773013174533844,
-0.23682695627212524,
0.4851786196231842,
-0.25789588689804077,
-0.004610419273376465,
0.052440494298934937,
0.010878428816795349,
-0.1622539460659027,
-0.37275445461273193,
-0.03353308141231537,
0.2981380224227905,
0.08636647462844849,
-0.016164803877472878,
-0.0029818490147590637,
0.1021042987704277,
-0.07975640147924423,
-0.003008240833878517,
-0.15544848144054413,
-0.3322067856788635,
0.1165371909737587,
0.14724498987197876,
0.19470559060573578,
0.16701370477676392,
-0.053953059017658234,
-0.24001404643058777,
-0.18599310517311096,
0.46923357248306274,
0.04062017798423767,
0.2234199494123459,
-0.13615617156028748,
0.3405207097530365,
0.42906028032302856,
0.5344385504722595,
-0.28160953521728516,
0.07217328995466232,
0.032790035009384155,
0.08643410354852676,
0.4831205904483795,
-0.2349259853363037,
0.07466655224561691,
0.2786791920661926,
-0.11924923956394196,
0.0491994246840477,
-0.34023600816726685,
-0.1727285087108612,
-0.2547360062599182,
0.09835311770439148,
0.11223381012678146,
-0.0018388675525784492,
0.0054129986092448235,
-0.06127312406897545,
-0.07910172641277313,
-0.08158965408802032,
0.016571901738643646,
-0.3894309103488922,
-0.06932204961776733,
0.15564624965190887,
-0.11541067063808441,
0.015997931361198425,
0.059237927198410034,
0.20302146673202515,
0.009794354438781738,
-0.0524289608001709,
0.2911641597747803,
0.12709856033325195,
0.11118440330028534,
-0.1909799873828888,
-0.17631687223911285,
0.004691518843173981,
0.21382761001586914,
0.14815178513526917,
-0.02907838672399521,
0.1604178547859192,
-0.23436830937862396,
-0.1400955319404602,
0.2342926561832428,
0.1486867070198059,
0.020620571449398994,
-0.12043088674545288,
0.1056559756398201,
0.14062277972698212,
-0.12489896267652512,
-0.02853161096572876,
0.17814530432224274,
0.11084794253110886,
0.1366320550441742,
0.11059849709272385,
0.15870606899261475,
0.44991493225097656,
-0.21001620590686798,
0.025973491370677948,
0.11526631563901901,
-0.3685958981513977,
0.12917537987232208,
-0.11547407507896423,
-0.040456511080265045,
0.005308408290147781,
0.1474834382534027,
-0.0111294686794281,
0.13959282636642456,
-0.32164716720581055,
0.30607354640960693,
0.30969566106796265,
-0.023712676018476486,
0.05864635109901428,
0.23911476135253906,
0.01480795443058014,
-0.13310979306697845,
0.30467915534973145,
0.01857598125934601,
0.3192398250102997,
0.042772985994815826,
0.8754275441169739,
-0.272227019071579,
-0.45505988597869873,
0.10648228973150253,
0.43658554553985596,
0.03211100772023201,
-0.21552914381027222,
0.15521663427352905,
0.09118608385324478,
-0.40597593784332275,
0.1209784597158432,
0.05810922011733055,
-0.1637459695339203,
0.657473087310791,
-0.11649444699287415,
0.16466790437698364,
-0.15811486542224884,
-0.14994096755981445,
0.3523966372013092,
0.19673556089401245,
-0.09543836116790771,
0.010715967044234276,
0.11992718279361725,
-0.11069288849830627,
-0.16985253989696503,
0.5139833688735962,
0.2285723239183426,
0.034792959690093994,
-0.4124753475189209,
0.03735283389687538,
0.107136070728302,
0.14290352165699005,
-0.07321160286664963,
0.138036847114563,
0.44498148560523987,
-0.18126782774925232,
0.2542766332626343,
0.036787159740924835,
-0.07882071286439896,
-0.13540196418762207,
0.043383754789829254,
-0.38847362995147705,
-0.39733782410621643,
0.4565662145614624,
0.10967668145895004,
-0.11010195314884186,
0.04526514559984207,
0.3206997513771057,
-0.6264177560806274,
-0.2374812215566635,
0.3614809215068817,
-0.1362902969121933,
-0.0500934012234211,
-0.24483497440814972,
0.08715891093015671,
0.08407621085643768,
0.6122646927833557,
0.21460853517055511,
0.3534941077232361,
-0.4017142355442047,
-0.14038477838039398,
-0.5742546916007996,
-0.21603280305862427,
0.17194154858589172,
-0.07661580294370651,
-0.2584016025066376,
0.14676685631275177,
-0.06859225779771805,
0.28950589895248413,
-0.21401123702526093,
0.1178646832704544,
0.17773322761058807,
0.02705768123269081,
-0.430539071559906,
0.11578315496444702,
0.058791302144527435,
0.004421898163855076,
0.31976118683815,
-0.11052559316158295,
-0.1742173284292221,
0.08242564648389816,
-0.05696408078074455,
-0.09089021384716034,
-0.06792822480201721,
0.23781514167785645,
0.16779708862304688,
0.09648948162794113,
0.08136258274316788,
0.4660528302192688,
-0.04932480677962303,
-0.2016535997390747,
-0.008784513920545578,
0.012513291090726852,
-0.37709811329841614,
-0.1661680042743683,
-0.07718321681022644,
0.1801460236310959,
-0.33483511209487915,
0.25497040152549744,
-0.016634495928883553,
-0.08482318371534348,
0.11921893060207367,
0.01841846853494644,
-0.1893487125635147,
-0.04945801943540573,
0.07420556992292404,
0.195068821310997,
0.22280582785606384,
0.7319666147232056,
-0.01056225597858429,
0.08575521409511566,
-0.09298598021268845,
-0.03421401232481003,
0.07086607813835144,
-0.052111849188804626,
-0.20773279666900635,
-0.13613852858543396,
0.02423723042011261,
0.09727302193641663,
0.13568156957626343,
-0.6967558860778809,
-0.33582890033721924,
0.014331405982375145,
-0.022863823920488358,
0.03177652135491371,
0.7183234095573425,
0.06665454804897308,
-0.14486512541770935,
-0.11753140389919281,
-0.2986988425254822,
0.053424231708049774,
-0.2820817530155182,
0.18920615315437317,
-0.34770846366882324
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | This is an interesting discussion indeed and it would be nice to make multi-task easier.
Probably the best would be to have a new type of dataset especially designed for that in order to easily combine and sample from the multiple datasets.
This way we could probably handle the combination of datasets with differing schemas as well (unlike T5). | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 59 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
This is an interesting discussion indeed and it would be nice to make multi-task easier.
Probably the best would be to have a new type of dataset especially designed for that in order to easily combine and sample from the multiple datasets.
This way we could probably handle the combination of datasets with differing schemas as well (unlike T5). | [
-0.07760576903820038,
-0.4301373362541199,
-0.05128105729818344,
-0.007647901773452759,
-0.24152879416942596,
0.11484136432409286,
0.1743364930152893,
0.09230956435203552,
0.28521808981895447,
-0.11796191334724426,
-0.24373745918273926,
0.27350884675979614,
-0.19464346766471863,
0.41696271300315857,
0.39819997549057007,
-0.45603516697883606,
0.007997095584869385,
-0.21966683864593506,
-0.2606225907802582,
0.37996965646743774,
0.04182820022106171,
0.09555917233228683,
-0.14734555780887604,
0.06278294324874878,
-0.2902207374572754,
-0.1371721774339676,
-0.34358692169189453,
0.08050669729709625,
0.10446936637163162,
0.0340154692530632,
0.19900573790073395,
0.37377867102622986,
0.00899704359471798,
0.10891927778720856,
-0.00011252853437326849,
-0.09093979001045227,
0.16050821542739868,
-0.0712214782834053,
0.1302853673696518,
-0.023051872849464417,
0.12360096722841263,
-0.35964643955230713,
0.06394293904304504,
-0.10716303437948227,
0.18151751160621643,
0.18675681948661804,
0.20179066061973572,
0.08393155038356781,
0.3181023597717285,
-0.3155003786087036,
0.0999816283583641,
0.29038479924201965,
-0.18832486867904663,
0.280779629945755,
-0.05406240373849869,
-0.0642036646604538,
0.03068152628839016,
0.22856448590755463,
0.6673146486282349,
-0.5304582118988037,
0.04461165517568588,
0.06839239597320557,
-0.02713405340909958,
0.04156407713890076,
0.11788807809352875,
-0.08518808335065842,
-0.30709508061408997,
-0.239467591047287,
-0.37350428104400635,
0.28026336431503296,
-0.07192579656839371,
-0.10643924027681351,
-0.23320834338665009,
-0.5333685874938965,
0.01573336496949196,
0.07696226239204407,
-0.2952456772327423,
0.05960957705974579,
-0.1627965122461319,
-0.019170589745044708,
-0.12913011014461517,
-0.12187917530536652,
-0.001456335186958313,
0.1736183613538742,
0.3086414337158203,
0.5555930137634277,
0.06791813671588898,
0.16606809198856354,
0.3354538083076477,
0.06970074027776718,
-0.09848681837320328,
-0.2893276810646057,
0.2836745083332062,
0.06580854207277298,
-0.4028254747390747,
-0.35675525665283203,
0.13010713458061218,
-0.26543211936950684,
0.28047773241996765,
0.13964121043682098,
0.16255822777748108,
0.09564383327960968,
-0.1668533980846405,
0.2518714666366577,
0.33976078033447266,
-0.02247934229671955,
-0.12287168949842453,
-0.13603001832962036,
0.017504721879959106,
-0.10887739807367325,
0.16654373705387115,
0.13609996438026428,
0.17564214766025543,
-0.0186630729585886,
-0.4268651306629181,
-0.11984290927648544,
-0.14647668600082397,
0.0982045829296112,
-0.18795841932296753,
-0.6031383275985718,
-0.09075364470481873,
-0.10779067128896713,
0.03100643679499626,
-0.15765944123268127,
-0.2877180278301239,
0.092652827501297,
-0.10346348583698273,
0.24397854506969452,
-0.13179226219654083,
0.00854057352989912,
-0.048577066510915756,
0.06551392376422882,
-0.423928439617157,
-0.04849141836166382,
0.29413989186286926,
0.09935413300991058,
0.04831109195947647,
0.16498593986034393,
-0.03427750617265701,
0.12868380546569824,
0.42059457302093506,
0.029048018157482147,
0.014121629297733307,
-0.0367378331720829,
0.17303933203220367,
-0.3192979693412781,
-0.011867158114910126,
0.2226768583059311,
-0.37173980474472046,
-0.11837560683488846,
-0.16984781622886658,
-0.2173645943403244,
0.09760744869709015,
0.03343378007411957,
-0.21831941604614258,
-0.3184994161128998,
-0.4913887679576874,
0.7129409909248352,
-0.044741190969944,
-0.04646164923906326,
-0.16467785835266113,
0.2666395902633667,
-0.2322615534067154,
-0.09799232333898544,
0.16326361894607544,
0.08497167378664017,
0.013150323182344437,
-0.2949587106704712,
-0.09312959760427475,
-0.10383567214012146,
-0.06481081992387772,
0.30172601342201233,
-0.16893525421619415,
0.21227431297302246,
0.06585872173309326,
0.13697415590286255,
0.2494572103023529,
-0.4536503851413727,
-0.048898711800575256,
0.33244845271110535,
-0.02496878057718277,
0.35705429315567017,
0.07683297246694565,
0.2123105525970459,
-0.0030691931024193764,
-0.2040671855211258,
0.19492629170417786,
1.017795205116272,
-0.3952714800834656,
-0.021733975037932396,
-0.11022846400737762,
-0.39061519503593445,
0.5425779819488525,
0.36107009649276733,
0.06735080480575562,
-0.3310126066207886,
-0.13180634379386902,
-0.008706456050276756,
0.09087163209915161,
0.07975569367408752,
0.04832107573747635,
-0.0628935918211937,
-0.34346044063568115,
0.04504135251045227,
-0.24580256640911102,
-0.19732028245925903,
-0.4192027747631073,
-0.020278949290513992,
0.016957003623247147,
0.29230332374572754,
0.3340206742286682,
-0.10002608597278595,
0.27135199308395386,
-0.3039945662021637,
-0.1537623554468155,
-0.31332990527153015,
0.11975884437561035,
-0.005619511008262634,
0.03799665346741676,
-0.24834029376506805,
-0.030674505978822708,
0.31918051838874817,
0.09926745295524597,
-0.13511954247951508,
-0.4337626099586487,
0.33981865644454956,
-0.047643229365348816,
0.04676056280732155,
-0.04639905318617821,
0.6206656098365784,
-0.19886362552642822,
-0.09158611297607422,
0.1701807677745819,
0.24870342016220093,
-0.3234960436820984,
0.2560337483882904,
0.32414016127586365,
0.35003429651260376,
0.19196629524230957,
-0.08836960047483444,
0.08618822693824768,
-0.012060839682817459,
-0.05773837864398956,
-0.19454273581504822,
-0.08406423777341843,
0.4658960700035095,
-0.18547146022319794,
0.41023844480514526,
-0.05356256663799286,
0.014754710718989372,
-0.19410167634487152,
-0.05506932735443115,
-0.18381235003471375,
0.4107012152671814,
0.3079740107059479,
-0.1972614824771881,
0.3365919291973114,
-0.11086127161979675,
-0.36304888129234314,
0.1967424750328064,
0.18514330685138702,
0.056777406483888626,
0.07615286111831665,
-0.03248913586139679,
-0.0191662535071373,
-0.29046300053596497,
-0.11108554899692535,
0.40457239747047424,
0.632398784160614,
0.28050968050956726,
0.11706024408340454,
-0.021244825795292854,
-0.25007444620132446,
-0.10282351821660995,
0.011356614530086517,
0.20606467127799988,
-0.016843674704432487,
0.15028434991836548,
0.04689302667975426,
0.07360973954200745,
0.043971844017505646,
-0.14593511819839478,
0.1934909075498581,
-0.1794009506702423,
-0.04956897348165512,
0.024611497297883034,
-0.1928529292345047,
-0.5652398467063904,
-0.21911503374576569,
0.0437881201505661,
-0.3279030919075012,
-0.3013741374015808,
0.15034149587154388,
0.05334058031439781,
-0.176954984664917,
0.15528973937034607,
0.174662783741951,
0.5224665999412537,
-0.44439470767974854,
-0.2338436096906662,
-0.06413104385137558,
-0.28284752368927,
-0.08073657006025314,
0.11607673764228821,
0.49301397800445557,
0.2858504056930542,
0.45890358090400696,
0.2643522024154663,
-0.04553256928920746,
0.0037953639402985573,
-0.3939478397369385,
0.029011324048042297,
-0.30691754817962646,
0.2791736125946045,
0.0830259770154953,
-0.21713970601558685,
0.15055492520332336,
-0.39499631524086,
-0.06443783640861511,
-0.04882184416055679,
-0.07792936265468597,
-0.028692929074168205,
-0.025047870352864265,
0.0897224098443985,
-0.17804251611232758,
-0.2269406020641327,
-0.6084065437316895,
-0.4707542657852173,
0.2826777398586273,
-0.28210893273353577,
0.07274039834737778,
0.038764555007219315,
-0.27793413400650024,
0.15081928670406342,
-0.15593431890010834,
0.028028899803757668,
-0.15452151000499725,
-0.11299090832471848,
-0.01863935962319374,
-0.3668549358844757,
-0.15962430834770203,
-0.41231536865234375,
-0.07378329336643219,
0.22635772824287415,
-0.07291725277900696,
-0.0498352125287056,
-0.2201995700597763,
0.06068301200866699,
-0.10324518382549286,
0.0564827024936676,
0.17424608767032623,
0.1718524992465973,
-0.22455747425556183,
0.11065275967121124,
-0.04123270884156227,
-0.20303326845169067,
0.20850899815559387,
0.36925259232521057,
0.3985558748245239,
0.17247524857521057,
-0.04534270614385605,
0.15867747366428375,
0.6988726258277893,
0.22570152580738068,
0.07469471544027328,
0.1957734227180481,
0.300357460975647,
-0.008464980870485306,
0.14122040569782257,
-0.233286514878273,
0.21620109677314758,
-0.13694700598716736,
0.49532997608184814,
0.11535324156284332,
0.1564604938030243,
-0.17848846316337585,
-0.2667303681373596,
0.05356660857796669,
-0.2868148386478424,
-0.18034493923187256,
0.23250894248485565,
-0.2959993779659271,
0.0018163472414016724,
-0.06489185988903046,
-0.46274006366729736,
-0.28313708305358887,
-0.04907607659697533,
-0.028592389076948166,
0.3023619055747986,
-0.01832866668701172,
0.16230705380439758,
-0.3587011694908142,
-0.02396807074546814,
-0.359493225812912,
0.16688692569732666,
0.09561147540807724,
0.25671476125717163,
-0.08165299892425537,
-0.045284949243068695,
-0.07541713118553162,
0.13249599933624268,
0.594111442565918,
-0.5726907253265381,
-0.11468027532100677,
0.11226196587085724,
0.06943963468074799,
-0.10702905058860779,
-0.11246588826179504,
-0.25311192870140076,
-0.022778909653425217,
0.41089943051338196,
0.3724684417247772,
-0.3512176275253296,
-0.3359483778476715,
0.27706092596054077,
-0.1780259758234024,
-0.06660392880439758,
-0.1773485690355301,
-0.1805456429719925,
-0.19922927021980286,
-0.11174333840608597,
-0.015011996030807495,
0.22503185272216797,
0.23601852357387543,
-0.09397950023412704,
0.1691284477710724,
-0.11902868747711182,
0.23430871963500977,
0.17777666449546814,
-0.020016271620988846,
-0.08604373782873154,
0.21967238187789917,
0.19012929499149323,
0.04374058172106743,
-0.12046508491039276,
-0.2854847311973572,
0.0902773067355156,
-0.08531789481639862,
0.04106679558753967,
0.32314562797546387,
-0.01695924811065197,
0.6543562412261963,
0.0035463571548461914,
0.35406139492988586,
0.29701897501945496,
-0.15183007717132568,
0.035120029002428055,
-0.22525565326213837,
0.1592191606760025,
0.1932837814092636,
0.2645816504955292,
-0.1670910269021988,
-0.2223948836326599,
0.5615092515945435,
0.3239040970802307,
-0.04171903058886528,
0.3951147198677063,
-0.5345005989074707,
-0.27463921904563904,
0.27251511812210083,
0.029302049428224564,
0.6709376573562622,
-0.08567734062671661,
0.2815999984741211,
0.012769563123583794,
-0.4185329079627991,
0.6093618273735046,
-0.356319785118103,
0.14552359282970428,
-0.07994046807289124,
-0.2315620630979538,
0.021089831367135048,
-0.07193601876497269,
-0.09989524632692337,
0.2743527889251709,
-0.34961992502212524,
0.3014124631881714,
0.44390183687210083,
-0.18051117658615112,
-0.03987343609333038,
0.5531432628631592,
-0.015312885865569115,
-0.357075572013855,
-0.03860893100500107,
0.06670358777046204,
-0.2900908589363098,
0.07109349220991135,
-0.1547674834728241,
-0.25153255462646484,
0.24413558840751648,
0.1927369385957718,
-0.3443204164505005,
0.06983192265033722,
0.018976649269461632,
0.18553580343723297,
0.22446368634700775,
-0.00212039053440094,
0.296608030796051,
-0.16361579298973083,
-0.031091906130313873,
-0.1591515690088272,
-0.11198890209197998,
0.1209486573934555,
-0.18845388293266296,
0.004920526873320341,
0.04263247922062874,
-0.1961912214756012,
0.5082728266716003,
-0.05026669800281525,
-0.17390188574790955,
-0.2432452142238617,
0.2771672308444977,
-0.4623684883117676,
-0.23436494171619415,
0.12246377766132355,
0.19409795105457306,
0.218156099319458,
-0.31469637155532837,
0.5614801645278931,
0.127997025847435,
-0.011074503883719444,
0.044554583728313446,
0.134901762008667,
-0.20838184654712677,
0.47530749440193176,
-0.2853441834449768,
-0.02586296945810318,
0.06688466668128967,
-0.004448145627975464,
-0.09673929959535599,
-0.3717647194862366,
-0.04464828968048096,
0.317708283662796,
0.16569329798221588,
-0.028410455211997032,
0.07400874048471451,
0.13821393251419067,
-0.0919293612241745,
-0.007477550767362118,
-0.16431035101413727,
-0.2981984615325928,
0.17177724838256836,
0.1826208084821701,
0.2225337028503418,
0.18226583302021027,
-0.07159329205751419,
-0.23599836230278015,
-0.122200608253479,
0.4769054651260376,
-0.008985381573438644,
0.24603387713432312,
-0.13987493515014648,
0.3845987617969513,
0.4304969310760498,
0.5406715273857117,
-0.25706756114959717,
0.12530672550201416,
0.04334171861410141,
0.08136966824531555,
0.5019499659538269,
-0.2255435287952423,
0.03800460323691368,
0.27418333292007446,
-0.1421244889497757,
0.04171761870384216,
-0.2888588309288025,
-0.16853713989257812,
-0.21639379858970642,
0.11692989617586136,
0.1269606649875641,
0.02414373867213726,
0.03174247592687607,
-0.05489098280668259,
-0.1292056441307068,
-0.05813824385404587,
-0.010787772946059704,
-0.37812095880508423,
-0.04661107808351517,
0.13476987183094025,
-0.062149014323949814,
0.04813924431800842,
0.045553840696811676,
0.24881413578987122,
-0.005483634769916534,
-0.04891292750835419,
0.3026910424232483,
0.1137172058224678,
0.13134883344173431,
-0.19243137538433075,
-0.22584998607635498,
-0.02276790142059326,
0.27811670303344727,
0.16005298495292664,
-0.08049098402261734,
0.15094342827796936,
-0.21033044159412384,
-0.1457175314426422,
0.1973719596862793,
0.10546581447124481,
0.06881042569875717,
-0.08835802972316742,
0.1466383934020996,
0.10758335143327713,
-0.0755477249622345,
0.013402312994003296,
0.1942145824432373,
0.07465550303459167,
0.07250766456127167,
0.10837576538324356,
0.1365595906972885,
0.4735901355743408,
-0.2260930985212326,
0.003198942169547081,
0.12325045466423035,
-0.3594176769256592,
0.15418648719787598,
-0.08749888837337494,
-0.06692662090063095,
-0.03102230653166771,
0.1314779371023178,
-0.059005070477724075,
0.13142891228199005,
-0.3177986741065979,
0.31435197591781616,
0.2902788519859314,
-0.016615577042102814,
-0.023868408054113388,
0.24449306726455688,
0.03816736862063408,
-0.14794549345970154,
0.2975652813911438,
0.04241354390978813,
0.3625638484954834,
0.03182324767112732,
0.8982052206993103,
-0.28706395626068115,
-0.4490219056606293,
0.08506786078214645,
0.4442313611507416,
0.09313870966434479,
-0.21840958297252655,
0.12272955477237701,
0.10584568232297897,
-0.3336717188358307,
0.12666091322898865,
0.027430633082985878,
-0.1679341197013855,
0.6969411373138428,
-0.08871020376682281,
0.13946983218193054,
-0.15565209090709686,
-0.16006094217300415,
0.37912964820861816,
0.15306229889392853,
-0.08720095455646515,
0.005124622955918312,
0.11803263425827026,
-0.11495539546012878,
-0.1713058054447174,
0.5400869250297546,
0.19663335382938385,
-0.016986824572086334,
-0.44110897183418274,
-0.002918851561844349,
0.09282286465167999,
0.18584536015987396,
-0.003108755685389042,
0.11664828658103943,
0.42755234241485596,
-0.17765967547893524,
0.2757040858268738,
0.016501324251294136,
-0.042451731860637665,
-0.12721548974514008,
0.04194376617670059,
-0.39963504672050476,
-0.44053223729133606,
0.43349674344062805,
0.1266334503889084,
-0.10133137553930283,
0.12239136546850204,
0.34221863746643066,
-0.625470757484436,
-0.21663399040699005,
0.32839295268058777,
-0.13515399396419525,
-0.09978494048118591,
-0.21278639137744904,
0.08299478888511658,
0.05206345394253731,
0.6268002986907959,
0.26694661378860474,
0.35594016313552856,
-0.367862343788147,
-0.10077333450317383,
-0.5913139581680298,
-0.1538389027118683,
0.15314844250679016,
-0.07130032777786255,
-0.22856467962265015,
0.15664465725421906,
-0.04573541134595871,
0.27950361371040344,
-0.16623638570308685,
0.15578556060791016,
0.22006641328334808,
0.0632854551076889,
-0.4629290997982025,
0.05816925689578056,
0.15672540664672852,
0.0008714217692613602,
0.26979321241378784,
-0.09562158584594727,
-0.18361014127731323,
0.10721481591463089,
-0.08659321069717407,
-0.13303770124912262,
-0.08308319747447968,
0.2785082459449768,
0.1443416178226471,
0.1257953643798828,
0.060521967709064484,
0.48311856389045715,
-0.013349970802664757,
-0.19535678625106812,
0.00032370537519454956,
-0.017219023779034615,
-0.36596015095710754,
-0.133477121591568,
-0.11219032108783722,
0.16162464022636414,
-0.40695860981941223,
0.3112413287162781,
0.020267846062779427,
-0.11749889701604843,
0.07889258116483688,
0.08205994963645935,
-0.19863159954547882,
-0.1077202707529068,
0.0925135388970375,
0.1740230917930603,
0.22926753759384155,
0.7064047455787659,
-0.009655654430389404,
0.08157234638929367,
-0.08162674307823181,
-0.024642569944262505,
0.013805702328681946,
0.001977735199034214,
-0.23659107089042664,
-0.09722098708152771,
0.035987578332424164,
0.04707097262144089,
0.14540337026119232,
-0.6879175305366516,
-0.3390010893344879,
0.07124495506286621,
0.008100252598524094,
0.060267698019742966,
0.7683095335960388,
0.13407115638256073,
-0.14332085847854614,
-0.10919389128684998,
-0.306508332490921,
0.028837325051426888,
-0.27584418654441833,
0.18561233580112457,
-0.3361104726791382
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | @thomwolf Are you suggesting making a wrapper class which can take existing datasets as arguments and do all the required sampling/combining, to present the same interface as a normal dataset?
That doesn't seem too complicated to implement.
| It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 37 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
@thomwolf Are you suggesting making a wrapper class which can take existing datasets as arguments and do all the required sampling/combining, to present the same interface as a normal dataset?
That doesn't seem too complicated to implement.
| [
-0.08985172212123871,
-0.3969329297542572,
-0.031665366142988205,
-0.037351638078689575,
-0.2264488786458969,
0.08738168329000473,
0.196954607963562,
0.06602276861667633,
0.33273035287857056,
-0.13962094485759735,
-0.22614936530590057,
0.3318239152431488,
-0.2025051862001419,
0.36451777815818787,
0.4015558958053589,
-0.5019195079803467,
-0.009031489491462708,
-0.173209547996521,
-0.3404366970062256,
0.34348368644714355,
0.01590494066476822,
0.08975976705551147,
-0.1299690455198288,
0.053992584347724915,
-0.2659047842025757,
-0.14809374511241913,
-0.3480379581451416,
0.10398368537425995,
0.09025157988071442,
0.00021010730415582657,
0.26544636487960815,
0.3834899067878723,
-0.004184707999229431,
0.11468689143657684,
-0.00011099899711553007,
-0.10409414768218994,
0.17799219489097595,
-0.061887532472610474,
0.13401706516742706,
-0.022732838988304138,
0.20591771602630615,
-0.374109148979187,
0.041294753551483154,
-0.14299587905406952,
0.09510346502065659,
0.18651211261749268,
0.14864693582057953,
0.06131582707166672,
0.4389665126800537,
-0.32718124985694885,
0.1137162297964096,
0.27153220772743225,
-0.21278294920921326,
0.21606014668941498,
-0.10353533178567886,
-0.08171606063842773,
0.03618605434894562,
0.294840008020401,
0.6407874822616577,
-0.525549590587616,
-0.026187747716903687,
0.09548534452915192,
-0.02736218273639679,
-0.026917368173599243,
0.16530895233154297,
-0.05579408258199692,
-0.3531099855899811,
-0.2346816062927246,
-0.3933756947517395,
0.26181381940841675,
-0.19633162021636963,
-0.1110704317688942,
-0.22825053334236145,
-0.5546967387199402,
0.04327018931508064,
0.05650652199983597,
-0.32799801230430603,
0.04984400421380997,
-0.16306138038635254,
0.01506592333316803,
-0.16031597554683685,
-0.1137707456946373,
-0.03513527661561966,
0.15094447135925293,
0.3342221677303314,
0.5391837358474731,
0.07172629982233047,
0.18103159964084625,
0.37623268365859985,
0.06643140316009521,
-0.15596938133239746,
-0.25584715604782104,
0.26040059328079224,
0.1465936303138733,
-0.30014485120773315,
-0.3815108835697174,
0.10290298610925674,
-0.20207494497299194,
0.26482439041137695,
0.16467323899269104,
0.09347937256097794,
0.1269809901714325,
-0.11747140437364578,
0.2820117175579071,
0.3259006440639496,
-0.0005844989791512489,
-0.05843723565340042,
-0.08932635933160782,
0.03309009224176407,
-0.08139177411794662,
0.16326531767845154,
0.12141101807355881,
0.1739644706249237,
0.06176479905843735,
-0.4309346079826355,
-0.12424077838659286,
-0.20832158625125885,
0.14269258081912994,
-0.12683850526809692,
-0.5166333913803101,
-0.06742709875106812,
-0.08390922099351883,
0.06903015822172165,
-0.08924680203199387,
-0.3010077476501465,
0.11446747928857803,
-0.022935112938284874,
0.21466878056526184,
-0.06969944387674332,
0.014183173887431622,
-0.05495689436793327,
0.11815536022186279,
-0.4216558337211609,
-0.016975730657577515,
0.3122232258319855,
0.09955611824989319,
0.09712179005146027,
0.1739337146282196,
-0.07775558531284332,
0.12298354506492615,
0.42270323634147644,
0.02999717742204666,
0.02881624549627304,
-0.03779754415154457,
0.14484578371047974,
-0.32560503482818604,
-0.00640280544757843,
0.18319693207740784,
-0.36248600482940674,
-0.15413984656333923,
-0.09662603586912155,
-0.16510260105133057,
0.12379004806280136,
0.05943754315376282,
-0.225196972489357,
-0.278982937335968,
-0.37818217277526855,
0.7292916178703308,
-0.0695025846362114,
-0.0614316388964653,
-0.17215341329574585,
0.29769450426101685,
-0.25143396854400635,
-0.07137693464756012,
0.18124361336231232,
0.07104992866516113,
-0.032820604741573334,
-0.38990500569343567,
-0.10039550811052322,
-0.10813398659229279,
-0.07206135243177414,
0.2687499225139618,
-0.20015178620815277,
0.21656769514083862,
0.04004433751106262,
0.16750960052013397,
0.25886863470077515,
-0.40507903695106506,
-0.10159724950790405,
0.28701913356781006,
-0.037553705275058746,
0.3858807384967804,
0.0768330916762352,
0.24547545611858368,
0.08919303864240646,
-0.17639228701591492,
0.2526644170284271,
1.007195234298706,
-0.3976956903934479,
-0.06931684166193008,
-0.10972339659929276,
-0.3863373100757599,
0.5040086507797241,
0.3668290972709656,
0.10830037295818329,
-0.23684129118919373,
-0.1491307020187378,
-0.05921328812837601,
0.06534458696842194,
0.04500487446784973,
0.10629874467849731,
-0.08196783810853958,
-0.34277451038360596,
0.0306718572974205,
-0.21699601411819458,
-0.20223864912986755,
-0.36724191904067993,
-0.0022578760981559753,
-0.0650901198387146,
0.3331246078014374,
0.3727763295173645,
-0.1935800313949585,
0.18135881423950195,
-0.2651146948337555,
-0.07853227853775024,
-0.2893359065055847,
0.13996614515781403,
-0.07206805050373077,
0.05796957388520241,
-0.2934381663799286,
-0.04770263284444809,
0.3240184485912323,
0.06630030274391174,
-0.09036258608102798,
-0.4725525379180908,
0.31648772954940796,
-0.06607367843389511,
0.041039589792490005,
-0.06410311907529831,
0.6213017702102661,
-0.1682785153388977,
-0.1320490837097168,
0.2150786817073822,
0.22514674067497253,
-0.3285653293132782,
0.2118608057498932,
0.3367438316345215,
0.24053168296813965,
0.17107175290584564,
-0.054370369762182236,
0.10397013276815414,
0.019159464165568352,
-0.012394202873110771,
-0.2296966016292572,
-0.10859379917383194,
0.5694274306297302,
-0.06802934408187866,
0.4326314330101013,
-0.02600593864917755,
0.04270171374082565,
-0.18314510583877563,
-0.11107334494590759,
-0.24281013011932373,
0.38110747933387756,
0.2990497648715973,
-0.21203340590000153,
0.35235998034477234,
-0.0513424351811409,
-0.3553396761417389,
0.13639584183692932,
0.13285274803638458,
0.0007288865745067596,
0.0813232958316803,
0.018113721162080765,
-0.06393145769834518,
-0.24718385934829712,
-0.097596175968647,
0.41166672110557556,
0.5995680689811707,
0.2978718876838684,
0.14136414229869843,
0.07985891401767731,
-0.2595907747745514,
-0.07501399517059326,
0.03891145437955856,
0.19106222689151764,
-0.07945381850004196,
0.15421119332313538,
0.010218745097517967,
0.057113002985715866,
-0.015598870813846588,
-0.09665244817733765,
0.12611661851406097,
-0.2244982272386551,
-0.02574707567691803,
0.04047059267759323,
-0.15040066838264465,
-0.5861160159111023,
-0.23188872635364532,
0.005161036271601915,
-0.31230658292770386,
-0.264523983001709,
0.1403566598892212,
0.03932912275195122,
-0.17840608954429626,
0.15653905272483826,
0.18521946668624878,
0.6711623072624207,
-0.4588552415370941,
-0.2282126098871231,
-0.05708080902695656,
-0.2689540684223175,
-0.11032205075025558,
0.12571704387664795,
0.42610594630241394,
0.27763330936431885,
0.5188313722610474,
0.30895715951919556,
-0.03489592671394348,
0.06895482540130615,
-0.3962318003177643,
0.05782635509967804,
-0.2660856246948242,
0.3105848729610443,
0.11344976723194122,
-0.22008086740970612,
0.17031775414943695,
-0.37428954243659973,
0.0022700424306094646,
-0.10265406221151352,
-0.03408002853393555,
-0.07405854016542435,
-0.0439092256128788,
0.08226968348026276,
-0.2027607560157776,
-0.19468384981155396,
-0.6382986903190613,
-0.47390538454055786,
0.3052135407924652,
-0.21334078907966614,
0.06977495551109314,
0.019458502531051636,
-0.25893715023994446,
0.17852020263671875,
-0.13915321230888367,
-0.013687675818800926,
-0.19458447396755219,
-0.12896260619163513,
0.01676156371831894,
-0.3375963270664215,
-0.1641012728214264,
-0.40518635511398315,
-0.20086050033569336,
0.22619260847568512,
-0.09001278877258301,
-0.06369993835687637,
-0.2524302005767822,
0.07718165218830109,
-0.12796750664710999,
0.11129318177700043,
0.2199832648038864,
0.1511763036251068,
-0.2682066857814789,
0.09364662319421768,
-0.029154960066080093,
-0.20805367827415466,
0.25715190172195435,
0.29497888684272766,
0.37840813398361206,
0.1561039388179779,
0.038204602897167206,
0.13332581520080566,
0.7063828110694885,
0.244694322347641,
0.031950805336236954,
0.1457706242799759,
0.30789634585380554,
0.017253555357456207,
0.1577180027961731,
-0.22609084844589233,
0.19193778932094574,
-0.1703614592552185,
0.44894129037857056,
0.10616723448038101,
0.19418981671333313,
-0.20405080914497375,
-0.2649410665035248,
0.05006055906414986,
-0.22742325067520142,
-0.23034411668777466,
0.26681944727897644,
-0.18870264291763306,
0.01172114908695221,
-0.0904022604227066,
-0.36917439103126526,
-0.24698743224143982,
-0.022600457072257996,
0.01634928770363331,
0.2658746540546417,
-0.023195773363113403,
0.12559154629707336,
-0.4113297164440155,
-0.03634204342961311,
-0.43079227209091187,
0.1822599619626999,
0.07882989197969437,
0.26000621914863586,
-0.06049288064241409,
-0.07115326076745987,
-0.08950991928577423,
0.10068007558584213,
0.5856121182441711,
-0.5367428660392761,
-0.17423446476459503,
0.11988365650177002,
0.07640215754508972,
-0.14059610664844513,
-0.06939823180437088,
-0.27343234419822693,
-0.044390156865119934,
0.45053955912590027,
0.3297434449195862,
-0.35634875297546387,
-0.2867952883243561,
0.29957589507102966,
-0.17227555811405182,
-0.09658411145210266,
-0.20668786764144897,
-0.15361671149730682,
-0.1994931697845459,
-0.13871708512306213,
0.05471811443567276,
0.18321537971496582,
0.15969343483448029,
-0.10423214733600616,
0.12230968475341797,
-0.11102566123008728,
0.2156314253807068,
0.19780366122722626,
0.009142642840743065,
-0.0450814850628376,
0.21428577601909637,
0.17898498475551605,
0.032369524240493774,
-0.14142334461212158,
-0.34136611223220825,
0.1296176016330719,
-0.06286951899528503,
0.129246324300766,
0.23772463202476501,
-0.015323157422244549,
0.6900310516357422,
0.042731717228889465,
0.3528766334056854,
0.31852808594703674,
-0.10639488697052002,
0.009463511407375336,
-0.3053719699382782,
0.130976140499115,
0.16529572010040283,
0.24443557858467102,
-0.11793570220470428,
-0.22836287319660187,
0.5872114896774292,
0.3297061622142792,
-0.08609949797391891,
0.3757953941822052,
-0.4737694263458252,
-0.3104903995990753,
0.32061368227005005,
0.04829271882772446,
0.7352595925331116,
-0.020149655640125275,
0.2903289496898651,
0.06005868315696716,
-0.380578875541687,
0.6396002173423767,
-0.3495901823043823,
0.1265997290611267,
-0.1399349421262741,
-0.20601844787597656,
0.00896688736975193,
-0.08151331543922424,
-0.06173834949731827,
0.2745792865753174,
-0.3608980178833008,
0.3065803349018097,
0.37564271688461304,
-0.22479894757270813,
-0.026938384398818016,
0.5579148530960083,
-0.02848581038415432,
-0.40201908349990845,
-0.07268825173377991,
0.10170149803161621,
-0.2750025987625122,
0.06954959034919739,
-0.16664573550224304,
-0.23241929709911346,
0.2085062861442566,
0.135392963886261,
-0.2649180293083191,
0.10901264101266861,
-0.021995829418301582,
0.15653371810913086,
0.2781093120574951,
0.021803833544254303,
0.27406981587409973,
-0.2461930215358734,
-0.08067634701728821,
-0.10604271292686462,
-0.08823463320732117,
0.13408753275871277,
-0.22273996472358704,
0.059132736176252365,
0.07656439393758774,
-0.16619165241718292,
0.529438853263855,
-0.029330454766750336,
-0.10595725476741791,
-0.20204520225524902,
0.23767605423927307,
-0.428960919380188,
-0.16126343607902527,
0.10507818311452866,
0.19494932889938354,
0.12262531369924545,
-0.35108932852745056,
0.5494362115859985,
0.09299609065055847,
-0.030742866918444633,
0.05949225276708603,
0.160847470164299,
-0.285043329000473,
0.46693888306617737,
-0.20441322028636932,
0.014505095779895782,
0.06675855070352554,
-0.03496868163347244,
-0.0981704369187355,
-0.3632012903690338,
-0.03582313656806946,
0.2880770266056061,
0.14274710416793823,
-0.045032914727926254,
0.008256874978542328,
0.17375093698501587,
-0.06492220610380173,
-0.000905974768102169,
-0.10859966278076172,
-0.367808997631073,
0.13817241787910461,
0.15505200624465942,
0.28181618452072144,
0.20770156383514404,
-0.1084919422864914,
-0.2485351711511612,
-0.22846619784832,
0.45401978492736816,
0.08564331382513046,
0.24932020902633667,
-0.13096801936626434,
0.36532971262931824,
0.40376007556915283,
0.555581271648407,
-0.28828108310699463,
0.047473788261413574,
0.030073771253228188,
0.09261932969093323,
0.48831918835639954,
-0.24070215225219727,
0.0004641436389647424,
0.271899551153183,
-0.1266116350889206,
0.06990136206150055,
-0.3354588449001312,
-0.18014976382255554,
-0.2789696156978607,
0.1032845601439476,
0.1215905100107193,
0.004378753714263439,
0.01943439617753029,
-0.025179700925946236,
-0.09327095746994019,
-0.07621203362941742,
-0.032401952892541885,
-0.42004576325416565,
-0.05962035059928894,
0.13473327457904816,
-0.07899188995361328,
0.04574663192033768,
-0.004300221800804138,
0.21682439744472504,
-0.0051980093121528625,
-0.04506361484527588,
0.27724528312683105,
0.08747966587543488,
0.14421889185905457,
-0.17655183374881744,
-0.142299085855484,
0.006133183836936951,
0.3090972304344177,
0.10410726070404053,
-0.028175629675388336,
0.1752343475818634,
-0.2041565477848053,
-0.07347287237644196,
0.26419705152511597,
0.19137436151504517,
0.02827773615717888,
-0.06573785841464996,
0.12197957932949066,
0.15415149927139282,
-0.13383066654205322,
0.03742099180817604,
0.24652691185474396,
0.052805643528699875,
0.12569384276866913,
0.13203656673431396,
0.15263524651527405,
0.4616323709487915,
-0.22779320180416107,
-0.009581963531672955,
0.13401474058628082,
-0.3001980781555176,
0.16639268398284912,
-0.1424228399991989,
-0.0036706216633319855,
-0.018843088299036026,
0.14484070241451263,
-0.030460692942142487,
0.17718975245952606,
-0.3630979657173157,
0.29315540194511414,
0.3141861855983734,
-0.01202450692653656,
0.04972722753882408,
0.21571552753448486,
0.011386286467313766,
-0.1301044374704361,
0.30930817127227783,
0.09537190198898315,
0.33699968457221985,
0.003113105893135071,
0.8959373831748962,
-0.3085148334503174,
-0.4987756013870239,
0.08208086341619492,
0.4228001832962036,
0.03482485190033913,
-0.19934433698654175,
0.08230765163898468,
0.1272721290588379,
-0.36981821060180664,
0.07597455382347107,
0.07843572646379471,
-0.18659235537052155,
0.6474287509918213,
-0.11679467558860779,
0.16359634697437286,
-0.1702311635017395,
-0.20496293902397156,
0.3429817855358124,
0.15966227650642395,
-0.1373148262500763,
0.027703264728188515,
0.11107563227415085,
-0.06848166882991791,
-0.162620410323143,
0.5162652134895325,
0.1743650883436203,
0.01610345020890236,
-0.44874659180641174,
0.041226696223020554,
0.0500359982252121,
0.15217286348342896,
-0.08710524439811707,
0.1192086935043335,
0.4416902959346771,
-0.16612105071544647,
0.24096046388149261,
0.038404934108257294,
-0.10613935440778732,
-0.15496879816055298,
0.014972109347581863,
-0.3957519233226776,
-0.4279155433177948,
0.4407232403755188,
0.12134898453950882,
-0.15100565552711487,
0.018220771104097366,
0.25174224376678467,
-0.6123269200325012,
-0.22717365622520447,
0.3545632064342499,
-0.1733732670545578,
-0.0767514556646347,
-0.22562576830387115,
0.08382952958345413,
0.03794964775443077,
0.6115517616271973,
0.21737883985042572,
0.35958364605903625,
-0.38429316878318787,
-0.1715811789035797,
-0.5617932081222534,
-0.18688622117042542,
0.14032000303268433,
-0.10462857782840729,
-0.24724486470222473,
0.16251887381076813,
-0.07911864668130875,
0.296741247177124,
-0.22634278237819672,
0.12328320741653442,
0.22285419702529907,
-0.024598680436611176,
-0.4108704924583435,
0.12129530310630798,
0.12449541687965393,
0.021148012951016426,
0.31346920132637024,
-0.08089778572320938,
-0.21032868325710297,
0.07324421405792236,
-0.07079584896564484,
-0.03564128652215004,
-0.08734466880559921,
0.26318782567977905,
0.1474705934524536,
0.1126747578382492,
0.0629216656088829,
0.5086536407470703,
-0.0262728463858366,
-0.16295559704303741,
0.02011765167117119,
-0.04937830939888954,
-0.38858604431152344,
-0.1232491210103035,
-0.08058828115463257,
0.21543635427951813,
-0.356221467256546,
0.2585195004940033,
0.004246872384101152,
-0.15498501062393188,
0.14422056078910828,
0.03260624781250954,
-0.2562313973903656,
-0.058259010314941406,
-0.01238970085978508,
0.21576139330863953,
0.21925483644008636,
0.7426397800445557,
0.0279543437063694,
0.08706794679164886,
-0.039152711629867554,
-0.009825295768678188,
0.0879296138882637,
-0.040988899767398834,
-0.22142860293388367,
-0.16324160993099213,
0.010918691754341125,
0.015441585332155228,
0.09817143529653549,
-0.664664626121521,
-0.36807185411453247,
0.04237039387226105,
-0.00760621577501297,
0.09818348288536072,
0.7144815325737,
0.08214789628982544,
-0.14683596789836884,
-0.14546498656272888,
-0.2757914364337921,
0.034837059676647186,
-0.245181605219841,
0.1932796835899353,
-0.39100319147109985
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | I guess we're looking at the end user writing something like:
``` python
ds = nlp.load_dataset('multitask-t5',datasets=["squad","cnn_dm",...], k=1000, t=2.0)
```
Using the t5 method of combining here (or this could be a function passed in as an arg)
Passing kwargs to each 'sub-dataset' might become tricky. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 45 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
I guess we're looking at the end user writing something like:
``` python
ds = nlp.load_dataset('multitask-t5',datasets=["squad","cnn_dm",...], k=1000, t=2.0)
```
Using the t5 method of combining here (or this could be a function passed in as an arg)
Passing kwargs to each 'sub-dataset' might become tricky. | [
-0.029288088902831078,
-0.3940451741218567,
-0.061029281467199326,
-0.025661781430244446,
-0.2608686685562134,
0.08258078247308731,
0.18105274438858032,
0.04695507138967514,
0.2868426442146301,
-0.1594534069299698,
-0.23304535448551178,
0.3090498447418213,
-0.20747075974941254,
0.38534146547317505,
0.37004518508911133,
-0.44683244824409485,
-0.007145114243030548,
-0.20719191431999207,
-0.2622194290161133,
0.3925706148147583,
0.03699757903814316,
0.11199010163545609,
-0.14147131145000458,
0.10980463773012161,
-0.30104702711105347,
-0.13675542175769806,
-0.3321911692619324,
0.10305800288915634,
0.11648961901664734,
0.01812893897294998,
0.21229058504104614,
0.3617035448551178,
-0.04755072668194771,
0.1438959836959839,
-0.00011497208470245823,
-0.044561855494976044,
0.14054232835769653,
-0.07454654574394226,
0.12798750400543213,
-0.038532182574272156,
0.1727735996246338,
-0.38791531324386597,
0.06748510897159576,
-0.13466739654541016,
0.21631953120231628,
0.15920688211917877,
0.1809328943490982,
0.06926152110099792,
0.40569382905960083,
-0.32851293683052063,
0.08759269118309021,
0.28492650389671326,
-0.19006860256195068,
0.34371376037597656,
-0.10634823888540268,
-0.1040673702955246,
0.03765280544757843,
0.2589143216609955,
0.586479902267456,
-0.5919791460037231,
0.053165215998888016,
0.08587002754211426,
0.012978112325072289,
-0.03543013706803322,
0.15835490822792053,
-0.028579317033290863,
-0.3110813796520233,
-0.22444447875022888,
-0.41868290305137634,
0.1887262761592865,
-0.10443753749132156,
-0.15518945455551147,
-0.2215287685394287,
-0.5562809109687805,
-0.017073914408683777,
-0.0037985313683748245,
-0.3029254674911499,
-0.002131476067006588,
-0.17310236394405365,
-0.03949776664376259,
-0.14767667651176453,
-0.10621414333581924,
-0.05107507482171059,
0.15497082471847534,
0.3348459005355835,
0.5709912180900574,
0.1295989602804184,
0.17109742760658264,
0.3198666572570801,
0.05387607216835022,
-0.13317297399044037,
-0.2922164499759674,
0.30810126662254333,
0.1642889529466629,
-0.36470866203308105,
-0.3597911298274994,
0.19177573919296265,
-0.25898075103759766,
0.23242563009262085,
0.09343147277832031,
0.12703199684619904,
0.08136390149593353,
-0.1447870135307312,
0.26923462748527527,
0.33163169026374817,
0.036866866052150726,
-0.10527094453573227,
-0.12733322381973267,
0.028762737289071083,
-0.15994568169116974,
0.23521608114242554,
0.096702441573143,
0.18593524396419525,
-0.022179249674081802,
-0.39544251561164856,
-0.16337111592292786,
-0.13463500142097473,
0.14888417720794678,
-0.19198034703731537,
-0.5355586409568787,
-0.16265323758125305,
-0.13995644450187683,
0.04749830812215805,
-0.13046738505363464,
-0.31422993540763855,
0.07659865915775299,
-0.030082136392593384,
0.1895587146282196,
-0.14268620312213898,
0.12083224207162857,
-0.052640534937381744,
0.07124754786491394,
-0.44809192419052124,
-0.046076878905296326,
0.2776446044445038,
0.10952538251876831,
0.08483003824949265,
0.1338437795639038,
0.014841295778751373,
0.12547995150089264,
0.4019385874271393,
0.03929182514548302,
-0.019937366247177124,
-0.03314119204878807,
0.16819153726100922,
-0.3317154347896576,
-0.006262622773647308,
0.17574232816696167,
-0.3530604839324951,
-0.1490301489830017,
-0.15961137413978577,
-0.1868329644203186,
0.12111593037843704,
0.024497399106621742,
-0.22084029018878937,
-0.320146381855011,
-0.4782353341579437,
0.6768113970756531,
-0.02763400226831436,
-0.06473112851381302,
-0.16472402215003967,
0.27578598260879517,
-0.2691701650619507,
-0.12027681618928909,
0.17447832226753235,
0.04582887887954712,
0.0011192001402378082,
-0.3560561239719391,
-0.06673183292150497,
-0.07920421659946442,
-0.07760482281446457,
0.25847122073173523,
-0.1712941974401474,
0.2623891234397888,
0.09088423103094101,
0.1857634335756302,
0.34088096022605896,
-0.4731498658657074,
-0.022683417424559593,
0.2970294952392578,
-0.05563241243362427,
0.41089126467704773,
0.07046730816364288,
0.2279609888792038,
-0.08120601624250412,
-0.2089109718799591,
0.2719021439552307,
1.0307587385177612,
-0.3764412999153137,
-0.02222232148051262,
-0.09570206701755524,
-0.3904014229774475,
0.5535184741020203,
0.34943294525146484,
0.07714053988456726,
-0.3079705238342285,
-0.1021806076169014,
-0.009633601643145084,
0.06673574447631836,
0.08410999178886414,
0.07473351806402206,
-0.08781086653470993,
-0.3393521010875702,
0.11391237378120422,
-0.21026675403118134,
-0.1518992781639099,
-0.3530142307281494,
0.033923424780368805,
0.024167057126760483,
0.31401926279067993,
0.25735369324684143,
-0.1301783323287964,
0.2086988389492035,
-0.28740155696868896,
-0.14865362644195557,
-0.2948305606842041,
0.10739141702651978,
-0.07125721871852875,
0.00028781965374946594,
-0.2379792034626007,
-0.03177569806575775,
0.3077721893787384,
0.13992391526699066,
-0.13622434437274933,
-0.4772080183029175,
0.29331836104393005,
-0.06322217732667923,
0.05785415694117546,
-0.056329090148210526,
0.6482879519462585,
-0.16215437650680542,
-0.06727927178144455,
0.19220829010009766,
0.32548788189888,
-0.3306891620159149,
0.2363167107105255,
0.3137441873550415,
0.3130967319011688,
0.16561448574066162,
0.006151299923658371,
0.1179901510477066,
0.011639727279543877,
-0.001240383367985487,
-0.21448662877082825,
-0.09475650638341904,
0.5063755512237549,
-0.19477367401123047,
0.4248299300670624,
-0.023951157927513123,
-0.002447165548801422,
-0.20531035959720612,
-0.015217259526252747,
-0.17521768808364868,
0.41539132595062256,
0.29060012102127075,
-0.23537112772464752,
0.29709145426750183,
-0.16056767106056213,
-0.37394168972969055,
0.17211991548538208,
0.17921608686447144,
0.018867194652557373,
0.03440475091338158,
-0.04453393071889877,
0.0077328160405159,
-0.2754381597042084,
-0.10600511729717255,
0.31868237257003784,
0.657733142375946,
0.2544577419757843,
0.1376100331544876,
0.06570452451705933,
-0.2021634876728058,
-0.05955902859568596,
0.048522621393203735,
0.21359135210514069,
-0.04889417812228203,
0.15909138321876526,
0.036246854811906815,
0.08083906024694443,
0.062116049230098724,
-0.16772831976413727,
0.1392093449831009,
-0.2044977992773056,
-0.11621741950511932,
0.054170407354831696,
-0.18401747941970825,
-0.6338428258895874,
-0.18930378556251526,
-0.009177061729133129,
-0.33165132999420166,
-0.2957558333873749,
0.13720130920410156,
0.05582486838102341,
-0.11464425921440125,
0.13877373933792114,
0.1970454901456833,
0.5815644264221191,
-0.43081381916999817,
-0.2768559753894806,
-0.03663846105337143,
-0.31371769309043884,
-0.10173463076353073,
0.1042480319738388,
0.4355733096599579,
0.2959771454334259,
0.5036947131156921,
0.2990516424179077,
-0.06889364868402481,
0.0986972227692604,
-0.4021720886230469,
0.06541772186756134,
-0.35339850187301636,
0.2585299611091614,
0.13582871854305267,
-0.2217332273721695,
0.14582960307598114,
-0.3897812068462372,
-0.05303334444761276,
-0.025669991970062256,
-0.07492633908987045,
-0.05133765935897827,
0.054068006575107574,
0.06931324303150177,
-0.19855494797229767,
-0.19036796689033508,
-0.6149934530258179,
-0.44191789627075195,
0.3062751293182373,
-0.22799837589263916,
0.08272532373666763,
0.06216789409518242,
-0.2821543216705322,
0.23458461463451385,
-0.08945947885513306,
0.025363514199852943,
-0.1702771782875061,
-0.05233986675739288,
0.010179545730352402,
-0.3848069906234741,
-0.1447841376066208,
-0.3393521010875702,
-0.039895057678222656,
0.22139781713485718,
-0.06605792045593262,
-0.029407277703285217,
-0.275092214345932,
0.08280210942029953,
-0.08778975158929825,
0.07219231128692627,
0.26224303245544434,
0.16565276682376862,
-0.2060343325138092,
0.13177178800106049,
-0.08111491054296494,
-0.27193501591682434,
0.21034687757492065,
0.33023664355278015,
0.37373843789100647,
0.18449366092681885,
0.03631783649325371,
0.18707406520843506,
0.7639586329460144,
0.24814295768737793,
0.0630788654088974,
0.14840328693389893,
0.2611876130104065,
-0.012645263224840164,
0.16147339344024658,
-0.1882694661617279,
0.1840166300535202,
-0.1733154058456421,
0.5277929902076721,
0.08122701942920685,
0.1695801317691803,
-0.14921659231185913,
-0.3321092426776886,
0.01802697777748108,
-0.3142361044883728,
-0.18452826142311096,
0.19016119837760925,
-0.2771725356578827,
0.01715637743473053,
-0.0910215675830841,
-0.4362218976020813,
-0.28573817014694214,
-0.037379682064056396,
-0.017000479623675346,
0.3356783390045166,
-0.0067284852266311646,
0.17077067494392395,
-0.33541008830070496,
-0.04341872036457062,
-0.42174914479255676,
0.1442059576511383,
0.058303818106651306,
0.23728248476982117,
-0.08073723316192627,
-0.07213886082172394,
-0.10103416442871094,
0.11182694882154465,
0.5621090531349182,
-0.5473767518997192,
-0.10901273787021637,
0.0950554609298706,
0.07976454496383667,
-0.12696273624897003,
-0.11654843389987946,
-0.2918790578842163,
0.02043408341705799,
0.42763039469718933,
0.37687990069389343,
-0.37812376022338867,
-0.29430466890335083,
0.2408275604248047,
-0.253957599401474,
-0.0721559077501297,
-0.1933041512966156,
-0.2405911237001419,
-0.2112833559513092,
-0.12438013404607773,
-0.005925334990024567,
0.2536102533340454,
0.23441138863563538,
-0.12050190567970276,
0.18363387882709503,
-0.08123081177473068,
0.2604242265224457,
0.24369797110557556,
0.010381605476140976,
-0.11040753871202469,
0.2441927194595337,
0.17174628376960754,
0.038996510207653046,
-0.12102335691452026,
-0.35914620757102966,
0.09985445439815521,
-0.021673571318387985,
0.0665009617805481,
0.2553040385246277,
-0.0018159598112106323,
0.6958091259002686,
0.046072423458099365,
0.3278181254863739,
0.27770739793777466,
-0.14805655181407928,
-0.00294533371925354,
-0.22390860319137573,
0.18585385382175446,
0.23404698073863983,
0.24906158447265625,
-0.14151260256767273,
-0.23254254460334778,
0.5836414098739624,
0.30703142285346985,
-0.08686482906341553,
0.43852701783180237,
-0.49418801069259644,
-0.33374685049057007,
0.21709124743938446,
0.02576620876789093,
0.7134889960289001,
-0.022532179951667786,
0.3297560513019562,
0.11808131635189056,
-0.41327381134033203,
0.5890750885009766,
-0.33622241020202637,
0.12408437579870224,
-0.054837848991155624,
-0.17275115847587585,
-0.011037005111575127,
-0.07591135799884796,
-0.10295803099870682,
0.2057555615901947,
-0.3488755226135254,
0.3369857966899872,
0.403509259223938,
-0.23023736476898193,
-0.047393523156642914,
0.5434771776199341,
-0.01447100006043911,
-0.3405782878398895,
-0.07095815986394882,
0.051304690539836884,
-0.2821178436279297,
0.06948010623455048,
-0.2126551866531372,
-0.25520122051239014,
0.21050375699996948,
0.15928402543067932,
-0.27442002296447754,
0.06679576635360718,
0.008197695016860962,
0.2008352279663086,
0.22477677464485168,
0.0355929359793663,
0.26400211453437805,
-0.17304955422878265,
-0.1037311851978302,
-0.1767415553331375,
-0.06488702446222305,
0.10578872263431549,
-0.2313130795955658,
0.03633556514978409,
0.0953330397605896,
-0.1507091224193573,
0.4938497543334961,
-0.07441737502813339,
-0.1055268719792366,
-0.2258998453617096,
0.26180723309516907,
-0.44568145275115967,
-0.2548680305480957,
0.13174155354499817,
0.16105252504348755,
0.18171535432338715,
-0.32188621163368225,
0.594508171081543,
0.08666715025901794,
0.05346443131566048,
0.018005715683102608,
0.17048421502113342,
-0.23972740769386292,
0.46453961730003357,
-0.32235217094421387,
0.0002985820174217224,
0.09918470680713654,
0.00014899671077728271,
-0.1518298089504242,
-0.4189448356628418,
-0.053586021065711975,
0.2748265862464905,
0.12449447810649872,
0.055341511964797974,
-0.01699470728635788,
0.11429896205663681,
-0.03799336776137352,
-0.0555114783346653,
-0.11189214885234833,
-0.2893211245536804,
0.1342899203300476,
0.2440171241760254,
0.1765127182006836,
0.1978479027748108,
-0.060454923659563065,
-0.2944514751434326,
-0.13006703555583954,
0.49924999475479126,
-0.016898449510335922,
0.2320835292339325,
-0.15137694776058197,
0.37086302042007446,
0.4106280207633972,
0.49037304520606995,
-0.24309992790222168,
0.057044617831707,
0.09853257983922958,
0.10004319995641708,
0.4676119089126587,
-0.22680512070655823,
0.047387488186359406,
0.2821199893951416,
-0.14611601829528809,
0.031245801597833633,
-0.3519592583179474,
-0.1358805149793625,
-0.24969330430030823,
0.12456847727298737,
0.12881559133529663,
-0.0284756850451231,
0.028416700661182404,
-0.11128637194633484,
-0.10461029410362244,
-0.057755425572395325,
0.04444064572453499,
-0.36330124735832214,
-0.09757275879383087,
0.1614966243505478,
-0.09412811696529388,
0.08671195060014725,
0.057051338255405426,
0.20702838897705078,
0.06947362422943115,
-0.07310886681079865,
0.33872056007385254,
0.12007106840610504,
0.08686429262161255,
-0.16815894842147827,
-0.14083035290241241,
0.01643984392285347,
0.29556000232696533,
0.180315762758255,
-0.06893271952867508,
0.1422436386346817,
-0.20938445627689362,
-0.19972947239875793,
0.207700714468956,
0.20243296027183533,
0.03528792783617973,
-0.13023819029331207,
0.10691758990287781,
0.09648489952087402,
-0.06001542881131172,
-0.01290728710591793,
0.23015180230140686,
0.08779247850179672,
0.07244819402694702,
0.11680930107831955,
0.11368687450885773,
0.4800723195075989,
-0.28227096796035767,
0.032748743891716,
0.09447218477725983,
-0.3594552278518677,
0.11638280749320984,
-0.08243821561336517,
-0.08555788546800613,
-0.014490868896245956,
0.12477198243141174,
0.00008924305438995361,
0.11933603882789612,
-0.33420151472091675,
0.3240496516227722,
0.26727110147476196,
0.015397857874631882,
0.01500190794467926,
0.1387517899274826,
0.04229075089097023,
-0.17318110167980194,
0.2679608464241028,
0.03501954674720764,
0.3751722574234009,
0.06041339784860611,
0.8366438746452332,
-0.2134696990251541,
-0.39151203632354736,
0.15799500048160553,
0.42227044701576233,
0.08762919157743454,
-0.21886204183101654,
0.13186512887477875,
0.09811235219240189,
-0.37548473477363586,
0.06979610025882721,
0.0569925457239151,
-0.1820814460515976,
0.6210576295852661,
-0.08598870038986206,
0.16826140880584717,
-0.11792021989822388,
-0.18515899777412415,
0.3580675721168518,
0.21875646710395813,
-0.0734490305185318,
-0.03959990292787552,
0.12822821736335754,
-0.061942100524902344,
-0.19880662858486176,
0.47432956099510193,
0.2133026421070099,
-0.0024094320833683014,
-0.48168647289276123,
0.03337985277175903,
0.10145311057567596,
0.17900331318378448,
0.0025961026549339294,
0.1369650661945343,
0.4460619390010834,
-0.15026038885116577,
0.20349398255348206,
-0.007044810801744461,
-0.03401816636323929,
-0.13445675373077393,
0.0641835480928421,
-0.4029550850391388,
-0.4237152338027954,
0.4620606303215027,
0.1102583110332489,
-0.14952698349952698,
0.11755184829235077,
0.37620967626571655,
-0.6295855045318604,
-0.26949018239974976,
0.33437567949295044,
-0.05823199078440666,
-0.08502033352851868,
-0.19609683752059937,
0.06549707800149918,
0.07512514293193817,
0.6126105189323425,
0.20807671546936035,
0.4082014858722687,
-0.3459770679473877,
-0.09671205282211304,
-0.5682133436203003,
-0.20369422435760498,
0.17174018919467926,
-0.15298008918762207,
-0.22418370842933655,
0.1183871328830719,
-0.06933384388685226,
0.27628377079963684,
-0.1890554279088974,
0.1030978187918663,
0.24528977274894714,
0.049819692969322205,
-0.4366210699081421,
0.08494247496128082,
0.19068224728107452,
0.0404028445482254,
0.2738911807537079,
-0.06394287198781967,
-0.22662179172039032,
0.04732493311166763,
-0.06836362183094025,
-0.09690745174884796,
-0.11419853568077087,
0.26815515756607056,
0.1839274764060974,
0.09595856070518494,
0.057073406875133514,
0.5114501714706421,
0.010969426482915878,
-0.15749332308769226,
0.0035766661167144775,
0.04371960833668709,
-0.36338210105895996,
-0.13569670915603638,
-0.09348143637180328,
0.13298873603343964,
-0.39160358905792236,
0.32264938950538635,
0.0057074506767094135,
-0.07805059105157852,
0.09187640249729156,
0.0003340801631566137,
-0.12278414517641068,
-0.11219880729913712,
0.04377824068069458,
0.2214047908782959,
0.18611274659633636,
0.7520402073860168,
-0.012685023248195648,
0.13772812485694885,
-0.09494926035404205,
-0.008783180266618729,
0.027268782258033752,
-0.06434722989797592,
-0.254292756319046,
-0.09406182914972305,
0.0674457997083664,
0.06809153407812119,
0.1432076394557953,
-0.6984319090843201,
-0.3541291356086731,
0.05046321079134941,
0.01615240052342415,
0.015999507158994675,
0.7800260186195374,
0.09473781287670135,
-0.13276270031929016,
-0.08945003151893616,
-0.36224567890167236,
0.0005289893597364426,
-0.22626979649066925,
0.16598626971244812,
-0.3741370439529419
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | From thinking upon @thomwolf 's suggestion, I've started experimenting:
```python
class MultitaskDataset(DatasetBuilder):
def __init__(self, *args, **kwargs):
super(MultitaskDataset, self).__init__(*args, **kwargs)
self._datasets = kwargs.get("datasets")
def _info(self):
return nlp.DatasetInfo(
description=_DESCRIPTION,
features=nlp.Features({
"source": nlp.Value("string"),
"target": nlp.Sequence(nlp.Value("string"))
})
)
def _get_common_splits(self):
'''Finds the common splits present in all self._datasets'''
min_set = None
for dataset in self._datasets:
if min_set != None:
min_set.intersection(set(dataset.keys()))
else:
min_set = set(dataset.keys())
return min_set
....
# Maybe this?:
squad = nlp.load_dataset("squad")
cnn_dm = nlp.load_dataset("cnn_dailymail","3.0.0")
multitask_dataset = nlp.load_dataset(
'multitask_dataset',
datasets=[squad,cnn_dailymail],
k=1000,
t=2.0
)
```
Does anyone know what methods of `MultitaskDataset` I would need to implement? Maybe `as_dataset` and `download_and_prepare`? Most of these should be just calling the methods of the sub-datasets.
I'm assuming DatasetBuilder is better than the more specific `GeneratorBasedBuilder`, `BeamBasedBuilder`, etc....
One of the other problems is that the dataset size is unknown till you construct it (as you can pick the sub-datasets). Am hoping not to need to make changes to `nlp.load_dataset` just for this class.
I'd appreciate it if anyone more familiar with nlp's internal workings could tell me if I'm on the right track! | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 177 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
From thinking upon @thomwolf 's suggestion, I've started experimenting:
```python
class MultitaskDataset(DatasetBuilder):
def __init__(self, *args, **kwargs):
super(MultitaskDataset, self).__init__(*args, **kwargs)
self._datasets = kwargs.get("datasets")
def _info(self):
return nlp.DatasetInfo(
description=_DESCRIPTION,
features=nlp.Features({
"source": nlp.Value("string"),
"target": nlp.Sequence(nlp.Value("string"))
})
)
def _get_common_splits(self):
'''Finds the common splits present in all self._datasets'''
min_set = None
for dataset in self._datasets:
if min_set != None:
min_set.intersection(set(dataset.keys()))
else:
min_set = set(dataset.keys())
return min_set
....
# Maybe this?:
squad = nlp.load_dataset("squad")
cnn_dm = nlp.load_dataset("cnn_dailymail","3.0.0")
multitask_dataset = nlp.load_dataset(
'multitask_dataset',
datasets=[squad,cnn_dailymail],
k=1000,
t=2.0
)
```
Does anyone know what methods of `MultitaskDataset` I would need to implement? Maybe `as_dataset` and `download_and_prepare`? Most of these should be just calling the methods of the sub-datasets.
I'm assuming DatasetBuilder is better than the more specific `GeneratorBasedBuilder`, `BeamBasedBuilder`, etc....
One of the other problems is that the dataset size is unknown till you construct it (as you can pick the sub-datasets). Am hoping not to need to make changes to `nlp.load_dataset` just for this class.
I'd appreciate it if anyone more familiar with nlp's internal workings could tell me if I'm on the right track! | [
-0.04102962464094162,
-0.3800145387649536,
-0.05613580346107483,
-0.05533301830291748,
-0.22696126997470856,
0.038144730031490326,
0.19116359949111938,
0.028541235253214836,
0.31403058767318726,
-0.16932375729084015,
-0.2113303542137146,
0.3226812183856964,
-0.21177791059017181,
0.3609279990196228,
0.41081103682518005,
-0.4081554114818573,
0.049611590802669525,
-0.23854923248291016,
-0.30185526609420776,
0.38168203830718994,
0.029433421790599823,
0.11054189503192902,
-0.18156084418296814,
0.11165952682495117,
-0.27534911036491394,
-0.14701829850673676,
-0.3376019597053528,
0.10576724261045456,
0.12588635087013245,
0.0001229001209139824,
0.2541155219078064,
0.4050154387950897,
-0.0645340085029602,
0.16401571035385132,
-0.00011387035192456096,
-0.028973150998353958,
0.23698236048221588,
-0.06454761326313019,
0.11490742862224579,
-0.07505476474761963,
0.20829960703849792,
-0.42716363072395325,
0.05915150046348572,
-0.16756829619407654,
0.1729607880115509,
0.15671946108341217,
0.1583680659532547,
0.04002629965543747,
0.39363449811935425,
-0.2916637063026428,
0.10325049608945847,
0.2875029742717743,
-0.15446846187114716,
0.27613866329193115,
-0.12511226534843445,
-0.047687649726867676,
0.036738425493240356,
0.2582833766937256,
0.5602096319198608,
-0.6138644218444824,
0.003775171935558319,
0.1158638596534729,
0.0011098384857177734,
0.004889128729701042,
0.15319645404815674,
-0.0207950621843338,
-0.35217273235321045,
-0.2176881730556488,
-0.403907835483551,
0.18628636002540588,
-0.1451551616191864,
-0.20172220468521118,
-0.23753756284713745,
-0.5448267459869385,
0.00467009749263525,
0.006173262372612953,
-0.26987841725349426,
-0.018358614295721054,
-0.20179776847362518,
-0.06324602663516998,
-0.12326838821172714,
-0.08969501405954361,
-0.03366662561893463,
0.15525320172309875,
0.31824880838394165,
0.5842540860176086,
0.09058930724859238,
0.16732612252235413,
0.36797162890434265,
0.04139312356710434,
-0.15085740387439728,
-0.2804940640926361,
0.3275359869003296,
0.14582251012325287,
-0.36985042691230774,
-0.303060919046402,
0.20416340231895447,
-0.23676475882530212,
0.22982433438301086,
0.10457167774438858,
0.09047483652830124,
0.11722014099359512,
-0.14798322319984436,
0.26190412044525146,
0.30457472801208496,
0.04612195864319801,
-0.09614870697259903,
-0.09544776380062103,
0.03467622399330139,
-0.08594397455453873,
0.19273574650287628,
0.1121780201792717,
0.1854979693889618,
-0.012385403737425804,
-0.3950411379337311,
-0.13390576839447021,
-0.12934401631355286,
0.16474467515945435,
-0.21528448164463043,
-0.4849030375480652,
-0.10857385396957397,
-0.11952342092990875,
0.11771436780691147,
-0.10458620637655258,
-0.3091358244419098,
0.09875422716140747,
-0.03895314037799835,
0.2612786889076233,
-0.1374974101781845,
0.13061656057834625,
-0.07104397565126419,
0.08409787714481354,
-0.4412364065647125,
-0.07710470259189606,
0.3059290945529938,
0.15183445811271667,
0.08070219308137894,
0.1679019182920456,
-0.0014318525791168213,
0.12360233068466187,
0.389382004737854,
0.015577927231788635,
0.0013970881700515747,
-0.0009414032101631165,
0.13964273035526276,
-0.3161430358886719,
0.020423350855708122,
0.1589083969593048,
-0.34745216369628906,
-0.19029992818832397,
-0.11934822052717209,
-0.16854071617126465,
0.14057381451129913,
0.03215441107749939,
-0.20059601962566376,
-0.23849985003471375,
-0.49818840622901917,
0.7015707492828369,
-0.05721471458673477,
-0.0934588611125946,
-0.175914466381073,
0.30375146865844727,
-0.24646390974521637,
-0.08007052540779114,
0.21196673810482025,
0.057640403509140015,
0.011351071298122406,
-0.3442132771015167,
-0.10541735589504242,
-0.0986817479133606,
-0.02154744416475296,
0.25007933378219604,
-0.16200295090675354,
0.27927154302597046,
0.05273354798555374,
0.20901422202587128,
0.279838889837265,
-0.48212292790412903,
-0.06264183670282364,
0.2596435844898224,
-0.044113803654909134,
0.42299899458885193,
0.05807698890566826,
0.19613584876060486,
-0.02601388469338417,
-0.1701488345861435,
0.29014694690704346,
0.9980716109275818,
-0.34383922815322876,
-0.019431522116065025,
-0.10914511233568192,
-0.359876424074173,
0.5201607346534729,
0.3251276910305023,
0.10994377732276917,
-0.2907424867153168,
-0.13588455319404602,
-0.015212766826152802,
0.12174706161022186,
0.07488220185041428,
0.08309371024370193,
-0.0717742070555687,
-0.3480933904647827,
0.06251135468482971,
-0.21467044949531555,
-0.16926828026771545,
-0.34028953313827515,
0.023376867175102234,
0.05374082177877426,
0.33713722229003906,
0.211589515209198,
-0.14518499374389648,
0.19584709405899048,
-0.255342960357666,
-0.14328446984291077,
-0.30226704478263855,
0.14626285433769226,
-0.06994940340518951,
0.013663891702890396,
-0.24087928235530853,
-0.031897496432065964,
0.3690546154975891,
0.11622273921966553,
-0.12677861750125885,
-0.4973999857902527,
0.3005133867263794,
-0.07422433793544769,
0.06661362200975418,
-0.03259079158306122,
0.6585509777069092,
-0.15063244104385376,
-0.0851476788520813,
0.1811935007572174,
0.28125569224357605,
-0.2942325174808502,
0.20129701495170593,
0.3036305606365204,
0.19760726392269135,
0.15173554420471191,
0.004687663167715073,
0.07329729199409485,
0.052242256700992584,
0.024796411395072937,
-0.23360514640808105,
-0.09858066588640213,
0.5100671052932739,
-0.1613478660583496,
0.452299028635025,
-0.028002260252833366,
0.025157766416668892,
-0.1460137516260147,
-0.02968289516866207,
-0.20386555790901184,
0.38019752502441406,
0.28941023349761963,
-0.18660050630569458,
0.3278832733631134,
-0.16236703097820282,
-0.3643941581249237,
0.15504823625087738,
0.13120117783546448,
0.012626104056835175,
0.054630741477012634,
-0.043492428958415985,
-0.013248145580291748,
-0.27911409735679626,
-0.10775341093540192,
0.3511252999305725,
0.6806016564369202,
0.23463593423366547,
0.19186411798000336,
0.06999503076076508,
-0.2855544984340668,
-0.07115587592124939,
0.0013609528541564941,
0.22168385982513428,
-0.04060807079076767,
0.16736525297164917,
0.06225525960326195,
0.042443666607141495,
0.02196458727121353,
-0.152826726436615,
0.1556808203458786,
-0.18520916998386383,
-0.093662790954113,
0.10740455240011215,
-0.22168302536010742,
-0.593887984752655,
-0.17749641835689545,
0.0022361506707966328,
-0.28781720995903015,
-0.3085006773471832,
0.10392729938030243,
0.05332016199827194,
-0.14587950706481934,
0.16206085681915283,
0.20494990050792694,
0.5456448197364807,
-0.42458266019821167,
-0.27564889192581177,
-0.04172290861606598,
-0.31425341963768005,
-0.11091042309999466,
0.10897095501422882,
0.45676755905151367,
0.33519771695137024,
0.48909059166908264,
0.3100678324699402,
-0.0816788449883461,
0.04969361424446106,
-0.40164679288864136,
0.047573596239089966,
-0.32548993825912476,
0.26705124974250793,
0.11735353618860245,
-0.2622724175453186,
0.16213956475257874,
-0.37220484018325806,
-0.0118264677003026,
-0.08734836429357529,
-0.08597197383642197,
-0.021902648732066154,
-0.019531672820448875,
0.05914955586194992,
-0.21000738441944122,
-0.15615111589431763,
-0.6618931293487549,
-0.45373156666755676,
0.3190036416053772,
-0.2383420616388321,
0.08222013711929321,
0.059315554797649384,
-0.295492947101593,
0.222370445728302,
-0.06498803198337555,
0.016361389309167862,
-0.1773642748594284,
-0.048845671117305756,
0.029317837208509445,
-0.3534867763519287,
-0.17807669937610626,
-0.37236499786376953,
-0.13820210099220276,
0.2802262604236603,
-0.06061965972185135,
-0.00712372362613678,
-0.25036323070526123,
0.09986145049333572,
-0.0790095180273056,
0.1057049036026001,
0.24656324088573456,
0.17851471900939941,
-0.2391587495803833,
0.13448840379714966,
-0.060159504413604736,
-0.2647288143634796,
0.24683836102485657,
0.28179123997688293,
0.3843090236186981,
0.18339258432388306,
0.05993513762950897,
0.1708054095506668,
0.6879076361656189,
0.22980087995529175,
0.06567364931106567,
0.1472759246826172,
0.25494474172592163,
0.019310712814331055,
0.16987480223178864,
-0.2620755732059479,
0.20821648836135864,
-0.21381089091300964,
0.4608769416809082,
0.045081254094839096,
0.1656011939048767,
-0.2366361767053604,
-0.29566115140914917,
0.02418256551027298,
-0.3138537108898163,
-0.2150166630744934,
0.19742123782634735,
-0.2264554798603058,
0.0024595558643341064,
-0.07362702488899231,
-0.379216730594635,
-0.2847122848033905,
-0.03315741568803787,
0.004512320272624493,
0.3330303430557251,
-0.0960419550538063,
0.11804568022489548,
-0.3570634126663208,
-0.0310059804469347,
-0.46974027156829834,
0.14145812392234802,
0.008326739072799683,
0.25842157006263733,
-0.05097510665655136,
-0.07873968780040741,
-0.08971892297267914,
0.07503249496221542,
0.6008839011192322,
-0.4771212637424469,
-0.12468117475509644,
0.15265104174613953,
0.11117656528949738,
-0.13729418814182281,
-0.1263008564710617,
-0.29125574231147766,
0.046896789222955704,
0.46849650144577026,
0.37232542037963867,
-0.3875475227832794,
-0.2634357810020447,
0.22910921275615692,
-0.21606238186359406,
-0.04498942941427231,
-0.1908903568983078,
-0.2358568012714386,
-0.2560034692287445,
-0.09917148947715759,
0.0442420095205307,
0.21777860820293427,
0.2320205718278885,
-0.12347625941038132,
0.21100057661533356,
-0.10897153615951538,
0.26126062870025635,
0.22021985054016113,
0.004205815494060516,
-0.027149219065904617,
0.20108652114868164,
0.17098407447338104,
0.03842533752322197,
-0.1398620754480362,
-0.3714185953140259,
0.13281747698783875,
0.004647500813007355,
0.07882440090179443,
0.24406200647354126,
-0.007657070644199848,
0.6334802508354187,
0.07391240447759628,
0.2964061498641968,
0.2896258234977722,
-0.14868685603141785,
0.017745528370141983,
-0.2544417679309845,
0.19163630902767181,
0.24283285439014435,
0.26264265179634094,
-0.14039891958236694,
-0.2564387619495392,
0.5900333523750305,
0.30693069100379944,
-0.09948912262916565,
0.4368514120578766,
-0.49968451261520386,
-0.3505488932132721,
0.2613230347633362,
0.022101111710071564,
0.6753665804862976,
0.005988597869873047,
0.31732290983200073,
0.16142034530639648,
-0.37519150972366333,
0.5796291828155518,
-0.3777523636817932,
0.16100859642028809,
-0.07037866860628128,
-0.1492103487253189,
0.004808923229575157,
-0.08049367368221283,
-0.03711894899606705,
0.22904330492019653,
-0.3471164405345917,
0.33152300119400024,
0.44647926092147827,
-0.20433306694030762,
-0.06859056651592255,
0.5156770944595337,
-0.023617537692189217,
-0.37427833676338196,
-0.12388628721237183,
0.07793339341878891,
-0.2607240080833435,
0.09877165406942368,
-0.15557417273521423,
-0.24808023869991302,
0.193296879529953,
0.14641070365905762,
-0.28790104389190674,
0.1049903854727745,
0.030854009091854095,
0.23830074071884155,
0.2569228708744049,
0.009897217154502869,
0.21698251366615295,
-0.194374218583107,
-0.054441049695014954,
-0.1598697453737259,
-0.06007956713438034,
0.12273116409778595,
-0.20815375447273254,
0.08337394893169403,
0.08152663707733154,
-0.2225058376789093,
0.5000624656677246,
-0.05308302864432335,
-0.1086621880531311,
-0.24004215002059937,
0.26080310344696045,
-0.4327811002731323,
-0.18399743735790253,
0.1675368994474411,
0.16328491270542145,
0.23204074800014496,
-0.3219020962715149,
0.6011402010917664,
0.11713387072086334,
-0.009043615311384201,
0.03524141013622284,
0.18379531800746918,
-0.2748798131942749,
0.5102388858795166,
-0.35661590099334717,
0.011908546090126038,
0.08584189414978027,
0.01222093403339386,
-0.14734867215156555,
-0.37615886330604553,
-0.03224923461675644,
0.29934805631637573,
0.08523876219987869,
0.031986914575099945,
-0.01090395450592041,
0.10516078025102615,
-0.0341632217168808,
-0.0448414646089077,
-0.09733837097883224,
-0.32608121633529663,
0.12282869964838028,
0.1837870478630066,
0.17996639013290405,
0.17217344045639038,
-0.08546741306781769,
-0.27731460332870483,
-0.18056967854499817,
0.4803909659385681,
0.023020224645733833,
0.20212793350219727,
-0.15253102779388428,
0.3534679412841797,
0.41968730092048645,
0.5000770688056946,
-0.2531452178955078,
0.055512458086013794,
0.07240822911262512,
0.07157933712005615,
0.4242958724498749,
-0.24605277180671692,
0.06022543087601662,
0.2450602799654007,
-0.12159861624240875,
0.04352039843797684,
-0.3518276512622833,
-0.14629203081130981,
-0.2637699544429779,
0.108505479991436,
0.10938438028097153,
0.0003897491842508316,
0.05136275663971901,
-0.09670047461986542,
-0.09724637866020203,
-0.06615409255027771,
-0.012980936095118523,
-0.3419173061847687,
-0.07169054448604584,
0.12081153690814972,
-0.06952276825904846,
0.04318970441818237,
0.07352231442928314,
0.18629994988441467,
0.039545293897390366,
-0.07555213570594788,
0.31191930174827576,
0.09127123653888702,
0.1235487088561058,
-0.16061893105506897,
-0.13676072657108307,
0.020297743380069733,
0.2227650284767151,
0.15596720576286316,
-0.04287651181221008,
0.11895954608917236,
-0.2020348459482193,
-0.1555565893650055,
0.2734251618385315,
0.22079382836818695,
0.02745632827281952,
-0.13336586952209473,
0.13120368123054504,
0.11210887134075165,
-0.11988216638565063,
-0.025684526190161705,
0.23964142799377441,
0.08068189024925232,
0.10649418830871582,
0.12201157957315445,
0.11496567726135254,
0.46063417196273804,
-0.2895886301994324,
0.04949895292520523,
0.11247304826974869,
-0.3702648878097534,
0.11843657493591309,
-0.1373874396085739,
-0.010501008480787277,
0.026158351451158524,
0.14512374997138977,
-0.004540286958217621,
0.11540011316537857,
-0.24399949610233307,
0.32384398579597473,
0.3000832796096802,
-0.010189592838287354,
0.03903508931398392,
0.1394422948360443,
0.021483201533555984,
-0.17022664844989777,
0.22123786807060242,
-0.012152723968029022,
0.3521032929420471,
0.0319325216114521,
0.8429731726646423,
-0.30105873942375183,
-0.3967202305793762,
0.12651823461055756,
0.40005436539649963,
0.06075844168663025,
-0.23886547982692719,
0.13217173516750336,
0.10595058649778366,
-0.3579234182834625,
0.060700055211782455,
0.0641697570681572,
-0.15428316593170166,
0.6550420522689819,
-0.14000152051448822,
0.16470623016357422,
-0.1756533533334732,
-0.21198037266731262,
0.3319481611251831,
0.20278312265872955,
-0.07796873897314072,
-0.011605443432927132,
0.12744788825511932,
-0.060983046889305115,
-0.19573882222175598,
0.4920666217803955,
0.2548990547657013,
0.05156734585762024,
-0.46568816900253296,
0.007283506449311972,
0.09706340730190277,
0.13736309111118317,
-0.0935613363981247,
0.1530829221010208,
0.4537775218486786,
-0.1514500081539154,
0.20709161460399628,
0.004273159429430962,
-0.05843540281057358,
-0.09915964305400848,
0.08272354304790497,
-0.3991204798221588,
-0.40854743123054504,
0.5045661330223083,
0.06087705120444298,
-0.11606736481189728,
0.08093591034412384,
0.3370765447616577,
-0.6575289964675903,
-0.260475218296051,
0.34948861598968506,
-0.08489373326301575,
-0.03731125593185425,
-0.22380787134170532,
0.07407914847135544,
0.07273796200752258,
0.6086328029632568,
0.16365867853164673,
0.3771527111530304,
-0.39702364802360535,
-0.10719912499189377,
-0.6464778184890747,
-0.21320584416389465,
0.0997607558965683,
-0.1670617014169693,
-0.2602815628051758,
0.13774150609970093,
-0.038988031446933746,
0.2751610279083252,
-0.2075420767068863,
0.05163240432739258,
0.25321558117866516,
0.026921281591057777,
-0.45630544424057007,
0.07905134558677673,
0.1370767205953598,
0.0201097559183836,
0.28374919295310974,
-0.07789784669876099,
-0.22131921350955963,
0.06585610657930374,
-0.056704044342041016,
-0.05049337446689606,
-0.08613930642604828,
0.27794787287712097,
0.17560851573944092,
0.03599392622709274,
0.04806513339281082,
0.5123879313468933,
-0.022415578365325928,
-0.17422173917293549,
-0.02602824941277504,
0.02857363596558571,
-0.3725864589214325,
-0.11181623488664627,
-0.12267301976680756,
0.21131892502307892,
-0.37687671184539795,
0.27004748582839966,
0.01695701666176319,
-0.10174858570098877,
0.12268924713134766,
-0.009532656520605087,
-0.17501015961170197,
-0.021082734689116478,
0.04411768168210983,
0.2265997976064682,
0.21104493737220764,
0.7624980211257935,
-0.00015050917863845825,
0.1709391474723816,
-0.07620479166507721,
-0.06651207059621811,
0.07553748041391373,
-0.11749524623155594,
-0.26458320021629333,
-0.15456560254096985,
0.0648573786020279,
0.04752340540289879,
0.11066454648971558,
-0.7056499123573303,
-0.3468591272830963,
0.016169268637895584,
-0.019177090376615524,
0.05395834520459175,
0.7361038327217102,
0.07266171276569366,
-0.14398175477981567,
-0.1310943216085434,
-0.3231854736804962,
0.02054028958082199,
-0.23995469510555267,
0.18913601338863373,
-0.3676549792289734
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | I think I would probably go for a `MultiDataset` wrapper around a list of `Dataset`.
I'm not sure we need to give it `k` and `t` parameters at creation, it can maybe be something along the lines of:
```python
squad = nlp.load_dataset("squad")
cnn_dm = nlp.load_dataset("cnn_dailymail","3.0.0")
multitask_dataset = nlp.MultiDataset(squad, cnn_dm)
batch = multitask_dataset.sample(10, temperature=2.0, k=1000)
```
The first proof-of-concept for multi-task datasets could definitely require that the provided datasets have the same name/type for columns (if needed you easily rename/cast a column prior to instantiating the `MultiDataset`).
It's good to think about it for some time though and don't overfit too much on the T5 examples (in particular for the ways/kwargs for sampling among datasets). | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 114 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
I think I would probably go for a `MultiDataset` wrapper around a list of `Dataset`.
I'm not sure we need to give it `k` and `t` parameters at creation, it can maybe be something along the lines of:
```python
squad = nlp.load_dataset("squad")
cnn_dm = nlp.load_dataset("cnn_dailymail","3.0.0")
multitask_dataset = nlp.MultiDataset(squad, cnn_dm)
batch = multitask_dataset.sample(10, temperature=2.0, k=1000)
```
The first proof-of-concept for multi-task datasets could definitely require that the provided datasets have the same name/type for columns (if needed you easily rename/cast a column prior to instantiating the `MultiDataset`).
It's good to think about it for some time though and don't overfit too much on the T5 examples (in particular for the ways/kwargs for sampling among datasets). | [
-0.030960330739617348,
-0.4186744689941406,
-0.03965791314840317,
-0.04687012732028961,
-0.22470249235630035,
0.09376334398984909,
0.16783766448497772,
0.037585847079753876,
0.2795366048812866,
-0.16709871590137482,
-0.22088007628917694,
0.3342224955558777,
-0.21486341953277588,
0.3291553556919098,
0.4196423292160034,
-0.4405980110168457,
0.02405460923910141,
-0.21915334463119507,
-0.2579808831214905,
0.37987810373306274,
0.065569207072258,
0.10199691355228424,
-0.1636253297328949,
0.05979228764772415,
-0.26799413561820984,
-0.16470766067504883,
-0.3614473044872284,
0.12241487950086594,
0.13698215782642365,
-0.010515410453081131,
0.21925154328346252,
0.3853780925273895,
-0.02397031895816326,
0.11684758216142654,
-0.00011339464981574565,
-0.07660691440105438,
0.1594887226819992,
-0.12002448737621307,
0.09109000861644745,
0.006583958864212036,
0.15462055802345276,
-0.4277091920375824,
0.07293383032083511,
-0.15843729674816132,
0.14493289589881897,
0.15658533573150635,
0.14506758749485016,
-0.0069006867706775665,
0.4177415370941162,
-0.255648672580719,
0.09768406301736832,
0.3037808835506439,
-0.1650868058204651,
0.2707972824573517,
-0.14200884103775024,
-0.06699219346046448,
0.027930142357945442,
0.2208583503961563,
0.6148960590362549,
-0.5899091362953186,
0.0041680708527565,
0.07856716215610504,
-0.014349911361932755,
0.007405588403344154,
0.15548290312290192,
-0.029883679002523422,
-0.3357184827327728,
-0.26306936144828796,
-0.39329853653907776,
0.21611791849136353,
-0.13005810976028442,
-0.17696866393089294,
-0.25059211254119873,
-0.5384417772293091,
0.017066888511180878,
0.03541639447212219,
-0.2903541922569275,
0.031573329120874405,
-0.2046491801738739,
-0.05459118261933327,
-0.1233537420630455,
-0.10292129218578339,
-0.006522908806800842,
0.15645073354244232,
0.3066308796405792,
0.571914553642273,
0.12777642905712128,
0.17128872871398926,
0.3525916635990143,
0.02389596775174141,
-0.14905191957950592,
-0.2876003086566925,
0.29404017329216003,
0.16211548447608948,
-0.4089536666870117,
-0.350779265165329,
0.13092613220214844,
-0.24935418367385864,
0.2844473719596863,
0.08810119330883026,
0.11836829036474228,
0.05591227114200592,
-0.13708598911762238,
0.28888919949531555,
0.3011118173599243,
0.03557530790567398,
-0.07668820768594742,
-0.1267349272966385,
0.021894332021474838,
-0.13308824598789215,
0.18895933032035828,
0.12626680731773376,
0.18178308010101318,
-0.008661901578307152,
-0.37493807077407837,
-0.13579264283180237,
-0.1604587286710739,
0.1738724410533905,
-0.16109979152679443,
-0.5166131258010864,
-0.11007818579673767,
-0.09324751049280167,
0.07216590642929077,
-0.09246727079153061,
-0.29434117674827576,
0.07609951496124268,
-0.04885469749569893,
0.2247583419084549,
-0.08821694552898407,
0.0521588958799839,
-0.06363727897405624,
0.08743637800216675,
-0.427127480506897,
-0.031100252643227577,
0.31112298369407654,
0.0953134298324585,
0.07913778722286224,
0.168320894241333,
-0.009065136313438416,
0.10786354541778564,
0.42135104537010193,
0.020736411213874817,
-0.005292035639286041,
-0.025720451027154922,
0.20524586737155914,
-0.2978519797325134,
0.013126444071531296,
0.1394488662481308,
-0.34433114528656006,
-0.12336943298578262,
-0.1408035159111023,
-0.16177307069301605,
0.10516715794801712,
0.026167768985033035,
-0.22706972062587738,
-0.26348572969436646,
-0.478713721036911,
0.7096784114837646,
-0.01631738245487213,
-0.04073471203446388,
-0.1800367534160614,
0.28762441873550415,
-0.26460060477256775,
-0.11316057294607162,
0.22921299934387207,
0.10030773282051086,
-0.043902475386857986,
-0.2998162806034088,
-0.07132072746753693,
-0.08353069424629211,
-0.08975840359926224,
0.2788395583629608,
-0.1998571902513504,
0.22274690866470337,
0.06801249086856842,
0.1548837423324585,
0.3027404546737671,
-0.4629935622215271,
-0.036578841507434845,
0.26916882395744324,
-0.035776667296886444,
0.38466617465019226,
0.0656006932258606,
0.22492584586143494,
0.019382182508707047,
-0.20013092458248138,
0.26398831605911255,
1.0421268939971924,
-0.4086361527442932,
0.0009426698088645935,
-0.09630396962165833,
-0.35686030983924866,
0.5225275158882141,
0.3448227047920227,
0.05289360508322716,
-0.2893567979335785,
-0.1473955512046814,
-0.005420439410954714,
0.07239223271608353,
0.058151524513959885,
0.09516756236553192,
-0.036987483501434326,
-0.3416345417499542,
0.069547139108181,
-0.22003597021102905,
-0.15002982318401337,
-0.44301098585128784,
0.019452519714832306,
0.04457852244377136,
0.343417763710022,
0.2352166473865509,
-0.13884490728378296,
0.22767773270606995,
-0.29061394929885864,
-0.13999690115451813,
-0.3124927580356598,
0.1317206770181656,
-0.050935596227645874,
0.031070612370967865,
-0.2207598239183426,
-0.035360001027584076,
0.3621315360069275,
0.14933723211288452,
-0.12701550126075745,
-0.48026585578918457,
0.327831506729126,
-0.07594688981771469,
0.03664093837141991,
-0.027286112308502197,
0.6227851510047913,
-0.15069270133972168,
-0.07301953434944153,
0.1906040608882904,
0.26689162850379944,
-0.28597161173820496,
0.2114320993423462,
0.3612278699874878,
0.27097657322883606,
0.17123503983020782,
-0.034092649817466736,
0.09529763460159302,
0.023809412494301796,
-0.0051742177456617355,
-0.22024020552635193,
-0.08570583909749985,
0.523391604423523,
-0.17810945212841034,
0.4187559187412262,
-0.04507885128259659,
0.03660005331039429,
-0.135530486702919,
-0.01814746856689453,
-0.19881552457809448,
0.41928932070732117,
0.2726353406906128,
-0.17454449832439423,
0.3594204783439636,
-0.1392040103673935,
-0.3428288698196411,
0.16008315980434418,
0.15589238703250885,
0.038506489247083664,
0.09078461676836014,
-0.0031082406640052795,
-0.04850035905838013,
-0.2614932954311371,
-0.10891598463058472,
0.3499148190021515,
0.6467791199684143,
0.2586943507194519,
0.13757577538490295,
0.013220415450632572,
-0.25058871507644653,
-0.06948138028383255,
0.03184850513935089,
0.16933591663837433,
-0.028486156836152077,
0.14386525750160217,
0.06159069389104843,
0.04908040165901184,
0.029332436621189117,
-0.17154915630817413,
0.18374310433864594,
-0.16221751272678375,
-0.07556957751512527,
0.07238435000181198,
-0.16648511588573456,
-0.5669125318527222,
-0.2283155769109726,
0.02773299813270569,
-0.3815072476863861,
-0.2889532148838043,
0.1047787070274353,
0.05141313001513481,
-0.12023964524269104,
0.18662790954113007,
0.20177417993545532,
0.5722042918205261,
-0.3877086043357849,
-0.29302436113357544,
-0.029145535081624985,
-0.3389906585216522,
-0.11456451565027237,
0.11243927478790283,
0.4557243883609772,
0.2603592276573181,
0.4842230975627899,
0.3259252607822418,
-0.03397265449166298,
0.0463758260011673,
-0.39842456579208374,
0.017644278705120087,
-0.3012903332710266,
0.2676166594028473,
0.07377395778894424,
-0.18586845695972443,
0.15339384973049164,
-0.40689191222190857,
-0.005612120032310486,
-0.021065721288323402,
-0.07087572664022446,
-0.05289333313703537,
0.004416038282215595,
0.09541960060596466,
-0.18347781896591187,
-0.19025975465774536,
-0.6412384510040283,
-0.43016278743743896,
0.2673931121826172,
-0.26016369462013245,
0.08659752458333969,
0.014041760936379433,
-0.2555754482746124,
0.17967817187309265,
-0.10786710679531097,
-0.0026078885421156883,
-0.16347719728946686,
-0.038953542709350586,
0.04661323130130768,
-0.35634130239486694,
-0.17569808661937714,
-0.3697788119316101,
-0.1142725795507431,
0.24605382978916168,
-0.06947679817676544,
-0.024847764521837234,
-0.2876040041446686,
0.09452758729457855,
-0.11205729842185974,
0.05305677652359009,
0.20907112956047058,
0.19394834339618683,
-0.22071023285388947,
0.13459806144237518,
-0.07369859516620636,
-0.29403573274612427,
0.23027512431144714,
0.27270710468292236,
0.38758090138435364,
0.1529558002948761,
0.07122115045785904,
0.17559175193309784,
0.7356224656105042,
0.25420889258384705,
0.018226033076643944,
0.15264949202537537,
0.25192463397979736,
-0.008517477661371231,
0.17827630043029785,
-0.24685533344745636,
0.17666278779506683,
-0.15473127365112305,
0.48757994174957275,
0.09875655174255371,
0.150802344083786,
-0.24501647055149078,
-0.3062400817871094,
0.05892613157629967,
-0.2685535252094269,
-0.2171599119901657,
0.24243071675300598,
-0.22875815629959106,
0.014071222394704819,
-0.08966025710105896,
-0.4162385165691376,
-0.2906377613544464,
-0.053883858025074005,
-0.022309914231300354,
0.3469157814979553,
-0.07768469303846359,
0.157317653298378,
-0.34134039282798767,
-0.046045079827308655,
-0.4354320168495178,
0.14782822132110596,
0.07338887453079224,
0.28789249062538147,
-0.06971289962530136,
-0.024439603090286255,
-0.11077514290809631,
0.10292797535657883,
0.6152392029762268,
-0.5185810327529907,
-0.12251298129558563,
0.10406072437763214,
0.08391129970550537,
-0.1375814527273178,
-0.10161551833152771,
-0.2601819336414337,
0.014867657795548439,
0.4297337532043457,
0.3357178568840027,
-0.3773830831050873,
-0.2934283912181854,
0.17445799708366394,
-0.20981255173683167,
-0.0844765156507492,
-0.16246354579925537,
-0.2532844543457031,
-0.22844791412353516,
-0.12505650520324707,
0.041776541620492935,
0.22972021996974945,
0.2200998067855835,
-0.06440145522356033,
0.16535009443759918,
-0.10738156735897064,
0.20170798897743225,
0.21851877868175507,
0.023033052682876587,
-0.040012627840042114,
0.2556941509246826,
0.1977343112230301,
0.039545901119709015,
-0.12689794600009918,
-0.3682379722595215,
0.06594017893075943,
-0.05863915756344795,
0.06726761162281036,
0.25432831048965454,
-0.03158362954854965,
0.6494699120521545,
0.04232773929834366,
0.339296817779541,
0.2956755757331848,
-0.171039417386055,
0.00383719801902771,
-0.227918803691864,
0.16946972906589508,
0.22283972799777985,
0.22637011110782623,
-0.15907901525497437,
-0.26187992095947266,
0.562938392162323,
0.29968640208244324,
-0.07139334082603455,
0.451677531003952,
-0.4898034334182739,
-0.3304513394832611,
0.2624640464782715,
0.0708131194114685,
0.6956494450569153,
-0.0626806989312172,
0.29476526379585266,
0.07930435985326767,
-0.36408501863479614,
0.6168705224990845,
-0.3644068241119385,
0.1506238430738449,
-0.1062217652797699,
-0.19690929353237152,
0.012675641104578972,
-0.09358709305524826,
-0.0731005147099495,
0.2685149312019348,
-0.38254672288894653,
0.3077969253063202,
0.42872554063796997,
-0.20226317644119263,
-0.025360627099871635,
0.5634380578994751,
0.05623336881399155,
-0.3985060155391693,
-0.15839296579360962,
0.06879620999097824,
-0.3081548810005188,
0.0543656125664711,
-0.1665422022342682,
-0.2580891251564026,
0.22570592164993286,
0.15583230555057526,
-0.3013504147529602,
0.06678961217403412,
-0.03523048013448715,
0.2177829146385193,
0.21286426484584808,
0.015265248715877533,
0.26790186762809753,
-0.11605891585350037,
-0.037850163877010345,
-0.15350617468357086,
-0.08397115767002106,
0.13552787899971008,
-0.19333329796791077,
0.0378146730363369,
0.01826782338321209,
-0.1867406666278839,
0.4988887310028076,
-0.06247975677251816,
-0.11852211505174637,
-0.21425199508666992,
0.28020739555358887,
-0.4461520314216614,
-0.19157014787197113,
0.14757505059242249,
0.1756839156150818,
0.1982739418745041,
-0.3049491345882416,
0.5695933699607849,
0.10945115983486176,
0.011156491935253143,
0.0341043621301651,
0.2101193368434906,
-0.27115949988365173,
0.5002744793891907,
-0.2811298668384552,
0.009963221848011017,
0.10484032332897186,
0.02505221962928772,
-0.11265336722135544,
-0.38574928045272827,
-0.030786365270614624,
0.31705957651138306,
0.13859906792640686,
0.008726745843887329,
0.028529450297355652,
0.11237525194883347,
-0.06501572579145432,
-0.02706974744796753,
-0.14490534365177155,
-0.35135406255722046,
0.131876140832901,
0.18006372451782227,
0.18757539987564087,
0.2329903244972229,
-0.028973333537578583,
-0.2715376913547516,
-0.16603974997997284,
0.44810593128204346,
0.03526157885789871,
0.20998844504356384,
-0.1294512003660202,
0.34659919142723083,
0.40914109349250793,
0.5483714938163757,
-0.2595946192741394,
0.07455826550722122,
0.055365972220897675,
0.11097997426986694,
0.459245502948761,
-0.2511613667011261,
0.076079823076725,
0.2771490514278412,
-0.12474247813224792,
0.03135416656732559,
-0.3204188942909241,
-0.1535581350326538,
-0.24974076449871063,
0.1109316274523735,
0.10442157834768295,
0.0042015002109110355,
0.004017968662083149,
-0.10565099865198135,
-0.11311247944831848,
-0.08425325900316238,
-0.00029867514967918396,
-0.3816279470920563,
-0.05959092080593109,
0.12420295178890228,
-0.03806604817509651,
0.0650605633854866,
0.036878831684589386,
0.18779055774211884,
0.023436088114976883,
-0.10253900289535522,
0.34939655661582947,
0.11723890900611877,
0.10813349485397339,
-0.1778067648410797,
-0.16322247684001923,
0.023343484848737717,
0.2428969442844391,
0.15198221802711487,
-0.06412412226200104,
0.12868019938468933,
-0.24157720804214478,
-0.12066946178674698,
0.236313134431839,
0.16919121146202087,
0.017447862774133682,
-0.1027127355337143,
0.13327622413635254,
0.11498117446899414,
-0.09520798921585083,
-0.03510065749287605,
0.27450206875801086,
0.07827584445476532,
0.134038507938385,
0.14364203810691833,
0.09875935316085815,
0.4728016257286072,
-0.23880432546138763,
0.009598851203918457,
0.14305885136127472,
-0.35201001167297363,
0.12352623045444489,
-0.1303715705871582,
-0.03644517436623573,
-0.011555921286344528,
0.10323746502399445,
-0.024381965398788452,
0.141191303730011,
-0.2700303792953491,
0.28077515959739685,
0.30520468950271606,
0.000443827360868454,
-0.03391337767243385,
0.2237342894077301,
0.05606946721673012,
-0.14373500645160675,
0.2464371919631958,
0.04788047820329666,
0.32649004459381104,
0.021484695374965668,
0.8898254632949829,
-0.25932177901268005,
-0.4453703463077545,
0.10914941877126694,
0.4276833236217499,
0.04372840002179146,
-0.20927919447422028,
0.1428680717945099,
0.10250184684991837,
-0.3528323173522949,
0.07324333488941193,
0.0668150931596756,
-0.21987570822238922,
0.650164008140564,
-0.10448980331420898,
0.21174612641334534,
-0.13323836028575897,
-0.16710615158081055,
0.3940386176109314,
0.17511966824531555,
-0.06507784128189087,
0.0157078355550766,
0.14367759227752686,
-0.12336216866970062,
-0.17897970974445343,
0.43864330649375916,
0.21286191046237946,
0.027808908373117447,
-0.46195387840270996,
0.0628170520067215,
0.09056828916072845,
0.14693021774291992,
-0.03955453634262085,
0.10659772902727127,
0.43498724699020386,
-0.1517581194639206,
0.23860199749469757,
0.013740068301558495,
-0.05349789932370186,
-0.19473107159137726,
0.07981115579605103,
-0.42988622188568115,
-0.378812700510025,
0.4788786768913269,
0.06758509576320648,
-0.11324054002761841,
0.05943562462925911,
0.33388450741767883,
-0.6175366044044495,
-0.2591392397880554,
0.3267904818058014,
-0.09543348848819733,
-0.06627240777015686,
-0.1992466002702713,
0.07281956076622009,
0.06321091949939728,
0.6397793292999268,
0.17726364731788635,
0.36059918999671936,
-0.3750837743282318,
-0.12910102307796478,
-0.6346372961997986,
-0.15605154633522034,
0.11392465233802795,
-0.17616349458694458,
-0.25313717126846313,
0.1707487851381302,
-0.04700475186109543,
0.3227485418319702,
-0.20954696834087372,
0.09758217632770538,
0.2715473473072052,
0.027108391746878624,
-0.4724886417388916,
0.0400509275496006,
0.09500536322593689,
0.04796040430665016,
0.28179454803466797,
-0.07571332156658173,
-0.19103200733661652,
0.06382099539041519,
-0.06736119091510773,
-0.08385732024908066,
-0.11887842416763306,
0.2494056522846222,
0.17716890573501587,
0.06206147000193596,
0.0344526432454586,
0.5532029867172241,
0.010818343609571457,
-0.1616266816854477,
0.031095368787646294,
0.028595712035894394,
-0.3770715296268463,
-0.1337224245071411,
-0.08216693997383118,
0.20839737355709076,
-0.39294594526290894,
0.2529560923576355,
-0.007655319292098284,
-0.025235764682292938,
0.11938372254371643,
0.011496465653181076,
-0.2017444372177124,
-0.02404690906405449,
0.08408021181821823,
0.24017967283725739,
0.20282059907913208,
0.7438056468963623,
-0.01443392038345337,
0.17315666377544403,
-0.08187657594680786,
-0.03745286911725998,
0.06602832674980164,
-0.13763946294784546,
-0.24784840643405914,
-0.13568419218063354,
0.03555174171924591,
0.06208350509405136,
0.12089323252439499,
-0.676857054233551,
-0.3293685019016266,
0.045108404010534286,
-0.0008667614310979843,
0.004000037908554077,
0.7409059405326843,
0.06504139304161072,
-0.11601370573043823,
-0.11704592406749725,
-0.3568640649318695,
0.033418286591768265,
-0.25153300166130066,
0.18174003064632416,
-0.37132352590560913
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | The problem with changing `k` and `t` per sampling is that you'd have to somehow remember which examples you'd already returned while re-weighting the remaining examples based on the new `k` and `t`values. It seems possible but complicated (I can't really see a reason why you'd want to change the weighting of datasets after you constructed the multidataset).
Wouldn't it be convenient if it implemented the dataset interface? Then if someone has code using a single nlp dataset, they can replace it with a multitask combination of more datasets without having to change other code. We would at least need to be able to pass it into a `DataLoader`.
| It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 109 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
The problem with changing `k` and `t` per sampling is that you'd have to somehow remember which examples you'd already returned while re-weighting the remaining examples based on the new `k` and `t`values. It seems possible but complicated (I can't really see a reason why you'd want to change the weighting of datasets after you constructed the multidataset).
Wouldn't it be convenient if it implemented the dataset interface? Then if someone has code using a single nlp dataset, they can replace it with a multitask combination of more datasets without having to change other code. We would at least need to be able to pass it into a `DataLoader`.
| [
-0.08343673497438431,
-0.37729135155677795,
-0.0540122427046299,
-0.08327743411064148,
-0.2122468650341034,
0.016944333910942078,
0.13349920511245728,
0.06816373765468597,
0.31245875358581543,
-0.0252598375082016,
-0.23778603971004486,
0.3599814176559448,
-0.15870383381843567,
0.3497789800167084,
0.3823589086532593,
-0.4798983037471771,
-0.0307442769408226,
-0.13304588198661804,
-0.368801474571228,
0.3823729157447815,
0.04090229421854019,
0.09933474659919739,
-0.12265481799840927,
0.0074624791741371155,
-0.2362724095582962,
-0.15221793949604034,
-0.34329670667648315,
0.09290042519569397,
0.18456219136714935,
-0.055031318217515945,
0.19634635746479034,
0.44995513558387756,
-0.017280213534832,
0.052321407943964005,
-0.00011072367487940937,
-0.08731884509325027,
0.13175973296165466,
-0.12002041190862656,
0.049835313111543655,
0.03783103823661804,
0.21656614542007446,
-0.4117274880409241,
-0.06971552222967148,
-0.18803787231445312,
0.10876727849245071,
0.21512407064437866,
0.18305854499340057,
0.024411894381046295,
0.41552120447158813,
-0.32108616828918457,
0.1293700933456421,
0.32684794068336487,
-0.22198718786239624,
0.23453129827976227,
-0.09464385360479355,
-0.15330490469932556,
0.09412934631109238,
0.3127889931201935,
0.4916841983795166,
-0.5477129817008972,
-0.06117916852235794,
0.14151130616664886,
0.0077215563505887985,
0.059617672115564346,
0.10257229208946228,
-0.051516398787498474,
-0.3251841366291046,
-0.20651036500930786,
-0.3548204004764557,
0.29408255219459534,
-0.18114712834358215,
-0.14917248487472534,
-0.19877654314041138,
-0.5856704711914062,
0.06005871295928955,
-0.010826671496033669,
-0.2997104227542877,
0.02046133577823639,
-0.14967502653598785,
-0.01279304176568985,
-0.12954580783843994,
-0.09831427037715912,
0.07478511333465576,
0.09907751530408859,
0.32749229669570923,
0.5603529214859009,
0.09386050701141357,
0.18363526463508606,
0.39189448952674866,
0.07738843560218811,
-0.21224841475486755,
-0.246026873588562,
0.2851274013519287,
0.09630567580461502,
-0.28267213702201843,
-0.3462059199810028,
0.1630009114742279,
-0.26397940516471863,
0.23295828700065613,
0.05783981829881668,
0.1677578091621399,
0.11276699602603912,
-0.13788184523582458,
0.2494640052318573,
0.28214171528816223,
0.05985120311379433,
0.010651610791683197,
-0.11803437769412994,
0.01498420536518097,
-0.05733748525381088,
0.1585502028465271,
0.09276801347732544,
0.21617823839187622,
-0.04497029632329941,
-0.40501436591148376,
-0.08261941373348236,
-0.2754175066947937,
0.1954956352710724,
-0.20601993799209595,
-0.5297425389289856,
-0.018626544624567032,
-0.11480327695608139,
0.023904889822006226,
-0.10028742998838425,
-0.3187437355518341,
0.16014358401298523,
-0.056539006531238556,
0.1746998280286789,
-0.1174469143152237,
0.07287582010030746,
-0.08563584089279175,
0.08851851522922516,
-0.49863627552986145,
0.02519451640546322,
0.25986430048942566,
0.08004923164844513,
0.16220256686210632,
0.16258688271045685,
-0.026162348687648773,
0.1506979614496231,
0.39101892709732056,
0.059601109474897385,
0.0018358007073402405,
-0.058130573481321335,
0.159010648727417,
-0.2949698865413666,
-0.042152438312768936,
0.1823381781578064,
-0.42464199662208557,
-0.15480473637580872,
-0.1469176709651947,
-0.07604150474071503,
0.16089080274105072,
0.04554303362965584,
-0.24469687044620514,
-0.2981192469596863,
-0.4465663731098175,
0.7699316143989563,
-0.009562753140926361,
-0.1129106730222702,
-0.10955851525068283,
0.20794659852981567,
-0.30656173825263977,
-0.0800890251994133,
0.2194678783416748,
0.032092414796352386,
-0.01905878446996212,
-0.40339744091033936,
-0.04226965457201004,
-0.037179749459028244,
-0.10395515710115433,
0.2644660174846649,
-0.21608860790729523,
0.18137189745903015,
0.07405565679073334,
0.17394699156284332,
0.2999929189682007,
-0.4679257273674011,
-0.08489702641963959,
0.23441095650196075,
-0.036087457090616226,
0.3289673626422882,
0.08498428016901016,
0.12413075566291809,
0.05196559429168701,
-0.17159166932106018,
0.17609819769859314,
0.9709120392799377,
-0.3548182249069214,
0.024371890351176262,
-0.1063789427280426,
-0.3863513469696045,
0.5253020524978638,
0.2912898063659668,
0.07079442590475082,
-0.2695537209510803,
-0.12689140439033508,
0.004664952866733074,
0.09227924048900604,
0.01856328919529915,
0.08767051994800568,
-0.04912332445383072,
-0.3308199942111969,
0.00919756293296814,
-0.2163790911436081,
-0.15521496534347534,
-0.3733971118927002,
0.05382620543241501,
-0.061897244304418564,
0.3879176378250122,
0.39867132902145386,
-0.1182982549071312,
0.2000267207622528,
-0.3578914999961853,
-0.033523861318826675,
-0.28234654664993286,
0.1489844024181366,
-0.013988636434078217,
0.04843536391854286,
-0.220911905169487,
-0.049511704593896866,
0.23565392196178436,
0.135026752948761,
-0.1555178165435791,
-0.40747788548469543,
0.30450940132141113,
0.020174410194158554,
-0.0015047937631607056,
-0.05420171096920967,
0.5833069086074829,
-0.1648831069469452,
-0.10873427987098694,
0.2087189257144928,
0.3047448396682739,
-0.3626171946525574,
0.29410797357559204,
0.31045353412628174,
0.19204077124595642,
0.15806689858436584,
0.019926097244024277,
0.1577107310295105,
-0.014536786824464798,
-0.06476853042840958,
-0.16084536910057068,
-0.041563235223293304,
0.641684353351593,
-0.04830150678753853,
0.34820738434791565,
-0.029241543263196945,
-0.031101044267416,
-0.17479848861694336,
-0.1673583984375,
-0.25965818762779236,
0.3309371769428253,
0.2930154800415039,
-0.27841484546661377,
0.3624514043331146,
-0.12749820947647095,
-0.4090743660926819,
0.15859650075435638,
0.19831007719039917,
0.05338207259774208,
0.12208328396081924,
0.011676155030727386,
-0.05402829498052597,
-0.30141010880470276,
-0.10330075025558472,
0.34477925300598145,
0.6520266532897949,
0.28751140832901,
0.168321892619133,
0.02160434052348137,
-0.2816527485847473,
-0.0925324335694313,
0.0023983940482139587,
0.13403041660785675,
-0.02989664115011692,
0.18200238049030304,
0.10243838280439377,
0.031474776566028595,
-0.08563199639320374,
-0.06431353092193604,
0.1644388884305954,
-0.21713696420192719,
-0.03231696039438248,
0.03986576944589615,
-0.1786455363035202,
-0.5128587484359741,
-0.29099470376968384,
0.035596031695604324,
-0.3008247911930084,
-0.30237075686454773,
0.180471733212471,
0.0911056250333786,
-0.22132958471775055,
0.21164461970329285,
0.23787373304367065,
0.6204198598861694,
-0.39749449491500854,
-0.1298801749944687,
-0.10952049493789673,
-0.346415251493454,
-0.10274597257375717,
0.12991203367710114,
0.3555278778076172,
0.2745726406574249,
0.4790083169937134,
0.2562704086303711,
-0.058410752564668655,
0.1019943505525589,
-0.40407466888427734,
0.026286358013749123,
-0.31978166103363037,
0.25025177001953125,
0.11853522062301636,
-0.18916471302509308,
0.15250933170318604,
-0.3981904983520508,
0.011865782551467419,
-0.14020149409770966,
-0.029884323477745056,
-0.059307198971509933,
0.011886273510754108,
0.1486315131187439,
-0.20273490250110626,
-0.2027556300163269,
-0.6083055734634399,
-0.42396363615989685,
0.2456139773130417,
-0.21168050169944763,
0.04542766883969307,
0.051857348531484604,
-0.2142132669687271,
0.14821317791938782,
-0.16540053486824036,
0.015459399670362473,
-0.1877848356962204,
-0.10263331979513168,
-0.006060328334569931,
-0.3906427025794983,
-0.10505229234695435,
-0.5042768120765686,
-0.12487228959798813,
0.2693501114845276,
-0.10490936785936356,
-0.10202071070671082,
-0.32057926058769226,
0.05709948390722275,
-0.09570686519145966,
0.01693490333855152,
0.2777612507343292,
0.10743658244609833,
-0.22773580253124237,
0.03465273976325989,
-0.06954748928546906,
-0.21417123079299927,
0.21847206354141235,
0.41094449162483215,
0.3875404894351959,
0.11120001971721649,
0.003796897828578949,
0.14250244200229645,
0.7288059592247009,
0.20422549545764923,
-0.006215959787368774,
0.24172458052635193,
0.2230886071920395,
0.059005945920944214,
0.1169361025094986,
-0.14880691468715668,
0.21649548411369324,
-0.13906502723693848,
0.5181334018707275,
0.13408225774765015,
0.14490383863449097,
-0.23636023700237274,
-0.26169705390930176,
0.001547597348690033,
-0.20625880360603333,
-0.24861380457878113,
0.2672934830188751,
-0.2329823076725006,
-0.03897733986377716,
-0.04308027774095535,
-0.35451382398605347,
-0.32712942361831665,
-0.04302404820919037,
0.021407146006822586,
0.16934068500995636,
-0.009691014885902405,
0.13491588830947876,
-0.44665461778640747,
0.007309667766094208,
-0.4875246286392212,
0.17486964166164398,
0.03552931174635887,
0.20631295442581177,
-0.014624364674091339,
-0.09552451968193054,
-0.13732275366783142,
0.10531467944383621,
0.49268484115600586,
-0.5116745829582214,
-0.0789996087551117,
0.08137321472167969,
0.06042468547821045,
-0.1340131163597107,
-0.1311509609222412,
-0.3227555453777313,
-0.07703298330307007,
0.44155260920524597,
0.37745487689971924,
-0.42304694652557373,
-0.3025462031364441,
0.22415241599082947,
-0.16462092101573944,
-0.09548047184944153,
-0.17159664630889893,
-0.21112145483493805,
-0.1963445544242859,
-0.15463081002235413,
0.07413271814584732,
0.14330701529979706,
0.26712173223495483,
-0.1253158301115036,
0.19032739102840424,
-0.10813811421394348,
0.18458861112594604,
0.17987221479415894,
0.015827741473913193,
-0.04419182613492012,
0.35392293334007263,
0.11021867394447327,
0.07063794136047363,
-0.1312553584575653,
-0.331958532333374,
0.10548806190490723,
-0.1351999193429947,
0.20508211851119995,
0.22697043418884277,
0.09067465364933014,
0.5530034899711609,
0.11436168849468231,
0.35768502950668335,
0.30341091752052307,
-0.06347424536943436,
0.12543818354606628,
-0.31384581327438354,
0.20288746058940887,
0.17584112286567688,
0.255044549703598,
-0.10684063285589218,
-0.2142479568719864,
0.5952865481376648,
0.28747767210006714,
-0.08879175782203674,
0.3823321461677551,
-0.5090104341506958,
-0.3641585409641266,
0.2897244095802307,
0.08487685024738312,
0.656855583190918,
-0.01266615092754364,
0.3372664153575897,
0.05917869508266449,
-0.304044246673584,
0.619907796382904,
-0.275953471660614,
0.14735527336597443,
-0.13500432670116425,
-0.24565301835536957,
0.03667672723531723,
-0.04864157363772392,
-0.08241482824087143,
0.2677815854549408,
-0.35127562284469604,
0.3676716387271881,
0.4438672661781311,
-0.1998153030872345,
-0.12936098873615265,
0.5204607844352722,
-0.08692405372858047,
-0.3249291777610779,
-0.11418372392654419,
0.09938503801822662,
-0.2334737628698349,
0.11657506227493286,
-0.1201619803905487,
-0.25054484605789185,
0.22407999634742737,
0.13571172952651978,
-0.22700893878936768,
0.04554489254951477,
-0.0658809021115303,
0.13693293929100037,
0.26868557929992676,
0.030229032039642334,
0.19252631068229675,
-0.2200113832950592,
-0.025525979697704315,
-0.10796047747135162,
-0.10625419020652771,
0.12955453991889954,
-0.1636422872543335,
0.07055357843637466,
0.13920392096042633,
-0.1475970298051834,
0.519082248210907,
0.012029826641082764,
-0.11477293074131012,
-0.19632449746131897,
0.26937335729599,
-0.3825450539588928,
-0.17794661223888397,
0.024098139256238937,
0.09247929602861404,
0.10347151011228561,
-0.3090542256832123,
0.5627153515815735,
0.12510044872760773,
-0.0283498615026474,
0.06166983023285866,
0.10210748761892319,
-0.22989562153816223,
0.5123823285102844,
-0.18565776944160461,
-0.03955163061618805,
0.05415235832333565,
0.09490837901830673,
-0.162653386592865,
-0.3041132986545563,
-0.04040642827749252,
0.24128533899784088,
0.1346210241317749,
-0.014453219249844551,
0.014386706054210663,
0.16485227644443512,
-0.17030954360961914,
0.04330530762672424,
-0.07534758746623993,
-0.34250274300575256,
0.15653546154499054,
0.2247285395860672,
0.21894203126430511,
0.2962503433227539,
-0.11109837889671326,
-0.185403510928154,
-0.12255635112524033,
0.4910305142402649,
0.09181749820709229,
0.2689322829246521,
-0.11989662051200867,
0.32257211208343506,
0.35474756360054016,
0.5900279879570007,
-0.3123571574687958,
0.07766600698232651,
0.06387640535831451,
0.1348428875207901,
0.5099009275436401,
-0.23741289973258972,
0.008969585411250591,
0.3305620849132538,
-0.11035560816526413,
0.07590006291866302,
-0.32956793904304504,
-0.17685595154762268,
-0.2944236099720001,
0.08765851706266403,
0.07303470373153687,
0.01262526586651802,
0.02389490231871605,
-0.03426353633403778,
-0.045068588107824326,
-0.1670873761177063,
0.005586780607700348,
-0.41685113310813904,
-0.10029646754264832,
0.20000974833965302,
-0.06102355197072029,
0.06438520550727844,
0.1422736495733261,
0.22846247255802155,
0.009681642055511475,
-0.1569228619337082,
0.2438974529504776,
0.16898371279239655,
0.10425110906362534,
-0.12324473261833191,
-0.1688486933708191,
-0.0028999894857406616,
0.21621885895729065,
0.08830443024635315,
-0.12145934253931046,
0.19059349596500397,
-0.20523498952388763,
-0.09061136096715927,
0.3178473114967346,
0.18736661970615387,
0.04893610253930092,
-0.1805138736963272,
0.1527685821056366,
0.16645275056362152,
-0.11254394799470901,
0.00039309359272010624,
0.15967324376106262,
0.11689897626638412,
0.15863487124443054,
0.14670749008655548,
0.14573132991790771,
0.38194525241851807,
-0.1910199075937271,
-0.041007544845342636,
0.08764426410198212,
-0.32143473625183105,
0.11080721020698547,
-0.060433123260736465,
-0.020613621920347214,
-0.03212401643395424,
0.18058408796787262,
-0.0632687360048294,
0.20519569516181946,
-0.4029552936553955,
0.2911439836025238,
0.33818021416664124,
-0.008856095373630524,
0.030189277604222298,
0.12258760631084442,
0.011403318494558334,
-0.13385038077831268,
0.3777519166469574,
0.05748779699206352,
0.3323083221912384,
0.05188056826591492,
0.9268810749053955,
-0.26295799016952515,
-0.4481849670410156,
0.06358546018600464,
0.531395673751831,
0.029138321056962013,
-0.3214201331138611,
0.06138929724693298,
0.06478064507246017,
-0.3745325803756714,
0.16029533743858337,
0.011612344533205032,
-0.1540061980485916,
0.6641727685928345,
-0.15340936183929443,
0.19332930445671082,
-0.16817286610603333,
-0.22600221633911133,
0.28352779150009155,
0.1881144493818283,
-0.1497504562139511,
0.044861018657684326,
0.07804491370916367,
-0.06418494880199432,
-0.12437944114208221,
0.5293444395065308,
0.17358122766017914,
-0.013322815299034119,
-0.4142281711101532,
-0.0032766656950116158,
0.14429627358913422,
0.16323961317539215,
-0.12115471810102463,
0.12707525491714478,
0.4776846468448639,
-0.17132806777954102,
0.2919730842113495,
0.0513656809926033,
-0.1416742503643036,
-0.16505253314971924,
0.0537252277135849,
-0.4065130352973938,
-0.4111208915710449,
0.4177228808403015,
0.13737979531288147,
-0.04147929698228836,
0.06708236783742905,
0.28556138277053833,
-0.5498070120811462,
-0.22149813175201416,
0.25499197840690613,
-0.17315132915973663,
-0.07097940146923065,
-0.22309298813343048,
0.09759379178285599,
0.044758934527635574,
0.6479761004447937,
0.2121247947216034,
0.252043753862381,
-0.35490432381629944,
-0.09994027018547058,
-0.5510979890823364,
-0.13988235592842102,
0.1789744794368744,
-0.10730129480361938,
-0.27738454937934875,
0.16404403746128082,
-0.03695596009492874,
0.27869564294815063,
-0.18398259580135345,
0.18127024173736572,
0.21143768727779388,
0.009155172854661942,
-0.4085698425769806,
0.1516011357307434,
0.018774323165416718,
0.041605498641729355,
0.31257539987564087,
-0.11525028198957443,
-0.15051111578941345,
0.021374668926000595,
-0.02663564123213291,
-0.04524409770965576,
-0.08165740966796875,
0.24790722131729126,
0.18512989580631256,
0.1656785011291504,
0.013480477035045624,
0.4840942621231079,
-0.07819250226020813,
-0.12652689218521118,
-0.02078770473599434,
-0.0746103897690773,
-0.4193073511123657,
-0.20675155520439148,
-0.09964479506015778,
0.21812179684638977,
-0.279577374458313,
0.3174080550670624,
-0.009172753430902958,
-0.11152945458889008,
0.15208293497562408,
0.06763426214456558,
-0.10436652600765228,
-0.05300787836313248,
0.11525581032037735,
0.09159116446971893,
0.19210441410541534,
0.7487508654594421,
0.06614496558904648,
0.0984087884426117,
-0.08251773566007614,
-0.11334868520498276,
0.0889340415596962,
-0.06935074925422668,
-0.18787801265716553,
-0.1619156152009964,
0.012331299483776093,
0.10883492976427078,
0.0035943370312452316,
-0.6421046257019043,
-0.30900102853775024,
0.0285690538585186,
0.04078555852174759,
0.03615572676062584,
0.7093765139579773,
0.05208500474691391,
-0.16649790108203888,
-0.12391172349452972,
-0.34871944785118103,
0.08365851640701294,
-0.33575519919395447,
0.06608189642429352,
-0.37589794397354126
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | A very janky (but working) implementation of `multitask_dataset.sample()` could be something like this:
```python
import nlp
import torch
class MultiDataset():
def __init__(self, *args, temperature=2.0, k=1000, maximum=None, scale=1):
self.datasets = args
self._dataloaders = {}
for split in self._get_common_splits():
split_datasets = [ds[split] for ds in self.datasets]
mixing_rates = self._calc_mixing_rates(split_datasets,temperature, k, maximum, scale)
weights = []
for i in range(len(self.datasets)):
weights += [mixing_rates[i]]*len(self.datasets[i][split])
self._dataloaders[split] = torch.utils.data.DataLoader(torch.utils.data.ConcatDataset(split_datasets),
sampler=torch.utils.data.sampler.WeightedRandomSampler(
num_samples=len(weights),
weights = weights,
replacement=True),
shuffle=False)
def _get_common_splits(self):
'''Finds the common splits present in all self.datasets'''
min_set = None
for dataset in self.datasets:
if min_set != None:
min_set.intersection(set(dataset.keys()))
else:
min_set = set(dataset.keys())
return min_set
def _calc_mixing_rates(self,datasets, temperature=2.0, k=1000, maximum=None, scale=1):
'''Work out the weighting of each dataset based on t and k'''
mixing_rates = []
for dataset in datasets:
rate = len(dataset)
rate *= scale
if maximum:
rate = min(rate, maximum)
if temperature != 1.0:
rate = rate ** (1.0/temperature)
mixing_rates.append(rate)
return mixing_rates
def sample(self,n,split):
batch = []
for example in self._dataloaders[split]:
batch.append(example)
n -= 1
if n == 0:
return batch
def flatten(dataset,flatten_fn):
for k in dataset.keys():
if isinstance(dataset[k],nlp.Dataset):
dataset[k] = dataset[k].map(flatten_fn,remove_columns=dataset[k].column_names)
# Squad
def flatten_squad(example):
return {"source": "squad context: " + example['context'] + " question: " + example['question'],"target":example["answers"]["text"]}
squad = nlp.load_dataset("squad")
flatten(squad,flatten_squad)
# CNN_DM
def flatten_cnn_dm(example):
return {"source": "cnn_dm: " + example['article'],"target":[example["highlights"]]}
cnn_dm = nlp.load_dataset("cnn_dailymail", "3.0.0")
flatten(cnn_dm,flatten_cnn_dm)
multitask_dataset = MultiDataset(squad, cnn_dm)
batch = multitask_dataset.sample(100,"train")
```
There's definitely a more sensible way than embedding `DataLoader`s inside. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 231 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
A very janky (but working) implementation of `multitask_dataset.sample()` could be something like this:
```python
import nlp
import torch
class MultiDataset():
def __init__(self, *args, temperature=2.0, k=1000, maximum=None, scale=1):
self.datasets = args
self._dataloaders = {}
for split in self._get_common_splits():
split_datasets = [ds[split] for ds in self.datasets]
mixing_rates = self._calc_mixing_rates(split_datasets,temperature, k, maximum, scale)
weights = []
for i in range(len(self.datasets)):
weights += [mixing_rates[i]]*len(self.datasets[i][split])
self._dataloaders[split] = torch.utils.data.DataLoader(torch.utils.data.ConcatDataset(split_datasets),
sampler=torch.utils.data.sampler.WeightedRandomSampler(
num_samples=len(weights),
weights = weights,
replacement=True),
shuffle=False)
def _get_common_splits(self):
'''Finds the common splits present in all self.datasets'''
min_set = None
for dataset in self.datasets:
if min_set != None:
min_set.intersection(set(dataset.keys()))
else:
min_set = set(dataset.keys())
return min_set
def _calc_mixing_rates(self,datasets, temperature=2.0, k=1000, maximum=None, scale=1):
'''Work out the weighting of each dataset based on t and k'''
mixing_rates = []
for dataset in datasets:
rate = len(dataset)
rate *= scale
if maximum:
rate = min(rate, maximum)
if temperature != 1.0:
rate = rate ** (1.0/temperature)
mixing_rates.append(rate)
return mixing_rates
def sample(self,n,split):
batch = []
for example in self._dataloaders[split]:
batch.append(example)
n -= 1
if n == 0:
return batch
def flatten(dataset,flatten_fn):
for k in dataset.keys():
if isinstance(dataset[k],nlp.Dataset):
dataset[k] = dataset[k].map(flatten_fn,remove_columns=dataset[k].column_names)
# Squad
def flatten_squad(example):
return {"source": "squad context: " + example['context'] + " question: " + example['question'],"target":example["answers"]["text"]}
squad = nlp.load_dataset("squad")
flatten(squad,flatten_squad)
# CNN_DM
def flatten_cnn_dm(example):
return {"source": "cnn_dm: " + example['article'],"target":[example["highlights"]]}
cnn_dm = nlp.load_dataset("cnn_dailymail", "3.0.0")
flatten(cnn_dm,flatten_cnn_dm)
multitask_dataset = MultiDataset(squad, cnn_dm)
batch = multitask_dataset.sample(100,"train")
```
There's definitely a more sensible way than embedding `DataLoader`s inside. | [
-0.08342069387435913,
-0.3881210684776306,
-0.05889216065406799,
-0.057947948575019836,
-0.2545417547225952,
0.06940446048974991,
0.19493108987808228,
0.05140962824225426,
0.3405598998069763,
-0.14826445281505585,
-0.2024366557598114,
0.3717307448387146,
-0.23944707214832306,
0.34754085540771484,
0.3872973918914795,
-0.4599965512752533,
0.024137496948242188,
-0.26757046580314636,
-0.26987913250923157,
0.372872531414032,
0.06227091699838638,
0.08812969923019409,
-0.18115802109241486,
0.08036620914936066,
-0.253978431224823,
-0.16344726085662842,
-0.34938856959342957,
0.10462121665477753,
0.15728846192359924,
-0.013106939382851124,
0.21203763782978058,
0.38126319646835327,
-0.04049615561962128,
0.13177934288978577,
-0.00011317195458104834,
-0.07457607984542847,
0.21052531898021698,
-0.07623793929815292,
0.08656489849090576,
-0.06524446606636047,
0.22962728142738342,
-0.4317649304866791,
0.036712341010570526,
-0.14333145320415497,
0.14059683680534363,
0.15172182023525238,
0.16424933075904846,
-0.007431387901306152,
0.3844814896583557,
-0.27362796664237976,
0.1117820143699646,
0.2874106466770172,
-0.15955950319766998,
0.26453638076782227,
-0.10869453102350235,
-0.04743973910808563,
0.04901283234357834,
0.26195451617240906,
0.6061145067214966,
-0.6340843439102173,
-0.014124855399131775,
0.10082323849201202,
-0.04980574548244476,
0.03194368630647659,
0.1234845295548439,
-0.08227281272411346,
-0.38277190923690796,
-0.23529961705207825,
-0.39225131273269653,
0.24548795819282532,
-0.17746689915657043,
-0.19453588128089905,
-0.22744829952716827,
-0.5580011010169983,
0.006252024322748184,
0.041994303464889526,
-0.3048388659954071,
0.05022188276052475,
-0.19981540739536285,
-0.06731575727462769,
-0.13756799697875977,
-0.0884879007935524,
0.011829979717731476,
0.17321613430976868,
0.3156491816043854,
0.5342774391174316,
0.10947057604789734,
0.17463421821594238,
0.34226953983306885,
0.042830877006053925,
-0.1386733502149582,
-0.2869671583175659,
0.34202083945274353,
0.1264592707157135,
-0.3712506592273712,
-0.3075862526893616,
0.1824488788843155,
-0.26114827394485474,
0.25415700674057007,
0.11465080082416534,
0.11636269837617874,
0.0927191823720932,
-0.12476164847612381,
0.2851978838443756,
0.3020440638065338,
0.015004457905888557,
-0.08135757595300674,
-0.08082705736160278,
0.0235547237098217,
-0.13282251358032227,
0.22979426383972168,
0.12041135877370834,
0.16450080275535583,
-0.030592776834964752,
-0.4087803363800049,
-0.06945730000734329,
-0.16123726963996887,
0.19764044880867004,
-0.2383095771074295,
-0.4846024811267853,
-0.14205893874168396,
-0.08315498381853104,
0.07923724502325058,
-0.09192671626806259,
-0.2979579269886017,
0.10018016397953033,
-0.0730477049946785,
0.2468690127134323,
-0.10002531111240387,
0.07183870673179626,
-0.0563451312482357,
0.09835048019886017,
-0.4394397735595703,
-0.06991691142320633,
0.32330963015556335,
0.1422458440065384,
0.1164548471570015,
0.1751137524843216,
-0.016917668282985687,
0.1301395744085312,
0.44203123450279236,
-0.001940365880727768,
0.02095779776573181,
-0.014059159904718399,
0.19523228704929352,
-0.3251470923423767,
0.004884026944637299,
0.22755245864391327,
-0.37265825271606445,
-0.14289042353630066,
-0.12809118628501892,
-0.15609100461006165,
0.11269738525152206,
0.03565201163291931,
-0.23599132895469666,
-0.2588002383708954,
-0.4986611306667328,
0.6829741597175598,
-0.029003135859966278,
-0.04187577962875366,
-0.15797123312950134,
0.2522135376930237,
-0.24844467639923096,
-0.12514978647232056,
0.21692107617855072,
0.06579447537660599,
-0.0024429522454738617,
-0.31193840503692627,
-0.12970860302448273,
-0.08177660405635834,
-0.03710111230611801,
0.22530728578567505,
-0.160078763961792,
0.2730770409107208,
0.0468321219086647,
0.20835669338703156,
0.2641535997390747,
-0.5000428557395935,
-0.04386594146490097,
0.2669200003147125,
-0.04217652231454849,
0.4183538258075714,
0.04843825474381447,
0.21280845999717712,
0.034804292023181915,
-0.16171272099018097,
0.2985629439353943,
1.0328640937805176,
-0.38605228066444397,
0.004557004198431969,
-0.09491436183452606,
-0.36517012119293213,
0.523317277431488,
0.33920562267303467,
0.0907391905784607,
-0.31951484084129333,
-0.1159665659070015,
-0.05300162360072136,
0.10058605670928955,
0.0858922004699707,
0.07345293462276459,
-0.07229658216238022,
-0.36503931879997253,
0.05978412181138992,
-0.2487354576587677,
-0.19382643699645996,
-0.3421441316604614,
0.03035864233970642,
0.11190621554851532,
0.2797664403915405,
0.24866735935211182,
-0.13200034201145172,
0.22297078371047974,
-0.25494569540023804,
-0.1298157125711441,
-0.3390694558620453,
0.141840398311615,
-0.059791356325149536,
0.03747944161295891,
-0.25106966495513916,
0.0015004873275756836,
0.34114083647727966,
0.1274174451828003,
-0.1505715250968933,
-0.47374796867370605,
0.28402599692344666,
-0.055938661098480225,
0.039368610829114914,
-0.022019052878022194,
0.6338948607444763,
-0.1646694540977478,
-0.0881076231598854,
0.1917855441570282,
0.28774401545524597,
-0.26854750514030457,
0.2172980159521103,
0.31826168298721313,
0.1692703366279602,
0.14662028849124908,
-0.02283206582069397,
0.09416678547859192,
0.062102653086185455,
-0.02409166470170021,
-0.21376866102218628,
-0.08747979253530502,
0.536893367767334,
-0.15059490501880646,
0.439378559589386,
-0.06569953262805939,
0.06121225655078888,
-0.1688978224992752,
-0.01765916496515274,
-0.18787500262260437,
0.4131902754306793,
0.3052521049976349,
-0.1949424296617508,
0.3491774797439575,
-0.18313732743263245,
-0.3764328956604004,
0.15709848701953888,
0.08929839730262756,
0.029830005019903183,
0.09827025234699249,
-0.043594785034656525,
-0.05164376646280289,
-0.2501388192176819,
-0.06704864650964737,
0.3425806164741516,
0.6638853549957275,
0.26290982961654663,
0.18624214828014374,
0.044392190873622894,
-0.24098923802375793,
-0.061129119247198105,
0.008607722818851471,
0.1747158169746399,
-0.08582823723554611,
0.16375651955604553,
0.05545458942651749,
0.033264581114053726,
0.049514539539813995,
-0.13218633830547333,
0.15407155454158783,
-0.18271619081497192,
-0.07683469355106354,
0.09348670393228531,
-0.20606431365013123,
-0.5439789295196533,
-0.1966906040906906,
0.022410670295357704,
-0.2867784798145294,
-0.2818972170352936,
0.09111475944519043,
0.09463920444250107,
-0.1386154294013977,
0.15519262850284576,
0.213479146361351,
0.5341398119926453,
-0.3972027003765106,
-0.29688242077827454,
-0.021574970334768295,
-0.34398654103279114,
-0.13003480434417725,
0.1255968064069748,
0.43872177600860596,
0.33325695991516113,
0.5198891758918762,
0.3033435642719269,
-0.08945310860872269,
0.047933146357536316,
-0.3372720777988434,
0.010944869369268417,
-0.2858090400695801,
0.285250723361969,
0.13329178094863892,
-0.24219299852848053,
0.1681118756532669,
-0.3485582172870636,
-0.025232821702957153,
-0.07369424402713776,
-0.08946512639522552,
-0.03885030001401901,
-0.0026784262154251337,
0.07000210881233215,
-0.17970307171344757,
-0.17550259828567505,
-0.6369869112968445,
-0.43897488713264465,
0.29911163449287415,
-0.2640557587146759,
0.09133274853229523,
-0.016800738871097565,
-0.2485501617193222,
0.18541932106018066,
-0.1101645976305008,
0.0057690260000526905,
-0.17779715359210968,
-0.09301428496837616,
0.026734184473752975,
-0.3839552402496338,
-0.18263915181159973,
-0.38308316469192505,
-0.1138099804520607,
0.21733051538467407,
-0.019879233092069626,
-0.023588884621858597,
-0.2534290552139282,
0.10554011911153793,
-0.06678193807601929,
0.06014016270637512,
0.2171061635017395,
0.15147016942501068,
-0.23825182020664215,
0.13472546637058258,
-0.058886781334877014,
-0.23463891446590424,
0.2361760139465332,
0.2706865072250366,
0.4174257814884186,
0.16836750507354736,
0.04018959030508995,
0.20723821222782135,
0.6981124877929688,
0.2486543357372284,
0.028429972007870674,
0.14254799485206604,
0.2371979057788849,
-0.005118515342473984,
0.188836932182312,
-0.2463115155696869,
0.21866951882839203,
-0.216200053691864,
0.48305827379226685,
0.028078727424144745,
0.1475924849510193,
-0.21976663172245026,
-0.2751489281654358,
0.0053660087287425995,
-0.2993876039981842,
-0.19954906404018402,
0.22123710811138153,
-0.27302905917167664,
0.011601664125919342,
-0.11817152798175812,
-0.34711340069770813,
-0.27148744463920593,
-0.03676827624440193,
0.01355339027941227,
0.30513429641723633,
-0.08174071460962296,
0.15701259672641754,
-0.3513631522655487,
-0.049009110778570175,
-0.4496108293533325,
0.15219715237617493,
0.041846055537462234,
0.2807386517524719,
-0.06174740195274353,
-0.060966841876506805,
-0.10398003458976746,
0.09561648964881897,
0.5847180485725403,
-0.5166595578193665,
-0.0955328494310379,
0.1287485510110855,
0.12548871338367462,
-0.13120079040527344,
-0.11914443969726562,
-0.2858884632587433,
0.07362529635429382,
0.4597931206226349,
0.34093767404556274,
-0.3444136381149292,
-0.2527545690536499,
0.219550222158432,
-0.1727745682001114,
-0.05759384483098984,
-0.18763361871242523,
-0.23618847131729126,
-0.2354423701763153,
-0.08206910640001297,
0.055361997336149216,
0.22892631590366364,
0.2281399816274643,
-0.11155793070793152,
0.19489000737667084,
-0.12732549011707306,
0.24054816365242004,
0.21754425764083862,
-0.0025133593007922173,
-0.024932891130447388,
0.1810740828514099,
0.17871515452861786,
0.044977836310863495,
-0.14879077672958374,
-0.3022290766239166,
0.09064795076847076,
-0.05727584287524223,
0.11080880463123322,
0.22470298409461975,
-0.020743336528539658,
0.629221498966217,
0.04769931733608246,
0.31856662034988403,
0.2778649628162384,
-0.19443348050117493,
-0.002981148660182953,
-0.2579376697540283,
0.20183704793453217,
0.22035077214241028,
0.26212093234062195,
-0.11640968173742294,
-0.2639237940311432,
0.5500637888908386,
0.3211117386817932,
-0.0659315288066864,
0.44204992055892944,
-0.5858772397041321,
-0.31232112646102905,
0.24330048263072968,
0.06730468571186066,
0.6210485100746155,
-0.01113668829202652,
0.2869623601436615,
0.08895482122898102,
-0.3830382227897644,
0.5410966873168945,
-0.3828495740890503,
0.1639019399881363,
-0.08226895332336426,
-0.1536538153886795,
0.01521679200232029,
-0.09603606164455414,
-0.040717847645282745,
0.25265881419181824,
-0.32958027720451355,
0.3504188358783722,
0.4120699167251587,
-0.20682260394096375,
-0.06753432005643845,
0.5238791108131409,
-0.013963611796498299,
-0.35267695784568787,
-0.04201924055814743,
0.08234072476625443,
-0.2836204767227173,
0.1062176525592804,
-0.14440613985061646,
-0.24390070140361786,
0.21701034903526306,
0.15858152508735657,
-0.3457740545272827,
0.08260709792375565,
-0.035912834107875824,
0.22727586328983307,
0.21372637152671814,
-0.03624611347913742,
0.20517532527446747,
-0.1772371083498001,
-0.07493124902248383,
-0.1512720286846161,
-0.03667150437831879,
0.12637118995189667,
-0.14632153511047363,
0.04019317030906677,
0.0808696299791336,
-0.2181077003479004,
0.4567464292049408,
-0.04643137380480766,
-0.1222226470708847,
-0.19975224137306213,
0.28687262535095215,
-0.42228835821151733,
-0.1803591549396515,
0.15953995287418365,
0.1727864146232605,
0.252602756023407,
-0.31159907579421997,
0.5563429594039917,
0.1483863890171051,
-0.01022356003522873,
0.03905479609966278,
0.18057703971862793,
-0.26042017340660095,
0.5079049468040466,
-0.36686787009239197,
0.014650382101535797,
0.08976055681705475,
0.020912379026412964,
-0.13653337955474854,
-0.36404064297676086,
-0.048243485391139984,
0.3149685859680176,
0.11398130655288696,
0.00437699630856514,
0.06601301580667496,
0.12075292319059372,
0.013668261468410492,
-0.04037732630968094,
-0.16214576363563538,
-0.34312987327575684,
0.11653603613376617,
0.1604323536157608,
0.1777603030204773,
0.18723280727863312,
-0.04996239393949509,
-0.2939014434814453,
-0.16337966918945312,
0.4305415153503418,
0.044078417122364044,
0.2024313360452652,
-0.13496211171150208,
0.35182130336761475,
0.3814525008201599,
0.49481624364852905,
-0.25800997018814087,
0.07705625146627426,
0.09505408257246017,
0.09604034572839737,
0.44298055768013,
-0.21446135640144348,
0.05208288133144379,
0.25334668159484863,
-0.11877486109733582,
0.0298747755587101,
-0.32196879386901855,
-0.15790030360221863,
-0.23781806230545044,
0.09774885326623917,
0.07003472000360489,
0.01756487973034382,
0.04143724963068962,
-0.10240134596824646,
-0.08863097429275513,
-0.07675354927778244,
-0.01117253303527832,
-0.32483306527137756,
-0.06518663465976715,
0.1471289098262787,
-0.10908211767673492,
0.04781116917729378,
0.07037888467311859,
0.19740544259548187,
-0.002258516848087311,
-0.08733029663562775,
0.2813519537448883,
0.12359531968832016,
0.18367765843868256,
-0.16559207439422607,
-0.1435876190662384,
-0.025252990424633026,
0.21271595358848572,
0.14612016081809998,
-0.07139419764280319,
0.16139699518680573,
-0.2196010947227478,
-0.15503615140914917,
0.25354963541030884,
0.22577472031116486,
0.02459389716386795,
-0.10969046503305435,
0.147075355052948,
0.11975523084402084,
-0.12432171404361725,
-0.0021177558228373528,
0.20850613713264465,
0.09803561121225357,
0.11718396842479706,
0.1034604012966156,
0.10285216569900513,
0.46599674224853516,
-0.3051430583000183,
0.03137544170022011,
0.10533096641302109,
-0.3483791947364807,
0.11580254137516022,
-0.08272500336170197,
-0.0022730231285095215,
0.0024448297917842865,
0.10375705361366272,
-0.0023502446711063385,
0.14066556096076965,
-0.23288805782794952,
0.3303033411502838,
0.3737262487411499,
0.0639888197183609,
0.007040075957775116,
0.1710142195224762,
0.0021042227745056152,
-0.11631642282009125,
0.23376409709453583,
0.020215503871440887,
0.35285112261772156,
0.03638788312673569,
0.8677213788032532,
-0.31640490889549255,
-0.44532158970832825,
0.10563317686319351,
0.39686667919158936,
0.05611910670995712,
-0.23129118978977203,
0.1447218805551529,
0.10362931340932846,
-0.3610672354698181,
0.0887259840965271,
0.06926026195287704,
-0.17860956490039825,
0.668048620223999,
-0.12029631435871124,
0.16749344766139984,
-0.1809268295764923,
-0.22236594557762146,
0.3528715968132019,
0.1628759801387787,
-0.10737734287977219,
-0.03565685451030731,
0.1072143018245697,
-0.10292467474937439,
-0.199831023812294,
0.4940883219242096,
0.24655316770076752,
0.048753246665000916,
-0.5133512020111084,
0.011973072774708271,
0.06946771591901779,
0.15743617713451385,
-0.07946465909481049,
0.10217936336994171,
0.4472751021385193,
-0.17720068991184235,
0.2422112673521042,
0.015447285026311874,
-0.057762470096349716,
-0.10079395771026611,
0.09602126479148865,
-0.4450973570346832,
-0.3861229419708252,
0.4605049788951874,
0.07121430337429047,
-0.10437770932912827,
0.0653752014040947,
0.3186512291431427,
-0.6325953006744385,
-0.26431936025619507,
0.35300230979919434,
-0.08635836839675903,
-0.05638347566127777,
-0.20915158092975616,
0.08163756877183914,
0.042112432420253754,
0.6012605428695679,
0.1831812858581543,
0.3498595654964447,
-0.3703472316265106,
-0.11620760709047318,
-0.6050469875335693,
-0.19771051406860352,
0.051925208419561386,
-0.15896077454090118,
-0.2622525990009308,
0.14968301355838776,
-0.06800580769777298,
0.326211154460907,
-0.23237250745296478,
0.09375449270009995,
0.263223797082901,
0.10629783570766449,
-0.45955148339271545,
0.056498199701309204,
0.1048322468996048,
0.030725767835974693,
0.3046696186065674,
-0.10057763755321503,
-0.22762726247310638,
0.046522561460733414,
-0.055756255984306335,
-0.06158817559480667,
-0.14107653498649597,
0.2911347448825836,
0.18577246367931366,
0.08580746501684189,
0.025451794266700745,
0.5246702432632446,
-0.0034383945167064667,
-0.14572028815746307,
-0.025782551616430283,
0.054995931684970856,
-0.3764566481113434,
-0.12250711768865585,
-0.0945226401090622,
0.1602577418088913,
-0.3817417621612549,
0.272300660610199,
0.011709699407219887,
-0.04529961571097374,
0.11852079629898071,
0.0029892444144934416,
-0.19630929827690125,
-0.030839137732982635,
0.06354299932718277,
0.23153410851955414,
0.17898130416870117,
0.7314297556877136,
-0.025483064353466034,
0.1557295322418213,
-0.07545021176338196,
-0.035311587154865265,
0.05345030128955841,
-0.13339698314666748,
-0.2366471290588379,
-0.2042839229106903,
0.06664758920669556,
0.05969949811697006,
0.1490631103515625,
-0.6794450879096985,
-0.33675849437713623,
0.03388065844774246,
-0.0028483830392360687,
0.060768578201532364,
0.7086071968078613,
0.07913337647914886,
-0.1290806531906128,
-0.11463317275047302,
-0.3271321952342987,
-0.00030950456857681274,
-0.25829946994781494,
0.2029401659965515,
-0.37882471084594727
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | Good spot! Here are my thoughts:
- Aside: Adding `MultitaskModel` to transformers might be a thing to raise - even though having task-specific heads has become unfashionable in recent times in favour of text-to-text type models.
- Adding the task name as an extra field also seems useful for these kind of models which have task-specific heads
- There is some validation of our approach that the user should be expected to `map` datasets into a common form.
- The size-proportional sampling (also called "Examples-proportional mixing") used here doesn't perform too badly in the T5 paper (it's comparable to temperature-scaled mixing in many cases but less flexible. This is only reasonable with a `K` maximum size parameter to prevent very large datasets dominating). This might be good for a first prototype using:
```python
def __iter__(self):
"""
For each batch, sample a task, and yield a batch from the respective
task Dataloader.
We use size-proportional sampling, but you could easily modify this
to sample from some-other distribution.
"""
task_choice_list = []
for i, task_name in enumerate(self.task_name_list):
task_choice_list += [i] * self.num_batches_dict[task_name]
task_choice_list = np.array(task_choice_list)
np.random.shuffle(task_choice_list)
dataloader_iter_dict = {
task_name: iter(dataloader)
for task_name, dataloader in self.dataloader_dict.items()
}
for task_choice in task_choice_list:
task_name = self.task_name_list[task_choice]
yield next(dataloader_iter_dict[task_name])
```
We'd just need to pull samples from the raw datasets and not from `DataLoader`s for each task. We can assume the user has done `dataset.shuffle()` if they want to.
Other sampling methods can later be implemented by changing how the `task_choice_list` is generated. This should allow more flexibility and not tie us to specific methods for sampling among datasets.
| It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 264 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
Good spot! Here are my thoughts:
- Aside: Adding `MultitaskModel` to transformers might be a thing to raise - even though having task-specific heads has become unfashionable in recent times in favour of text-to-text type models.
- Adding the task name as an extra field also seems useful for these kind of models which have task-specific heads
- There is some validation of our approach that the user should be expected to `map` datasets into a common form.
- The size-proportional sampling (also called "Examples-proportional mixing") used here doesn't perform too badly in the T5 paper (it's comparable to temperature-scaled mixing in many cases but less flexible. This is only reasonable with a `K` maximum size parameter to prevent very large datasets dominating). This might be good for a first prototype using:
```python
def __iter__(self):
"""
For each batch, sample a task, and yield a batch from the respective
task Dataloader.
We use size-proportional sampling, but you could easily modify this
to sample from some-other distribution.
"""
task_choice_list = []
for i, task_name in enumerate(self.task_name_list):
task_choice_list += [i] * self.num_batches_dict[task_name]
task_choice_list = np.array(task_choice_list)
np.random.shuffle(task_choice_list)
dataloader_iter_dict = {
task_name: iter(dataloader)
for task_name, dataloader in self.dataloader_dict.items()
}
for task_choice in task_choice_list:
task_name = self.task_name_list[task_choice]
yield next(dataloader_iter_dict[task_name])
```
We'd just need to pull samples from the raw datasets and not from `DataLoader`s for each task. We can assume the user has done `dataset.shuffle()` if they want to.
Other sampling methods can later be implemented by changing how the `task_choice_list` is generated. This should allow more flexibility and not tie us to specific methods for sampling among datasets.
| [
-0.005270712077617645,
-0.4564434885978699,
-0.04090085253119469,
-0.033153802156448364,
-0.24214433133602142,
0.0899883434176445,
0.22626745700836182,
0.03379298001527786,
0.3455828130245209,
-0.18324880301952362,
-0.1746247559785843,
0.27823755145072937,
-0.21712930500507355,
0.3147799074649811,
0.3954232633113861,
-0.4474583864212036,
0.05297614261507988,
-0.268787145614624,
-0.2423509955406189,
0.37680453062057495,
0.023829326033592224,
0.1376442164182663,
-0.165048286318779,
0.10277897119522095,
-0.3490171432495117,
-0.14932627975940704,
-0.29104581475257874,
0.10549008846282959,
0.14364416897296906,
0.0494338721036911,
0.24418769776821136,
0.3417590260505676,
-0.031972579658031464,
0.1957811713218689,
-0.00011775486927945167,
-0.02630411460995674,
0.2295907735824585,
-0.05339072644710541,
0.13802748918533325,
-0.05143082141876221,
0.13814207911491394,
-0.37766194343566895,
0.06772827357053757,
-0.12424972653388977,
0.19982796907424927,
0.26353877782821655,
0.18150970339775085,
0.130659282207489,
0.3444681763648987,
-0.3399111032485962,
0.05876673758029938,
0.27942800521850586,
-0.20459185540676117,
0.3041354715824127,
-0.08195006102323532,
0.047511495649814606,
0.0006847735494375229,
0.24062517285346985,
0.6316858530044556,
-0.6122636795043945,
0.009547203779220581,
0.11814531683921814,
0.020631732419133186,
-0.07559317350387573,
0.21316513419151306,
-0.07582761347293854,
-0.3081117272377014,
-0.20631641149520874,
-0.401638001203537,
0.19827395677566528,
-0.13543862104415894,
-0.12603074312210083,
-0.17508959770202637,
-0.5726632475852966,
-0.09653259068727493,
0.07819853723049164,
-0.2844803035259247,
0.015646645799279213,
-0.1918289214372635,
-0.048152048140764236,
-0.13264106214046478,
-0.12773174047470093,
-0.03177602216601372,
0.13176490366458893,
0.3510734736919403,
0.6222617626190186,
0.1479904055595398,
0.15523606538772583,
0.38221311569213867,
0.1009344831109047,
-0.08788469433784485,
-0.2404811978340149,
0.313900351524353,
0.1148008406162262,
-0.39394763112068176,
-0.3623136281967163,
0.2042005956172943,
-0.2805655598640442,
0.22935116291046143,
0.06943339109420776,
0.16647127270698547,
0.08447271585464478,
-0.1230989471077919,
0.26120567321777344,
0.31291449069976807,
0.004651205614209175,
-0.13495278358459473,
-0.09768775850534439,
0.0522313192486763,
-0.07296288758516312,
0.23544877767562866,
0.10745201259851456,
0.1639312356710434,
-0.01664864271879196,
-0.43312445282936096,
-0.08164000511169434,
-0.13500460982322693,
0.16052022576332092,
-0.12132032215595245,
-0.5605202317237854,
-0.03214416280388832,
-0.14209012687206268,
0.1316174864768982,
-0.09903281182050705,
-0.305805504322052,
0.13915681838989258,
-0.08490349352359772,
0.2681118845939636,
-0.09449831396341324,
0.13290256261825562,
-0.03960466757416725,
0.048502255231142044,
-0.44950002431869507,
-0.06491013616323471,
0.32811102271080017,
0.2135879248380661,
0.052876412868499756,
0.13712136447429657,
-0.001447327435016632,
0.07443195581436157,
0.35362860560417175,
0.054831210523843765,
-0.010001584887504578,
0.04295624420046806,
0.07790768146514893,
-0.30953723192214966,
-0.027146007865667343,
0.21304695308208466,
-0.3466987609863281,
-0.135694682598114,
-0.16489878296852112,
-0.2356416881084442,
0.1343439370393753,
-0.014896339736878872,
-0.18980468809604645,
-0.2510468661785126,
-0.5263704657554626,
0.659267246723175,
-0.030561067163944244,
-0.057073093950748444,
-0.12782695889472961,
0.32526862621307373,
-0.24029703438282013,
-0.07828085869550705,
0.12975382804870605,
0.045841217041015625,
0.03465936705470085,
-0.37421631813049316,
-0.09624490141868591,
-0.08568520843982697,
-0.04035698622465134,
0.30118250846862793,
-0.18863238394260406,
0.2752721905708313,
0.09550352394580841,
0.13118724524974823,
0.21981319785118103,
-0.48723840713500977,
-0.03061848320066929,
0.29354098439216614,
-0.02629059925675392,
0.37811198830604553,
0.07428215444087982,
0.24824485182762146,
-0.04977637156844139,
-0.18438968062400818,
0.25284382700920105,
0.9806959629058838,
-0.3445678651332855,
0.007813209667801857,
-0.12597227096557617,
-0.3848101496696472,
0.593819797039032,
0.3565863072872162,
0.1247875839471817,
-0.28234657645225525,
-0.13511595129966736,
0.08289138972759247,
0.09046825021505356,
0.11593087017536163,
0.07905609905719757,
-0.09205912053585052,
-0.3260628283023834,
0.023914657533168793,
-0.16235792636871338,
-0.11649957299232483,
-0.4359433054924011,
0.010673858225345612,
-0.029216019436717033,
0.35977673530578613,
0.21428415179252625,
-0.10928668826818466,
0.2714816927909851,
-0.2791427969932556,
-0.12076298892498016,
-0.3025941848754883,
0.07069007307291031,
-0.1252288818359375,
-0.0336623452603817,
-0.28421685099601746,
-0.014253232628107071,
0.28782302141189575,
0.17413687705993652,
-0.09134804457426071,
-0.4625680446624756,
0.3106144964694977,
-0.1135096624493599,
0.07947522401809692,
-0.07837453484535217,
0.6710865497589111,
-0.13304346799850464,
-0.05170928314328194,
0.18674391508102417,
0.2545601725578308,
-0.30537280440330505,
0.2602539658546448,
0.3174130320549011,
0.3043522834777832,
0.19623766839504242,
-0.05067839100956917,
0.08027397096157074,
0.07100621610879898,
-0.006333452183753252,
-0.2542903423309326,
-0.168838769197464,
0.45542824268341064,
-0.17983192205429077,
0.46422210335731506,
-0.07356216758489609,
-0.006369562819600105,
-0.20803198218345642,
-0.04436568543314934,
-0.2130458801984787,
0.44610467553138733,
0.29147422313690186,
-0.16969943046569824,
0.21452738344669342,
-0.10940782725811005,
-0.35217347741127014,
0.14893800020217896,
0.13902010023593903,
0.03116176277399063,
0.03513643145561218,
0.012584585696458817,
0.006687812507152557,
-0.2945304214954376,
-0.11442479491233826,
0.2900373935699463,
0.5758762955665588,
0.218854159116745,
0.13711366057395935,
0.01795647293329239,
-0.20882201194763184,
-0.09033512324094772,
0.013694152235984802,
0.2752791941165924,
0.01692286692559719,
0.19390946626663208,
0.015642074868083,
0.06455541402101517,
0.04245805740356445,
-0.20732952654361725,
0.15761087834835052,
-0.20261123776435852,
-0.0598207488656044,
0.03191634267568588,
-0.18620602786540985,
-0.5582317113876343,
-0.25548040866851807,
-0.010924034751951694,
-0.3671207129955292,
-0.2729373276233673,
0.15407200157642365,
0.0434349849820137,
-0.16207273304462433,
0.1376049518585205,
0.2474062144756317,
0.6375616192817688,
-0.4645482301712036,
-0.23034031689167023,
-0.14063900709152222,
-0.3725029528141022,
-0.07144743204116821,
0.07383935153484344,
0.4597983956336975,
0.2861062288284302,
0.38312235474586487,
0.33520054817199707,
-0.07496833056211472,
0.10937522351741791,
-0.4088929295539856,
0.01039048284292221,
-0.28102684020996094,
0.24833275377750397,
0.08054860681295395,
-0.21447692811489105,
0.17429618537425995,
-0.39816129207611084,
-0.06309565901756287,
-0.02732512727379799,
-0.06673935800790787,
-0.004362684674561024,
-0.0064717913046479225,
0.08041532337665558,
-0.19725613296031952,
-0.16866174340248108,
-0.6268006563186646,
-0.4757333993911743,
0.32473599910736084,
-0.2877430319786072,
0.06258346885442734,
0.09646835178136826,
-0.27044060826301575,
0.12282240390777588,
-0.07755089551210403,
-0.006085807457566261,
-0.12584716081619263,
-0.042075514793395996,
0.027647659182548523,
-0.3368200957775116,
-0.14505460858345032,
-0.3748606741428375,
-0.09668285399675369,
0.22548219561576843,
-0.07548362761735916,
-0.014169111847877502,
-0.14891380071640015,
0.10138890147209167,
-0.16277535259723663,
0.1472623199224472,
0.13594429194927216,
0.1742737591266632,
-0.2007133513689041,
0.16263291239738464,
-0.018707377836108208,
-0.32956135272979736,
0.2292134165763855,
0.37306100130081177,
0.45728522539138794,
0.17798158526420593,
0.054322533309459686,
0.16411493718624115,
0.7202291488647461,
0.2120826542377472,
0.11296965181827545,
0.1207050234079361,
0.339720755815506,
-0.09869544208049774,
0.16566073894500732,
-0.23940826952457428,
0.2550593912601471,
-0.17682713270187378,
0.47674137353897095,
0.049709927290678024,
0.2018958032131195,
-0.20101477205753326,
-0.281904935836792,
-0.030092597007751465,
-0.29803550243377686,
-0.21822118759155273,
0.2677379250526428,
-0.2083997130393982,
0.040124133229255676,
-0.07382592558860779,
-0.40090104937553406,
-0.2804727256298065,
-0.06336963176727295,
0.056344639509916306,
0.4238353371620178,
-0.05789089947938919,
0.17249959707260132,
-0.33453816175460815,
-0.06981953233480453,
-0.40455499291419983,
0.05911160632967949,
0.0287389624863863,
0.23816978931427002,
-0.09146816283464432,
-0.06206570565700531,
-0.0657404214143753,
0.16588729619979858,
0.6495797038078308,
-0.47983986139297485,
-0.10412196815013885,
0.08365978300571442,
0.08293940126895905,
-0.043583016842603683,
-0.1442505419254303,
-0.24003960192203522,
-0.045977845788002014,
0.43813803791999817,
0.4039085805416107,
-0.3940846025943756,
-0.2811402976512909,
0.1908789575099945,
-0.25683602690696716,
-0.12578126788139343,
-0.23165160417556763,
-0.21141904592514038,
-0.17475789785385132,
-0.1496141254901886,
0.051150932908058167,
0.264576256275177,
0.21153360605239868,
-0.1040395125746727,
0.13656336069107056,
-0.01972043327987194,
0.23842531442642212,
0.21176308393478394,
-0.014663837850093842,
-0.0997283011674881,
0.2485458254814148,
0.12894083559513092,
0.03632749244570732,
-0.16067296266555786,
-0.34276020526885986,
0.07137365639209747,
0.04164756461977959,
0.1356404423713684,
0.28387314081192017,
-0.00841048639267683,
0.6613308787345886,
0.07133970409631729,
0.38200536370277405,
0.295071005821228,
-0.03617727756500244,
-0.006972946226596832,
-0.27927374839782715,
0.13812753558158875,
0.18902543187141418,
0.2439100444316864,
-0.19070518016815186,
-0.17326833307743073,
0.5538422465324402,
0.2548624277114868,
-0.10853821784257889,
0.38894686102867126,
-0.5794233083724976,
-0.28470340371131897,
0.28209590911865234,
0.06647150218486786,
0.7568140029907227,
-0.022754795849323273,
0.29468196630477905,
0.05107128620147705,
-0.46020108461380005,
0.5372833609580994,
-0.4241015911102295,
0.1517772525548935,
-0.048981014639139175,
-0.11968086659908295,
-0.010851796716451645,
-0.10564872622489929,
-0.10179810971021652,
0.30793994665145874,
-0.33810174465179443,
0.30630993843078613,
0.49197500944137573,
-0.23215794563293457,
-0.07935892790555954,
0.5174073576927185,
0.09096956253051758,
-0.3882366120815277,
0.00893926341086626,
0.008923366665840149,
-0.25484174489974976,
0.1692943274974823,
-0.19708052277565002,
-0.2969512343406677,
0.19138270616531372,
0.1274462193250656,
-0.2990952134132385,
0.08042872697114944,
0.08365587890148163,
0.2613987922668457,
0.32197779417037964,
0.001385912299156189,
0.30562031269073486,
-0.21544677019119263,
-0.08355700969696045,
-0.18756043910980225,
-0.10171757638454437,
0.16740213334560394,
-0.22281646728515625,
0.07013489305973053,
0.04552353546023369,
-0.18126130104064941,
0.5122028589248657,
-0.07783924788236618,
-0.12757037580013275,
-0.275188684463501,
0.25064870715141296,
-0.45339494943618774,
-0.2337384968996048,
0.1493915319442749,
0.14604678750038147,
0.2355833649635315,
-0.3322303891181946,
0.5851309299468994,
0.08234508335590363,
-0.005585554987192154,
0.01226550992578268,
0.18602252006530762,
-0.20392747223377228,
0.5055809617042542,
-0.3174498975276947,
0.04855109751224518,
0.08217541873455048,
-0.043954454362392426,
-0.1198650524020195,
-0.40590372681617737,
-0.09712445735931396,
0.3543564975261688,
0.09507563710212708,
0.025455109775066376,
-0.05688740685582161,
0.13590461015701294,
-0.1269838511943817,
-0.05918329581618309,
-0.1386878788471222,
-0.39263230562210083,
0.10445506870746613,
0.2105829417705536,
0.201763316988945,
0.16465380787849426,
-0.07526347041130066,
-0.25805097818374634,
-0.21936975419521332,
0.5150886178016663,
-0.02673773095011711,
0.20104709267616272,
-0.16419154405593872,
0.375638484954834,
0.42429500818252563,
0.5418851375579834,
-0.2086775302886963,
0.06487932801246643,
0.06177882105112076,
0.08104370534420013,
0.37772032618522644,
-0.2797585427761078,
0.04444727674126625,
0.22707773745059967,
-0.18765462934970856,
0.006583523005247116,
-0.27863770723342896,
-0.10919923335313797,
-0.2729395031929016,
0.13855046033859253,
0.147890105843544,
0.035220738500356674,
-0.003477866295725107,
-0.08391064405441284,
-0.045493949204683304,
-0.018514038994908333,
-0.061204250901937485,
-0.38703739643096924,
-0.02604971081018448,
0.18790309131145477,
-0.04360799118876457,
0.05576164275407791,
0.017927583307027817,
0.2448146641254425,
0.04288823530077934,
-0.06855219602584839,
0.36694198846817017,
0.09157950431108475,
0.15586097538471222,
-0.14030107855796814,
-0.2409391552209854,
0.020427793264389038,
0.2335359752178192,
0.139428973197937,
-0.009182199835777283,
0.19073864817619324,
-0.23085370659828186,
-0.13711145520210266,
0.1696343868970871,
0.12699580192565918,
0.07510606944561005,
-0.10606863349676132,
0.09852870553731918,
0.07580418139696121,
-0.11297906190156937,
-0.023444492369890213,
0.21591240167617798,
0.09666826575994492,
0.04326470568776131,
0.11526884138584137,
0.14180317521095276,
0.49411487579345703,
-0.2662070393562317,
0.08396876603364944,
0.1088305115699768,
-0.3563464283943176,
0.13451825082302094,
-0.1554356962442398,
-0.020224642008543015,
0.029280882328748703,
0.1533055156469345,
-0.01826348900794983,
0.11684288829565048,
-0.35832130908966064,
0.3812861144542694,
0.2211315631866455,
-0.003973167389631271,
0.03103131428360939,
0.20100942254066467,
0.050393808633089066,
-0.2398848980665207,
0.20653469860553741,
0.027465254068374634,
0.28734877705574036,
0.06632684916257858,
0.8376128673553467,
-0.2126876711845398,
-0.3841235935688019,
0.14744503796100616,
0.4088926911354065,
0.046499524265527725,
-0.20879638195037842,
0.16752348840236664,
0.13624891638755798,
-0.3738655149936676,
0.06661009788513184,
0.04919600859284401,
-0.14546628296375275,
0.6858696937561035,
-0.10418245196342468,
0.11888362467288971,
-0.07461725920438766,
-0.21313542127609253,
0.384389728307724,
0.16913066804409027,
-0.0546514056622982,
-0.06694069504737854,
0.13790003955364227,
-0.11123915016651154,
-0.1763106733560562,
0.49055102467536926,
0.20801791548728943,
0.009057771414518356,
-0.45847073197364807,
0.020228872075676918,
0.1295265257358551,
0.13868214190006256,
-0.05805091932415962,
0.17673495411872864,
0.47014448046684265,
-0.07212406396865845,
0.15682095289230347,
-0.03370370715856552,
-0.010842632502317429,
-0.12366794049739838,
0.04220827668905258,
-0.41784194111824036,
-0.3098796010017395,
0.5140645503997803,
0.09148631989955902,
-0.17002195119857788,
0.09728050231933594,
0.3429412841796875,
-0.6166440844535828,
-0.2568531334400177,
0.29943743348121643,
-0.11552081257104874,
-0.09028030931949615,
-0.23393946886062622,
0.0465732216835022,
0.1041128933429718,
0.6218817830085754,
0.14806923270225525,
0.3906702995300293,
-0.3981969654560089,
-0.10698513686656952,
-0.5736942887306213,
-0.23161479830741882,
0.13995277881622314,
-0.05170750617980957,
-0.17874516546726227,
0.09441905468702316,
-0.06492910534143448,
0.22461533546447754,
-0.256145179271698,
-0.019427163526415825,
0.21327170729637146,
0.09001754224300385,
-0.4094822406768799,
0.16877318918704987,
0.18962767720222473,
0.068280890583992,
0.3064979016780853,
-0.03220444172620773,
-0.15833808481693268,
0.20729203522205353,
-0.1309206485748291,
-0.13873668015003204,
-0.08773781359195709,
0.24361661076545715,
0.18980833888053894,
0.046843431890010834,
0.021143078804016113,
0.4844205677509308,
-0.004028007388114929,
-0.2120710015296936,
0.010847926139831543,
-0.0026888842694461346,
-0.3256473243236542,
-0.17872539162635803,
-0.07713405787944794,
0.20804090797901154,
-0.36006876826286316,
0.2944648563861847,
-0.009957587346434593,
-0.1363239586353302,
0.02387673407793045,
-0.008793317712843418,
-0.2192276418209076,
-0.025523681193590164,
0.03367118537425995,
0.23170852661132812,
0.24931330978870392,
0.6675169467926025,
0.01665070280432701,
0.09321210533380508,
-0.08999074250459671,
-0.05048945173621178,
0.026074931025505066,
-0.01502169854938984,
-0.24134978652000427,
-0.14494483172893524,
0.03302671015262604,
0.01468677818775177,
0.18479904532432556,
-0.7851413488388062,
-0.39457643032073975,
-0.021979182958602905,
0.03141116723418236,
0.0848199725151062,
0.701366126537323,
0.12302403151988983,
-0.1750701665878296,
-0.09732478857040405,
-0.34183692932128906,
0.020174965262413025,
-0.22876331210136414,
0.17516592144966125,
-0.36070096492767334
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | Another thought: Multitasking over benchmarks (represented as Meta-datasets in nlp) is probably a common use case. Would be nice to pass an entire benchmark to our `MultiDataset` wrapper rather than having to pass individual components. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 35 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
Another thought: Multitasking over benchmarks (represented as Meta-datasets in nlp) is probably a common use case. Would be nice to pass an entire benchmark to our `MultiDataset` wrapper rather than having to pass individual components. | [
-0.06561257690191269,
-0.3723561465740204,
-0.06819301843643188,
-0.049267709255218506,
-0.2852722406387329,
0.13376593589782715,
0.21648038923740387,
0.12065184116363525,
0.3021675944328308,
-0.1421176940202713,
-0.1687704473733902,
0.3203653395175934,
-0.16379880905151367,
0.3486941456794739,
0.4185852110385895,
-0.41218042373657227,
0.031688444316387177,
-0.21076568961143494,
-0.21456116437911987,
0.4246906638145447,
0.0625796988606453,
0.08338528871536255,
-0.16562975943088531,
0.10172660648822784,
-0.29676884412765503,
-0.1877509206533432,
-0.33034709095954895,
0.12289676070213318,
0.1802750527858734,
-0.006745514459908009,
0.21674300730228424,
0.3386645019054413,
-0.005247997120022774,
0.07626133412122726,
-0.00011275351425865665,
-0.07976371049880981,
0.21804775297641754,
-0.05337457358837128,
0.10312984883785248,
-0.013962417840957642,
0.19306248426437378,
-0.36390167474746704,
0.04667441546916962,
-0.10680350661277771,
0.168757826089859,
0.1935688704252243,
0.17223404347896576,
-0.07640406489372253,
0.3412652909755707,
-0.2545016407966614,
0.10234159231185913,
0.3156692087650299,
-0.23991090059280396,
0.29766952991485596,
-0.11138313263654709,
-0.08681921660900116,
0.011975457891821861,
0.24389182031154633,
0.671851396560669,
-0.6273881196975708,
-0.06007193773984909,
0.057241737842559814,
-0.03238601237535477,
0.04977741837501526,
0.09267555177211761,
-0.13015508651733398,
-0.3021056056022644,
-0.21089527010917664,
-0.33772188425064087,
0.25109922885894775,
-0.15973111987113953,
-0.13706070184707642,
-0.22889843583106995,
-0.5552747249603271,
-0.013059410266578197,
0.051291950047016144,
-0.3080897033214569,
0.031833216547966,
-0.17259512841701508,
-0.006247218698263168,
-0.10114537924528122,
-0.12405448406934738,
0.057553812861442566,
0.08909878879785538,
0.33570656180381775,
0.5584868788719177,
0.12079384922981262,
0.1740795075893402,
0.36989516019821167,
0.0731532946228981,
-0.08478496223688126,
-0.25911930203437805,
0.27419862151145935,
0.10016472637653351,
-0.4158090353012085,
-0.31035926938056946,
0.1395321786403656,
-0.2330121099948883,
0.3023061752319336,
0.09700149297714233,
0.13515186309814453,
0.11098425835371017,
-0.12362208217382431,
0.2736952304840088,
0.3402844965457916,
0.03425619378685951,
-0.07769947499036789,
-0.16922658681869507,
0.010786432772874832,
-0.14165517687797546,
0.18027429282665253,
0.11355341970920563,
0.20747898519039154,
0.02580343186855316,
-0.43926802277565,
-0.13691231608390808,
-0.22848019003868103,
0.163488507270813,
-0.25956225395202637,
-0.5688910484313965,
-0.11211642622947693,
-0.09568820148706436,
0.06208207085728645,
-0.1388760209083557,
-0.26140207052230835,
0.13918064534664154,
-0.09216346591711044,
0.26953399181365967,
-0.06885512173175812,
0.006288326345384121,
-0.05109159275889397,
0.08796742558479309,
-0.45554232597351074,
-0.010129228234291077,
0.33236196637153625,
0.10064949095249176,
0.08620400726795197,
0.1457323431968689,
-0.019783131778240204,
0.062231436371803284,
0.38701415061950684,
0.011976772919297218,
-0.004459694027900696,
-0.012135099619626999,
0.18673944473266602,
-0.3140554130077362,
0.02921934798359871,
0.18315307796001434,
-0.3368549346923828,
-0.08135093003511429,
-0.14553308486938477,
-0.14867334067821503,
0.1425742655992508,
0.03213296830654144,
-0.22536857426166534,
-0.28603845834732056,
-0.5482082962989807,
0.6673356294631958,
-0.011244222521781921,
-0.06299498677253723,
-0.16312560439109802,
0.3023531436920166,
-0.3023782968521118,
-0.09308987855911255,
0.17095297574996948,
0.013165690004825592,
0.021748218685388565,
-0.27748388051986694,
-0.16175632178783417,
-0.07043299078941345,
-0.10190135985612869,
0.3153511583805084,
-0.1921916902065277,
0.30844223499298096,
0.04201127588748932,
0.1713876873254776,
0.2346702516078949,
-0.48465967178344727,
-0.032916322350502014,
0.3313533663749695,
-0.07133089005947113,
0.401894748210907,
0.050246935337781906,
0.22615402936935425,
0.055643998086452484,
-0.17825017869472504,
0.23286056518554688,
0.9699898958206177,
-0.3880669176578522,
0.009526556357741356,
-0.08592958003282547,
-0.3920598328113556,
0.5433835983276367,
0.3569908142089844,
0.059595491737127304,
-0.24156567454338074,
-0.14711663126945496,
-0.012277972884476185,
0.08712254464626312,
0.10982911288738251,
0.09951728582382202,
-0.07516493648290634,
-0.42072439193725586,
0.023374471813440323,
-0.2236105054616928,
-0.19864052534103394,
-0.43184375762939453,
0.018178671598434448,
0.021138910204172134,
0.22960224747657776,
0.3293682634830475,
-0.13701951503753662,
0.24782595038414001,
-0.279499351978302,
-0.046550583094358444,
-0.37557777762413025,
0.1250409185886383,
-0.051529660820961,
0.008913092315196991,
-0.20238712430000305,
-0.04816081374883652,
0.3567744493484497,
0.17522487044334412,
-0.12952224910259247,
-0.3912130892276764,
0.3071179986000061,
-0.052944689989089966,
0.03812495991587639,
-0.040555454790592194,
0.6141847968101501,
-0.21523290872573853,
-0.057151585817337036,
0.1891898810863495,
0.24514198303222656,
-0.27274125814437866,
0.28847983479499817,
0.35366785526275635,
0.27539190649986267,
0.19267572462558746,
-0.03591683506965637,
0.054176971316337585,
0.06028128042817116,
-0.032949987798929214,
-0.2539370059967041,
-0.05172360688447952,
0.49388670921325684,
-0.12789620459079742,
0.46705737709999084,
-0.06947565078735352,
0.053518541157245636,
-0.1416846364736557,
-0.03650067746639252,
-0.1959550529718399,
0.44116976857185364,
0.29005083441734314,
-0.21228128671646118,
0.3862041234970093,
-0.10933716595172882,
-0.3189101815223694,
0.17448747158050537,
0.13803300261497498,
0.0512457899749279,
0.06468277424573898,
-0.009072475135326385,
-0.03657042235136032,
-0.272716224193573,
-0.0716029703617096,
0.3707674443721771,
0.6577780246734619,
0.23860488831996918,
0.17744719982147217,
0.014817635528743267,
-0.22931432723999023,
-0.0808015987277031,
-0.031207077205181122,
0.19398143887519836,
0.026519775390625,
0.09888973087072372,
0.013474501669406891,
0.022317294031381607,
0.048615291714668274,
-0.140078604221344,
0.15098978579044342,
-0.16983996331691742,
-0.009785115718841553,
0.04137495905160904,
-0.22050823271274567,
-0.5566984415054321,
-0.21707725524902344,
0.029173608869314194,
-0.3283434808254242,
-0.2532225251197815,
0.10271672159433365,
0.12225048243999481,
-0.13139253854751587,
0.1512339860200882,
0.23217689990997314,
0.6160979270935059,
-0.4460151791572571,
-0.2688652276992798,
-0.08353511989116669,
-0.3008219003677368,
-0.11323411017656326,
0.12900160253047943,
0.45876020193099976,
0.301447331905365,
0.3852967321872711,
0.3329293727874756,
-0.009069617837667465,
-0.021664714440703392,
-0.34239283204078674,
-0.03896350413560867,
-0.2504136562347412,
0.25898978114128113,
0.03648291528224945,
-0.24169911444187164,
0.14477303624153137,
-0.38711997866630554,
-0.0762285441160202,
-0.076802097260952,
-0.07060395181179047,
-0.08701084554195404,
0.031285360455513,
0.1460472047328949,
-0.18527090549468994,
-0.15247860550880432,
-0.5852789282798767,
-0.47434401512145996,
0.29749834537506104,
-0.29475653171539307,
0.05387391522526741,
-0.10809855908155441,
-0.31336092948913574,
0.19335013628005981,
-0.12611320614814758,
-0.019432134926319122,
-0.13752521574497223,
-0.09073202311992645,
-0.05549386516213417,
-0.33968839049339294,
-0.15745006501674652,
-0.39757785201072693,
-0.0830496996641159,
0.2783389091491699,
-0.04936185106635094,
-0.042478594928979874,
-0.15597312152385712,
0.13113842904567719,
-0.15483488142490387,
0.06006859242916107,
0.09263874590396881,
0.17417500913143158,
-0.23634229600429535,
0.12928353250026703,
-0.028270836919546127,
-0.26209717988967896,
0.23682940006256104,
0.28308534622192383,
0.3746201694011688,
0.17052826285362244,
0.022374117746949196,
0.238032728433609,
0.7015316486358643,
0.23946097493171692,
0.05487408488988876,
0.16642330586910248,
0.28170809149742126,
-0.023641463369131088,
0.11926232278347015,
-0.2199317067861557,
0.15194281935691833,
-0.1884620487689972,
0.4781736135482788,
0.10397278517484665,
0.15760928392410278,
-0.25659656524658203,
-0.27070897817611694,
0.030139897018671036,
-0.2531300187110901,
-0.17043861746788025,
0.21320009231567383,
-0.3159545958042145,
0.03342357650399208,
-0.06611943244934082,
-0.39819636940956116,
-0.22175011038780212,
-0.01891930401325226,
-0.014532038941979408,
0.28800368309020996,
-0.04299434274435043,
0.1606459766626358,
-0.3352032005786896,
-0.031863465905189514,
-0.408568799495697,
0.11785230040550232,
0.09698818624019623,
0.33181166648864746,
-0.08659662306308746,
-0.045031748712062836,
-0.08494347333908081,
0.11186127364635468,
0.5522233247756958,
-0.4672243297100067,
-0.09274457395076752,
0.10849891602993011,
0.06989067047834396,
-0.09652112424373627,
-0.08832485973834991,
-0.2206001579761505,
0.045805923640728,
0.42899057269096375,
0.3607071042060852,
-0.2990397810935974,
-0.28864553570747375,
0.15508930385112762,
-0.21957731246948242,
-0.04865565150976181,
-0.18476983904838562,
-0.21510964632034302,
-0.1798703968524933,
-0.13402646780014038,
0.06568881869316101,
0.23183833062648773,
0.2185508757829666,
-0.08076180517673492,
0.15293242037296295,
-0.11033450067043304,
0.15788644552230835,
0.1860540509223938,
-0.043711405247449875,
-0.09453729540109634,
0.15242967009544373,
0.20288051664829254,
0.013336161151528358,
-0.1537550985813141,
-0.30702757835388184,
0.02104792185127735,
0.013778546825051308,
0.13222724199295044,
0.24650096893310547,
-0.017967522144317627,
0.6386029720306396,
-0.04344119131565094,
0.3078649342060089,
0.3434125781059265,
-0.15040098130702972,
-0.06010924279689789,
-0.28928837180137634,
0.16420391201972961,
0.18684609234333038,
0.2574945390224457,
-0.12326844781637192,
-0.187174990773201,
0.5725806355476379,
0.33587220311164856,
-0.06958144903182983,
0.4539729654788971,
-0.5722923874855042,
-0.31260859966278076,
0.24356551468372345,
0.05923977866768837,
0.5774691104888916,
-0.08398005366325378,
0.2616599202156067,
-0.0199696384370327,
-0.41017359495162964,
0.5315449237823486,
-0.37374430894851685,
0.1534079760313034,
-0.05188099294900894,
-0.24385567009449005,
0.020601386204361916,
-0.08406281471252441,
-0.007088042795658112,
0.3127877712249756,
-0.3229181170463562,
0.3246552050113678,
0.48921066522598267,
-0.22829663753509521,
-0.0012176278978586197,
0.5655282139778137,
0.025864582508802414,
-0.37018075585365295,
0.01694345660507679,
0.06858357042074203,
-0.2902955412864685,
0.08192048966884613,
-0.15320712327957153,
-0.21072693169116974,
0.22035029530525208,
0.17975349724292755,
-0.352019727230072,
0.058837808668613434,
0.026805616915225983,
0.21444062888622284,
0.20536550879478455,
0.03536912798881531,
0.2878018915653229,
-0.17419615387916565,
-0.060969769954681396,
-0.15786191821098328,
-0.08689059317111969,
0.12871664762496948,
-0.19305962324142456,
0.0364055410027504,
0.09449713677167892,
-0.20959554612636566,
0.45646899938583374,
-0.060330793261528015,
-0.14519859850406647,
-0.22870060801506042,
0.27023714780807495,
-0.5092924237251282,
-0.14957068860530853,
0.1981714516878128,
0.147306427359581,
0.28635287284851074,
-0.29994630813598633,
0.5590230822563171,
0.10002879798412323,
-0.015114353969693184,
0.04153593257069588,
0.19969823956489563,
-0.23633220791816711,
0.5029985308647156,
-0.3028043806552887,
-0.015231341123580933,
0.06073188781738281,
0.05679795891046524,
-0.1458495557308197,
-0.3981848657131195,
-0.07032734155654907,
0.2884272634983063,
0.14057910442352295,
-0.004567045718431473,
0.0554143562912941,
0.09924254566431046,
0.050652071833610535,
0.019722655415534973,
-0.20058375597000122,
-0.324292927980423,
0.13359788060188293,
0.14717687666416168,
0.20381349325180054,
0.22745782136917114,
-0.0952349454164505,
-0.3026587665081024,
-0.19763077795505524,
0.45944756269454956,
-0.029067862778902054,
0.17826800048351288,
-0.12853685021400452,
0.34765633940696716,
0.40746334195137024,
0.5269021987915039,
-0.2459169179201126,
0.11764289438724518,
0.04560831934213638,
0.1269548535346985,
0.5051091909408569,
-0.21541807055473328,
-0.0042850300669670105,
0.3125104010105133,
-0.13643276691436768,
0.06286744773387909,
-0.2663431763648987,
-0.16179120540618896,
-0.19228850305080414,
0.10798419266939163,
0.12295631319284439,
0.025694001466035843,
0.02970491349697113,
-0.11089315265417099,
-0.09539107978343964,
-0.040935371071100235,
-0.055806245654821396,
-0.3989924490451813,
-0.06124714016914368,
0.09844258427619934,
-0.06748118996620178,
0.07659310102462769,
0.024723634123802185,
0.2167934626340866,
-0.03503827005624771,
-0.1232563853263855,
0.24483482539653778,
0.11760400980710983,
0.17357222735881805,
-0.15246367454528809,
-0.1608661264181137,
-0.036695994436740875,
0.22497503459453583,
0.1443028301000595,
-0.05042234808206558,
0.19050449132919312,
-0.23372295498847961,
-0.07541358470916748,
0.24634647369384766,
0.10478648543357849,
0.09123042970895767,
-0.08847752213478088,
0.17272531986236572,
0.10370082408189774,
-0.08446706831455231,
-0.020609991624951363,
0.23100976645946503,
0.05959821864962578,
0.11645430326461792,
0.13184748589992523,
0.1963878571987152,
0.46792519092559814,
-0.18571580946445465,
-0.0031028352677822113,
0.11268300563097,
-0.38476091623306274,
0.12622153759002686,
-0.1879337579011917,
-0.07245918363332748,
-0.028666596859693527,
0.13434644043445587,
-0.017931785434484482,
0.1367465853691101,
-0.2621413469314575,
0.3380008637905121,
0.3889702558517456,
0.0716743916273117,
-0.007467169314622879,
0.22169539332389832,
0.06501398980617523,
-0.15316633880138397,
0.25695449113845825,
0.05426362156867981,
0.3002220690250397,
0.012245923280715942,
0.8360199928283691,
-0.324025422334671,
-0.4433022141456604,
0.11316011101007462,
0.36561208963394165,
0.051835596561431885,
-0.21638917922973633,
0.23777315020561218,
0.13523787260055542,
-0.33631283044815063,
0.0876116156578064,
0.06379147619009018,
-0.1809615045785904,
0.7053232192993164,
-0.1334047168493271,
0.14903201162815094,
-0.08333371579647064,
-0.2459767758846283,
0.36664891242980957,
0.1151495948433876,
-0.07119186222553253,
-0.00048232264816761017,
0.05708689987659454,
-0.11510632932186127,
-0.17619889974594116,
0.53257817029953,
0.18094301223754883,
0.018203895539045334,
-0.44259965419769287,
0.01007156539708376,
0.014929790049791336,
0.17563772201538086,
-0.07289613783359528,
0.1774269938468933,
0.4411538541316986,
-0.1820056140422821,
0.24563755095005035,
0.005940483883023262,
-0.04617801681160927,
-0.1398257613182068,
0.046848829835653305,
-0.4108136296272278,
-0.4485563635826111,
0.4289397895336151,
0.07663736492395401,
-0.12908506393432617,
0.08759172260761261,
0.36286261677742004,
-0.5635618567466736,
-0.25134044885635376,
0.31865552067756653,
-0.20191657543182373,
-0.1316317617893219,
-0.20967750251293182,
0.0823572501540184,
0.049965281039476395,
0.6422715783119202,
0.20109823346138,
0.39153286814689636,
-0.3583631217479706,
-0.17929266393184662,
-0.5960274338722229,
-0.17861217260360718,
0.08641770482063293,
-0.08518502861261368,
-0.22825589776039124,
0.1549057960510254,
-0.11009537428617477,
0.33917397260665894,
-0.17584379017353058,
0.07582423090934753,
0.2411535084247589,
0.00003824010491371155,
-0.414818674325943,
0.09212320297956467,
0.12537765502929688,
-0.017391210421919823,
0.28541383147239685,
-0.10768580436706543,
-0.14416517317295074,
0.1217658519744873,
-0.07111340016126633,
-0.07582584768533707,
-0.11642725765705109,
0.2526834011077881,
0.1565539836883545,
0.1055905669927597,
0.01008404977619648,
0.4512917101383209,
0.01785183697938919,
-0.1485949009656906,
-0.051521334797143936,
0.03749128058552742,
-0.3527217209339142,
-0.18147292733192444,
-0.10226456820964813,
0.14909955859184265,
-0.4346385598182678,
0.29576852917671204,
0.02136603742837906,
-0.06180842965841293,
0.1016729325056076,
0.005676994565874338,
-0.25479844212532043,
-0.058563075959682465,
0.031436383724212646,
0.1994289755821228,
0.2543521523475647,
0.7323935627937317,
-0.00232667475938797,
0.1040797159075737,
-0.05692112073302269,
0.03094632364809513,
-0.02811811864376068,
-0.08862250298261642,
-0.25010132789611816,
-0.13463179767131805,
0.05298812687397003,
0.07657415419816971,
0.0841163694858551,
-0.6738630533218384,
-0.40565288066864014,
0.053689200431108475,
0.022415632382035255,
0.05789883807301521,
0.7152572274208069,
0.02755647711455822,
-0.1257437765598297,
-0.1139771044254303,
-0.3888225853443146,
0.008579626679420471,
-0.22798483073711395,
0.21922320127487183,
-0.40185993909835815
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | Here's a fully working implementation based on the `__iter__` function of @zphang.
- I've generated the task choice list in the constructor as it allows us to index into the MultiDataset just like a normal dataset. I'm changing `task_choice_list` into a list of `(dataset_idx, example_idx)` so each entry references a unique dataset example. The shuffling has to be done before this as we don't want to shuffle within each task (we assume this is done by the user if this is what they intend).
- I'm slightly concerned this list could become very large if many large datasets were used. Can't see a way round it at the moment though.
- I've used `task.info.builder_name` as the dataset name. Not sure if this is correct.
- I'd love to add some of the other `Dataset` methods (map, slicing by column, etc...). Would be great to implement the whole interface so a single dataset can be simply replaced by this.
- This does everything on the individual example-level. If some application required batches all from a single task in turn we can't really do that.
```python
import nlp
import numpy as np
class MultiDataset:
def __init__(self,tasks):
self.tasks = tasks
# Create random order of tasks
# Using size-proportional sampling
task_choice_list = []
for i, task in enumerate(self.tasks):
task_choice_list += [i] * len(task)
task_choice_list = np.array(task_choice_list)
np.random.shuffle(task_choice_list)
# Add index into each dataset
# - We don't want to shuffle within each task
counters = {}
self.task_choice_list = []
for i in range(len(task_choice_list)):
idx = counters.get(task_choice_list[i],0)
self.task_choice_list.append((task_choice_list[i],idx))
counters[task_choice_list[i]] = idx + 1
def __len__(self):
return np.sum([len(t) for t in self.tasks])
def __repr__(self):
task_str = ", ".join([str(t) for t in self.tasks])
return f"MultiDataset(tasks: {task_str})"
def __getitem__(self,key):
if isinstance(key, int):
task_idx, example_idx = self.task_choice_list[key]
task = self.tasks[task_idx]
example = task[example_idx]
example["task_name"] = task.info.builder_name
return example
elif isinstance(key, slice):
raise NotImplementedError()
def __iter__(self):
for i in range(len(self)):
yield self[i]
def load_multitask(*datasets):
'''Create multitask datasets per split'''
def _get_common_splits(datasets):
'''Finds the common splits present in all self.datasets'''
min_set = None
for dataset in datasets:
if min_set != None:
min_set.intersection(set(dataset.keys()))
else:
min_set = set(dataset.keys())
return min_set
common_splits = _get_common_splits(datasets)
out = {}
for split in common_splits:
out[split] = MultiDataset([d[split] for d in datasets])
return out
##########################################
# Dataset Flattening
def flatten(dataset,flatten_fn):
for k in dataset.keys():
if isinstance(dataset[k],nlp.Dataset):
dataset[k] = dataset[k].map(flatten_fn,remove_columns=dataset[k].column_names)
# Squad
def flatten_squad(example):
return {"source": "squad context: " + example['context'] + " question: " + example['question'],
"target":example["answers"]["text"]}
squad = nlp.load_dataset("squad")
flatten(squad,flatten_squad)
# CNN_DM
def flatten_cnn_dm(example):
return {"source": "cnn_dm: " + example['article'],"target":[example["highlights"]]}
cnn_dm = nlp.load_dataset("cnn_dailymail", "3.0.0")
flatten(cnn_dm,flatten_cnn_dm)
#############################################
mtds = load_multitask(squad,cnn_dm)
for example in mtds["train"]:
print(example["task_name"],example["target"])
```
Let me know if you have any thoughts. I've started using this in some of my projects and it seems to work. If people are happy with the general approach for a first version, I can make a pull request. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 469 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
Here's a fully working implementation based on the `__iter__` function of @zphang.
- I've generated the task choice list in the constructor as it allows us to index into the MultiDataset just like a normal dataset. I'm changing `task_choice_list` into a list of `(dataset_idx, example_idx)` so each entry references a unique dataset example. The shuffling has to be done before this as we don't want to shuffle within each task (we assume this is done by the user if this is what they intend).
- I'm slightly concerned this list could become very large if many large datasets were used. Can't see a way round it at the moment though.
- I've used `task.info.builder_name` as the dataset name. Not sure if this is correct.
- I'd love to add some of the other `Dataset` methods (map, slicing by column, etc...). Would be great to implement the whole interface so a single dataset can be simply replaced by this.
- This does everything on the individual example-level. If some application required batches all from a single task in turn we can't really do that.
```python
import nlp
import numpy as np
class MultiDataset:
def __init__(self,tasks):
self.tasks = tasks
# Create random order of tasks
# Using size-proportional sampling
task_choice_list = []
for i, task in enumerate(self.tasks):
task_choice_list += [i] * len(task)
task_choice_list = np.array(task_choice_list)
np.random.shuffle(task_choice_list)
# Add index into each dataset
# - We don't want to shuffle within each task
counters = {}
self.task_choice_list = []
for i in range(len(task_choice_list)):
idx = counters.get(task_choice_list[i],0)
self.task_choice_list.append((task_choice_list[i],idx))
counters[task_choice_list[i]] = idx + 1
def __len__(self):
return np.sum([len(t) for t in self.tasks])
def __repr__(self):
task_str = ", ".join([str(t) for t in self.tasks])
return f"MultiDataset(tasks: {task_str})"
def __getitem__(self,key):
if isinstance(key, int):
task_idx, example_idx = self.task_choice_list[key]
task = self.tasks[task_idx]
example = task[example_idx]
example["task_name"] = task.info.builder_name
return example
elif isinstance(key, slice):
raise NotImplementedError()
def __iter__(self):
for i in range(len(self)):
yield self[i]
def load_multitask(*datasets):
'''Create multitask datasets per split'''
def _get_common_splits(datasets):
'''Finds the common splits present in all self.datasets'''
min_set = None
for dataset in datasets:
if min_set != None:
min_set.intersection(set(dataset.keys()))
else:
min_set = set(dataset.keys())
return min_set
common_splits = _get_common_splits(datasets)
out = {}
for split in common_splits:
out[split] = MultiDataset([d[split] for d in datasets])
return out
##########################################
# Dataset Flattening
def flatten(dataset,flatten_fn):
for k in dataset.keys():
if isinstance(dataset[k],nlp.Dataset):
dataset[k] = dataset[k].map(flatten_fn,remove_columns=dataset[k].column_names)
# Squad
def flatten_squad(example):
return {"source": "squad context: " + example['context'] + " question: " + example['question'],
"target":example["answers"]["text"]}
squad = nlp.load_dataset("squad")
flatten(squad,flatten_squad)
# CNN_DM
def flatten_cnn_dm(example):
return {"source": "cnn_dm: " + example['article'],"target":[example["highlights"]]}
cnn_dm = nlp.load_dataset("cnn_dailymail", "3.0.0")
flatten(cnn_dm,flatten_cnn_dm)
#############################################
mtds = load_multitask(squad,cnn_dm)
for example in mtds["train"]:
print(example["task_name"],example["target"])
```
Let me know if you have any thoughts. I've started using this in some of my projects and it seems to work. If people are happy with the general approach for a first version, I can make a pull request. | [
-0.002134092152118683,
-0.39335891604423523,
-0.04490877687931061,
0.011329784989356995,
-0.22390787303447723,
0.021761052310466766,
0.19789783656597137,
0.027536004781723022,
0.41430220007896423,
-0.19782714545726776,
-0.23707209527492523,
0.39821067452430725,
-0.19453246891498566,
0.302828848361969,
0.3515961468219757,
-0.4019326865673065,
-0.022123195230960846,
-0.24198278784751892,
-0.2949601113796234,
0.35135418176651,
0.060441792011260986,
0.19776856899261475,
-0.21249975264072418,
0.06919260323047638,
-0.21596956253051758,
-0.17891055345535278,
-0.3551909029483795,
0.15981325507164001,
0.0868036150932312,
0.008535115979611874,
0.2525821328163147,
0.42071613669395447,
-0.047911107540130615,
0.1720024198293686,
-0.00011538730177562684,
-0.04062813147902489,
0.22244948148727417,
-0.12262426316738129,
0.05334298685193062,
-0.0625763088464737,
0.1727963387966156,
-0.41804441809654236,
0.07642097771167755,
-0.17792534828186035,
0.168304443359375,
0.1507711559534073,
0.12851466238498688,
0.018031105399131775,
0.39563190937042236,
-0.26081591844558716,
0.10167448222637177,
0.3133843243122101,
-0.15474574267864227,
0.3200138211250305,
-0.13475903868675232,
-0.021238267421722412,
0.025054844096302986,
0.25627315044403076,
0.6043381690979004,
-0.547825813293457,
-0.039860256016254425,
0.09073145687580109,
0.020382096990942955,
-0.08250826597213745,
0.12837648391723633,
-0.027154281735420227,
-0.3430268168449402,
-0.2517932951450348,
-0.3898296058177948,
0.220865398645401,
-0.0587255135178566,
-0.18009454011917114,
-0.22417059540748596,
-0.5440153479576111,
-0.05742250755429268,
0.0014682058244943619,
-0.2000161111354828,
-0.09796569496393204,
-0.20692285895347595,
-0.07884536683559418,
-0.08055788278579712,
-0.10031530261039734,
-0.05526137351989746,
0.1227860078215599,
0.28622689843177795,
0.5722646713256836,
0.09168432652950287,
0.16959592700004578,
0.4112890958786011,
-0.00377008318901062,
-0.1038934737443924,
-0.27631962299346924,
0.2889995872974396,
0.10878873616456985,
-0.4652678370475769,
-0.35177066922187805,
0.2077229917049408,
-0.27356263995170593,
0.2420552670955658,
0.11815419048070908,
0.1267671287059784,
0.14092016220092773,
-0.17259527742862701,
0.23502519726753235,
0.31019917130470276,
0.16164404153823853,
-0.08544173091650009,
-0.14018547534942627,
-0.0408443957567215,
-0.10049774497747421,
0.2605676054954529,
0.09310336410999298,
0.13976170122623444,
-0.024156570434570312,
-0.43835675716400146,
-0.1129164919257164,
-0.1902087926864624,
0.17506974935531616,
-0.23685747385025024,
-0.46511077880859375,
-0.1156223937869072,
-0.13347432017326355,
0.16438165307044983,
-0.0893157348036766,
-0.32635942101478577,
0.09385561943054199,
-0.06360591948032379,
0.22851410508155823,
-0.16430963575839996,
0.09540645778179169,
-0.05092413350939751,
0.07936447858810425,
-0.4200189709663391,
-0.10349610447883606,
0.3041563630104065,
0.20076040923595428,
0.08877842128276825,
0.10183322429656982,
0.041355617344379425,
0.16144338250160217,
0.3386405408382416,
-0.018589990213513374,
0.07116767764091492,
-0.00675012543797493,
0.1700589954853058,
-0.24186667799949646,
0.023634018376469612,
0.08572132885456085,
-0.327629029750824,
-0.14327853918075562,
-0.1162455603480339,
-0.17121268808841705,
0.09555090963840485,
0.001571817323565483,
-0.2470017969608307,
-0.21890217065811157,
-0.5296895503997803,
0.6929859519004822,
0.009013980627059937,
-0.07522498071193695,
-0.17376235127449036,
0.21700376272201538,
-0.2249675691127777,
-0.11346260458230972,
0.18577587604522705,
0.13063430786132812,
-0.019459588453173637,
-0.2366185039281845,
-0.08683812618255615,
-0.11565864086151123,
0.007798895239830017,
0.25118836760520935,
-0.1722692847251892,
0.311110258102417,
0.0009649060666561127,
0.25110113620758057,
0.26969873905181885,
-0.4574740529060364,
-0.08002284914255142,
0.29960525035858154,
-0.07061275094747543,
0.49156177043914795,
0.06509648263454437,
0.2020913064479828,
0.01994803547859192,
-0.20112177729606628,
0.27416419982910156,
0.9725066423416138,
-0.3398754298686981,
-0.045466549694538116,
-0.13535133004188538,
-0.3082437217235565,
0.5843701958656311,
0.2936512231826782,
0.0460602231323719,
-0.23651698231697083,
-0.1625548005104065,
0.025136027485132217,
0.13693943619728088,
0.11461334675550461,
0.10209725052118301,
-0.043395839631557465,
-0.3110347390174866,
0.06801388412714005,
-0.16123905777931213,
-0.13331198692321777,
-0.4370240569114685,
0.03781503438949585,
0.04610864818096161,
0.34421592950820923,
0.1861216127872467,
-0.04249907284975052,
0.2013804018497467,
-0.24291640520095825,
-0.20070357620716095,
-0.3231874108314514,
0.12822404503822327,
-0.034077659249305725,
-0.006764721125364304,
-0.3257838785648346,
-0.04058927297592163,
0.39110177755355835,
0.11225387454032898,
-0.14964769780635834,
-0.5206971764564514,
0.2977626323699951,
-0.08318758755922318,
0.07015018165111542,
0.00023986026644706726,
0.6380751729011536,
-0.09240628033876419,
-0.1353624016046524,
0.18318232893943787,
0.3113526403903961,
-0.247738316655159,
0.14653019607067108,
0.3683391809463501,
0.17878328263759613,
0.17248530685901642,
-0.053787339478731155,
0.04117811471223831,
0.014778591692447662,
0.06409095227718353,
-0.2540859282016754,
-0.04174523800611496,
0.4979396462440491,
-0.20704549551010132,
0.4949684143066406,
-0.05947215482592583,
0.09615933895111084,
-0.07772010564804077,
0.003605946898460388,
-0.21134963631629944,
0.41704657673835754,
0.2573397755622864,
-0.16382722556591034,
0.31977397203445435,
-0.1749093234539032,
-0.389285683631897,
0.2181686908006668,
0.14777934551239014,
0.0507119856774807,
-0.0239395871758461,
-0.004027266055345535,
-0.004173837602138519,
-0.2835710644721985,
-0.08406413346529007,
0.2592909634113312,
0.6727411150932312,
0.21467217803001404,
0.17579340934753418,
-0.0035536978393793106,
-0.21288852393627167,
-0.07563171535730362,
0.01703471690416336,
0.21315500140190125,
-0.018384750932455063,
0.1383446455001831,
0.06322658807039261,
0.055012837052345276,
0.02725990116596222,
-0.16887202858924866,
0.16363954544067383,
-0.15025180578231812,
-0.11828188598155975,
0.11910352855920792,
-0.2400861531496048,
-0.6449166536331177,
-0.1902637928724289,
-0.005381044000387192,
-0.33743420243263245,
-0.3379825949668884,
0.06197679787874222,
0.09609253704547882,
-0.09279252588748932,
0.17458873987197876,
0.33908799290657043,
0.5370780825614929,
-0.42260855436325073,
-0.2787001132965088,
-0.07020194083452225,
-0.31300246715545654,
-0.22870567440986633,
0.10595953464508057,
0.47611004114151,
0.3147261440753937,
0.4362727403640747,
0.33345887064933777,
-0.07831181585788727,
-0.01110665313899517,
-0.40816831588745117,
0.07382825762033463,
-0.3157109022140503,
0.2591186761856079,
0.10779214650392532,
-0.16198177635669708,
0.1569957733154297,
-0.3664079010486603,
-0.05445985123515129,
0.02567255310714245,
-0.10825203359127045,
0.00573563389480114,
-0.02132081426680088,
0.06178305298089981,
-0.2249404340982437,
-0.20574063062667847,
-0.6049152612686157,
-0.3986760079860687,
0.33175164461135864,
-0.26845747232437134,
0.15955230593681335,
0.11135069280862808,
-0.2901904284954071,
0.21595753729343414,
-0.06657834351062775,
-0.03549857437610626,
-0.19768497347831726,
-0.0266132615506649,
0.04863820970058441,
-0.33357229828834534,
-0.22930164635181427,
-0.33347997069358826,
-0.0837489664554596,
0.2851191461086273,
-0.06061399728059769,
-0.01924038678407669,
-0.21448425948619843,
0.13713258504867554,
-0.09409275650978088,
0.1131659746170044,
0.18199409544467926,
0.262392520904541,
-0.22190825641155243,
0.151618093252182,
-0.13297538459300995,
-0.33784160017967224,
0.28923559188842773,
0.3065319359302521,
0.4667800962924957,
0.2628144323825836,
0.05958127602934837,
0.19852983951568604,
0.7363940477371216,
0.2467275857925415,
0.0307711623609066,
0.16282278299331665,
0.24470634758472443,
-0.008579332381486893,
0.12864334881305695,
-0.29556161165237427,
0.24368076026439667,
-0.20570030808448792,
0.489105224609375,
0.046842485666275024,
0.12142494320869446,
-0.2784973382949829,
-0.3198149800300598,
0.09729421138763428,
-0.29605522751808167,
-0.24099452793598175,
0.22886088490486145,
-0.2286773920059204,
-0.029668159782886505,
-0.0462922677397728,
-0.37965264916419983,
-0.30280715227127075,
-0.03775858134031296,
0.024953655898571014,
0.36506718397140503,
-0.08353621512651443,
0.1451680064201355,
-0.3331809639930725,
-0.05883096531033516,
-0.47370094060897827,
0.11649078875780106,
0.02723412774503231,
0.30089789628982544,
-0.07650651037693024,
-0.10251370072364807,
-0.09614039957523346,
0.09850404411554337,
0.7110233902931213,
-0.4442327916622162,
-0.1452292501926422,
0.14357194304466248,
0.09769856929779053,
-0.09330227971076965,
-0.12175722420215607,
-0.286529541015625,
0.11032100766897202,
0.5207927823066711,
0.3619166314601898,
-0.45472973585128784,
-0.26354849338531494,
0.14256997406482697,
-0.21809375286102295,
-0.04638509079813957,
-0.18992525339126587,
-0.2505958378314972,
-0.267026424407959,
-0.09710871428251266,
0.042247943580150604,
0.22509314119815826,
0.2796405553817749,
-0.11629276722669601,
0.2169063538312912,
-0.07204927504062653,
0.17009702324867249,
0.21983088552951813,
0.0008597709238529205,
-0.026834923774003983,
0.2566705346107483,
0.1444438099861145,
0.08391493558883667,
-0.09641501307487488,
-0.3558114767074585,
0.1244937926530838,
-0.028675835579633713,
0.13755030930042267,
0.3451254367828369,
-0.06954695284366608,
0.5981544256210327,
0.15671080350875854,
0.300218790769577,
0.22123482823371887,
-0.13670648634433746,
-0.013893641531467438,
-0.1888938546180725,
0.23657336831092834,
0.21810726821422577,
0.20831653475761414,
-0.14313693344593048,
-0.24706344306468964,
0.4849056303501129,
0.25417226552963257,
-0.13027405738830566,
0.476606547832489,
-0.46295660734176636,
-0.3232702612876892,
0.23429572582244873,
0.08237838000059128,
0.7584080100059509,
-0.025766268372535706,
0.24822090566158295,
0.2218545377254486,
-0.3872930407524109,
0.5620597004890442,
-0.2961157560348511,
0.15221048891544342,
-0.060211144387722015,
-0.15607114136219025,
-0.00347258523106575,
-0.10052992403507233,
-0.06659532338380814,
0.19200065732002258,
-0.3005223870277405,
0.3170953691005707,
0.47413086891174316,
-0.25450611114501953,
-0.02542540617287159,
0.5520507097244263,
0.07409633696079254,
-0.4449000060558319,
-0.06325917690992355,
0.05981096625328064,
-0.27754122018814087,
0.1279604285955429,
-0.1231735423207283,
-0.32199662923812866,
0.19604867696762085,
0.14368201792240143,
-0.3340367078781128,
0.08418518304824829,
0.0025326660834252834,
0.2179051786661148,
0.3024013042449951,
-0.018724113702774048,
0.24353772401809692,
-0.15538766980171204,
-0.06911833584308624,
-0.2024182826280594,
-0.08242576569318771,
0.12338769435882568,
-0.15316855907440186,
0.11678958684206009,
0.09096910059452057,
-0.23128847777843475,
0.5451806783676147,
-0.09264493733644485,
-0.07114842534065247,
-0.24564054608345032,
0.22469687461853027,
-0.40141743421554565,
-0.20007510483264923,
0.20054173469543457,
0.16138680279254913,
0.1955033242702484,
-0.2907208204269409,
0.5905134081840515,
0.12673096358776093,
-0.003993481397628784,
0.01494215615093708,
0.22409652173519135,
-0.23790514469146729,
0.4939917027950287,
-0.33471783995628357,
0.03277841955423355,
0.10144218802452087,
0.04158319905400276,
-0.10776830464601517,
-0.43384358286857605,
-0.0012157373130321503,
0.33424779772758484,
0.07582005858421326,
0.051432013511657715,
-0.08145014941692352,
0.0753398984670639,
-0.04821406304836273,
-0.09353338181972504,
-0.1852855235338211,
-0.343398779630661,
0.08340653777122498,
0.2625080943107605,
0.14033231139183044,
0.22585955262184143,
-0.062351763248443604,
-0.30122557282447815,
-0.18288251757621765,
0.4282068610191345,
-0.09056003391742706,
0.17181049287319183,
-0.1609405279159546,
0.31565916538238525,
0.41203197836875916,
0.46285828948020935,
-0.24442191421985626,
0.016906801611185074,
0.022539852187037468,
0.09322279691696167,
0.3734447658061981,
-0.2316666543483734,
0.07709383964538574,
0.24294085800647736,
-0.13898323476314545,
0.04263536259531975,
-0.34411028027534485,
-0.12457103282213211,
-0.26963165402412415,
0.11243967711925507,
0.13527867197990417,
-0.04004848748445511,
0.004309933632612228,
-0.13928300142288208,
-0.1367930918931961,
-0.06827154010534286,
-0.03434345871210098,
-0.40052008628845215,
-0.10314901173114777,
0.08782876282930374,
-0.04722622409462929,
0.06675795465707779,
0.06176084280014038,
0.16811507940292358,
0.05270761623978615,
-0.08132509887218475,
0.3830561935901642,
0.09156361222267151,
0.07138912379741669,
-0.18555381894111633,
-0.16798439621925354,
0.05471840500831604,
0.27849191427230835,
0.1424303948879242,
-0.04896392673254013,
0.06975305825471878,
-0.2131606638431549,
-0.1310153305530548,
0.21939092874526978,
0.2282593697309494,
0.05144962668418884,
-0.19707223773002625,
0.1387762725353241,
0.08696110546588898,
-0.07299178838729858,
-0.02421017922461033,
0.2587135136127472,
0.061155978590250015,
0.058103013783693314,
0.15578004717826843,
0.13392274081707,
0.434079110622406,
-0.18399573862552643,
0.04718610644340515,
0.168609157204628,
-0.37249696254730225,
0.053001344203948975,
-0.1925286501646042,
-0.12392839789390564,
0.04347006604075432,
0.1779736578464508,
-0.02071366086602211,
0.11280078440904617,
-0.18534862995147705,
0.2707878351211548,
0.3122725486755371,
0.009716758504509926,
0.047666821628808975,
0.13717655837535858,
-0.05930173769593239,
-0.18108198046684265,
0.20019416511058807,
0.057559527456760406,
0.344394713640213,
0.018697895109653473,
0.8508671522140503,
-0.27619698643684387,
-0.3828795254230499,
0.17217466235160828,
0.40964171290397644,
0.03172902390360832,
-0.18231992423534393,
0.08489298075437546,
0.07741566747426987,
-0.34510067105293274,
0.01853763684630394,
0.03847333788871765,
-0.17038504779338837,
0.6866495609283447,
-0.13125543296337128,
0.11843216419219971,
-0.22235529124736786,
-0.2760984003543854,
0.3105562627315521,
0.17144030332565308,
-0.05652574449777603,
0.06068401038646698,
0.13091380894184113,
-0.09606015682220459,
-0.16307991743087769,
0.4281635582447052,
0.20537415146827698,
0.07103633880615234,
-0.4505877196788788,
-0.05537906661629677,
0.10227978229522705,
0.11845840513706207,
-0.08575428277254105,
0.1549680233001709,
0.44376876950263977,
-0.12202142179012299,
0.2705669105052948,
-0.023743653669953346,
-0.02321956679224968,
-0.13216739892959595,
0.16326655447483063,
-0.3313332200050354,
-0.3735797107219696,
0.4598417580127716,
0.0828370600938797,
-0.11625508964061737,
0.096751868724823,
0.29102209210395813,
-0.6527736783027649,
-0.24476014077663422,
0.25609290599823,
-0.061829231679439545,
-0.0006644940003752708,
-0.1802777647972107,
0.06906038522720337,
0.08660949766635895,
0.6433354616165161,
0.1645336002111435,
0.30600106716156006,
-0.4014545679092407,
-0.12584923207759857,
-0.6316568851470947,
-0.21747547388076782,
0.17937438189983368,
-0.1384008228778839,
-0.17036277055740356,
0.18058349192142487,
-0.007043749094009399,
0.24776320159435272,
-0.26092439889907837,
-0.006971346214413643,
0.32927176356315613,
0.042966850101947784,
-0.5192553400993347,
0.039342351257801056,
0.16072025895118713,
0.11304482817649841,
0.26529285311698914,
-0.020683681592345238,
-0.20508523285388947,
0.10758026689291,
-0.06017396226525307,
-0.0842016264796257,
-0.11822482943534851,
0.23890498280525208,
0.2081911563873291,
0.005505956709384918,
0.06280198693275452,
0.4919825494289398,
0.00655258446931839,
-0.1701352894306183,
-0.0049099065363407135,
0.09330549091100693,
-0.3385924696922302,
-0.1612526774406433,
-0.10824744403362274,
0.22235333919525146,
-0.34201085567474365,
0.3595678508281708,
-0.017937785014510155,
-0.08411504328250885,
0.13189372420310974,
0.025731749832630157,
-0.2636851668357849,
0.02853337861597538,
-0.008091215044260025,
0.27323272824287415,
0.20005379617214203,
0.7247750163078308,
0.03976457193493843,
0.17260219156742096,
-0.16154934465885162,
-0.04141373932361603,
0.10445643961429596,
-0.17149558663368225,
-0.28233763575553894,
-0.1106865257024765,
0.0700385794043541,
0.031754955649375916,
0.13340839743614197,
-0.7072269320487976,
-0.3839820623397827,
0.006639160681515932,
-0.032671090215444565,
0.024425268173217773,
0.6573563814163208,
0.045901108533144,
-0.10253019630908966,
-0.13903044164180756,
-0.32310807704925537,
0.09402622282505035,
-0.23133821785449982,
0.18395085632801056,
-0.3546333312988281
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | Hey! Happy to jump into the discussion here. I'm still getting familiar with bits of this code, but the reasons I sampled over data loaders rather than datasets is 1) ensuring that each sampled batch corresponds to only 1 task (in case of different inputs formats/downstream models) and 2) potentially having different batch sizes per task (e.g. some tasks have very long/short inputs). How are you currently dealing with these in your PR? | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 73 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
Hey! Happy to jump into the discussion here. I'm still getting familiar with bits of this code, but the reasons I sampled over data loaders rather than datasets is 1) ensuring that each sampled batch corresponds to only 1 task (in case of different inputs formats/downstream models) and 2) potentially having different batch sizes per task (e.g. some tasks have very long/short inputs). How are you currently dealing with these in your PR? | [
-0.089605912566185,
-0.37051939964294434,
-0.04412396624684334,
-0.06419703364372253,
-0.22869302332401276,
0.02895078808069229,
0.26768994331359863,
0.023359674960374832,
0.39509493112564087,
-0.10933448374271393,
-0.17059293389320374,
0.32033535838127136,
-0.2015971690416336,
0.37548592686653137,
0.39844679832458496,
-0.4378180503845215,
-0.002576962113380432,
-0.25555214285850525,
-0.32734400033950806,
0.386793851852417,
0.0030521005392074585,
0.1184615045785904,
-0.14524981379508972,
0.056555770337581635,
-0.28478386998176575,
-0.1290682703256607,
-0.3320092260837555,
0.1075512170791626,
0.09705879539251328,
-0.011513208039104939,
0.2389511913061142,
0.3638802170753479,
-0.0029583927243947983,
0.1261327862739563,
-0.00011568747140699998,
-0.0413927361369133,
0.22455735504627228,
-0.08851228654384613,
0.06489241123199463,
-0.04569900035858154,
0.17900121212005615,
-0.3761778771877289,
0.0587877556681633,
-0.14258654415607452,
0.20260292291641235,
0.17821501195430756,
0.17752519249916077,
0.04718811810016632,
0.3459145426750183,
-0.325434148311615,
0.08241245150566101,
0.32058289647102356,
-0.20827698707580566,
0.26400527358055115,
-0.11156594008207321,
-0.05021269619464874,
0.07479416579008102,
0.3185981512069702,
0.6831016540527344,
-0.5693524479866028,
-0.07522604614496231,
0.10948421061038971,
0.01886456273496151,
-0.06389616429805756,
0.15395689010620117,
-0.08444515615701675,
-0.30900242924690247,
-0.24644428491592407,
-0.4362654387950897,
0.2125432789325714,
-0.11863141506910324,
-0.1288323998451233,
-0.2360723912715912,
-0.6045428514480591,
-0.029127713292837143,
0.07235994935035706,
-0.2734473645687103,
-0.009662054479122162,
-0.21529704332351685,
-0.049840640276670456,
-0.17386050522327423,
-0.1056186780333519,
-0.031104769557714462,
0.14210346341133118,
0.3534389138221741,
0.5484317541122437,
0.07717563211917877,
0.21021884679794312,
0.41617828607559204,
0.0839209035038948,
-0.11613135039806366,
-0.27954208850860596,
0.3173259496688843,
0.12179888784885406,
-0.362846702337265,
-0.34425222873687744,
0.17837625741958618,
-0.2727919816970825,
0.2653511166572571,
0.14319467544555664,
0.13283757865428925,
0.05661197006702423,
-0.1277903914451599,
0.2421325445175171,
0.3584884703159332,
0.08159485459327698,
-0.09061955660581589,
-0.11054693162441254,
0.011070534586906433,
-0.104486383497715,
0.22195321321487427,
0.10372351109981537,
0.1453361213207245,
-0.015399766154587269,
-0.47164249420166016,
-0.08467715978622437,
-0.2308618575334549,
0.11420813202857971,
-0.18811652064323425,
-0.5452074408531189,
-0.0772758275270462,
-0.14436036348342896,
0.11034156382083893,
-0.0899566188454628,
-0.2681082487106323,
0.11734405905008316,
-0.05604647845029831,
0.2535909414291382,
-0.13841092586517334,
0.0487503707408905,
-0.04957445710897446,
0.06132807955145836,
-0.45848968625068665,
-0.09332135319709778,
0.2870364189147949,
0.1720787137746811,
0.12903091311454773,
0.12023808807134628,
-0.019157595932483673,
0.14410105347633362,
0.33735769987106323,
0.028595805168151855,
0.013049967586994171,
0.010992974042892456,
0.18654197454452515,
-0.30493977665901184,
0.011405512690544128,
0.23146317899227142,
-0.34904929995536804,
-0.10899230092763901,
-0.20152640342712402,
-0.191081702709198,
0.16736048460006714,
0.01393076404929161,
-0.21046435832977295,
-0.26141491532325745,
-0.5597923994064331,
0.6944102644920349,
-0.03270464390516281,
-0.10934729874134064,
-0.1405429244041443,
0.25908997654914856,
-0.16008715331554413,
-0.08462845534086227,
0.15515024960041046,
0.048239149153232574,
-0.04864697903394699,
-0.36557188630104065,
-0.07868274301290512,
-0.1202850490808487,
0.05071509629487991,
0.2679360508918762,
-0.22832441329956055,
0.2701062560081482,
0.01878887228667736,
0.19740863144397736,
0.2476557493209839,
-0.47684672474861145,
-0.03297758102416992,
0.3645944595336914,
-0.04434584081172943,
0.4032135009765625,
0.10897742956876755,
0.20473596453666687,
0.042717427015304565,
-0.20092684030532837,
0.24048028886318207,
1.0242564678192139,
-0.3771039843559265,
0.008823161944746971,
-0.12261933088302612,
-0.394635945558548,
0.541912853717804,
0.3336596190929413,
0.08739255368709564,
-0.26467570662498474,
-0.11319314688444138,
0.02093157172203064,
0.14002995193004608,
0.06807200610637665,
0.09149998426437378,
-0.06338704377412796,
-0.3728696405887604,
0.0450839102268219,
-0.21324503421783447,
-0.0941624864935875,
-0.36404529213905334,
0.02004189044237137,
-0.07089449465274811,
0.3300633728504181,
0.2768281102180481,
-0.1019618809223175,
0.29011070728302,
-0.25997963547706604,
-0.135525643825531,
-0.29892638325691223,
0.08099536597728729,
-0.09198111295700073,
0.019625477492809296,
-0.3017862141132355,
-0.04352949559688568,
0.3114902675151825,
0.09314753115177155,
-0.11146549880504608,
-0.5201099514961243,
0.2931293249130249,
-0.03599860519170761,
0.06156433746218681,
-0.05629589036107063,
0.5926676392555237,
-0.1611739993095398,
-0.12305725365877151,
0.1540277600288391,
0.30346107482910156,
-0.26907262206077576,
0.22715787589550018,
0.28728780150413513,
0.18800130486488342,
0.16485334932804108,
-0.016521990299224854,
0.13337045907974243,
0.005181150510907173,
-0.012539949268102646,
-0.22247466444969177,
-0.07112563401460648,
0.4943295121192932,
-0.17993195354938507,
0.48739567399024963,
-0.044665250927209854,
0.015739629045128822,
-0.18632057309150696,
-0.047534674406051636,
-0.23269318044185638,
0.4075046479701996,
0.31928834319114685,
-0.17949745059013367,
0.3725854158401489,
-0.08623794466257095,
-0.35132768750190735,
0.17856436967849731,
0.09627662599086761,
0.00019782409071922302,
0.021255694329738617,
-0.012915138155221939,
-0.009134769439697266,
-0.3338388502597809,
-0.11009958386421204,
0.3355424404144287,
0.6644570827484131,
0.24936822056770325,
0.17727503180503845,
-0.02865043841302395,
-0.19699712097644806,
-0.09434285759925842,
0.03606759011745453,
0.21235433220863342,
-0.024822061881422997,
0.15700215101242065,
-0.010826410725712776,
0.03673912212252617,
-0.001910082995891571,
-0.14514292776584625,
0.14484195411205292,
-0.20404064655303955,
-0.0847463607788086,
0.08304194360971451,
-0.20195826888084412,
-0.6090875864028931,
-0.24757292866706848,
-0.017396800220012665,
-0.32901883125305176,
-0.2885229289531708,
0.10992706567049026,
0.08244891464710236,
-0.15863145887851715,
0.14156243205070496,
0.22592276334762573,
0.6497545838356018,
-0.4458458721637726,
-0.2383548468351364,
-0.0980750024318695,
-0.2736438512802124,
-0.117884062230587,
0.0897928923368454,
0.43891486525535583,
0.2987906038761139,
0.4678769111633301,
0.33576488494873047,
-0.07294581085443497,
0.09495680779218674,
-0.3517071604728699,
0.03553077206015587,
-0.2930786609649658,
0.30988240242004395,
0.13900691270828247,
-0.1824033409357071,
0.19600293040275574,
-0.3770199120044708,
-0.06796406954526901,
-0.04905340075492859,
-0.09277120977640152,
-0.06871572136878967,
-0.026185188442468643,
0.07875314354896545,
-0.19790859520435333,
-0.14304092526435852,
-0.6475343108177185,
-0.4276149272918701,
0.26240986585617065,
-0.2563132047653198,
0.05381118506193161,
0.056188713759183884,
-0.27896520495414734,
0.16724108159542084,
-0.11408741027116776,
-0.030198896303772926,
-0.16675274074077606,
-0.11565938591957092,
-0.022315409034490585,
-0.34140515327453613,
-0.16686159372329712,
-0.43680325150489807,
-0.08814220875501633,
0.20312467217445374,
-0.01946449466049671,
-0.019430149346590042,
-0.1868307739496231,
0.15789034962654114,
-0.12860511243343353,
0.1338551938533783,
0.22555002570152283,
0.14002405107021332,
-0.24906912446022034,
0.1449832171201706,
-0.06924641877412796,
-0.2159963995218277,
0.22665101289749146,
0.31023120880126953,
0.467271089553833,
0.20428210496902466,
0.021375082433223724,
0.1477930098772049,
0.7359363436698914,
0.2251024693250656,
0.06165266036987305,
0.15805065631866455,
0.2971978187561035,
-0.01152196153998375,
0.10848712921142578,
-0.20904192328453064,
0.2638307213783264,
-0.1977590024471283,
0.48094671964645386,
0.08564785122871399,
0.1445295810699463,
-0.18779566884040833,
-0.2808536887168884,
0.008959051221609116,
-0.2754811942577362,
-0.22052472829818726,
0.24758362770080566,
-0.27491945028305054,
0.008521296083927155,
-0.07700526714324951,
-0.36289533972740173,
-0.28628259897232056,
-0.039261214435100555,
-0.007199836894869804,
0.3148205876350403,
0.03027878701686859,
0.16325710713863373,
-0.3991277515888214,
-0.0698733702301979,
-0.4792785048484802,
0.12462051212787628,
0.05004148557782173,
0.2723785936832428,
-0.07456652075052261,
-0.1068066880106926,
-0.0809648185968399,
0.13911302387714386,
0.6718359589576721,
-0.4680737555027008,
-0.12010304629802704,
0.04675668850541115,
0.08207770437002182,
-0.059772148728370667,
-0.12703664600849152,
-0.2370416522026062,
0.020004617050290108,
0.4522354304790497,
0.35549548268318176,
-0.41076329350471497,
-0.2772553265094757,
0.22630614042282104,
-0.16873975098133087,
-0.08126749098300934,
-0.22157131135463715,
-0.21372485160827637,
-0.17879274487495422,
-0.12051863968372345,
0.022924095392227173,
0.19871008396148682,
0.2567111849784851,
-0.17587724328041077,
0.1802804172039032,
-0.09640815109014511,
0.2749904990196228,
0.18857160210609436,
-0.004854738712310791,
-0.061227165162563324,
0.19523654878139496,
0.1555696725845337,
0.07697056978940964,
-0.113992840051651,
-0.2888616919517517,
0.11771614104509354,
-0.09440399706363678,
0.09064487367868423,
0.27966850996017456,
-0.02780107781291008,
0.689308226108551,
0.08675223588943481,
0.33508390188217163,
0.26983949542045593,
-0.08435344696044922,
-0.015831395983695984,
-0.2550775706768036,
0.17849378287792206,
0.1570008099079132,
0.2542005777359009,
-0.15993042290210724,
-0.26166704297065735,
0.5813794732093811,
0.30217254161834717,
-0.07488243281841278,
0.4123922884464264,
-0.5658517479896545,
-0.318134605884552,
0.32106220722198486,
0.008235007524490356,
0.6767164468765259,
-0.011694639921188354,
0.2966558635234833,
0.09642036259174347,
-0.29173049330711365,
0.5918289422988892,
-0.30680662393569946,
0.13567262887954712,
-0.08629504591226578,
-0.1570109874010086,
-0.0007165279239416122,
-0.1022060215473175,
-0.06825951486825943,
0.2856675386428833,
-0.26939907670021057,
0.34069037437438965,
0.45153963565826416,
-0.25932610034942627,
-0.062463678419589996,
0.49701982736587524,
0.0402609184384346,
-0.3902255594730377,
-0.053388237953186035,
0.03806687891483307,
-0.2636737823486328,
0.15802627801895142,
-0.1339806616306305,
-0.2760329842567444,
0.2424040138721466,
0.09275698661804199,
-0.2599031627178192,
0.10794831067323685,
0.00268064858391881,
0.21478167176246643,
0.31649458408355713,
0.024473756551742554,
0.24765875935554504,
-0.18959127366542816,
-0.15023545920848846,
-0.17084519565105438,
-0.06086115539073944,
0.1315786987543106,
-0.14995667338371277,
0.07499956339597702,
0.102250836789608,
-0.18703822791576385,
0.5334511399269104,
-0.060373108834028244,
-0.08038945496082306,
-0.2575185298919678,
0.22078363597393036,
-0.45324862003326416,
-0.15675629675388336,
0.15572863817214966,
0.17293328046798706,
0.1708429902791977,
-0.3983144462108612,
0.5807892680168152,
0.13632537424564362,
0.01606684923171997,
-0.0007992703467607498,
0.16640503704547882,
-0.22039063274860382,
0.5007694363594055,
-0.3107818067073822,
0.009038269519805908,
0.07070198655128479,
0.006287731230258942,
-0.12925174832344055,
-0.41762956976890564,
-0.04808884114027023,
0.29771342873573303,
0.0980951339006424,
0.050419896841049194,
-0.009111844003200531,
0.1802223026752472,
-0.11553867161273956,
-0.03041183203458786,
-0.11281539499759674,
-0.29369795322418213,
0.13766293227672577,
0.18977539241313934,
0.2009892612695694,
0.19345170259475708,
-0.080145925283432,
-0.32933810353279114,
-0.19233445823192596,
0.4907073974609375,
-0.03517528250813484,
0.20113804936408997,
-0.08926887065172195,
0.35346731543540955,
0.3922426402568817,
0.45730820298194885,
-0.23124614357948303,
0.034198909997940063,
0.07259204983711243,
0.09041831642389297,
0.42385488748550415,
-0.21112433075904846,
0.054924800992012024,
0.29967108368873596,
-0.15968696773052216,
0.03289360553026199,
-0.29686519503593445,
-0.12285886704921722,
-0.24775631725788116,
0.11770706623792648,
0.12449154257774353,
-0.019673800095915794,
0.0004341951571404934,
-0.10363554954528809,
-0.059410009533166885,
-0.056695543229579926,
0.01615842431783676,
-0.3881985545158386,
-0.07074013352394104,
0.0800229012966156,
-0.05661024525761604,
0.0591755136847496,
0.018896304070949554,
0.30536022782325745,
0.03774084895849228,
-0.04799099266529083,
0.3157254755496979,
0.12572357058525085,
0.08717876672744751,
-0.15319716930389404,
-0.1950373500585556,
0.01724487543106079,
0.30177685618400574,
0.17275962233543396,
-0.03927139192819595,
0.16133424639701843,
-0.16719713807106018,
-0.15903237462043762,
0.22609040141105652,
0.22319786250591278,
0.040098268538713455,
-0.1603206843137741,
0.11157452315092087,
0.08390440046787262,
-0.09768814593553543,
0.01281345821917057,
0.1506921797990799,
0.11321600526571274,
0.061028238385915756,
0.1405305117368698,
0.1759590059518814,
0.45911073684692383,
-0.25382113456726074,
-0.0028148703277111053,
0.14726129174232483,
-0.241718128323555,
0.09182550013065338,
-0.07453352212905884,
-0.04242352768778801,
0.022125471383333206,
0.17669157683849335,
0.016910109668970108,
0.12707734107971191,
-0.3183577060699463,
0.2580792307853699,
0.3101721704006195,
0.005789011716842651,
0.014650922268629074,
0.09429790824651718,
-0.06749280542135239,
-0.18665936589241028,
0.3170960545539856,
0.00961320847272873,
0.3464251458644867,
0.04529720917344093,
0.8753758072853088,
-0.333763062953949,
-0.4275134801864624,
0.15399391949176788,
0.4489407539367676,
0.05686268210411072,
-0.22211354970932007,
0.037358127534389496,
0.1282808780670166,
-0.3681759238243103,
0.11881013214588165,
0.016469597816467285,
-0.1489974409341812,
0.6261696815490723,
-0.11506859958171844,
0.14155372977256775,
-0.19208960235118866,
-0.25172507762908936,
0.3088245391845703,
0.1510942578315735,
-0.108719602227211,
0.003981549292802811,
0.08623930811882019,
-0.03195403516292572,
-0.08976559340953827,
0.4948278069496155,
0.24426431953907013,
0.044602397829294205,
-0.4217642843723297,
-0.05275574326515198,
0.06980518996715546,
0.15835505723953247,
-0.09271027147769928,
0.14168429374694824,
0.45747143030166626,
-0.1465977430343628,
0.2598172724246979,
-0.01205808948725462,
-0.028776679188013077,
-0.10949544608592987,
0.10569151490926743,
-0.40160274505615234,
-0.36630117893218994,
0.45456865429878235,
0.09633444249629974,
-0.10901318490505219,
0.05089858919382095,
0.2974779009819031,
-0.6373802423477173,
-0.23752887547016144,
0.30419301986694336,
-0.12987762689590454,
-0.07157358527183533,
-0.18063612282276154,
0.06053189933300018,
0.05796731263399124,
0.6411347985267639,
0.24478359520435333,
0.35875189304351807,
-0.41919270157814026,
-0.12837077677249908,
-0.5469263195991516,
-0.25038862228393555,
0.14156486093997955,
-0.07870977371931076,
-0.26345714926719666,
0.1379135400056839,
-0.0405026450753212,
0.25394564867019653,
-0.2701578736305237,
0.10107435286045074,
0.23565635085105896,
0.09575535356998444,
-0.43658798933029175,
0.08838328719139099,
0.13122275471687317,
0.10667721927165985,
0.25308340787887573,
-0.095354363322258,
-0.17096666991710663,
0.10993611812591553,
-0.12099019438028336,
-0.08666327595710754,
-0.08444841206073761,
0.3115096390247345,
0.22627808153629303,
0.048147864639759064,
0.0510241873562336,
0.5658936500549316,
0.008747503161430359,
-0.1783832162618637,
0.01966799423098564,
0.009437719359993935,
-0.34356987476348877,
-0.1645628809928894,
-0.08115561306476593,
0.15427017211914062,
-0.3199593722820282,
0.341757595539093,
-0.01973627507686615,
-0.11823641508817673,
0.10428188741207123,
0.0029659494757652283,
-0.22956092655658722,
-0.05096949636936188,
0.005004383623600006,
0.18253229558467865,
0.25139597058296204,
0.7283111810684204,
0.028254516422748566,
0.09515015035867691,
-0.07251247763633728,
0.00252331979572773,
0.03102754056453705,
-0.10433545708656311,
-0.21575942635536194,
-0.17576856911182404,
0.044877730309963226,
0.013303913176059723,
0.12388886511325836,
-0.7102764844894409,
-0.3642635643482208,
0.019617607817053795,
0.013225267641246319,
0.08402018249034882,
0.7129794359207153,
0.07473532855510712,
-0.14252953231334686,
-0.1384013146162033,
-0.3290698826313019,
0.051101960241794586,
-0.23991230130195618,
0.19118718802928925,
-0.3383631706237793
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | The short answer is - I'm not! Everything is currently on a per-example basis. It would be fairly simple to add a `batch_size` argument which would ensure that every `batch_size` examples come from the same task. That should suit most use-cases (unless you wanted to ensure batches all came from the same task and apply something like `SortishSampler` on each task first)
Your notebook was really inspiring by the way - thanks! | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 72 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
The short answer is - I'm not! Everything is currently on a per-example basis. It would be fairly simple to add a `batch_size` argument which would ensure that every `batch_size` examples come from the same task. That should suit most use-cases (unless you wanted to ensure batches all came from the same task and apply something like `SortishSampler` on each task first)
Your notebook was really inspiring by the way - thanks! | [
-0.09565509855747223,
-0.43038490414619446,
-0.04629374295473099,
-0.06745029985904694,
-0.25789403915405273,
0.00994720309972763,
0.20224888622760773,
0.0762408971786499,
0.29039692878723145,
-0.11092473566532135,
-0.18591398000717163,
0.29462260007858276,
-0.23009233176708221,
0.3789541721343994,
0.41002357006073,
-0.45200076699256897,
0.024441152811050415,
-0.17720666527748108,
-0.29455074667930603,
0.3627450466156006,
0.015423532575368881,
0.14288915693759918,
-0.15470293164253235,
0.08106376975774765,
-0.3128843605518341,
-0.1692613661289215,
-0.34849420189857483,
0.1008625477552414,
0.13701575994491577,
-0.02462046965956688,
0.2090308964252472,
0.3778529763221741,
0.03400932997465134,
0.1013946384191513,
-0.00011142913717776537,
-0.09728643298149109,
0.20507881045341492,
-0.09062542021274567,
0.10297657549381256,
-0.05900318920612335,
0.16401755809783936,
-0.36792224645614624,
-0.0027356501668691635,
-0.1269502341747284,
0.15940651297569275,
0.22511357069015503,
0.20238101482391357,
0.08568350970745087,
0.39888113737106323,
-0.30972468852996826,
0.11813074350357056,
0.3286946713924408,
-0.18170085549354553,
0.2379731386899948,
-0.08357029408216476,
-0.06251056492328644,
0.060989417135715485,
0.2345285415649414,
0.6071350574493408,
-0.5887547135353088,
-0.06404925137758255,
0.14051803946495056,
0.038545072078704834,
0.021421082317829132,
0.14441192150115967,
-0.03873608261346817,
-0.29622358083724976,
-0.2327665090560913,
-0.436235636472702,
0.2806541621685028,
-0.16127413511276245,
-0.13062629103660583,
-0.26345258951187134,
-0.5633004903793335,
-0.0008530186023563147,
0.0014622323215007782,
-0.330098420381546,
0.0447884127497673,
-0.21435779333114624,
-0.03346632048487663,
-0.1524394005537033,
-0.060267433524131775,
-0.040601130574941635,
0.11201082170009613,
0.3631240725517273,
0.5616533756256104,
0.08171787858009338,
0.13045671582221985,
0.37812310457229614,
0.058417245745658875,
-0.19902943074703217,
-0.25620630383491516,
0.283736914396286,
0.11374115943908691,
-0.3466759920120239,
-0.3419148325920105,
0.17506253719329834,
-0.1930898129940033,
0.32280901074409485,
0.10108862072229385,
0.09349600970745087,
0.09113761782646179,
-0.10029951483011246,
0.29205912351608276,
0.3476564884185791,
0.12236909568309784,
-0.05660543590784073,
-0.12424623966217041,
0.03975958377122879,
-0.06336762011051178,
0.20475304126739502,
0.1504272222518921,
0.1986272633075714,
-0.007035126909613609,
-0.4239499568939209,
-0.11359044164419174,
-0.1826791614294052,
0.1420108526945114,
-0.21429969370365143,
-0.5234177112579346,
-0.02995612658560276,
-0.13044431805610657,
0.08226405084133148,
-0.05673923343420029,
-0.2853320837020874,
0.09736412763595581,
-0.08805631101131439,
0.1967231184244156,
-0.12846842408180237,
0.07483383268117905,
-0.08253393322229385,
0.07176254689693451,
-0.4690384864807129,
-0.04859989881515503,
0.30152595043182373,
0.10744746029376984,
0.13133534789085388,
0.13816618919372559,
-0.037743523716926575,
0.13288018107414246,
0.33942851424217224,
0.03031250089406967,
-0.0003314018249511719,
-0.03616652265191078,
0.1575368493795395,
-0.33455827832221985,
-0.04376903548836708,
0.15608330070972443,
-0.4061703383922577,
-0.15703800320625305,
-0.1264195740222931,
-0.21524950861930847,
0.133074089884758,
0.054886993020772934,
-0.2345520704984665,
-0.25436773896217346,
-0.4572625458240509,
0.7054925560951233,
-0.04623884707689285,
-0.03340630233287811,
-0.13866668939590454,
0.2801205515861511,
-0.2386481612920761,
-0.07164382934570312,
0.15914331376552582,
0.09545499086380005,
0.0009736567735671997,
-0.3780563175678253,
-0.03246134892106056,
-0.10533332824707031,
-0.06803711503744125,
0.31936413049697876,
-0.17716695368289948,
0.18924599885940552,
0.05113614350557327,
0.20222042500972748,
0.24152293801307678,
-0.49662354588508606,
-0.03344199061393738,
0.30526047945022583,
-0.03650673106312752,
0.35196825861930847,
0.07787430286407471,
0.1823500245809555,
0.09818743914365768,
-0.1924564093351364,
0.26532721519470215,
1.0035319328308105,
-0.38286933302879333,
0.02205587737262249,
-0.12745912373065948,
-0.4010966122150421,
0.485562801361084,
0.32760196924209595,
0.023421039804816246,
-0.31363844871520996,
-0.13007831573486328,
-0.025605181232094765,
0.09931136667728424,
0.06988118588924408,
0.076529361307621,
-0.0697745680809021,
-0.31873446702957153,
0.013977974653244019,
-0.15631629526615143,
-0.13527324795722961,
-0.42362886667251587,
0.03415093570947647,
-0.06946314871311188,
0.3329486846923828,
0.32506078481674194,
-0.13765057921409607,
0.21762609481811523,
-0.2634049654006958,
-0.10048367083072662,
-0.3129211664199829,
0.14184829592704773,
-0.10447484254837036,
0.05392620339989662,
-0.2799592614173889,
-0.0749286562204361,
0.3310255706310272,
0.08667045831680298,
-0.12241573631763458,
-0.46758055686950684,
0.24261586368083954,
-0.10650403052568436,
0.01754605397582054,
0.0072994716465473175,
0.6171311140060425,
-0.14959514141082764,
-0.07000717520713806,
0.2050333321094513,
0.28201788663864136,
-0.2821090817451477,
0.2547474801540375,
0.2886514663696289,
0.22653207182884216,
0.18389946222305298,
0.01291370764374733,
0.10476886481046677,
-0.018239326775074005,
-0.03309943526983261,
-0.1843896210193634,
-0.1276172399520874,
0.5337749123573303,
-0.11340467631816864,
0.42374786734580994,
0.010280590504407883,
-0.0016263797879219055,
-0.18574842810630798,
-0.08734390139579773,
-0.2569582760334015,
0.3532719314098358,
0.32422077655792236,
-0.21554210782051086,
0.3575747609138489,
-0.09278329461812973,
-0.3873850405216217,
0.1576668620109558,
0.18133816123008728,
0.022451937198638916,
0.08836881071329117,
0.02248459868133068,
-0.04399360716342926,
-0.28928107023239136,
-0.0826866552233696,
0.3609902560710907,
0.6006553769111633,
0.3052535951137543,
0.1733636111021042,
0.02706008218228817,
-0.30429166555404663,
-0.11205678433179855,
0.01522761583328247,
0.18314236402511597,
-0.030197111889719963,
0.15285545587539673,
0.04158672317862511,
0.05599968880414963,
-0.04895707964897156,
-0.16611436009407043,
0.09252741187810898,
-0.17580817639827728,
-0.0818902924656868,
0.039575956761837006,
-0.1671431064605713,
-0.5780366659164429,
-0.2460935115814209,
0.04412256181240082,
-0.3262541890144348,
-0.2550859749317169,
0.15884125232696533,
0.029434477910399437,
-0.16992655396461487,
0.1729968786239624,
0.2292766571044922,
0.6286777257919312,
-0.43886107206344604,
-0.18500059843063354,
-0.10761904716491699,
-0.3222368061542511,
-0.15262538194656372,
0.12096057832241058,
0.4160206913948059,
0.29050713777542114,
0.4932442307472229,
0.28309208154678345,
-0.02600112557411194,
0.10474321991205215,
-0.37736454606056213,
0.0544515997171402,
-0.2754265069961548,
0.28514426946640015,
0.11039245128631592,
-0.2209576517343521,
0.15785640478134155,
-0.39220544695854187,
-0.05006009340286255,
-0.12310837209224701,
-0.09991288930177689,
-0.08157984912395477,
-0.026580937206745148,
0.042091358453035355,
-0.19186259806156158,
-0.1675722897052765,
-0.6334234476089478,
-0.46810728311538696,
0.34189003705978394,
-0.21221736073493958,
0.10471151024103165,
0.05770028755068779,
-0.260682612657547,
0.16616946458816528,
-0.15556229650974274,
0.02795892022550106,
-0.16115033626556396,
-0.08060229569673538,
0.02716047689318657,
-0.3650359511375427,
-0.16097742319107056,
-0.42607778310775757,
-0.13156574964523315,
0.2117251604795456,
-0.08573517948389053,
-0.01816057786345482,
-0.25038695335388184,
0.07165047526359558,
-0.13314282894134521,
0.11693156510591507,
0.26750215888023376,
0.1917031705379486,
-0.23755095899105072,
0.09199521690607071,
-0.030880069360136986,
-0.23764263093471527,
0.24059653282165527,
0.3334428071975708,
0.39254167675971985,
0.14052046835422516,
0.030540477484464645,
0.19585338234901428,
0.7353606820106506,
0.25642988085746765,
0.023826051503419876,
0.18662703037261963,
0.262111634016037,
0.02463659644126892,
0.1601390242576599,
-0.16981855034828186,
0.25950542092323303,
-0.17571207880973816,
0.4492540955543518,
0.12856148183345795,
0.18453162908554077,
-0.2333071380853653,
-0.24578745663166046,
-0.01603533700108528,
-0.26773956418037415,
-0.20620620250701904,
0.24365229904651642,
-0.2004663497209549,
-0.005440384149551392,
-0.09856343269348145,
-0.3882952928543091,
-0.2598908245563507,
-0.032904163002967834,
0.01779084838926792,
0.28791072964668274,
0.002848885953426361,
0.16430744528770447,
-0.3194672763347626,
-0.05563710257411003,
-0.4845142960548401,
0.14956317842006683,
0.0722145363688469,
0.2689267098903656,
-0.06599932909011841,
-0.10260532796382904,
-0.11336347460746765,
0.08600842952728271,
0.6084622740745544,
-0.46098771691322327,
-0.12899242341518402,
0.029675118625164032,
0.09475579857826233,
-0.12481449544429779,
-0.10218705236911774,
-0.26836177706718445,
-0.06343230605125427,
0.46247395873069763,
0.37933453917503357,
-0.3683632016181946,
-0.30867621302604675,
0.25277942419052124,
-0.21676290035247803,
-0.055353112518787384,
-0.23541662096977234,
-0.21979960799217224,
-0.1814945936203003,
-0.1528942734003067,
0.09308324754238129,
0.22387365996837616,
0.17905890941619873,
-0.10410721600055695,
0.12050007283687592,
-0.07052141427993774,
0.20699217915534973,
0.23102611303329468,
0.03242017328739166,
-0.02489125356078148,
0.20212386548519135,
0.1299932450056076,
0.07291962206363678,
-0.12812314927577972,
-0.3435955345630646,
0.052055779844522476,
-0.07871638238430023,
0.1674790382385254,
0.2720282971858978,
0.038946542888879776,
0.6369619965553284,
0.09319525957107544,
0.34834831953048706,
0.24644875526428223,
-0.10002975910902023,
0.028285130858421326,
-0.26440945267677307,
0.11702169477939606,
0.19253741204738617,
0.24081192910671234,
-0.1332411915063858,
-0.1824222058057785,
0.614434003829956,
0.32102546095848083,
-0.07534254342317581,
0.391568660736084,
-0.4802115559577942,
-0.29888367652893066,
0.3047894239425659,
0.04767713323235512,
0.6780330538749695,
-0.008658498525619507,
0.2885777950286865,
0.10952302813529968,
-0.35490506887435913,
0.566443920135498,
-0.3462432622909546,
0.15785478055477142,
-0.1039699837565422,
-0.19105485081672668,
0.007184026762843132,
-0.08794987201690674,
-0.0487314909696579,
0.26887238025665283,
-0.346708744764328,
0.34354397654533386,
0.4566826820373535,
-0.2356591522693634,
-0.0808056890964508,
0.5609844923019409,
-0.04154323786497116,
-0.40955644845962524,
-0.08284197747707367,
0.07587035745382309,
-0.28342705965042114,
0.1413346827030182,
-0.17460066080093384,
-0.2745565176010132,
0.25787800550460815,
0.1064663827419281,
-0.27389299869537354,
0.09171746671199799,
-0.050028443336486816,
0.17283344268798828,
0.27562379837036133,
0.03175937384366989,
0.1917441040277481,
-0.20281726121902466,
-0.06302553415298462,
-0.19644108414649963,
-0.07966642826795578,
0.1545015126466751,
-0.14524778723716736,
0.1055343821644783,
0.08784648030996323,
-0.20984166860580444,
0.5108199119567871,
-0.053067002445459366,
-0.10169781744480133,
-0.2674711346626282,
0.2604370415210724,
-0.404293417930603,
-0.17751352488994598,
0.1069343164563179,
0.13696087896823883,
0.20796982944011688,
-0.2924808859825134,
0.562729001045227,
0.09027546644210815,
-0.005863044410943985,
0.0553344264626503,
0.15226761996746063,
-0.27232444286346436,
0.5453824996948242,
-0.2550191581249237,
0.01121600717306137,
0.051902733743190765,
0.011895991861820221,
-0.14888283610343933,
-0.36376792192459106,
-0.08748200535774231,
0.2741847634315491,
0.09738309681415558,
-0.0001752413809299469,
-0.013708025217056274,
0.14800365269184113,
-0.11333446204662323,
-0.02041766792535782,
-0.12666328251361847,
-0.3535959720611572,
0.1792508363723755,
0.21609561145305634,
0.255737841129303,
0.2160109281539917,
-0.07465711236000061,
-0.2411779910326004,
-0.1948138028383255,
0.481928288936615,
0.027669668197631836,
0.2639501988887787,
-0.13278573751449585,
0.3500426709651947,
0.41728389263153076,
0.5425980091094971,
-0.2901419401168823,
0.019488610327243805,
0.0454469695687294,
0.11256442964076996,
0.45981836318969727,
-0.24196511507034302,
0.07676403969526291,
0.28588104248046875,
-0.13011102378368378,
0.07015644013881683,
-0.36212149262428284,
-0.17070725560188293,
-0.26530221104621887,
0.10153092443943024,
0.10833417624235153,
0.047189466655254364,
0.003176143392920494,
-0.019687756896018982,
-0.07955944538116455,
-0.09573731571435928,
0.01848379150032997,
-0.3760214149951935,
-0.09828223288059235,
0.15372036397457123,
-0.06953905522823334,
0.04239383339881897,
0.12043493986129761,
0.20509055256843567,
0.04669894278049469,
-0.06932926177978516,
0.32367491722106934,
0.12583911418914795,
0.07482606917619705,
-0.152202770113945,
-0.16026020050048828,
0.007074616849422455,
0.228685662150383,
0.13647708296775818,
-0.06157446652650833,
0.16175296902656555,
-0.2716624438762665,
-0.13608995079994202,
0.24081090092658997,
0.14597174525260925,
0.07060440629720688,
-0.1579345017671585,
0.11631929874420166,
0.14452940225601196,
-0.11241625249385834,
0.0010166900465264916,
0.20374658703804016,
0.05654647946357727,
0.1279764175415039,
0.15175622701644897,
0.16456280648708344,
0.45382368564605713,
-0.2142961472272873,
0.036483701318502426,
0.1422029286623001,
-0.37099385261535645,
0.1153038889169693,
-0.13379791378974915,
-0.025103040039539337,
0.024295121431350708,
0.1567724496126175,
-0.009453639388084412,
0.21674735844135284,
-0.34670162200927734,
0.286684513092041,
0.31906288862228394,
-0.03136871010065079,
0.055136896669864655,
0.19727474451065063,
-0.0020191464573144913,
-0.16688492894172668,
0.27943533658981323,
0.0712997242808342,
0.3188144564628601,
0.05534609407186508,
0.8951666951179504,
-0.24943052232265472,
-0.4379865825176239,
0.0884794294834137,
0.3954373002052307,
0.024619698524475098,
-0.22906865179538727,
0.10322864353656769,
0.08457624167203903,
-0.3302842974662781,
0.09990286827087402,
0.04174529388546944,
-0.1267833560705185,
0.6448746919631958,
-0.08233323693275452,
0.14766822755336761,
-0.15032018721103668,
-0.23305943608283997,
0.3292797803878784,
0.17817792296409607,
-0.11302310228347778,
0.01350913755595684,
0.09902162849903107,
-0.10855188965797424,
-0.1989586353302002,
0.5276767611503601,
0.24399083852767944,
0.055927641689777374,
-0.4059012234210968,
0.007024959195405245,
0.11586366593837738,
0.1438957005739212,
-0.0914529487490654,
0.10737704485654831,
0.45036906003952026,
-0.14932742714881897,
0.2122393548488617,
0.03401569277048111,
-0.06872900575399399,
-0.09852886199951172,
0.03311299532651901,
-0.4560564458370209,
-0.3647690713405609,
0.45689019560813904,
0.10242491215467453,
-0.08989409357309341,
0.042917583137750626,
0.30867794156074524,
-0.6284581422805786,
-0.18853935599327087,
0.2987588047981262,
-0.13009721040725708,
-0.07465946674346924,
-0.226114422082901,
0.08871965855360031,
0.07111990451812744,
0.5859489440917969,
0.21885667741298676,
0.3504166305065155,
-0.40086090564727783,
-0.09598863869905472,
-0.6091051697731018,
-0.20071932673454285,
0.11933498084545135,
-0.08799003809690475,
-0.2137719988822937,
0.1967511624097824,
-0.10631450265645981,
0.2746657431125641,
-0.1899932473897934,
0.11173813045024872,
0.1823192536830902,
0.019365869462490082,
-0.410337895154953,
0.15257962048053741,
0.09875050187110901,
0.011352420784533024,
0.30674174427986145,
-0.09572204947471619,
-0.17017151415348053,
0.08457707613706589,
-0.07569790631532669,
-0.08605210483074188,
-0.051421307027339935,
0.2711256146430969,
0.177827849984169,
0.04539426043629646,
0.05552592873573303,
0.46028751134872437,
-0.04975072667002678,
-0.1465172916650772,
-0.02097504958510399,
-0.02138887718319893,
-0.39996081590652466,
-0.17749813199043274,
-0.08906073868274689,
0.17003121972084045,
-0.3348320424556732,
0.2429094910621643,
-0.045284342020750046,
-0.10608506947755814,
0.12069018185138702,
0.01244242861866951,
-0.13162121176719666,
-0.03240446001291275,
0.03830353915691376,
0.1873740255832672,
0.22846576571464539,
0.7360840439796448,
0.037493448704481125,
0.08689642697572708,
-0.09599662572145462,
-0.05491313338279724,
0.05435870587825775,
-0.0933588370680809,
-0.23394675552845,
-0.17539487779140472,
0.07947839796543121,
0.09167444705963135,
0.07787445187568665,
-0.6713752746582031,
-0.35351088643074036,
0.010525266639888287,
0.010181214660406113,
0.07833001017570496,
0.7260480523109436,
0.0725812315940857,
-0.15513916313648224,
-0.15334570407867432,
-0.35617515444755554,
0.06008966267108917,
-0.2716900408267975,
0.18187421560287476,
-0.4164087772369385
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | @zphang is having different batch sizes per task actually helpful? Would be interesting to know as it's not something I've come across as a technique used by any MTL papers. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 30 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
@zphang is having different batch sizes per task actually helpful? Would be interesting to know as it's not something I've come across as a technique used by any MTL papers. | [
-0.09692946076393127,
-0.4622396230697632,
-0.0760454311966896,
0.017250370234251022,
-0.3047633171081543,
0.05286409705877304,
0.22632108628749847,
0.0648951306939125,
0.27689695358276367,
-0.11790058016777039,
-0.17251448333263397,
0.2042178213596344,
-0.25846895575523376,
0.4444766640663147,
0.4080318808555603,
-0.41051334142684937,
0.01412723958492279,
-0.2733161449432373,
-0.25001782178878784,
0.39677631855010986,
0.05055207014083862,
0.08481955528259277,
-0.17099374532699585,
0.06342427432537079,
-0.2406720668077469,
-0.1341973841190338,
-0.33941224217414856,
0.08957769721746445,
0.13409462571144104,
0.027393341064453125,
0.14990709722042084,
0.3057301640510559,
0.027069568634033203,
0.14519339799880981,
-0.00011703865311574191,
-0.10317887365818024,
0.22462084889411926,
-0.054976049810647964,
0.1232357919216156,
-0.038753315806388855,
0.11764193326234818,
-0.4690667986869812,
0.0013235188089311123,
-0.0907580778002739,
0.2729416787624359,
0.1990501880645752,
0.24085494875907898,
0.05113822966814041,
0.30715295672416687,
-0.3036268651485443,
0.08462028950452805,
0.2716985046863556,
-0.23924672603607178,
0.3131469190120697,
-0.04093202203512192,
-0.03336239606142044,
0.06543538719415665,
0.2598797082901001,
0.7037147283554077,
-0.5388643741607666,
0.0035533681511878967,
0.11596065759658813,
0.028103845193982124,
-0.02197091281414032,
0.13279148936271667,
-0.07223215699195862,
-0.2183319330215454,
-0.2454034984111786,
-0.3490258753299713,
0.20940148830413818,
-0.05419587343931198,
-0.08673951774835587,
-0.21434032917022705,
-0.5842260718345642,
-0.01856834813952446,
0.05227081477642059,
-0.31707563996315,
0.1362728774547577,
-0.20855456590652466,
-0.07745707035064697,
-0.19316914677619934,
-0.10364755243062973,
-0.01954682543873787,
0.10086800158023834,
0.37002772092819214,
0.5515717267990112,
0.05214407667517662,
0.16430193185806274,
0.34780994057655334,
0.022836746647953987,
-0.10691865533590317,
-0.2457597851753235,
0.2928490936756134,
0.12592414021492004,
-0.3565714359283447,
-0.31134793162345886,
0.18628336489200592,
-0.2371802031993866,
0.2858080267906189,
0.0631810873746872,
0.138044074177742,
0.03951591998338699,
-0.10145283490419388,
0.20296594500541687,
0.38573843240737915,
0.0993378609418869,
-0.08045104891061783,
-0.14554136991500854,
0.02665870450437069,
-0.16947418451309204,
0.19106584787368774,
0.15759554505348206,
0.1533164232969284,
-0.08121535927057266,
-0.4698123335838318,
-0.13959723711013794,
-0.24632911384105682,
0.12415027618408203,
-0.18019165098667145,
-0.5548356175422668,
-0.0691334456205368,
-0.20435214042663574,
0.02727869153022766,
-0.12810075283050537,
-0.28909409046173096,
0.13472476601600647,
-0.08762967586517334,
0.214901864528656,
-0.13607242703437805,
0.0736110731959343,
-0.04291800782084465,
0.06124958395957947,
-0.4702683687210083,
-0.10851015150547028,
0.2724396586418152,
0.18824900686740875,
0.07662239670753479,
0.11885008960962296,
-0.04511091113090515,
0.11725416779518127,
0.3278566598892212,
0.015721550211310387,
-0.005909577012062073,
0.018595241010189056,
0.21519234776496887,
-0.30850884318351746,
-0.09372919797897339,
0.26277410984039307,
-0.38236239552497864,
-0.049495212733745575,
-0.22280102968215942,
-0.17501145601272583,
0.15861161053180695,
0.013053161092102528,
-0.13337019085884094,
-0.24674835801124573,
-0.5358600616455078,
0.697175920009613,
0.02937692403793335,
-0.061253421008586884,
-0.15396425127983093,
0.2474062740802765,
-0.2110527604818344,
-0.1469140499830246,
0.08802923560142517,
0.06152331084012985,
-0.07157882302999496,
-0.3473765552043915,
-0.03984358534216881,
-0.08777216076850891,
0.016239985823631287,
0.3379491865634918,
-0.19569717347621918,
0.2697061002254486,
0.07623136043548584,
0.12101085484027863,
0.2956903874874115,
-0.476119726896286,
-0.04213965684175491,
0.390820175409317,
-0.029752977192401886,
0.35634106397628784,
0.12997449934482574,
0.24874745309352875,
-0.019198745489120483,
-0.1718997359275818,
0.271645188331604,
0.9539661407470703,
-0.40128350257873535,
0.03243052214384079,
-0.1284985989332199,
-0.42581912875175476,
0.543549656867981,
0.2887674570083618,
0.09507393836975098,
-0.29588890075683594,
-0.08115897327661514,
0.05353764444589615,
0.1472449004650116,
0.11203370988368988,
0.12126529216766357,
-0.06787087023258209,
-0.39558130502700806,
0.023653171956539154,
-0.19152000546455383,
-0.10706014931201935,
-0.4190426766872406,
-0.00041070953011512756,
-0.09667230397462845,
0.28670555353164673,
0.34507930278778076,
-0.07108791172504425,
0.30363717675209045,
-0.31333690881729126,
-0.08020229637622833,
-0.3391849398612976,
0.07497363537549973,
-0.11293651163578033,
0.008267991244792938,
-0.3027854859828949,
-0.06041332334280014,
0.3214498460292816,
0.13272058963775635,
-0.15883849561214447,
-0.46373850107192993,
0.21984809637069702,
-0.06655080616474152,
0.07297089695930481,
-0.00666128471493721,
0.6013066172599792,
-0.2415640652179718,
-0.09500335901975632,
0.14528265595436096,
0.2679252028465271,
-0.299379825592041,
0.23697508871555328,
0.27708864212036133,
0.26271796226501465,
0.21460813283920288,
0.0410454235970974,
0.18638215959072113,
-0.10739432275295258,
-0.06513874232769012,
-0.21716970205307007,
-0.07372831553220749,
0.46423768997192383,
-0.13604456186294556,
0.4431438744068146,
-0.04130062460899353,
-0.0566461980342865,
-0.23851515352725983,
-0.04269199073314667,
-0.20221060514450073,
0.36900603771209717,
0.346292644739151,
-0.18958206474781036,
0.29735490679740906,
-0.10137459635734558,
-0.3327430486679077,
0.15534891188144684,
0.11895051598548889,
0.09320920705795288,
0.05557187274098396,
-0.012828655540943146,
-0.03845524787902832,
-0.2931990623474121,
-0.14500270783901215,
0.3609068989753723,
0.6997568607330322,
0.21742130815982819,
0.18000757694244385,
0.027522051706910133,
-0.15481916069984436,
-0.1363481879234314,
0.01572834700345993,
0.17999452352523804,
-0.04321042820811272,
0.17419418692588806,
0.020082473754882812,
0.04398118332028389,
0.05878257006406784,
-0.13080242276191711,
0.1434115320444107,
-0.20149387419223785,
-0.047282423824071884,
0.007521247491240501,
-0.2275293916463852,
-0.6512364149093628,
-0.31002578139305115,
0.024343740195035934,
-0.32361945509910583,
-0.24214555323123932,
0.07698924094438553,
-0.0048471540212631226,
-0.14679472148418427,
0.09195514023303986,
0.1915389895439148,
0.6404305100440979,
-0.4318293333053589,
-0.1751062422990799,
-0.024588823318481445,
-0.25083744525909424,
-0.15639027953147888,
0.09369319677352905,
0.46999046206474304,
0.24401961266994476,
0.44433027505874634,
0.28168702125549316,
-0.06684494763612747,
0.1097661629319191,
-0.36882132291793823,
0.022475695237517357,
-0.23586614429950714,
0.2514667510986328,
0.13616536557674408,
-0.2515857219696045,
0.19181431829929352,
-0.33062925934791565,
-0.0595003105700016,
-0.10711772739887238,
-0.0802377462387085,
-0.14460302889347076,
-0.017944375053048134,
0.06091843172907829,
-0.2195328027009964,
-0.16286656260490417,
-0.6563556790351868,
-0.4274236559867859,
0.2951757311820984,
-0.2354220300912857,
0.09205666184425354,
0.043100208044052124,
-0.27662020921707153,
0.16108903288841248,
-0.11539875715970993,
0.005506050772964954,
-0.11043908447027206,
-0.12340137362480164,
-0.06430646777153015,
-0.3830776810646057,
-0.1486847698688507,
-0.3794017434120178,
-0.032762687653303146,
0.21915201842784882,
-0.013218598440289497,
-0.06567730754613876,
-0.13860058784484863,
0.09972245246171951,
-0.19404825568199158,
0.07510499656200409,
0.28883856534957886,
0.07945150882005692,
-0.319480299949646,
0.13742370903491974,
-0.041642311960458755,
-0.24689237773418427,
0.1678505539894104,
0.3495776653289795,
0.4843297600746155,
0.18409183621406555,
0.022530749440193176,
0.16180536150932312,
0.7138544321060181,
0.23926421999931335,
0.0766744539141655,
0.12391601502895355,
0.2778066396713257,
-0.027644697576761246,
0.1562185138463974,
-0.1513795107603073,
0.34679901599884033,
-0.13601285219192505,
0.4500523805618286,
0.12394806742668152,
0.21397534012794495,
-0.1946689486503601,
-0.26240062713623047,
-0.008469192311167717,
-0.26845115423202515,
-0.1703488528728485,
0.2559317946434021,
-0.25556179881095886,
0.04936530441045761,
-0.06720227003097534,
-0.47130462527275085,
-0.26852676272392273,
-0.04070999100804329,
-0.04501011222600937,
0.3134015202522278,
-0.07623101025819778,
0.19009241461753845,
-0.3363175690174103,
-0.1390690803527832,
-0.45425480604171753,
0.14053946733474731,
0.0639503002166748,
0.31060701608657837,
-0.04748229682445526,
-0.06474945694208145,
-0.08007955551147461,
0.16260182857513428,
0.632561206817627,
-0.48288804292678833,
-0.14991649985313416,
0.01430671289563179,
0.10305802524089813,
-0.08692990243434906,
-0.1750025898218155,
-0.24498915672302246,
0.004539084155112505,
0.479754239320755,
0.3700738549232483,
-0.3253914415836334,
-0.2802450656890869,
0.22733959555625916,
-0.20513926446437836,
-0.05097851902246475,
-0.2206481695175171,
-0.22033728659152985,
-0.12599384784698486,
-0.0952446386218071,
0.07316489517688751,
0.17764103412628174,
0.24161872267723083,
-0.15876393020153046,
0.18788014352321625,
-0.020658457651734352,
0.25508973002433777,
0.19459588825702667,
-0.011927492916584015,
-0.09128223359584808,
0.25237223505973816,
0.11457347869873047,
-0.0004393830895423889,
-0.0798569768667221,
-0.2460368275642395,
0.07207027077674866,
-0.10971249639987946,
0.190028578042984,
0.3117481768131256,
-0.054916299879550934,
0.6821686029434204,
0.07290752232074738,
0.3269188702106476,
0.2302166223526001,
-0.09951400756835938,
0.04348275437951088,
-0.1924857199192047,
0.13781525194644928,
0.17686715722084045,
0.22169776260852814,
-0.18922297656536102,
-0.2239363044500351,
0.528230607509613,
0.36822310090065,
-0.021432846784591675,
0.3635031282901764,
-0.6384041905403137,
-0.29502901434898376,
0.24399606883525848,
0.03697985038161278,
0.6201876997947693,
0.0012556388974189758,
0.33115464448928833,
-0.028299134224653244,
-0.3404572010040283,
0.5145268440246582,
-0.34301185607910156,
0.17477640509605408,
-0.06714172661304474,
-0.1301722675561905,
0.022789793089032173,
-0.10523968935012817,
-0.034400612115859985,
0.31344133615493774,
-0.27450644969940186,
0.3359679579734802,
0.456587016582489,
-0.252425879240036,
-0.12036937475204468,
0.5019968152046204,
-0.0001567639410495758,
-0.35710829496383667,
-0.02680341899394989,
0.025746513158082962,
-0.24538461863994598,
0.13652129471302032,
-0.2202281355857849,
-0.2273554801940918,
0.22728466987609863,
0.15298545360565186,
-0.3146008253097534,
0.043000757694244385,
-0.022224413231015205,
0.1911669373512268,
0.2674507200717926,
0.009535141289234161,
0.28806072473526,
-0.20601823925971985,
-0.11121505498886108,
-0.15486127138137817,
-0.06647570431232452,
0.09129486232995987,
-0.11013207584619522,
0.09081569314002991,
0.08554096519947052,
-0.18792080879211426,
0.4651317000389099,
-0.0855831652879715,
-0.04987715184688568,
-0.23923173546791077,
0.24239274859428406,
-0.3915676474571228,
-0.22097721695899963,
0.20412571728229523,
0.19909922778606415,
0.23439092934131622,
-0.3496168255805969,
0.5967292189598083,
0.1162034422159195,
0.06519228219985962,
0.0013032052665948868,
0.17796741425991058,
-0.1788136065006256,
0.5910233855247498,
-0.314308762550354,
-0.025047242641448975,
0.04015878587961197,
-0.06175950914621353,
-0.03130720555782318,
-0.43369677662849426,
-0.07607503980398178,
0.29465779662132263,
0.14731964468955994,
0.04011417180299759,
0.0717901960015297,
0.06344659626483917,
-0.02486107125878334,
0.006633184850215912,
-0.08219344168901443,
-0.27645164728164673,
0.21565306186676025,
0.21482691168785095,
0.1768282800912857,
0.24704399704933167,
-0.06320678442716599,
-0.2921832203865051,
-0.11573338508605957,
0.46784716844558716,
-0.030524883419275284,
0.21433034539222717,
-0.14435702562332153,
0.42935043573379517,
0.48022541403770447,
0.530646562576294,
-0.20600423216819763,
0.08634337782859802,
0.11954668909311295,
0.09168408066034317,
0.41203543543815613,
-0.11529964953660965,
0.016234416514635086,
0.3485611081123352,
-0.20053066313266754,
0.06389868259429932,
-0.34794434905052185,
-0.11550619453191757,
-0.23809635639190674,
0.12806586921215057,
0.13986657559871674,
0.02418089471757412,
0.04037763178348541,
-0.10755089670419693,
-0.05919549986720085,
-0.025316566228866577,
0.01723877340555191,
-0.3293403387069702,
-0.06795446574687958,
0.10453064739704132,
-0.02551407739520073,
0.01560242846608162,
0.09028692543506622,
0.3568156063556671,
0.07297879457473755,
-0.09809212386608124,
0.3494691550731659,
0.13369181752204895,
0.12953081727027893,
-0.15184414386749268,
-0.21585924923419952,
-0.04204421490430832,
0.25913774967193604,
0.17298948764801025,
-0.14142590761184692,
0.12014445662498474,
-0.23301860690116882,
-0.12351971864700317,
0.2052648663520813,
0.23218905925750732,
0.07684158533811569,
-0.122011199593544,
0.13692417740821838,
0.06485418975353241,
-0.04432760179042816,
-0.004679646342992783,
0.18947122991085052,
0.09242015331983566,
0.021239016205072403,
0.1604587584733963,
0.18984167277812958,
0.491852343082428,
-0.2660159468650818,
0.02571577951312065,
0.08390630781650543,
-0.3478933572769165,
0.10506007075309753,
-0.15809708833694458,
-0.051642633974552155,
0.019299719482660294,
0.19063270092010498,
-0.05377303436398506,
0.13644802570343018,
-0.29196619987487793,
0.3588845729827881,
0.25594577193260193,
0.05868406966328621,
-0.013341095298528671,
0.13964232802391052,
-0.039308078587055206,
-0.20437990128993988,
0.33291295170783997,
0.001500256359577179,
0.3294956684112549,
0.0227276012301445,
0.8239642381668091,
-0.22451286017894745,
-0.4310363233089447,
0.1677999198436737,
0.4035542905330658,
0.02263050153851509,
-0.24922962486743927,
0.12385421991348267,
0.10800222307443619,
-0.3104625344276428,
0.15777724981307983,
0.009082529693841934,
-0.11470045149326324,
0.610750675201416,
-0.0843510627746582,
0.16867589950561523,
-0.1848052740097046,
-0.23177820444107056,
0.36075055599212646,
0.06150561198592186,
-0.11912199854850769,
0.031436216086149216,
0.01417490839958191,
-0.08980607986450195,
-0.13866446912288666,
0.5110017657279968,
0.19786587357521057,
0.081528440117836,
-0.36255207657814026,
-0.08625247329473495,
0.12035311758518219,
0.23069064319133759,
-0.13932983577251434,
0.1242808923125267,
0.5147860050201416,
-0.18943671882152557,
0.22483006119728088,
-0.03141586855053902,
-0.027002189308404922,
-0.07785665988922119,
0.05451780557632446,
-0.46020689606666565,
-0.439922958612442,
0.43461498618125916,
0.04109242931008339,
-0.11985763907432556,
0.05708657205104828,
0.3916843831539154,
-0.6262600421905518,
-0.21965065598487854,
0.3360733687877655,
-0.1508597582578659,
-0.08783331513404846,
-0.24786406755447388,
0.0547993928194046,
0.061759378761053085,
0.6547306776046753,
0.2686643898487091,
0.36167648434638977,
-0.3674938678741455,
-0.13172833621501923,
-0.5774894952774048,
-0.18853691220283508,
0.09687363356351852,
-0.026180535554885864,
-0.2875889539718628,
0.23825030028820038,
-0.11827684193849564,
0.21939203143119812,
-0.1281169354915619,
0.10893572866916656,
0.17497077584266663,
0.07805293798446655,
-0.42623019218444824,
0.11324359476566315,
0.0924319177865982,
0.08165434002876282,
0.2756972908973694,
-0.0810507982969284,
-0.145060196518898,
0.03609946370124817,
-0.12800279259681702,
-0.14890071749687195,
-0.09801290929317474,
0.325968861579895,
0.22520777583122253,
0.09227751195430756,
0.03513903170824051,
0.5028657913208008,
0.028904594480991364,
-0.19265466928482056,
-0.07568523287773132,
0.004324430599808693,
-0.35453489422798157,
-0.16355344653129578,
-0.058457862585783005,
0.1632135659456253,
-0.4496609568595886,
0.3605155050754547,
0.04926588013768196,
-0.11139626055955887,
0.09741541743278503,
0.021948814392089844,
-0.09885645657777786,
-0.09097623080015182,
0.08899564296007156,
0.15876539051532745,
0.28199058771133423,
0.7396944165229797,
0.018032066524028778,
0.0463823527097702,
-0.09544427692890167,
0.010541828349232674,
-0.01951901614665985,
-0.07139810919761658,
-0.21920379996299744,
-0.20084403455257416,
0.07530634105205536,
-0.03850242495536804,
0.08397188782691956,
-0.6680576205253601,
-0.4091363251209259,
0.031875986605882645,
0.04847077280282974,
0.072431281208992,
0.7247989177703857,
0.054000239819288254,
-0.18400411307811737,
-0.11854550242424011,
-0.3672237694263458,
0.031231006607413292,
-0.27500683069229126,
0.1617080718278885,
-0.3264085054397583
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | > @zphang is having different batch sizes per task actually helpful? Would be interesting to know as it's not something I've come across as a technique used by any MTL papers.
I think having different batch sizes per task is particularly helpful in some scenarios where each task has different amount of data. For example, the problem I'm currently facing is one task has tens of thousands of samples while one task has a couple hundreds. I think in this case different batch size could help. But if using the same batch size is a lot simpler to implement, I guess it makes sense to go with that. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 108 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
> @zphang is having different batch sizes per task actually helpful? Would be interesting to know as it's not something I've come across as a technique used by any MTL papers.
I think having different batch sizes per task is particularly helpful in some scenarios where each task has different amount of data. For example, the problem I'm currently facing is one task has tens of thousands of samples while one task has a couple hundreds. I think in this case different batch size could help. But if using the same batch size is a lot simpler to implement, I guess it makes sense to go with that. | [
-0.15286675095558167,
-0.4851095676422119,
-0.08828960359096527,
0.04388965666294098,
-0.30230510234832764,
0.02592063695192337,
0.26860570907592773,
0.09124504774808884,
0.27223020792007446,
-0.07411901652812958,
-0.16744045913219452,
0.12118718028068542,
-0.2572723925113678,
0.44997718930244446,
0.3634524643421173,
-0.4062099754810333,
0.030634447932243347,
-0.2730120122432709,
-0.22879037261009216,
0.4066848158836365,
0.036920905113220215,
0.051403194665908813,
-0.13749776780605316,
0.048646025359630585,
-0.2384946346282959,
-0.1524750143289566,
-0.31967318058013916,
0.055579692125320435,
0.19754554331302643,
0.0446510948240757,
0.11467425525188446,
0.3015516400337219,
0.047315604984760284,
0.15700912475585938,
-0.00011640706361504272,
-0.08212161064147949,
0.22991494834423065,
-0.020130040124058723,
0.07947728037834167,
-0.019034460186958313,
0.13090094923973083,
-0.5154120326042175,
-0.03750036656856537,
-0.10425849258899689,
0.27347856760025024,
0.21355989575386047,
0.2659730613231659,
0.03253559768199921,
0.25440889596939087,
-0.2947164475917816,
0.09862411767244339,
0.32211872935295105,
-0.2970360517501831,
0.2996929883956909,
-0.010349847376346588,
-0.014742083847522736,
0.05328204482793808,
0.26293087005615234,
0.6999955177307129,
-0.49931326508522034,
0.0012699216604232788,
0.16061906516551971,
0.027350855991244316,
0.02736656367778778,
0.1041140928864479,
-0.05754975974559784,
-0.14754286408424377,
-0.2259558141231537,
-0.3079743981361389,
0.24689793586730957,
-0.08192551881074905,
-0.06607357412576675,
-0.23695698380470276,
-0.6513186097145081,
-0.007324228063225746,
0.04993279278278351,
-0.350864440202713,
0.186945840716362,
-0.18846456706523895,
-0.09649688005447388,
-0.15846090018749237,
-0.05361082777380943,
-0.007652949541807175,
0.06648024171590805,
0.37570899724960327,
0.505257248878479,
0.013429434970021248,
0.1736924797296524,
0.3467084467411041,
0.03121255710721016,
-0.10651373118162155,
-0.24471548199653625,
0.2853563129901886,
0.10458505898714066,
-0.370259553194046,
-0.2722153663635254,
0.1617216169834137,
-0.2643088102340698,
0.2712612748146057,
0.023664042353630066,
0.1709330826997757,
0.021655306220054626,
-0.0688675120472908,
0.17013107240200043,
0.40976235270500183,
0.1125168651342392,
-0.09519147127866745,
-0.1455383598804474,
0.04109416529536247,
-0.1776212751865387,
0.18310831487178802,
0.20799770951271057,
0.14859290421009064,
-0.13576693832874298,
-0.46563732624053955,
-0.08216294646263123,
-0.25629374384880066,
0.149321511387825,
-0.20054562389850616,
-0.5421443581581116,
-0.04683934897184372,
-0.23184806108474731,
-0.00907492358237505,
-0.11373697966337204,
-0.29090937972068787,
0.14404302835464478,
-0.11999651044607162,
0.22714763879776,
-0.16093432903289795,
0.07435385882854462,
-0.05789913237094879,
0.004685141146183014,
-0.44629794359207153,
-0.1151442751288414,
0.2692190110683441,
0.16773712635040283,
0.08348635584115982,
0.0706988051533699,
-0.06737266480922699,
0.1179807186126709,
0.28367072343826294,
-0.004396373406052589,
-0.032980822026729584,
0.0396023765206337,
0.22117272019386292,
-0.2768903374671936,
-0.1352517157793045,
0.3050745725631714,
-0.3997878432273865,
-0.022525280714035034,
-0.23434147238731384,
-0.19428640604019165,
0.18709267675876617,
0.020744837820529938,
-0.1286899745464325,
-0.22317004203796387,
-0.5973215103149414,
0.6830006837844849,
0.06751823425292969,
-0.046523068100214005,
-0.15667149424552917,
0.17821726202964783,
-0.19402453303337097,
-0.17894062399864197,
0.011592505499720573,
0.08312460780143738,
-0.06165241450071335,
-0.3461354076862335,
0.0005171513184905052,
-0.11840665340423584,
0.01542605459690094,
0.3973841071128845,
-0.1924615055322647,
0.28655773401260376,
0.09445212036371231,
0.12006457149982452,
0.2664092183113098,
-0.4741748869419098,
-0.049382515251636505,
0.45079997181892395,
-0.019094228744506836,
0.35060596466064453,
0.1672840714454651,
0.26022273302078247,
0.0020201322622597218,
-0.17475318908691406,
0.23725655674934387,
0.897196888923645,
-0.4060541093349457,
0.08358100056648254,
-0.13938406109809875,
-0.42281439900398254,
0.5240345597267151,
0.3101251423358917,
0.10595034062862396,
-0.3104816973209381,
-0.06986040621995926,
0.04622741416096687,
0.13682276010513306,
0.09810622781515121,
0.12557418644428253,
-0.057762593030929565,
-0.4325707256793976,
-0.0024137496948242188,
-0.19192519783973694,
-0.06833679974079132,
-0.49648332595825195,
0.0032335594296455383,
-0.15541516244411469,
0.2653364837169647,
0.373635470867157,
-0.058589108288288116,
0.34154415130615234,
-0.3247836232185364,
-0.0682685375213623,
-0.3196665942668915,
0.07444004714488983,
-0.095672607421875,
0.03928646072745323,
-0.3197908401489258,
-0.06206240504980087,
0.3237813413143158,
0.12032066285610199,
-0.14445088803768158,
-0.42558753490448,
0.1923220306634903,
-0.037724703550338745,
0.08093027770519257,
0.016697179526090622,
0.5754867196083069,
-0.2911287546157837,
-0.12075145542621613,
0.10930070281028748,
0.24802979826927185,
-0.28013497591018677,
0.218608558177948,
0.21097564697265625,
0.2668554484844208,
0.2549041509628296,
0.12753558158874512,
0.2021847516298294,
-0.1201392412185669,
-0.09720626473426819,
-0.2197658121585846,
-0.03213990479707718,
0.4492030143737793,
-0.09584534168243408,
0.4679342210292816,
-0.04142171889543533,
-0.1082647442817688,
-0.22867216169834137,
-0.04206334054470062,
-0.20951564610004425,
0.35186707973480225,
0.3388044238090515,
-0.1527581363916397,
0.3212238848209381,
-0.087537482380867,
-0.32107263803482056,
0.15290342271327972,
0.0971042811870575,
0.0753893256187439,
0.05987535044550896,
-0.015522070229053497,
-0.04942823201417923,
-0.29519227147102356,
-0.16740113496780396,
0.3495880365371704,
0.7306103110313416,
0.22298802435398102,
0.199818953871727,
-0.0016516447067260742,
-0.16649731993675232,
-0.16180893778800964,
-0.007260546088218689,
0.19259782135486603,
-0.019021527841687202,
0.2063293755054474,
0.026077844202518463,
0.010703608393669128,
0.047556810081005096,
-0.14258532226085663,
0.12812857329845428,
-0.19433893263339996,
-0.039021871984004974,
0.001227010041475296,
-0.21815864741802216,
-0.6630979180335999,
-0.34492602944374084,
0.03966861218214035,
-0.2795931100845337,
-0.22961638867855072,
0.09637437760829926,
0.006200697273015976,
-0.20221716165542603,
0.09744243323802948,
0.254486620426178,
0.6557924747467041,
-0.4205453097820282,
-0.1220015361905098,
-0.011811692267656326,
-0.2465246468782425,
-0.18224331736564636,
0.08044181764125824,
0.4787087142467499,
0.1971724033355713,
0.4226318597793579,
0.25549378991127014,
-0.07075680047273636,
0.08091455698013306,
-0.3518063724040985,
0.025702081620693207,
-0.2472161501646042,
0.24243246018886566,
0.11621172726154327,
-0.23505277931690216,
0.19698333740234375,
-0.33835020661354065,
-0.03175120800733566,
-0.11529534310102463,
-0.07352644205093384,
-0.1828647404909134,
-0.022766556590795517,
0.04582684114575386,
-0.21434494853019714,
-0.14710214734077454,
-0.6761797070503235,
-0.423672616481781,
0.3288804292678833,
-0.2589181661605835,
0.08312936127185822,
0.06865055114030838,
-0.2425619661808014,
0.11010250449180603,
-0.12082317471504211,
0.02017778903245926,
-0.10749750584363937,
-0.1358654946088791,
-0.10516944527626038,
-0.3834722936153412,
-0.16408587992191315,
-0.44173675775527954,
-0.0516645610332489,
0.2295835167169571,
0.027340183034539223,
-0.10455960780382156,
-0.13729692995548248,
0.09618252515792847,
-0.22930790483951569,
0.07182342559099197,
0.30790358781814575,
0.05160655081272125,
-0.3560315668582916,
0.13332213461399078,
-0.012046035379171371,
-0.21837742626667023,
0.1295343041419983,
0.3778134286403656,
0.4913676977157593,
0.14920908212661743,
0.024773813784122467,
0.124551922082901,
0.7539142370223999,
0.20179390907287598,
0.05993613600730896,
0.10636746883392334,
0.24882110953330994,
-0.016944710165262222,
0.1358460783958435,
-0.11611085385084152,
0.39773058891296387,
-0.13664868474006653,
0.42631685733795166,
0.17098723351955414,
0.19975197315216064,
-0.2030813843011856,
-0.1982661336660385,
-0.04472185671329498,
-0.2616236209869385,
-0.1858825981616974,
0.28222328424453735,
-0.2242661416530609,
0.052601393312215805,
-0.08051186800003052,
-0.43985608220100403,
-0.28615260124206543,
-0.030420005321502686,
-0.0606733113527298,
0.27411603927612305,
-0.09199515730142593,
0.1816534548997879,
-0.3203604519367218,
-0.15978267788887024,
-0.4608957767486572,
0.1459830105304718,
0.08875874429941177,
0.3017204701900482,
-0.012456808239221573,
-0.08777286857366562,
-0.07358933985233307,
0.20257049798965454,
0.6373814344406128,
-0.448762983083725,
-0.1601756364107132,
-0.005617394112050533,
0.060697779059410095,
-0.1331735998392105,
-0.21247753500938416,
-0.25151216983795166,
-0.0027016708627343178,
0.46255674958229065,
0.3910315930843353,
-0.35132133960723877,
-0.29208096861839294,
0.19622765481472015,
-0.16269074380397797,
-0.05591331794857979,
-0.23227892816066742,
-0.24113264679908752,
-0.10254239290952682,
-0.10813840478658676,
0.11773519963026047,
0.15848436951637268,
0.23454245924949646,
-0.16833293437957764,
0.16883863508701324,
-0.03416452556848526,
0.21754100918769836,
0.17560702562332153,
0.0023399870842695236,
-0.08446931838989258,
0.28032708168029785,
0.11757074296474457,
-0.018795277923345566,
-0.052353084087371826,
-0.18998877704143524,
0.08903008699417114,
-0.16537903249263763,
0.1914764791727066,
0.32191795110702515,
-0.03718516603112221,
0.6493061780929565,
0.09719540178775787,
0.33552613854408264,
0.19747206568717957,
-0.057175107300281525,
0.10656420886516571,
-0.20644065737724304,
0.16744470596313477,
0.1632019430398941,
0.19573616981506348,
-0.2039257436990738,
-0.25002917647361755,
0.5089166164398193,
0.4079136550426483,
-0.00573991984128952,
0.33328256011009216,
-0.6443974375724792,
-0.25987666845321655,
0.23563896119594574,
0.007103554904460907,
0.5431056618690491,
0.005898706614971161,
0.3782307207584381,
-0.04366758465766907,
-0.3120470643043518,
0.480791300535202,
-0.329947829246521,
0.16691383719444275,
-0.04985711723566055,
-0.14279991388320923,
0.07683635503053665,
-0.09651876986026764,
-0.05870380252599716,
0.3432524800300598,
-0.2126275897026062,
0.3445494771003723,
0.4961307644844055,
-0.2248227298259735,
-0.17989489436149597,
0.47908806800842285,
-0.012490028515458107,
-0.37976929545402527,
0.0026413705199956894,
0.029900487512350082,
-0.2305547446012497,
0.1625853329896927,
-0.21588605642318726,
-0.20611076056957245,
0.2247900366783142,
0.13790561258792877,
-0.3079603314399719,
-0.02638571709394455,
-0.056044258177280426,
0.19251877069473267,
0.2610135078430176,
-0.017162799835205078,
0.25520721077919006,
-0.24698877334594727,
-0.1174718588590622,
-0.17436350882053375,
-0.05939333140850067,
0.0534650981426239,
-0.0917482003569603,
0.11164909601211548,
0.07159196585416794,
-0.196152463555336,
0.46401092410087585,
-0.07571911811828613,
-0.021194279193878174,
-0.22428280115127563,
0.2308792769908905,
-0.3635616898536682,
-0.22265037894248962,
0.20926348865032196,
0.14877155423164368,
0.23195645213127136,
-0.31442898511886597,
0.5743623971939087,
0.08713354170322418,
0.07795141637325287,
0.010979234240949154,
0.15689313411712646,
-0.12796767055988312,
0.632997453212738,
-0.2941191792488098,
-0.07013058662414551,
-0.006362538784742355,
-0.08990371972322464,
0.01585724577307701,
-0.44756096601486206,
-0.06190013140439987,
0.27504709362983704,
0.13799363374710083,
0.028833702206611633,
0.09607603400945663,
0.04632272198796272,
-0.07321404665708542,
0.024421604350209236,
-0.05657602846622467,
-0.26283934712409973,
0.21956144273281097,
0.2410237193107605,
0.18731345236301422,
0.27172982692718506,
-0.0618717260658741,
-0.2633691430091858,
-0.10183098167181015,
0.46383529901504517,
-0.013535238802433014,
0.24274982511997223,
-0.09981803596019745,
0.4236372113227844,
0.4712507724761963,
0.5466607809066772,
-0.20703789591789246,
0.07370539009571075,
0.13231545686721802,
0.09527561068534851,
0.39160600304603577,
-0.05915419012308121,
0.04130518063902855,
0.40140238404273987,
-0.18922612071037292,
0.08920939266681671,
-0.34877458214759827,
-0.12751220166683197,
-0.22972330451011658,
0.1274731308221817,
0.15703818202018738,
0.03752823919057846,
0.05876712128520012,
-0.08815532922744751,
-0.013388663530349731,
-0.044957131147384644,
0.06431731581687927,
-0.2907070815563202,
-0.07052233815193176,
0.08662541955709457,
0.019152451306581497,
0.014970462769269943,
0.12828858196735382,
0.4145223796367645,
0.07437916845083237,
-0.08982579410076141,
0.3278343081474304,
0.1382105052471161,
0.1572459191083908,
-0.12971729040145874,
-0.21711261570453644,
-0.08144602924585342,
0.271614134311676,
0.1716535985469818,
-0.1672322154045105,
0.09358740597963333,
-0.21850991249084473,
-0.08033723384141922,
0.1846635341644287,
0.24251602590084076,
0.07674828171730042,
-0.12868699431419373,
0.17664793133735657,
0.07307992875576019,
-0.023402612656354904,
-0.0032811930868774652,
0.13657668232917786,
0.09947994351387024,
0.039155375212430954,
0.2060372680425644,
0.2117108404636383,
0.5047973990440369,
-0.23348025977611542,
0.01652560383081436,
0.06762964278459549,
-0.3135484457015991,
0.09969207644462585,
-0.13878469169139862,
-0.016195103526115417,
0.028218304738402367,
0.2262643724679947,
-0.08678199350833893,
0.15465793013572693,
-0.30596089363098145,
0.32733529806137085,
0.2416602075099945,
0.03566158562898636,
-0.023880433291196823,
0.12478074431419373,
-0.03723393380641937,
-0.20662887394428253,
0.3375938832759857,
-0.029000192880630493,
0.31513136625289917,
0.009087376296520233,
0.7983553409576416,
-0.2380809187889099,
-0.3960985839366913,
0.15436698496341705,
0.4071566164493561,
0.008456403389573097,
-0.2650139033794403,
0.10717974603176117,
0.13453203439712524,
-0.2611269950866699,
0.20869114995002747,
-0.047895628958940506,
-0.0980665534734726,
0.5933933258056641,
-0.06555300951004028,
0.17357707023620605,
-0.16121459007263184,
-0.26063650846481323,
0.34757816791534424,
0.008399970829486847,
-0.12483534216880798,
0.05821116641163826,
-0.029602721333503723,
-0.09513767063617706,
-0.10379637777805328,
0.5061762928962708,
0.18733710050582886,
0.09599249064922333,
-0.34532904624938965,
-0.12983378767967224,
0.14326107501983643,
0.2453797608613968,
-0.18993660807609558,
0.11646673828363419,
0.4996979534626007,
-0.19961269199848175,
0.2697572112083435,
-0.025633160024881363,
-0.051957614719867706,
-0.04092942550778389,
0.044215790927410126,
-0.48897045850753784,
-0.41631606221199036,
0.4167274534702301,
0.03329203277826309,
-0.09751677513122559,
0.05186869949102402,
0.38108333945274353,
-0.6517300009727478,
-0.19317051768302917,
0.30628684163093567,
-0.1815161406993866,
-0.08955494314432144,
-0.24177534878253937,
0.05955817550420761,
0.039202868938446045,
0.7016072273254395,
0.2924351990222931,
0.32732290029525757,
-0.3832719027996063,
-0.08002852648496628,
-0.571548342704773,
-0.1767008900642395,
0.018201462924480438,
0.000060731545090675354,
-0.2943786084651947,
0.26411956548690796,
-0.12518629431724548,
0.22162367403507233,
-0.0940609872341156,
0.08814497292041779,
0.14160360395908356,
0.07060161978006363,
-0.4327945411205292,
0.09113295376300812,
0.050961028784513474,
0.08235752582550049,
0.30425775051116943,
-0.07882454246282578,
-0.13369040191173553,
0.05160808935761452,
-0.13522720336914062,
-0.17467184364795685,
-0.08309835195541382,
0.31040307879447937,
0.21442070603370667,
0.10870148241519928,
0.01488940604031086,
0.4607813358306885,
0.05151563882827759,
-0.18575263023376465,
-0.12474758923053741,
-0.022356001660227776,
-0.3448331952095032,
-0.1339934766292572,
-0.05004814639687538,
0.17086800932884216,
-0.4427906274795532,
0.3610150218009949,
0.04574093595147133,
-0.12132153660058975,
0.11556059122085571,
0.034114062786102295,
-0.050387606024742126,
-0.06718190014362335,
0.12175998836755753,
0.12575607001781464,
0.279092401266098,
0.6992523670196533,
0.02689368464052677,
0.020200582221150398,
-0.08986503630876541,
-0.024383937940001488,
-0.03306381404399872,
-0.05258099362254143,
-0.20456336438655853,
-0.21896520256996155,
0.095838762819767,
-0.060808442533016205,
0.1070447787642479,
-0.6410905718803406,
-0.38680341839790344,
0.05448320880532265,
0.06030602380633354,
0.058844875544309616,
0.6827636361122131,
0.07146307826042175,
-0.2238549441099167,
-0.11899231374263763,
-0.37256860733032227,
0.041019268333911896,
-0.29618901014328003,
0.1502608358860016,
-0.3555028438568115
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | I think that instead of proportional to size sampling you should specify weights or probabilities for drawing a batch from each dataset. We should also ensure that the smaller datasets are repeated so that the encoder layer doesn't overtrain on the largest dataset. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 43 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
I think that instead of proportional to size sampling you should specify weights or probabilities for drawing a batch from each dataset. We should also ensure that the smaller datasets are repeated so that the encoder layer doesn't overtrain on the largest dataset. | [
-0.10336709767580032,
-0.43319427967071533,
-0.02786410227417946,
-0.014036096632480621,
-0.2707732319831848,
0.08221616595983505,
0.15497680008411407,
0.07477396726608276,
0.3294964134693146,
-0.09032988548278809,
-0.16610202193260193,
0.26055219769477844,
-0.1972145438194275,
0.4019600450992584,
0.3530553877353668,
-0.464892715215683,
-0.05361878126859665,
-0.20055332779884338,
-0.3664042055606842,
0.33402031660079956,
0.015646427869796753,
0.08674705028533936,
-0.1794654130935669,
0.019072607159614563,
-0.2719663977622986,
-0.11051621288061142,
-0.39493507146835327,
0.1083938479423523,
0.11043483018875122,
-0.013923369348049164,
0.1876085251569748,
0.344235360622406,
0.06541892141103745,
0.05401723459362984,
-0.00011230397649342194,
-0.12137141078710556,
0.21756750345230103,
-0.09191820025444031,
0.13066019117832184,
-0.000581890344619751,
0.07844532281160355,
-0.47050097584724426,
-0.007732077036052942,
-0.1358966827392578,
0.20232844352722168,
0.17046016454696655,
0.29044148325920105,
0.00826919823884964,
0.39299511909484863,
-0.330892413854599,
0.09726569056510925,
0.25307148694992065,
-0.15323781967163086,
0.26218825578689575,
-0.1310252845287323,
-0.02023126929998398,
0.10178595036268234,
0.2531665563583374,
0.6352720260620117,
-0.534798264503479,
-0.036832697689533234,
0.10696162283420563,
0.025654474273324013,
0.03074496239423752,
0.1634942889213562,
-0.08338319510221481,
-0.319130539894104,
-0.33498701453208923,
-0.4021603465080261,
0.23699527978897095,
-0.14883258938789368,
-0.08392999321222305,
-0.24520662426948547,
-0.5854561924934387,
0.0016671568155288696,
0.016477355733513832,
-0.31532639265060425,
0.11600280553102493,
-0.20372825860977173,
-0.0343724749982357,
-0.25125688314437866,
-0.14696136116981506,
-0.0434427373111248,
0.14494892954826355,
0.3343847692012787,
0.5547493696212769,
0.08374859392642975,
0.16105499863624573,
0.3695610463619232,
0.057474397122859955,
-0.12632228434085846,
-0.31179752945899963,
0.29279690980911255,
0.10796751827001572,
-0.36916103959083557,
-0.3550264537334442,
0.13920462131500244,
-0.20298609137535095,
0.2949889004230499,
0.10299038887023926,
0.025053909048438072,
0.0836867168545723,
-0.07621697336435318,
0.25609761476516724,
0.371712327003479,
0.09638257324695587,
-0.08300160616636276,
-0.06298963725566864,
0.002955302596092224,
-0.06848469376564026,
0.143419548869133,
0.17668959498405457,
0.1238449364900589,
0.003416826482862234,
-0.4794355034828186,
-0.12967386841773987,
-0.258689820766449,
0.07781024277210236,
-0.15980178117752075,
-0.47638750076293945,
-0.06893062591552734,
-0.11731699109077454,
0.029383741319179535,
-0.08602423220872879,
-0.2983452081680298,
0.11831432580947876,
-0.09277249127626419,
0.23073945939540863,
-0.0812850296497345,
0.03701058402657509,
-0.04833853244781494,
0.07137130200862885,
-0.4358130693435669,
-0.058910809457302094,
0.2667330503463745,
0.12061843276023865,
0.10626675933599472,
0.16640640795230865,
0.013974253088235855,
0.15166302025318146,
0.3776472508907318,
0.016560018062591553,
0.005949541926383972,
-0.06492958962917328,
0.21329852938652039,
-0.3031078577041626,
0.0006738565862178802,
0.1707688421010971,
-0.36183294653892517,
-0.14570215344429016,
-0.19035518169403076,
-0.16295641660690308,
0.0947001725435257,
0.017278699204325676,
-0.1942499876022339,
-0.26328516006469727,
-0.44688764214515686,
0.7332510352134705,
0.026847876608371735,
-0.017139391973614693,
-0.1802855134010315,
0.26064807176589966,
-0.2235586792230606,
-0.06396756321191788,
0.2086058259010315,
0.12475068867206573,
-0.01690937951207161,
-0.3514384627342224,
-0.046797093003988266,
-0.014810100197792053,
0.034520648419857025,
0.36155638098716736,
-0.22166237235069275,
0.12773405015468597,
0.06172608584165573,
0.1461106836795807,
0.2180098593235016,
-0.4322619140148163,
-0.09815126657485962,
0.4060342013835907,
-0.01648067682981491,
0.3736610412597656,
0.1182851642370224,
0.19480188190937042,
0.12559908628463745,
-0.1956963837146759,
0.2478085160255432,
1.0400981903076172,
-0.4225592613220215,
0.022193072363734245,
-0.1649436354637146,
-0.3881130814552307,
0.5052050352096558,
0.36283397674560547,
0.09461911022663116,
-0.3206784129142761,
-0.1631169617176056,
-0.02661627158522606,
0.11877448856830597,
0.041435401886701584,
0.10451119393110275,
-0.009234648197889328,
-0.4052465260028839,
-0.022486738860607147,
-0.22144317626953125,
-0.07816123217344284,
-0.33089834451675415,
0.015293266624212265,
-0.08741414546966553,
0.32746365666389465,
0.34056544303894043,
-0.1058153510093689,
0.2896713316440582,
-0.2984875738620758,
-0.13058176636695862,
-0.33861082792282104,
0.11447054147720337,
-0.03951864689588547,
0.07346740365028381,
-0.2365601360797882,
-0.06718042492866516,
0.35986921191215515,
0.08904337137937546,
-0.1385277658700943,
-0.5096867680549622,
0.3090386390686035,
-0.057400934398174286,
0.06364452093839645,
-0.025107532739639282,
0.5965563654899597,
-0.19375944137573242,
-0.12890784442424774,
0.144881010055542,
0.22485199570655823,
-0.3346216678619385,
0.1949298083782196,
0.33768734335899353,
0.1734292060136795,
0.20787860453128815,
-0.08267894387245178,
0.17195725440979004,
-0.029911600053310394,
-0.09459737688302994,
-0.1404891014099121,
-0.03039642423391342,
0.500379741191864,
-0.11950579285621643,
0.44350945949554443,
-0.018835991621017456,
0.015261845663189888,
-0.2615099847316742,
-0.09255734086036682,
-0.21653792262077332,
0.35943979024887085,
0.33664095401763916,
-0.19295254349708557,
0.36073407530784607,
-0.05211370438337326,
-0.35946547985076904,
0.14874233305454254,
0.20372150838375092,
0.08420239388942719,
0.046032264828681946,
0.020731162279844284,
-0.10165785998106003,
-0.2789604663848877,
-0.10182248055934906,
0.461579829454422,
0.5798784494400024,
0.27897465229034424,
0.19102543592453003,
0.0029391925781965256,
-0.2511984705924988,
-0.0801590234041214,
0.03535642474889755,
0.2158656269311905,
-0.05848614126443863,
0.140546053647995,
0.024648314341902733,
0.009310554713010788,
0.01067931205034256,
-0.11853775382041931,
0.14683032035827637,
-0.18777890503406525,
-0.01490294560790062,
0.06336440145969391,
-0.19838862121105194,
-0.616385817527771,
-0.3052637577056885,
-0.015071871690452099,
-0.3515801727771759,
-0.2869986593723297,
0.13720376789569855,
-0.003792528063058853,
-0.138868510723114,
0.16575412452220917,
0.12699683010578156,
0.5480082631111145,
-0.42024415731430054,
-0.17030328512191772,
-0.02358926087617874,
-0.23749884963035583,
-0.12512165307998657,
0.10783182084560394,
0.47286322712898254,
0.2611252963542938,
0.43125152587890625,
0.28128984570503235,
-0.03624339774250984,
0.12175818532705307,
-0.34444907307624817,
0.04084836691617966,
-0.2936261296272278,
0.2540331780910492,
0.011807881295681,
-0.20614619553089142,
0.13463850319385529,
-0.4294755458831787,
-0.060518667101860046,
-0.01937848888337612,
-0.053349561989307404,
-0.028743047267198563,
-0.02822124771773815,
0.03259540721774101,
-0.17166337370872498,
-0.20089346170425415,
-0.6588301658630371,
-0.45629560947418213,
0.28352153301239014,
-0.20028935372829437,
0.09491465985774994,
0.02516014315187931,
-0.23395322263240814,
0.08987870067358017,
-0.16715110838413239,
-0.0019509382545948029,
-0.12760667502880096,
-0.12098366022109985,
0.08369611948728561,
-0.3582075834274292,
-0.16718408465385437,
-0.47265341877937317,
-0.1242687925696373,
0.24180172383785248,
-0.07113957405090332,
-0.07343463599681854,
-0.18778802454471588,
0.07646550983190536,
-0.19489236176013947,
0.07409609109163284,
0.26539111137390137,
0.10548775643110275,
-0.2660580277442932,
0.10515215992927551,
0.002967294305562973,
-0.13249753415584564,
0.2176908701658249,
0.345712274312973,
0.4796205461025238,
0.15022984147071838,
0.11335104703903198,
0.19090749323368073,
0.6792360544204712,
0.32960841059684753,
0.007964439690113068,
0.21351279318332672,
0.3103100657463074,
0.024073563516139984,
0.19754567742347717,
-0.21085034310817719,
0.34230101108551025,
-0.11590605974197388,
0.454321026802063,
0.10699529945850372,
0.151146799325943,
-0.24436338245868683,
-0.24342335760593414,
0.024328678846359253,
-0.20640727877616882,
-0.17803643643856049,
0.2593960165977478,
-0.22649115324020386,
0.020161356776952744,
-0.09770283102989197,
-0.36491405963897705,
-0.23557128012180328,
-0.05439337342977524,
-0.031282514333724976,
0.2283371239900589,
0.011614084243774414,
0.17223304510116577,
-0.3531283736228943,
-0.10165946185588837,
-0.4612160325050354,
0.20466774702072144,
0.05774303153157234,
0.301775187253952,
-0.01998644694685936,
-0.08469295501708984,
-0.1292436569929123,
0.12709130346775055,
0.5680522918701172,
-0.4728291928768158,
-0.2209477573633194,
-0.025382880121469498,
0.09025241434574127,
-0.09211970865726471,
-0.10572792589664459,
-0.21971237659454346,
-0.025454366579651833,
0.41992703080177307,
0.3062419295310974,
-0.36397260427474976,
-0.27792614698410034,
0.2682923674583435,
-0.1646314561367035,
-0.07220476865768433,
-0.14969685673713684,
-0.21267953515052795,
-0.13832350075244904,
-0.17088139057159424,
0.0775844007730484,
0.12965193390846252,
0.19336852431297302,
-0.13969531655311584,
0.16703511774539948,
-0.10889354348182678,
0.2603113055229187,
0.1859169900417328,
0.05234674736857414,
-0.027580726891756058,
0.19997909665107727,
0.17190344631671906,
0.05351324379444122,
-0.10656812787055969,
-0.23571938276290894,
0.1216953694820404,
-0.032500628381967545,
0.07200022041797638,
0.29760974645614624,
0.03904136270284653,
0.6938973069190979,
0.042601972818374634,
0.367055743932724,
0.22503027319908142,
-0.06475947052240372,
0.08747007697820663,
-0.21818453073501587,
0.1336088329553604,
0.22997234761714935,
0.20788517594337463,
-0.16687704622745514,
-0.22111359238624573,
0.5431409478187561,
0.2985454499721527,
-0.00961148738861084,
0.3315664231777191,
-0.5390052199363708,
-0.2511659264564514,
0.29675745964050293,
0.040164604783058167,
0.6300408840179443,
-0.007101081311702728,
0.2938927710056305,
-0.03298947587609291,
-0.3371446132659912,
0.5710722804069519,
-0.330727756023407,
0.19199493527412415,
-0.14019986987113953,
-0.24169905483722687,
-0.00279105082154274,
-0.0857037603855133,
-0.07936576753854752,
0.2763812243938446,
-0.33719825744628906,
0.36917930841445923,
0.4814932346343994,
-0.2480582892894745,
-0.1045876145362854,
0.5050842761993408,
-0.05645810812711716,
-0.3726613223552704,
-0.11116635799407959,
0.06115485727787018,
-0.27586644887924194,
0.09509329497814178,
-0.11868716776371002,
-0.3008018732070923,
0.27083778381347656,
0.12162388861179352,
-0.24231112003326416,
0.16438499093055725,
-0.050431910902261734,
0.1845231056213379,
0.25303924083709717,
0.008703038096427917,
0.27064093947410583,
-0.1624799370765686,
-0.08966235816478729,
-0.11695253849029541,
-0.07923764735460281,
0.11518245935440063,
-0.14977088570594788,
0.012844467535614967,
0.11990493535995483,
-0.2024591565132141,
0.4892711639404297,
-0.009573008865118027,
-0.13599589467048645,
-0.21550917625427246,
0.3113110661506653,
-0.38764089345932007,
-0.17851831018924713,
0.10874960571527481,
0.18113838136196136,
0.22955557703971863,
-0.35972678661346436,
0.5780019760131836,
0.1318092793226242,
0.027300912886857986,
0.03078719787299633,
0.14182829856872559,
-0.2512468993663788,
0.5130019783973694,
-0.27598828077316284,
-0.038096215575933456,
0.04208821803331375,
0.007354706525802612,
-0.08804501593112946,
-0.35103803873062134,
-0.03188447654247284,
0.283353328704834,
0.12923085689544678,
0.021556593477725983,
0.06551934033632278,
0.17462104558944702,
-0.07396022230386734,
-0.06540042906999588,
-0.13226768374443054,
-0.3194485902786255,
0.15650279819965363,
0.07593652606010437,
0.19611230492591858,
0.1613200157880783,
-0.07628889381885529,
-0.21275311708450317,
-0.21801771223545074,
0.5112912654876709,
0.021172910928726196,
0.25781238079071045,
-0.18163955211639404,
0.30822059512138367,
0.3887070417404175,
0.5697489976882935,
-0.2556871175765991,
0.11726082861423492,
0.055237285792827606,
0.06974649429321289,
0.46103349328041077,
-0.2023731768131256,
0.04363477602601051,
0.2892819941043854,
-0.14841970801353455,
0.06235472857952118,
-0.3408699035644531,
-0.14281439781188965,
-0.23465700447559357,
0.09880520403385162,
0.15117910504341125,
-0.019357137382030487,
0.009457303211092949,
-0.06798816472291946,
-0.09655873477458954,
-0.11638102680444717,
0.013011522591114044,
-0.4335089921951294,
-0.068189337849617,
0.11059035360813141,
-0.03718041256070137,
-0.045462995767593384,
0.07459377497434616,
0.23765985667705536,
0.001246139407157898,
-0.020071543753147125,
0.3473857641220093,
0.13781443238258362,
0.13269758224487305,
-0.16679096221923828,
-0.27622732520103455,
-0.01261458545923233,
0.2735847234725952,
0.1634385883808136,
-0.07122205942869186,
0.10352066904306412,
-0.24374069273471832,
-0.08736574649810791,
0.26286137104034424,
0.20636211335659027,
0.0771169364452362,
-0.17260372638702393,
0.15144741535186768,
0.11271845549345016,
-0.07894737273454666,
-0.0010420656763017178,
0.20892126858234406,
0.07174256443977356,
0.08645141124725342,
0.17023196816444397,
0.15795131027698517,
0.4282063841819763,
-0.24424384534358978,
-0.007555047050118446,
0.10386931896209717,
-0.34369808435440063,
0.14428013563156128,
-0.07468444108963013,
-0.01689911261200905,
-0.05834301933646202,
0.11644040048122406,
-0.042675282806158066,
0.22477833926677704,
-0.2821715474128723,
0.250227153301239,
0.30582141876220703,
0.00996827520430088,
-0.042123544961214066,
0.20314428210258484,
0.0018033422529697418,
-0.22454063594341278,
0.33291447162628174,
0.0851997509598732,
0.3855224847793579,
0.048954181373119354,
0.8560094237327576,
-0.24788807332515717,
-0.4657871425151825,
0.037295930087566376,
0.4859018623828888,
0.04150879383087158,
-0.27084872126579285,
0.14337950944900513,
0.09598004072904587,
-0.4118724465370178,
0.16141974925994873,
0.07498539984226227,
-0.18442364037036896,
0.6622331142425537,
-0.05848798155784607,
0.16207745671272278,
-0.19061189889907837,
-0.17011427879333496,
0.36753860116004944,
0.14315113425254822,
-0.13632890582084656,
0.07419116050004959,
0.1387922167778015,
-0.10969686508178711,
-0.14287377893924713,
0.5203854441642761,
0.2531953752040863,
0.03317749872803688,
-0.4345836639404297,
-0.022072333842515945,
0.16021208465099335,
0.16314104199409485,
-0.10989037156105042,
0.1235361397266388,
0.40921056270599365,
-0.1710437536239624,
0.2681717872619629,
0.013457048684358597,
-0.0643920972943306,
-0.17000040411949158,
-0.0010199770331382751,
-0.4380497634410858,
-0.38811764121055603,
0.4196394085884094,
0.11488635092973709,
-0.05141694098711014,
0.019021131098270416,
0.2460399568080902,
-0.687714159488678,
-0.2315683513879776,
0.3309122920036316,
-0.1353486329317093,
-0.10280797630548477,
-0.2420894056558609,
0.07230069488286972,
-0.015390504151582718,
0.6274807453155518,
0.29352179169654846,
0.33659446239471436,
-0.4087728261947632,
-0.15738613903522491,
-0.5566297173500061,
-0.1426028609275818,
0.10983379185199738,
-0.1562354564666748,
-0.2828674912452698,
0.23817487061023712,
-0.09585996717214584,
0.23567375540733337,
-0.21898658573627472,
0.13313177227973938,
0.21304944157600403,
0.09838514029979706,
-0.4491214454174042,
0.12216770648956299,
0.10001176595687866,
0.04428112506866455,
0.2792525291442871,
-0.09820935130119324,
-0.1715533584356308,
0.053720925003290176,
-0.10322336852550507,
-0.008149050176143646,
-0.016879189759492874,
0.24552473425865173,
0.0991356372833252,
0.12277588248252869,
0.0672542005777359,
0.5235679149627686,
-0.033524513244628906,
-0.2191493958234787,
0.005622748285531998,
-0.0402335561811924,
-0.41220858693122864,
-0.13063281774520874,
-0.07771554589271545,
0.2438381016254425,
-0.34682708978652954,
0.26382020115852356,
-0.04028177261352539,
-0.12499444931745529,
0.12921610474586487,
0.031963687390089035,
-0.12255164980888367,
-0.05809997022151947,
0.05785603076219559,
0.21735650300979614,
0.21858006715774536,
0.712125837802887,
0.03826141357421875,
0.10666997730731964,
-0.028916187584400177,
-0.024187881499528885,
0.0697459951043129,
-0.08190585672855377,
-0.22436916828155518,
-0.2049376666545868,
0.02550646662712097,
0.06479815393686295,
0.07541317492723465,
-0.6441550254821777,
-0.3265171945095062,
0.011607188731431961,
0.004460446536540985,
0.04752181097865105,
0.7026143074035645,
0.11499851942062378,
-0.14029523730278015,
-0.133981391787529,
-0.2580876052379608,
-0.0005197040736675262,
-0.32983556389808655,
0.20005002617835999,
-0.30358052253723145
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | Are there any references for people doing different batch sizes per task in the literature? I've only seen constant batch sizes with differing numbers of batches for each task which seems sufficient to prevent the impact of large datasets (Read 3.5.3 of the [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) for example).
| It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 47 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
Are there any references for people doing different batch sizes per task in the literature? I've only seen constant batch sizes with differing numbers of batches for each task which seems sufficient to prevent the impact of large datasets (Read 3.5.3 of the [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) for example).
| [
-0.0643157884478569,
-0.46592262387275696,
-0.08466394245624542,
-0.03106280416250229,
-0.2937632203102112,
0.014267697930335999,
0.27487197518348694,
-0.0015316680073738098,
0.32739582657814026,
-0.08819639682769775,
-0.14839480817317963,
0.1096205785870552,
-0.166634663939476,
0.4398263096809387,
0.3444587290287018,
-0.3664792776107788,
0.03876933455467224,
-0.2969401478767395,
-0.27085453271865845,
0.3853917121887207,
0.03808407485485077,
0.041931621730327606,
-0.13354316353797913,
0.08822565525770187,
-0.28080931305885315,
-0.2636697292327881,
-0.38970765471458435,
0.03443445637822151,
0.1399758756160736,
0.051349662244319916,
0.23408935964107513,
0.307551771402359,
0.048616886138916016,
0.27919378876686096,
-0.00011687174264807254,
-0.08377620577812195,
0.2308100014925003,
-0.01913651078939438,
0.11680890619754791,
-0.0018155276775360107,
0.15380114316940308,
-0.4783225357532501,
0.005464307498186827,
-0.11083638668060303,
0.2739708125591278,
0.15680430829524994,
0.25918132066726685,
0.10646338760852814,
0.28866541385650635,
-0.3447949290275574,
0.09772253036499023,
0.2746815085411072,
-0.21083860099315643,
0.22634679079055786,
-0.11846130341291428,
-0.01419290155172348,
0.07735439389944077,
0.2606106102466583,
0.7055602073669434,
-0.5410453081130981,
-0.0727652832865715,
0.07944448292255402,
0.04223468899726868,
0.011969641782343388,
0.1090795248746872,
-0.17149625718593597,
-0.2628779411315918,
-0.297519713640213,
-0.32956618070602417,
0.22085723280906677,
-0.08587924391031265,
-0.09882543236017227,
-0.26016151905059814,
-0.6264215111732483,
-0.03642530366778374,
0.03155381232500076,
-0.3546121120452881,
0.16949914395809174,
-0.2045310139656067,
-0.1291305273771286,
-0.234602689743042,
-0.10024101287126541,
-0.026420921087265015,
0.07539796084165573,
0.34746411442756653,
0.5395692586898804,
0.0419699102640152,
0.12721998989582062,
0.39268121123313904,
-0.03826463222503662,
-0.08897200226783752,
-0.27377161383628845,
0.2567116618156433,
0.13433712720870972,
-0.39920154213905334,
-0.29389309883117676,
0.1546253263950348,
-0.26450997591018677,
0.31528714299201965,
0.08219506591558456,
0.08174525946378708,
0.051612235605716705,
-0.14183208346366882,
0.19767314195632935,
0.4014679193496704,
0.1253281980752945,
-0.09977950900793076,
-0.11220314353704453,
0.04722511023283005,
-0.1615312397480011,
0.21224674582481384,
0.18241596221923828,
0.14265777170658112,
-0.13860581815242767,
-0.5396937131881714,
-0.16719037294387817,
-0.27625465393066406,
0.1414400339126587,
-0.18073806166648865,
-0.574489176273346,
-0.02044694870710373,
-0.15083536505699158,
0.020509587600827217,
-0.09436807781457901,
-0.27212539315223694,
0.09609212726354599,
-0.11833249777555466,
0.26906847953796387,
-0.16005444526672363,
0.0736631453037262,
-0.05052114650607109,
0.04711295664310455,
-0.47076326608657837,
-0.1046871617436409,
0.2876485586166382,
0.17828719317913055,
0.09426694363355637,
0.18709905445575714,
-0.03195817023515701,
0.08593122661113739,
0.30259835720062256,
-0.06191828101873398,
-0.05103866010904312,
0.039355069398880005,
0.24605825543403625,
-0.26802659034729004,
-0.087934210896492,
0.2486291378736496,
-0.3791605830192566,
-0.05903386324644089,
-0.23170897364616394,
-0.15932096540927887,
0.15850937366485596,
-0.0022806283086538315,
-0.1443961262702942,
-0.2504304051399231,
-0.5782618522644043,
0.6736925840377808,
0.06236782297492027,
-0.05668482556939125,
-0.16031387448310852,
0.2204204499721527,
-0.14365476369857788,
-0.18698127567768097,
0.0599556565284729,
0.018210165202617645,
-0.032834481447935104,
-0.3329956531524658,
0.03664219379425049,
-0.03524135798215866,
0.003587670624256134,
0.4364960789680481,
-0.1851608157157898,
0.28957483172416687,
0.08100872486829758,
0.12182895839214325,
0.2664524018764496,
-0.4424835443496704,
-0.011515280231833458,
0.41733318567276,
0.05032651871442795,
0.3307779133319855,
0.12340635061264038,
0.23189181089401245,
0.04421749711036682,
-0.2073780745267868,
0.2358897477388382,
0.97413569688797,
-0.37452682852745056,
0.09668097645044327,
-0.05804971978068352,
-0.46580228209495544,
0.4411907196044922,
0.2258761078119278,
0.08976149559020996,
-0.2925753593444824,
-0.07390519231557846,
-0.054094135761260986,
0.057376813143491745,
0.08964527398347855,
0.09594698995351791,
0.047746121883392334,
-0.4209632873535156,
0.0964864194393158,
-0.18344923853874207,
-0.050520528107881546,
-0.44608891010284424,
-0.010563749819993973,
-0.08277759701013565,
0.19561369717121124,
0.3746560215950012,
-0.09083861112594604,
0.3362386226654053,
-0.3263072669506073,
-0.09256401658058167,
-0.34133198857307434,
0.06611593812704086,
-0.12174712121486664,
0.09767484664916992,
-0.30773478746414185,
0.0007403865456581116,
0.33542773127555847,
0.09459519386291504,
-0.10449420660734177,
-0.4976728558540344,
0.17593219876289368,
-0.036461055278778076,
-0.008630004711449146,
0.05814778804779053,
0.5408447980880737,
-0.1912010908126831,
-0.08414341509342194,
0.1043061912059784,
0.28971901535987854,
-0.2685345411300659,
0.2316524237394333,
0.31108570098876953,
0.26073765754699707,
0.21135921776294708,
0.118392214179039,
0.2055724859237671,
-0.10977359116077423,
-0.09943695366382599,
-0.22493010759353638,
-0.10347156971693039,
0.46075230836868286,
-0.13459336757659912,
0.5010107755661011,
-0.02969755232334137,
-0.07168645411729813,
-0.18867169320583344,
-0.017303455621004105,
-0.1613268405199051,
0.45697250962257385,
0.3395251929759979,
-0.17075707018375397,
0.3268982768058777,
-0.09833280742168427,
-0.3560428321361542,
0.05383462458848953,
0.022897612303495407,
0.05386388674378395,
0.08113538473844528,
-0.0080033540725708,
-0.030827999114990234,
-0.29537585377693176,
-0.1262146532535553,
0.3653463125228882,
0.6546183824539185,
0.22161778807640076,
0.2182420790195465,
-0.06149466335773468,
-0.22549623250961304,
-0.15221518278121948,
-0.025874458253383636,
0.2021447867155075,
0.006639918778091669,
0.16049888730049133,
0.026298027485609055,
-0.005736664868891239,
0.08471231907606125,
-0.1053382009267807,
0.11840752512216568,
-0.22522202134132385,
-0.08519266545772552,
0.005405334755778313,
-0.22219176590442657,
-0.6311858296394348,
-0.3055891692638397,
0.015079880133271217,
-0.30497050285339355,
-0.23138725757598877,
0.03909820318222046,
0.07374662160873413,
-0.11424049735069275,
0.08188289403915405,
0.21158628165721893,
0.637373685836792,
-0.43466487526893616,
-0.10998263210058212,
-0.03147666156291962,
-0.24741141498088837,
-0.14098459482192993,
0.0675954818725586,
0.4684332013130188,
0.2097017914056778,
0.4605121910572052,
0.3219369053840637,
-0.10924215614795685,
0.11420060694217682,
-0.32258519530296326,
0.026337826624512672,
-0.2005293071269989,
0.242381289601326,
0.04370402172207832,
-0.15862421691417694,
0.176504448056221,
-0.33668437600135803,
-0.07314237952232361,
-0.06108460575342178,
-0.05285245180130005,
-0.1735837459564209,
-0.07025719434022903,
0.05648849159479141,
-0.14883579313755035,
-0.10039744526147842,
-0.6727861166000366,
-0.39646661281585693,
0.3388640284538269,
-0.25696566700935364,
0.06550872325897217,
0.02542121335864067,
-0.19426095485687256,
0.07539035379886627,
-0.14416266977787018,
-0.017736678943037987,
-0.07496719062328339,
-0.12288616597652435,
-0.02914408966898918,
-0.4028762876987457,
-0.1595148891210556,
-0.37320849299430847,
-0.02167428284883499,
0.19834546744823456,
0.0170576311647892,
-0.06768269091844559,
-0.09868606925010681,
0.02911701239645481,
-0.1789454072713852,
0.1095881536602974,
0.34813860058784485,
0.083240807056427,
-0.3999960124492645,
0.15140101313591003,
-0.055636562407016754,
-0.24908709526062012,
0.14666146039962769,
0.2859276831150055,
0.4913572371006012,
0.21992048621177673,
0.008941875770688057,
0.15517903864383698,
0.7662396430969238,
0.2730218172073364,
0.02362293377518654,
0.0985933467745781,
0.28743621706962585,
0.02550457790493965,
0.12757091224193573,
-0.11887826025485992,
0.3374464809894562,
-0.17567282915115356,
0.4366201162338257,
0.06794396042823792,
0.20402318239212036,
-0.16058145463466644,
-0.23380237817764282,
-0.0395277664065361,
-0.32576462626457214,
-0.17143847048282623,
0.25072628259658813,
-0.2517654299736023,
0.07811987400054932,
-0.1435822695493698,
-0.43167445063591003,
-0.29271435737609863,
-0.016961131244897842,
-0.0676080733537674,
0.3017239272594452,
-0.081898532807827,
0.20029884576797485,
-0.33506572246551514,
-0.16427873075008392,
-0.38935917615890503,
0.17401209473609924,
-0.002374277450144291,
0.299874484539032,
-0.037796445190906525,
-0.014264572411775589,
-0.07898098230361938,
0.17510312795639038,
0.5862996578216553,
-0.4357353448867798,
-0.14293211698532104,
-0.014258298091590405,
0.1116923838853836,
-0.1409677416086197,
-0.19628870487213135,
-0.25150614976882935,
0.053072646260261536,
0.5074841380119324,
0.37952733039855957,
-0.3611524701118469,
-0.31687700748443604,
0.19735835492610931,
-0.19273711740970612,
-0.0932251363992691,
-0.22613464295864105,
-0.21406161785125732,
-0.16825458407402039,
-0.0791085958480835,
0.14117708802223206,
0.13951720297336578,
0.15919187664985657,
-0.2341109663248062,
0.14947552978992462,
-0.07838371396064758,
0.28221195936203003,
0.17640581727027893,
-0.018854636698961258,
-0.07879453897476196,
0.24801918864250183,
0.10285070538520813,
0.017769701778888702,
-0.08682434260845184,
-0.16271844506263733,
0.03729332238435745,
-0.131301611661911,
0.1557673066854477,
0.29673823714256287,
0.013812731020152569,
0.6570740938186646,
0.10724851489067078,
0.4018983542919159,
0.20059719681739807,
-0.11568357050418854,
0.05698535218834877,
-0.19889219105243683,
0.12703147530555725,
0.23611553013324738,
0.24626266956329346,
-0.22283609211444855,
-0.24729734659194946,
0.5878698229789734,
0.3816869556903839,
-0.054454490542411804,
0.40503570437431335,
-0.6244817972183228,
-0.26055192947387695,
0.231800839304924,
0.024833209812641144,
0.599092423915863,
-0.013116806745529175,
0.29962143301963806,
-0.07944035530090332,
-0.35769355297088623,
0.459354043006897,
-0.3115878105163574,
0.1631142646074295,
-0.07900004088878632,
-0.08968059718608856,
0.07022058218717575,
-0.13893498480319977,
0.018397986888885498,
0.2944927215576172,
-0.235673725605011,
0.37945178151130676,
0.4121044874191284,
-0.2506578862667084,
-0.1553017944097519,
0.4758174419403076,
-0.034751228988170624,
-0.3831048309803009,
0.05561334267258644,
0.024736668914556503,
-0.2695632576942444,
0.17046722769737244,
-0.21481552720069885,
-0.200601726770401,
0.23190727829933167,
0.16014274954795837,
-0.35234177112579346,
0.023304615169763565,
-0.016125215217471123,
0.22780883312225342,
0.2794572114944458,
-0.049164604395627975,
0.2548297047615051,
-0.16728553175926208,
-0.10953828692436218,
-0.12556107342243195,
-0.03871750086545944,
0.10054507851600647,
-0.11218119412660599,
0.03601551055908203,
0.03847880661487579,
-0.17122697830200195,
0.43994638323783875,
-0.05404619872570038,
-0.08606556057929993,
-0.2332594096660614,
0.22317694127559662,
-0.2976759970188141,
-0.2963246703147888,
0.1337805688381195,
0.12846246361732483,
0.15110750496387482,
-0.31660398840904236,
0.5542105436325073,
0.16135236620903015,
0.0931546688079834,
0.007157033309340477,
0.16346269845962524,
-0.12557080388069153,
0.6486729979515076,
-0.3296874761581421,
-0.010702870786190033,
0.03142017126083374,
-0.09077974408864975,
0.006326589733362198,
-0.4751659631729126,
-0.05922219157218933,
0.2901131510734558,
0.11815185844898224,
0.04533172398805618,
0.09262455254793167,
0.0931677594780922,
0.026724770665168762,
-0.010842042975127697,
-0.10102419555187225,
-0.2596004009246826,
0.17278236150741577,
0.16765490174293518,
0.18941771984100342,
0.19720377027988434,
-0.05612855777144432,
-0.27054280042648315,
-0.10723855346441269,
0.4969039559364319,
-0.01926862820982933,
0.21876312792301178,
-0.11857306212186813,
0.3374301791191101,
0.4945826828479767,
0.5996097922325134,
-0.1953844577074051,
0.09189862757921219,
0.1511169970035553,
0.09730382263660431,
0.4130692183971405,
-0.085114024579525,
0.01588013395667076,
0.35309118032455444,
-0.20409706234931946,
0.037824276834726334,
-0.2977036237716675,
-0.1182650551199913,
-0.1918211579322815,
0.11325032263994217,
0.1212540715932846,
0.046959877014160156,
0.028699621558189392,
-0.14802198112010956,
0.009298676624894142,
-0.05196170136332512,
0.06106187030673027,
-0.25682711601257324,
-0.07784226536750793,
0.11179018765687943,
0.0003042444586753845,
0.08506157249212265,
0.14502769708633423,
0.37398841977119446,
0.04396069794893265,
-0.06393073499202728,
0.3479340076446533,
0.10780222713947296,
0.17816533148288727,
-0.15824896097183228,
-0.21071095764636993,
-0.05424991995096207,
0.2973994016647339,
0.14296922087669373,
-0.1791614294052124,
0.08633353561162949,
-0.1817280501127243,
-0.12257352471351624,
0.14351685345172882,
0.2863256335258484,
0.08999732881784439,
-0.11031541973352432,
0.21582332253456116,
0.061415016651153564,
0.006081629544496536,
0.002305425703525543,
0.17192593216896057,
0.1008213683962822,
-0.004941221326589584,
0.1974208801984787,
0.17235052585601807,
0.43909674882888794,
-0.2788703441619873,
0.029636621475219727,
0.09111108630895615,
-0.34259915351867676,
0.09730203449726105,
-0.1335470825433731,
-0.0017445646226406097,
-0.021511781960725784,
0.2189338356256485,
0.0036812033504247665,
0.14514659345149994,
-0.3186529278755188,
0.34929797053337097,
0.2836127281188965,
0.041865069419145584,
-0.03126334771513939,
0.1697319746017456,
-0.13565263152122498,
-0.23886196315288544,
0.2818862199783325,
-0.007455453276634216,
0.2914676368236542,
0.006257347762584686,
0.8371669054031372,
-0.27607426047325134,
-0.4076002240180969,
0.11187384277582169,
0.40588104724884033,
-0.008414365351200104,
-0.24195267260074615,
0.05891671031713486,
0.1356607973575592,
-0.21899615228176117,
0.18768543004989624,
0.005946461111307144,
-0.15572084486484528,
0.6309082508087158,
-0.0868590772151947,
0.15201355516910553,
-0.13946127891540527,
-0.1847788691520691,
0.3204897940158844,
0.06872246414422989,
-0.04573506861925125,
0.10238135606050491,
-0.0006037354469299316,
-0.08211371302604675,
-0.13777108490467072,
0.5545239448547363,
0.27132341265678406,
0.05069413036108017,
-0.3948327600955963,
-0.05802081897854805,
0.12167657911777496,
0.18451707065105438,
-0.09898988157510757,
0.12961964309215546,
0.4572368562221527,
-0.21894459426403046,
0.21530205011367798,
-0.018487699329853058,
-0.033718667924404144,
-0.06840468943119049,
0.03277232125401497,
-0.46991270780563354,
-0.35822170972824097,
0.4419861137866974,
0.03924168273806572,
-0.15338796377182007,
0.09869474172592163,
0.3518230617046356,
-0.6634207963943481,
-0.2220752239227295,
0.39307525753974915,
-0.15513268113136292,
-0.11853007227182388,
-0.19786436855793,
0.05703792721033096,
0.12376956641674042,
0.650640606880188,
0.30440041422843933,
0.315585196018219,
-0.33722466230392456,
-0.15077969431877136,
-0.5069020390510559,
-0.21034398674964905,
-0.015344548970460892,
-0.04891415685415268,
-0.31534719467163086,
0.21218296885490417,
-0.13832110166549683,
0.16271944344043732,
-0.1201680451631546,
0.09354358166456223,
0.22755911946296692,
0.18092060089111328,
-0.460758239030838,
0.12454557418823242,
0.09379181265830994,
0.10597744584083557,
0.2719220519065857,
-0.08295974135398865,
-0.15479181706905365,
0.08311773091554642,
-0.1303596794605255,
-0.0644197016954422,
-0.005010437220335007,
0.37014827132225037,
0.1331891119480133,
0.08900219202041626,
0.06753277778625488,
0.5516717433929443,
0.08134457468986511,
-0.16196118295192719,
-0.06577123701572418,
0.034855637699365616,
-0.3513203561306,
-0.1360032856464386,
-0.08042474091053009,
0.1183290183544159,
-0.4727519750595093,
0.30819860100746155,
0.06809171289205551,
-0.1501397043466568,
0.051804423332214355,
0.016798460856080055,
-0.035492897033691406,
-0.10962076485157013,
0.10881707817316055,
0.15477821230888367,
0.34218019247055054,
0.717380702495575,
0.013488717377185822,
0.051124148070812225,
-0.11207713931798935,
0.016379019245505333,
-0.041447192430496216,
-0.10039984434843063,
-0.20996205508708954,
-0.24219325184822083,
0.09355348348617554,
-0.043549247086048126,
0.12603627145290375,
-0.5950586199760437,
-0.34497857093811035,
0.003527292050421238,
0.05697786062955856,
0.09147070348262787,
0.6922088265419006,
0.08021368086338043,
-0.19983115792274475,
-0.12055380642414093,
-0.3673868775367737,
0.051314473152160645,
-0.29429328441619873,
0.0956127792596817,
-0.31406641006469727
] |
https://github.com/huggingface/datasets/issues/217 | Multi-task dataset mixing | Hi,
regarding building T5 dataset , I think we can use datasets https://github.com/huggingface/datasets and then need something similar to tf.data.experimental.sample_from_datasets, do you know if similar functionality exist in pytorch? Which can sample multiple datasets with the given rates. thanks. | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
| 39 | Multi-task dataset mixing
It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
Hi,
regarding building T5 dataset , I think we can use datasets https://github.com/huggingface/datasets and then need something similar to tf.data.experimental.sample_from_datasets, do you know if similar functionality exist in pytorch? Which can sample multiple datasets with the given rates. thanks. | [
-0.033307574689388275,
-0.5136857032775879,
-0.02777966670691967,
0.06664924323558807,
-0.25032734870910645,
0.04263012856245041,
0.1753961741924286,
0.060455355793237686,
0.20672665536403656,
-0.1286959946155548,
-0.2596333622932434,
0.17233319580554962,
-0.16145704686641693,
0.5526630878448486,
0.3689039647579193,
-0.42828068137168884,
-0.033644311130046844,
-0.22553157806396484,
-0.3311319649219513,
0.3586280345916748,
0.16255369782447815,
0.12674082815647125,
-0.1310737431049347,
0.011625438928604126,
-0.3748592734336853,
-0.05233381688594818,
-0.3290127217769623,
-0.014158792793750763,
0.07128327339887619,
0.1565447300672531,
0.14056597650051117,
0.343787282705307,
-0.045731376856565475,
0.3042815923690796,
-0.00012068864452885464,
-0.0008572041988372803,
0.061606451869010925,
-0.12618549168109894,
0.11212606728076935,
-0.03864641487598419,
0.2874492406845093,
-0.3399031162261963,
0.053131043910980225,
-0.17077600955963135,
0.13239771127700806,
0.13732117414474487,
0.23634573817253113,
0.07320478558540344,
0.4259689450263977,
-0.22620758414268494,
0.042793527245521545,
0.46675702929496765,
-0.28901153802871704,
0.29696953296661377,
0.003143012523651123,
-0.037487998604774475,
-0.0336274728178978,
0.21709588170051575,
0.7237206697463989,
-0.404282808303833,
0.06341977417469025,
0.04022970795631409,
-0.013890817761421204,
-0.011367347091436386,
0.21762865781784058,
-0.007717118598520756,
-0.3298623263835907,
-0.2981940805912018,
-0.3776232600212097,
0.249018132686615,
0.0038080736994743347,
-0.18128225207328796,
-0.22731944918632507,
-0.5786259174346924,
-0.052297983318567276,
-0.008305491879582405,
-0.3058779537677765,
0.02888064831495285,
-0.28044208884239197,
-0.07985904812812805,
-0.15180154144763947,
-0.13654440641403198,
-0.11704954504966736,
0.18049582839012146,
0.3751619756221771,
0.46168068051338196,
0.06983566284179688,
0.17935660481452942,
0.25237786769866943,
0.13546818494796753,
-0.05440989509224892,
-0.30060815811157227,
0.29202115535736084,
0.18487879633903503,
-0.35682132840156555,
-0.3436088562011719,
0.07527995854616165,
-0.3887392282485962,
0.35672807693481445,
0.12050751596689224,
0.16586101055145264,
0.010490525513887405,
-0.14146848022937775,
0.11952164024114609,
0.3928675651550293,
-0.09637761116027832,
-0.1670006811618805,
-0.11347857862710953,
-0.025100111961364746,
-0.25130605697631836,
0.07018402218818665,
0.09315343201160431,
0.1699230968952179,
-0.10998507589101791,
-0.36253732442855835,
-0.12453190237283707,
-0.1382128745317459,
0.09857957065105438,
-0.032947439700365067,
-0.5224338173866272,
-0.21595120429992676,
-0.1834096610546112,
-0.03497084230184555,
-0.08714625984430313,
-0.284088671207428,
0.0498402938246727,
-0.0025754645466804504,
0.21522320806980133,
-0.2706935405731201,
0.04158273711800575,
-0.04056726396083832,
0.02727458067238331,
-0.3746243119239807,
-0.04783228039741516,
0.29492121934890747,
0.05317297205328941,
0.1146203801035881,
0.16285616159439087,
0.19290168583393097,
0.12154622375965118,
0.4489949941635132,
-0.028123173862695694,
-0.010045245289802551,
-0.023936744779348373,
0.14568474888801575,
-0.21127967536449432,
-0.019119448959827423,
0.33989524841308594,
-0.3035700023174286,
-0.06994908303022385,
-0.1554131805896759,
-0.19051958620548248,
0.09611622989177704,
-0.05094454810023308,
-0.2012614905834198,
-0.3853227198123932,
-0.4683864414691925,
0.6835903525352478,
0.0639658123254776,
-0.0959390252828598,
-0.20830407738685608,
0.20528583228588104,
-0.21099448204040527,
-0.0864718109369278,
0.1614258587360382,
0.06823398917913437,
-0.01320141926407814,
-0.37244030833244324,
0.041984524577856064,
-0.10054001212120056,
0.008564971387386322,
0.30295640230178833,
-0.15408705174922943,
0.22199967503547668,
0.08476705104112625,
0.11213968694210052,
0.3399461805820465,
-0.479181170463562,
-0.009698720648884773,
0.3526689410209656,
-0.04269430786371231,
0.29657697677612305,
0.1470525711774826,
0.27371567487716675,
-0.07260718941688538,
-0.15075428783893585,
0.12967126071453094,
0.9934558272361755,
-0.3805125653743744,
-0.017214447259902954,
-0.0795985758304596,
-0.3645017445087433,
0.48016631603240967,
0.35858508944511414,
0.19760920107364655,
-0.36574697494506836,
-0.18771952390670776,
-0.005163594149053097,
0.0852503553032875,
0.006785046309232712,
0.08330795913934708,
0.024008266627788544,
-0.23442037403583527,
0.10306419432163239,
-0.19651690125465393,
-0.23357394337654114,
-0.4084452688694,
0.041435323655605316,
-0.05092465132474899,
0.37805959582328796,
0.35174524784088135,
-0.05343758687376976,
0.2586511969566345,
-0.2782157063484192,
-0.12434379756450653,
-0.3101751208305359,
0.034565918147563934,
-0.023269139230251312,
0.0006010346114635468,
-0.26450568437576294,
-0.09321190416812897,
0.260556161403656,
0.03617440164089203,
-0.0949815958738327,
-0.4310052692890167,
0.4275183379650116,
0.02262904867529869,
-0.03463855758309364,
-0.03160158544778824,
0.5317655205726624,
-0.24605217576026917,
-0.11966552585363388,
0.10470794141292572,
0.21626326441764832,
-0.20524659752845764,
0.15738517045974731,
0.22795149683952332,
0.3987584710121155,
0.23988604545593262,
-0.08323948830366135,
0.05731647461652756,
-0.05171791836619377,
-0.06435868889093399,
-0.21896958351135254,
-0.004287399351596832,
0.40685945749282837,
-0.2748064398765564,
0.40373435616493225,
-0.007485587149858475,
-0.02760295756161213,
-0.2262641042470932,
0.010464470833539963,
-0.12387334555387497,
0.4250919222831726,
0.34055137634277344,
-0.24968089163303375,
0.3180716037750244,
-0.13490408658981323,
-0.347717821598053,
0.23370882868766785,
0.12683451175689697,
0.019252199679613113,
0.00021502375602722168,
-0.04031014442443848,
0.015348073095083237,
-0.2949424386024475,
-0.13681767880916595,
0.3106762766838074,
0.6342358589172363,
0.19913358986377716,
0.13627763092517853,
-0.06178681552410126,
-0.18401041626930237,
-0.061751168221235275,
0.07712703943252563,
0.1738758236169815,
-0.07647082209587097,
0.21138346195220947,
-0.013369981199502945,
0.10678858309984207,
0.041692160069942474,
-0.16831189393997192,
0.25196754932403564,
-0.17216463387012482,
-0.16441883146762848,
0.048586875200271606,
-0.17014376819133759,
-0.6914837956428528,
-0.11620110273361206,
0.08361642807722092,
-0.29779037833213806,
-0.25566723942756653,
0.15189403295516968,
0.130579873919487,
-0.09642691910266876,
0.17519433796405792,
0.16043365001678467,
0.49070101976394653,
-0.3046950697898865,
-0.3377012014389038,
-0.0032319799065589905,
-0.2629941403865814,
-0.07772117853164673,
0.04284592345356941,
0.4357629120349884,
0.4183099567890167,
0.49025580286979675,
0.19848904013633728,
-0.07153211534023285,
-0.04202023148536682,
-0.38981831073760986,
0.15624688565731049,
-0.3618420362472534,
0.36245065927505493,
0.06319830566644669,
-0.12011861801147461,
0.07015429437160492,
-0.3186580538749695,
-0.014650960452854633,
-0.0883055105805397,
-0.14835074543952942,
-0.0626271665096283,
-0.09027517586946487,
0.07648736238479614,
-0.1306277960538864,
-0.16166287660598755,
-0.6078256964683533,
-0.39203643798828125,
0.1981445550918579,
-0.18852905929088593,
0.07596120238304138,
0.15446597337722778,
-0.2840275764465332,
0.24272455275058746,
-0.1273290067911148,
0.08162131905555725,
-0.132224902510643,
-0.14825524389743805,
-0.016928914934396744,
-0.40536534786224365,
-0.22016756236553192,
-0.4019721746444702,
-0.01956525817513466,
0.16767029464244843,
0.052456971257925034,
-0.0996360257267952,
-0.39100709557533264,
0.0016656983643770218,
0.0276724211871624,
0.058360401540994644,
0.2569243311882019,
0.11975869536399841,
-0.28187525272369385,
0.1681641787290573,
-0.14121797680854797,
-0.18737377226352692,
0.2724555730819702,
0.3120083510875702,
0.36048623919487,
0.17845940589904785,
-0.0021588318049907684,
0.12795649468898773,
0.9331138134002686,
0.2947481870651245,
0.004239201545715332,
0.18400788307189941,
0.13027022778987885,
0.01915886253118515,
0.0827958956360817,
-0.19149282574653625,
0.20076070725917816,
-0.11971068382263184,
0.4675973653793335,
0.10902044922113419,
0.08792636543512344,
-0.016809163615107536,
-0.2927389144897461,
0.09595124423503876,
-0.3363724946975708,
-0.2571498155593872,
0.20428669452667236,
-0.34242308139801025,
0.10670784115791321,
-0.1269156038761139,
-0.40862467885017395,
-0.37843674421310425,
-0.07600965350866318,
-0.09919141232967377,
0.2852097153663635,
0.10526390373706818,
0.1705242097377777,
-0.38959264755249023,
-0.050177156925201416,
-0.4277200698852539,
0.14170679450035095,
0.12198345363140106,
0.2932141423225403,
-0.08066634088754654,
-0.0009058080613613129,
-0.061951398849487305,
0.1394701898097992,
0.5762676000595093,
-0.48940569162368774,
-0.09264400601387024,
0.1321839541196823,
-0.09517456591129303,
-0.1648751050233841,
-0.02935931831598282,
-0.3096029460430145,
0.05311177670955658,
0.3403048813343048,
0.34198248386383057,
-0.4822687804698944,
-0.4431769847869873,
0.2855309844017029,
-0.07070653140544891,
-0.06597499549388885,
-0.16693171858787537,
-0.16285689175128937,
-0.23329249024391174,
-0.048672597855329514,
-0.08596397191286087,
0.3517230451107025,
0.24646826088428497,
-0.14004094898700714,
0.2022763192653656,
-0.0320151150226593,
0.2508801221847534,
0.20811602473258972,
-0.0859517753124237,
-0.07969799637794495,
0.19456399977207184,
0.2547481060028076,
0.03491140902042389,
-0.10541506111621857,
-0.30441224575042725,
0.14299854636192322,
-0.14487148821353912,
-0.11757621169090271,
0.2817603051662445,
0.06203855946660042,
0.6452473402023315,
0.0720042958855629,
0.34857362508773804,
0.34181270003318787,
-0.14397569000720978,
0.0882176011800766,
-0.10354958474636078,
0.20663754642009735,
0.22724993526935577,
0.25939416885375977,
-0.11130636185407639,
-0.2703574001789093,
0.545784056186676,
0.3118358850479126,
0.018796496093273163,
0.4668085277080536,
-0.566470205783844,
-0.26695170998573303,
0.2087348848581314,
0.043551236391067505,
0.7242981791496277,
-0.06499601900577545,
0.4172830879688263,
0.14827373623847961,
-0.3961779475212097,
0.5780623555183411,
-0.215780571103096,
0.04198579862713814,
-0.14468619227409363,
-0.3205392062664032,
0.024116365239024162,
-0.13038353621959686,
-0.20336803793907166,
0.22062033414840698,
-0.2274605631828308,
0.2735256254673004,
0.370996356010437,
-0.21724531054496765,
-0.03466954082250595,
0.48724400997161865,
-0.08320412784814835,
-0.3102732300758362,
-0.007831737399101257,
-0.005010316148400307,
-0.27206099033355713,
0.1534225195646286,
-0.15633094310760498,
-0.27250993251800537,
0.18027876317501068,
0.22555722296237946,
-0.36308759450912476,
-0.03686496615409851,
-0.04107169061899185,
0.17539943754673004,
0.27989450097084045,
-0.06461715698242188,
0.22811898589134216,
-0.058995965868234634,
-0.044314779341220856,
-0.18439990282058716,
-0.13139384984970093,
0.11050482094287872,
-0.25417792797088623,
0.03881377726793289,
0.13085919618606567,
-0.08861708641052246,
0.47457197308540344,
-0.10375446081161499,
-0.14080700278282166,
-0.21365085244178772,
0.2007814347743988,
-0.453219473361969,
-0.2897721529006958,
-0.02821923792362213,
0.046036411076784134,
0.1446157693862915,
-0.312000572681427,
0.5833741426467896,
0.02064930647611618,
0.0554836131632328,
-0.03234788402915001,
0.20651651918888092,
-0.1736728399991989,
0.4253310561180115,
-0.3541755974292755,
-0.043095387518405914,
0.05548543483018875,
0.0381491482257843,
-0.04922188073396683,
-0.3953079879283905,
0.07578082382678986,
0.4156874120235443,
0.16333788633346558,
0.031431667506694794,
0.1543506383895874,
0.10619043558835983,
-0.18556252121925354,
0.11073176562786102,
-0.07481802254915237,
-0.19344593584537506,
0.12716929614543915,
0.3633471131324768,
0.16826599836349487,
0.12084878981113434,
-0.0636971965432167,
-0.2312946617603302,
-0.18166883289813995,
0.5214850306510925,
-0.014888845384120941,
0.22884076833724976,
-0.15737080574035645,
0.4722117781639099,
0.42730841040611267,
0.47415345907211304,
-0.19213160872459412,
0.11956621706485748,
0.11680854111909866,
0.08993293344974518,
0.5097169876098633,
-0.24610280990600586,
0.04991716891527176,
0.26596879959106445,
-0.21029984951019287,
-0.0020564980804920197,
-0.3129919469356537,
-0.08803519606590271,
-0.26381611824035645,
0.1546061933040619,
0.1326218843460083,
0.017633747309446335,
0.08132201433181763,
-0.10233192890882492,
-0.20836412906646729,
-0.10318643599748611,
0.13714444637298584,
-0.2286568284034729,
-0.07985039055347443,
0.2186506688594818,
0.004845131188631058,
-0.015345089137554169,
-0.068305104970932,
0.32523876428604126,
0.06706158816814423,
-0.003959596157073975,
0.3423418700695038,
0.15840312838554382,
0.16730660200119019,
-0.1784554421901703,
-0.16622069478034973,
-0.02740786224603653,
0.32666876912117004,
0.09608419239521027,
-0.06478893756866455,
0.058879733085632324,
-0.1197936087846756,
-0.18889734148979187,
0.18732768297195435,
0.252206027507782,
0.030034566298127174,
-0.027139021083712578,
0.21464210748672485,
0.032238349318504333,
-0.03687313199043274,
0.0016330728540197015,
0.13352444767951965,
0.005256228148937225,
0.08753183484077454,
0.12357059866189957,
0.009909719228744507,
0.4867095947265625,
-0.1714266985654831,
-0.04055001586675644,
0.0002595053520053625,
-0.25957179069519043,
0.16239137947559357,
0.033877670764923096,
-0.054903820157051086,
-0.018305223435163498,
0.0721062496304512,
-0.03674392029643059,
0.12226544320583344,
-0.33030378818511963,
0.3012450635433197,
0.27697938680648804,
-0.08719229698181152,
-0.015070218592882156,
0.23038509488105774,
-0.08356519043445587,
-0.1979319304227829,
0.31108635663986206,
0.0794963538646698,
0.4178653061389923,
-0.009903520345687866,
0.9180453419685364,
-0.3006817102432251,
-0.46471014618873596,
0.0114987101405859,
0.521208643913269,
0.1481102854013443,
-0.25235995650291443,
0.06891939043998718,
0.08991686254739761,
-0.2977737486362457,
0.09773918986320496,
-0.00985107570886612,
-0.18153205513954163,
0.3974483013153076,
-0.010155841708183289,
0.19723674654960632,
-0.13021765649318695,
-0.1488286554813385,
0.34921994805336,
0.17988654971122742,
-0.006385877728462219,
0.08323796093463898,
0.03972797095775604,
-0.10503023862838745,
-0.17178542912006378,
0.512056291103363,
0.08268113434314728,
-0.07022848725318909,
-0.5144467353820801,
0.02289751172065735,
0.15500828623771667,
0.1871427595615387,
0.12166750431060791,
0.2046428918838501,
0.4158378839492798,
-0.19626441597938538,
0.36525964736938477,
-0.08221453428268433,
-0.03379257768392563,
-0.1805470585823059,
0.060573041439056396,
-0.42835405468940735,
-0.46482202410697937,
0.46828126907348633,
0.05242529138922691,
-0.1495819091796875,
0.16356703639030457,
0.24570178985595703,
-0.6194168329238892,
-0.27177971601486206,
0.3253089487552643,
-0.17062537372112274,
-0.09467184543609619,
-0.14008155465126038,
0.035228483378887177,
0.015107783488929272,
0.7085172533988953,
0.24064163863658905,
0.44719892740249634,
-0.315765917301178,
-0.06770211458206177,
-0.5137102603912354,
-0.13571268320083618,
0.18594777584075928,
-0.07559124380350113,
-0.18541374802589417,
0.055791862308979034,
0.04734198376536369,
0.31720685958862305,
-0.08298158645629883,
0.16424773633480072,
0.18251392245292664,
0.19075411558151245,
-0.5117713212966919,
-0.04429372027516365,
-0.02375224232673645,
0.23374833166599274,
0.24095776677131653,
-0.1344553381204605,
-0.21129365265369415,
0.11336624622344971,
-0.11925771832466125,
-0.1077665239572525,
-0.12228408455848694,
0.3494461178779602,
0.057619608938694,
0.10408392548561096,
0.07577160745859146,
0.5753726959228516,
0.06265414506196976,
-0.19473980367183685,
0.04764499515295029,
-0.05116250365972519,
-0.2982564866542816,
-0.09186168760061264,
-0.07321731746196747,
0.11370620131492615,
-0.3598741590976715,
0.3518761694431305,
0.013054776936769485,
-0.02684737928211689,
0.11974893510341644,
-0.05373900383710861,
-0.07982286810874939,
-0.13715922832489014,
0.06085861474275589,
0.19985537230968475,
0.25871768593788147,
0.7949317097663879,
-0.15307685732841492,
0.13903599977493286,
-0.136479914188385,
0.054477520287036896,
0.10467610508203506,
-0.12959527969360352,
-0.21673181653022766,
-0.11664855480194092,
0.056867823004722595,
0.04489794000983238,
0.1433515101671219,
-0.5357406735420227,
-0.2840758264064789,
0.12216448783874512,
0.005257561802864075,
0.01748190075159073,
0.7596602439880371,
0.2824134826660156,
-0.17513993382453918,
-0.05176655203104019,
-0.18941739201545715,
0.008700868114829063,
-0.22647400200366974,
0.09785190224647522,
-0.2878146767616272
] |
https://github.com/huggingface/datasets/issues/216 | ❓ How to get ROUGE-2 with the ROUGE metric ? | For the rouge2 metric you can do
```python
rouge = nlp.load_metric('rouge')
with open("pred.txt") as p, open("ref.txt") as g:
for lp, lg in zip(p, g):
rouge.add(lp, lg)
score = rouge.compute(rouge_types=["rouge2"])
```
Note that I just did a PR to have both `.add` and `.add_batch` for metrics, that's why now this is `rouge.add(lp, lg)` and not `rouge.add([lp], [lg])` | I'm trying to use ROUGE metric, but I don't know how to get the ROUGE-2 metric.
---
I compute scores with :
```python
import nlp
rouge = nlp.load_metric('rouge')
with open("pred.txt") as p, open("ref.txt") as g:
for lp, lg in zip(p, g):
rouge.add([lp], [lg])
score = rouge.compute()
```
then : _(print only the F-score for readability)_
```python
for k, s in score.items():
print(k, s.mid.fmeasure)
```
It gives :
>rouge1 0.7915168355671788
rougeL 0.7915168355671788
---
**How can I get the ROUGE-2 score ?**
Also, it's seems weird that ROUGE-1 and ROUGE-L scores are the same. Did I made a mistake ?
@lhoestq | 56 | ❓ How to get ROUGE-2 with the ROUGE metric ?
I'm trying to use ROUGE metric, but I don't know how to get the ROUGE-2 metric.
---
I compute scores with :
```python
import nlp
rouge = nlp.load_metric('rouge')
with open("pred.txt") as p, open("ref.txt") as g:
for lp, lg in zip(p, g):
rouge.add([lp], [lg])
score = rouge.compute()
```
then : _(print only the F-score for readability)_
```python
for k, s in score.items():
print(k, s.mid.fmeasure)
```
It gives :
>rouge1 0.7915168355671788
rougeL 0.7915168355671788
---
**How can I get the ROUGE-2 score ?**
Also, it's seems weird that ROUGE-1 and ROUGE-L scores are the same. Did I made a mistake ?
@lhoestq
For the rouge2 metric you can do
```python
rouge = nlp.load_metric('rouge')
with open("pred.txt") as p, open("ref.txt") as g:
for lp, lg in zip(p, g):
rouge.add(lp, lg)
score = rouge.compute(rouge_types=["rouge2"])
```
Note that I just did a PR to have both `.add` and `.add_batch` for metrics, that's why now this is `rouge.add(lp, lg)` and not `rouge.add([lp], [lg])` | [
0.08258108794689178,
-0.44010576605796814,
-0.09260924160480499,
0.38070476055145264,
-0.059492915868759155,
-0.13712067902088165,
-0.35067734122276306,
0.09061785042285919,
0.023502390831708908,
0.23529517650604248,
-0.25593215227127075,
0.16841155290603638,
-0.021551262587308884,
0.0022065434604883194,
0.09740171581506729,
-0.3178660273551941,
0.03742338716983795,
-0.034754619002342224,
0.16254767775535583,
-0.20558613538742065,
-0.15831172466278076,
0.3564315736293793,
-0.06628049910068512,
0.2676071226596832,
0.05491020530462265,
0.2283007800579071,
0.1845669150352478,
0.20209896564483643,
-0.41247719526290894,
-0.17358002066612244,
0.14888527989387512,
0.005113102495670319,
0.23019932210445404,
0.2997414171695709,
-0.00011345054372213781,
-0.22685754299163818,
0.1634780466556549,
-0.09964220225811005,
0.10824410617351532,
-0.5389814972877502,
0.06842269003391266,
-0.28030285239219666,
-0.11710111051797867,
-0.050361551344394684,
-0.07701852172613144,
-0.2652798295021057,
-0.30860161781311035,
-0.15958648920059204,
0.30006319284439087,
0.1558416783809662,
0.13660411536693573,
-0.20554155111312866,
-0.062215328216552734,
-0.10612590610980988,
0.2618381977081299,
-0.10174711048603058,
0.11459247022867203,
0.5414437055587769,
0.2648921608924866,
0.003537917509675026,
0.1269058734178543,
0.1456470936536789,
0.257468044757843,
0.06553101539611816,
0.3002891540527344,
0.21130600571632385,
0.31865453720092773,
-0.11210070550441742,
-0.19202959537506104,
0.2805585265159607,
0.12960241734981537,
-0.13421276211738586,
-0.3024217486381531,
0.10026524215936661,
0.07765419036149979,
-0.5770214796066284,
-0.2875575125217438,
-0.1081860288977623,
0.15919633209705353,
-0.21189618110656738,
-0.19137609004974365,
-0.043242041021585464,
-0.15449902415275574,
0.10635067522525787,
0.07333448529243469,
-0.011296898126602173,
-0.05365904048085213,
0.1988222599029541,
0.18406569957733154,
-0.003397800028324127,
-0.5394580364227295,
0.21521182358264923,
-0.31420913338661194,
0.2942136824131012,
-0.3065517246723175,
-0.09514324367046356,
0.1869504153728485,
0.40665122866630554,
0.10325301438570023,
0.3489795923233032,
0.11953452974557877,
-0.2580716609954834,
-0.2762497663497925,
0.08729451149702072,
-0.0699591338634491,
0.4045150578022003,
0.1960495412349701,
0.33812788128852844,
-0.028442755341529846,
0.06927013397216797,
0.19545549154281616,
-0.0628727450966835,
0.24693496525287628,
-0.477272629737854,
-0.06356947124004364,
0.47708311676979065,
-0.007767818868160248,
-0.5834073424339294,
-0.4587995707988739,
-0.028733234852552414,
-0.33794182538986206,
-0.20797036588191986,
0.15752938389778137,
0.10549388825893402,
-0.20728549361228943,
0.32331016659736633,
-0.03419395536184311,
0.2794032096862793,
-0.3262602984905243,
-0.11367299407720566,
-0.15017735958099365,
0.2062860131263733,
-0.20226049423217773,
0.22359485924243927,
0.15393972396850586,
0.1776576191186905,
0.2562238574028015,
0.21195411682128906,
0.2691628336906433,
0.05984320491552353,
0.206268310546875,
-0.23722785711288452,
-0.1175270602107048,
-0.14814883470535278,
-0.034479040652513504,
0.07741092145442963,
0.18840716779232025,
-0.27248072624206543,
-0.12267474830150604,
-0.0750536099076271,
-0.3015037775039673,
-0.008742023259401321,
0.15920142829418182,
0.13326062262058258,
0.1258605420589447,
0.016422824934124947,
-0.21359172463417053,
0.3548072576522827,
-0.15039575099945068,
-0.2694520652294159,
0.20135003328323364,
-0.07212784141302109,
-0.2583310306072235,
-0.12636497616767883,
0.229312926530838,
-0.3264336585998535,
-0.1708659529685974,
0.044310376048088074,
0.2678411304950714,
-0.08543580770492554,
0.0589672327041626,
0.3666200339794159,
0.001542154117487371,
0.19801342487335205,
-0.15210579335689545,
-0.5923177599906921,
0.6651851534843445,
-0.7773891091346741,
-0.06579917669296265,
-0.0005512686911970377,
-0.11361725628376007,
-0.15772925317287445,
0.13908840715885162,
0.029332460835576057,
-0.29635360836982727,
-0.20137320458889008,
0.34006622433662415,
-0.031104527413845062,
-0.15010927617549896,
-0.3194095492362976,
-0.09263476729393005,
0.3367890417575836,
0.4528050422668457,
-0.1628921777009964,
-0.04249311611056328,
-0.11781185120344162,
-0.08548697084188461,
-0.04174085706472397,
0.40881645679473877,
0.06966608017683029,
-0.1271551549434662,
0.021893665194511414,
-0.18314959108829498,
0.16435667872428894,
0.22998657822608948,
-0.29093894362449646,
0.25405171513557434,
0.10766575485467911,
-0.9638234376907349,
-0.22757470607757568,
0.4533107876777649,
-0.2547580599784851,
-0.6550406217575073,
-0.20376752316951752,
0.30906230211257935,
-0.267272412776947,
0.09786076843738556,
-0.16166384518146515,
0.36613017320632935,
0.06151813641190529,
-0.12694668769836426,
0.0966961458325386,
0.06017623841762543,
-0.0041922759264707565,
-0.3270718455314636,
-0.13261853158473969,
0.10517538338899612,
0.07881283015012741,
0.2529539167881012,
0.45298293232917786,
0.45500147342681885,
0.2661784291267395,
0.14760726690292358,
0.23407462239265442,
0.22817136347293854,
0.11697328090667725,
0.31659629940986633,
0.2823440134525299,
0.16588659584522247,
0.06816911697387695,
-0.06692637503147125,
0.45915114879608154,
0.3160407245159149,
-0.1627158522605896,
-0.1957533061504364,
0.4131929874420166,
-0.48462292551994324,
0.12427695840597153,
0.02790401130914688,
0.012188298627734184,
-0.20597581565380096,
0.12720182538032532,
-0.40661925077438354,
0.004663527011871338,
0.23972061276435852,
-0.10887444019317627,
0.13831034302711487,
-0.26548025012016296,
0.07673659920692444,
-0.06142597645521164,
0.19538286328315735,
0.021580249071121216,
-0.036684490740299225,
-0.13535982370376587,
-0.0005483701825141907,
-0.04335637390613556,
-0.09061428904533386,
-0.20829978585243225,
0.18548327684402466,
0.17604230344295502,
0.2232331484556198,
0.12233252823352814,
-0.36821696162223816,
-0.1841251105070114,
-0.05356618016958237,
-0.05732809007167816,
0.01605123095214367,
0.023728959262371063,
0.11102567613124847,
-0.04540029168128967,
0.13835087418556213,
-0.2840757369995117,
-0.2592443823814392,
0.10575349628925323,
-0.3508680760860443,
0.10057410597801208,
-0.09940055012702942,
-0.11004475504159927,
-0.17763330042362213,
-0.5282851457595825,
-0.13439330458641052,
-0.34777477383613586,
-0.02615341544151306,
0.07551563531160355,
0.29761871695518494,
-0.2034304291009903,
0.21936559677124023,
0.1803237348794937,
-0.10814427584409714,
0.32815560698509216,
0.10603396594524384,
-0.21061009168624878,
-0.2679211497306824,
0.17807482182979584,
-0.22155316174030304,
0.00794026255607605,
0.24635574221611023,
-0.12963180243968964,
-0.0070066433399915695,
0.15435971319675446,
-0.25496116280555725,
-0.09858129918575287,
-0.05393761396408081,
0.22666512429714203,
0.06242278963327408,
-0.28835684061050415,
-0.20405727624893188,
0.3045308291912079,
0.23586663603782654,
-0.02450849488377571,
-0.26168835163116455,
0.03409318998456001,
-0.19851455092430115,
0.20603370666503906,
0.05213009938597679,
-0.1808527708053589,
0.06330019235610962,
-0.08067408204078674,
0.48391538858413696,
0.2462226003408432,
-0.07296387851238251,
0.2791990339756012,
-0.31181883811950684,
0.25193145871162415,
0.31410759687423706,
0.37752383947372437,
-0.3375564217567444,
-0.2846829891204834,
0.3150167763233185,
-0.41623079776763916,
-0.3131350874900818,
-0.09678226709365845,
0.06253829598426819,
-0.01308748871088028,
-0.08516383916139603,
0.06592926383018494,
-0.34703490138053894,
0.038814082741737366,
-0.04131891578435898,
-0.12303416430950165,
0.18541406095027924,
0.24729016423225403,
-0.26667720079421997,
-0.05914100259542465,
-0.10685434937477112,
0.08153663575649261,
-0.013448402285575867,
0.10353471338748932,
0.539858877658844,
-0.2782626748085022,
0.117824025452137,
0.1310109794139862,
0.34448790550231934,
0.3714722990989685,
0.434383362531662,
0.054828941822052,
0.16002950072288513,
0.029156070202589035,
0.08967453241348267,
-0.17208315432071686,
0.30430662631988525,
0.07725410908460617,
-0.1583978682756424,
0.07002720236778259,
0.15498226881027222,
0.4240894615650177,
-0.286934494972229,
-0.032308634370565414,
-0.10816021263599396,
0.10679011046886444,
-0.08260096609592438,
-0.2662002444267273,
-0.039601199328899384,
-0.08259433507919312,
0.04221716523170471,
-0.1264973282814026,
-0.10205937922000885,
0.3080264925956726,
0.036289945244789124,
0.20763379335403442,
0.1973811239004135,
-0.3730541467666626,
-0.08608078956604004,
-0.3050489127635956,
0.47342896461486816,
0.09159312397241592,
-0.003033999353647232,
0.12427844107151031,
0.09895651787519455,
-0.017055027186870575,
-0.1943625658750534,
0.4446818232536316,
0.036086879670619965,
0.1932583898305893,
0.2945857346057892,
-0.19206935167312622,
-0.6826237440109253,
-0.17620927095413208,
-0.311749130487442,
0.27777206897735596,
0.16995884478092194,
0.08621401339769363,
-0.17443932592868805,
0.05788734555244446,
0.19328731298446655,
0.0027839879039674997,
-0.1897599697113037,
0.027196433395147324,
-0.3189568519592285,
0.015282370150089264,
0.32539811730384827,
-0.21736928820610046,
-0.1152779683470726,
0.5167665481567383,
-0.08533593267202377,
0.3249630033969879,
0.09882186353206635,
-0.25806885957717896,
0.4550524950027466,
-0.0021251123398542404,
0.24309459328651428,
0.1178697943687439,
-0.18184949457645416,
0.15938431024551392,
-0.13895103335380554,
-0.5745752453804016,
0.33481115102767944,
0.09035544097423553,
-0.5968520045280457,
-0.10880055278539658,
0.008119766600430012,
0.482616126537323,
0.030374452471733093,
-0.05051330104470253,
-0.08396968990564346,
-0.44186127185821533,
-0.11237742006778717,
-0.5094912648200989,
-0.13879278302192688,
0.27017706632614136,
-0.006576824467629194,
-0.11409132182598114,
-0.3621308505535126,
0.5230097770690918,
0.3907356858253479,
-0.3316461443901062,
0.35048040747642517,
-0.2329196184873581,
-0.20785191655158997,
0.2235560566186905,
0.07861392945051193,
0.775036633014679,
0.2355675995349884,
-0.03162864223122597,
0.12106257677078247,
-0.25697922706604004,
0.5335091352462769,
-0.6500673294067383,
0.07334858179092407,
-0.21515586972236633,
-0.2684263288974762,
-0.0399848148226738,
0.06009354814887047,
0.048211779445409775,
0.18227218091487885,
0.08014319837093353,
0.5681716799736023,
-0.060079678893089294,
-0.1525992602109909,
-0.030920585617423058,
0.253612220287323,
0.09966520965099335,
-0.12943436205387115,
-0.1757190078496933,
0.16745387017726898,
-0.13291697204113007,
0.00017710775136947632,
-0.2708410322666168,
0.11507498472929001,
-0.5599819421768188,
0.06690462678670883,
-0.14745119214057922,
-0.13702517747879028,
-0.18371473252773285,
0.17790457606315613,
0.13588501513004303,
-0.422540545463562,
-0.3310343325138092,
0.5675361156463623,
0.7250475883483887,
0.06679413467645645,
-0.2974841892719269,
0.2634715139865875,
-0.17508473992347717,
0.11545809358358383,
0.03641796484589577,
-0.09256507456302643,
0.05644341930747032,
-0.028397109359502792,
-0.02011878788471222,
0.3248104751110077,
0.34698501229286194,
-0.002152740955352783,
-0.17017726600170135,
0.009425781667232513,
-0.14369578659534454,
0.0441509485244751,
-0.059258632361888885,
0.24112549424171448,
0.3410099744796753,
0.07543078064918518,
0.0871412456035614,
0.22685506939888,
-0.5656342506408691,
-0.052645422518253326,
0.2004537433385849,
-0.19524170458316803,
0.1426815539598465,
0.2905636429786682,
0.03757728263735771,
-0.2935364842414856,
-0.22153693437576294,
0.087562695145607,
0.07894840836524963,
-0.005834855139255524,
-0.04641561210155487,
0.016472788527607918,
-0.06334849447011948,
0.018273118883371353,
0.28729677200317383,
0.15044651925563812,
0.03996008634567261,
0.5065686702728271,
0.31823664903640747,
-0.1310807168483734,
0.25226715207099915,
-0.4538985788822174,
-0.2241072654724121,
0.19057047367095947,
0.08486626297235489,
-0.0875307023525238,
-0.08937273919582367,
-0.08392098546028137,
0.13785170018672943,
0.5422527194023132,
-0.2892587184906006,
-0.2375672161579132,
-0.04240000993013382,
0.14428775012493134,
-0.16340003907680511,
-0.1392480432987213,
-0.10749558359384537,
0.14073379337787628,
0.06438962370157242,
0.04496776685118675,
-0.18612557649612427,
-0.17945623397827148,
-0.2494579404592514,
0.13138766586780548,
-0.1495247781276703,
0.1688951998949051,
-0.06284715980291367,
0.0750800371170044,
0.184679314494133,
-0.0817183405160904,
-0.05887413024902344,
0.3747633099555969,
0.37351560592651367,
0.3379557132720947,
-0.034392427653074265,
0.10218104720115662,
-0.056325025856494904,
-0.01782960817217827,
0.21329344809055328,
0.2078014612197876,
0.07900924235582352,
-0.008537612855434418,
0.14385941624641418,
-0.016868434846401215,
-0.2875359356403351,
-0.08986053615808487,
-0.14779503643512726,
-0.22689494490623474,
0.14476278424263,
-0.01856979727745056,
0.20657122135162354,
-0.2133338451385498,
0.37987709045410156,
0.13268625736236572,
-0.07608423382043839,
0.18973122537136078,
-0.18290534615516663,
0.142856165766716,
-0.1198011115193367,
0.4061797559261322,
0.1726001352071762,
0.25368455052375793,
-0.21503499150276184,
0.258207231760025,
-0.03328472375869751,
0.15419086813926697,
-0.011892654001712799,
-0.008982258848845959,
-0.027472414076328278,
-0.3529618978500366,
0.21023724973201752,
-0.45130017399787903,
0.13748317956924438,
-0.07608513534069061,
0.34516963362693787,
-0.14173296093940735,
0.0866357758641243,
0.09466511011123657,
0.11317452043294907,
0.20618659257888794,
0.057095009833574295,
0.38195013999938965,
0.05865370109677315,
0.16471195220947266,
-0.335029274225235,
0.25033360719680786,
0.03729299455881119,
-0.056034669280052185,
0.06057799607515335,
0.13486745953559875,
0.040382590144872665,
-0.1946026086807251,
-0.1217292845249176,
0.10459183156490326,
0.12302770465612411,
-0.3937950134277344,
-0.3598281443119049,
-0.2577280104160309,
-0.1975317746400833,
-0.056885093450546265,
-0.004423275589942932,
0.09338743984699249,
-0.14682918787002563,
0.0563250407576561,
-0.05959995090961456,
-0.29237163066864014,
-0.39882606267929077,
0.15627151727676392,
0.3441053032875061,
-0.07433145493268967,
0.10791286826133728,
0.20615988969802856,
0.31274670362472534,
0.31578972935676575,
0.3679596781730652,
0.13274119794368744,
0.08966721594333649,
-0.5088682770729065,
0.05510064586997032,
-0.1820521205663681,
-0.07493680715560913,
0.036594685167074203,
0.2758980691432953,
0.19292783737182617,
-0.17557163536548615,
0.3166452646255493,
0.1541426181793213,
-0.10532339662313461,
0.3391841650009155,
-0.14225688576698303,
0.05937499925494194,
-0.4119409918785095,
0.5525149703025818,
0.03649605065584183,
0.20788806676864624,
-0.20443935692310333,
0.05917360261082649,
-0.4736991822719574,
-0.18732239305973053,
-0.5115628242492676,
0.06559547781944275,
0.061522603034973145,
-0.3025529980659485,
0.0779670923948288,
0.0898432731628418,
0.02408474311232567,
0.08686594665050507,
0.42110979557037354,
-0.337667852640152,
-0.19173681735992432,
-0.3841714859008789,
-0.36229798197746277,
-0.0484888069331646,
0.11754702031612396,
-0.24215459823608398,
0.287210077047348,
-0.06774679571390152,
0.5412331223487854,
0.15837721526622772,
0.48342883586883545,
0.053993307054042816,
0.17747852206230164,
-0.2007937878370285,
-0.012257155030965805,
-0.09126216173171997,
-0.1045587807893753,
-0.10259967297315598,
0.2286399006843567,
-0.21448929607868195,
-0.1760862171649933,
0.03683061897754669,
-0.15790441632270813,
-0.26630884408950806,
0.24678465723991394,
0.691580057144165,
0.3145759701728821,
0.3558570146560669,
0.46494171023368835,
-0.01913050189614296,
0.03927036374807358,
-0.05851421132683754,
-0.0018537133000791073,
-0.05582123622298241,
0.15834486484527588,
-0.38414108753204346,
0.3125041127204895,
-0.3025667369365692,
-0.22766633331775665,
0.10168598592281342,
0.6001899242401123,
0.0094134621322155,
-0.20100079476833344,
-0.3931237757205963,
-0.07098311185836792,
0.01847902685403824,
-0.14986251294612885,
-0.4123910963535309,
0.3378525674343109,
-0.015125848352909088,
0.44271761178970337,
-0.009619802236557007,
-0.13172677159309387,
0.4783710837364197,
-0.36559662222862244,
0.06721772253513336,
0.06162618100643158,
0.38429126143455505,
0.2618565261363983,
-0.07773260772228241,
-0.19687703251838684,
-0.03381256014108658,
0.3542482852935791,
0.19263824820518494,
-0.0012842845171689987,
0.16451631486415863,
-0.18422242999076843,
-0.10394720733165741,
-0.15975956618785858,
-0.019801974296569824,
0.06336133182048798,
0.041653603315353394,
0.10203620791435242,
-0.16577692329883575
] |
https://github.com/huggingface/datasets/issues/216 | ❓ How to get ROUGE-2 with the ROUGE metric ? | Well I just tested with the official script and both rouge1 and rougeL return exactly the same thing for the input you gave, so this is actually fine ^^
I hope it helped :) | I'm trying to use ROUGE metric, but I don't know how to get the ROUGE-2 metric.
---
I compute scores with :
```python
import nlp
rouge = nlp.load_metric('rouge')
with open("pred.txt") as p, open("ref.txt") as g:
for lp, lg in zip(p, g):
rouge.add([lp], [lg])
score = rouge.compute()
```
then : _(print only the F-score for readability)_
```python
for k, s in score.items():
print(k, s.mid.fmeasure)
```
It gives :
>rouge1 0.7915168355671788
rougeL 0.7915168355671788
---
**How can I get the ROUGE-2 score ?**
Also, it's seems weird that ROUGE-1 and ROUGE-L scores are the same. Did I made a mistake ?
@lhoestq | 34 | ❓ How to get ROUGE-2 with the ROUGE metric ?
I'm trying to use ROUGE metric, but I don't know how to get the ROUGE-2 metric.
---
I compute scores with :
```python
import nlp
rouge = nlp.load_metric('rouge')
with open("pred.txt") as p, open("ref.txt") as g:
for lp, lg in zip(p, g):
rouge.add([lp], [lg])
score = rouge.compute()
```
then : _(print only the F-score for readability)_
```python
for k, s in score.items():
print(k, s.mid.fmeasure)
```
It gives :
>rouge1 0.7915168355671788
rougeL 0.7915168355671788
---
**How can I get the ROUGE-2 score ?**
Also, it's seems weird that ROUGE-1 and ROUGE-L scores are the same. Did I made a mistake ?
@lhoestq
Well I just tested with the official script and both rouge1 and rougeL return exactly the same thing for the input you gave, so this is actually fine ^^
I hope it helped :) | [
0.12398985028266907,
-0.4979516863822937,
-0.08898454159498215,
0.3463147282600403,
-0.08415494859218597,
-0.22060829401016235,
-0.37294113636016846,
0.08035792410373688,
0.03604584187269211,
0.22104912996292114,
-0.21847869455814362,
0.23340590298175812,
-0.011109267361462116,
-0.0014878809452056885,
0.07686223834753036,
-0.28436294198036194,
-0.011588193476200104,
-0.03263472020626068,
0.08533450961112976,
-0.24821986258029938,
-0.10775785148143768,
0.4054567217826843,
-0.1544710248708725,
0.2524571418762207,
0.0654294490814209,
0.31669625639915466,
0.17007912695407867,
0.2143232226371765,
-0.432865709066391,
-0.18212689459323883,
0.1652716100215912,
0.050362877547740936,
0.1496959924697876,
0.23267795145511627,
-0.00011426618584664539,
-0.2925373613834381,
0.1849438101053238,
-0.1414392739534378,
0.1738622784614563,
-0.6005355715751648,
0.058325670659542084,
-0.26914966106414795,
-0.08119745552539825,
-0.06456467509269714,
-0.11102306842803955,
-0.19320020079612732,
-0.2885153889656067,
-0.12736788392066956,
0.37436389923095703,
0.23226219415664673,
0.12809447944164276,
-0.20203982293605804,
-0.06131395697593689,
-0.05112773925065994,
0.2469228208065033,
-0.08830800652503967,
0.08550673723220825,
0.5601398348808289,
0.2660447955131531,
-0.037467509508132935,
0.08142390102148056,
0.15097472071647644,
0.23171231150627136,
0.009744605049490929,
0.3903578817844391,
0.1786264032125473,
0.2437993288040161,
-0.09382613003253937,
-0.2231394350528717,
0.3274887502193451,
0.18336084485054016,
-0.15424370765686035,
-0.23367217183113098,
0.15244010090827942,
0.02727609872817993,
-0.5276973247528076,
-0.2502237558364868,
-0.09636014699935913,
0.2021206021308899,
-0.15361133217811584,
-0.24245628714561462,
-0.030754176899790764,
-0.21640445291996002,
0.08503448963165283,
0.0001808665692806244,
-0.007078118622303009,
-0.0669672042131424,
0.16879890859127045,
0.20319344103336334,
0.011866047978401184,
-0.5337000489234924,
0.2507757544517517,
-0.3072173595428467,
0.34942129254341125,
-0.37095728516578674,
-0.16411639750003815,
0.1327212005853653,
0.4145554304122925,
0.10024333745241165,
0.40116071701049805,
0.22469398379325867,
-0.14048725366592407,
-0.2672233581542969,
0.10991980135440826,
-0.03308255225419998,
0.4469318687915802,
0.22990906238555908,
0.31486496329307556,
-0.027802959084510803,
0.0251830592751503,
0.14823849499225616,
-0.02264481410384178,
0.23133672773838043,
-0.4569520354270935,
-0.038008276373147964,
0.39786893129348755,
-0.027401171624660492,
-0.6806557774543762,
-0.4113559126853943,
0.051422327756881714,
-0.3216814398765564,
-0.14020563662052155,
0.11257842928171158,
0.09805742651224136,
-0.19216439127922058,
0.3302401006221771,
-0.007844313979148865,
0.23737473785877228,
-0.33151912689208984,
-0.14027734100818634,
-0.07846415042877197,
0.2287808507680893,
-0.25133201479911804,
0.21520091593265533,
0.18882833421230316,
0.21518711745738983,
0.24487322568893433,
0.20560823380947113,
0.30322444438934326,
0.029208816587924957,
0.2829257845878601,
-0.24809260666370392,
-0.02712104469537735,
-0.14943145215511322,
-0.07167099416255951,
0.06048443913459778,
0.11274956166744232,
-0.2844976484775543,
-0.09193716943264008,
-0.05520528554916382,
-0.2921653687953949,
0.009701360017061234,
0.14610490202903748,
0.13343559205532074,
0.07843891531229019,
0.012796679511666298,
-0.11202722042798996,
0.3773157596588135,
-0.20596805214881897,
-0.266198992729187,
0.21629923582077026,
-0.14620406925678253,
-0.28263214230537415,
-0.1256779283285141,
0.21286293864250183,
-0.30434638261795044,
-0.1561819463968277,
0.08477066457271576,
0.252817302942276,
-0.05326258763670921,
0.014622434973716736,
0.4060991406440735,
0.0686083734035492,
0.1522846221923828,
-0.09097429364919662,
-0.5238792896270752,
0.6502180695533752,
-0.7507557272911072,
-0.09616754949092865,
0.03446264564990997,
-0.08055101335048676,
-0.10891734063625336,
0.0822356790304184,
0.021923156455159187,
-0.31465744972229004,
-0.14471255242824554,
0.2815755009651184,
0.010718575678765774,
-0.08700942993164062,
-0.3107841908931732,
-0.1504412591457367,
0.39708665013313293,
0.4027329087257385,
-0.07194815576076508,
-0.08274514973163605,
-0.1770651638507843,
-0.1273576319217682,
-0.01692304015159607,
0.4076850116252899,
0.03755701333284378,
-0.12502336502075195,
0.11389748752117157,
-0.19675952196121216,
0.14640352129936218,
0.2724829614162445,
-0.3126000463962555,
0.3493416905403137,
0.07731414586305618,
-0.8894877433776855,
-0.1724054217338562,
0.4622158408164978,
-0.2256922870874405,
-0.6651107668876648,
-0.215151846408844,
0.31093209981918335,
-0.3100336790084839,
0.10217571258544922,
-0.22574597597122192,
0.3516812324523926,
0.1139783263206482,
-0.1536424160003662,
0.20693835616111755,
0.06197982281446457,
0.0069307852536439896,
-0.319097638130188,
-0.16207371652126312,
0.10615421831607819,
0.058505259454250336,
0.25599825382232666,
0.4742416441440582,
0.4499499499797821,
0.2268802970647812,
0.1688266396522522,
0.2143983542919159,
0.2538841962814331,
0.03497163951396942,
0.2582990527153015,
0.2095763087272644,
0.19598032534122467,
-0.018469657748937607,
-0.07744132727384567,
0.5199008584022522,
0.30376124382019043,
-0.1541360318660736,
-0.19438409805297852,
0.4662749767303467,
-0.490393728017807,
0.0574420765042305,
0.030122719705104828,
0.0035352911800146103,
-0.2344088852405548,
0.048947256058454514,
-0.42692822217941284,
0.008210279047489166,
0.33786410093307495,
-0.07221493124961853,
0.1508098691701889,
-0.21438349783420563,
0.07765595614910126,
-0.05872390419244766,
0.16696760058403015,
-0.023158831521868706,
-0.07007049769163132,
-0.09916801005601883,
0.04828318953514099,
-0.05247817933559418,
-0.08713283389806747,
-0.14648213982582092,
0.1367141604423523,
0.14246432483196259,
0.17149512469768524,
0.2192104160785675,
-0.411747545003891,
-0.18401682376861572,
-0.007912367582321167,
-0.1532539576292038,
0.01218420173972845,
0.015409678220748901,
0.06150931119918823,
-0.07383880019187927,
0.051839955151081085,
-0.30490612983703613,
-0.30222752690315247,
0.06790249794721603,
-0.3260825276374817,
0.0888369232416153,
-0.10181143134832382,
-0.14128339290618896,
-0.17434781789779663,
-0.4596985876560211,
-0.1507117599248886,
-0.3067990243434906,
-0.037475667893886566,
0.07321762293577194,
0.2997561991214752,
-0.29844796657562256,
0.21187353134155273,
0.20868787169456482,
-0.0963938757777214,
0.3506270945072174,
0.09900619089603424,
-0.29849109053611755,
-0.21889367699623108,
0.14851553738117218,
-0.22972330451011658,
0.010996153578162193,
0.20694665610790253,
-0.15003857016563416,
-0.0032068798318505287,
0.14732468128204346,
-0.2885560691356659,
-0.09995420277118683,
-0.02525819092988968,
0.16488490998744965,
0.05572685971856117,
-0.3303431272506714,
-0.2132261097431183,
0.35807982087135315,
0.1570579558610916,
-0.0432528555393219,
-0.250110387802124,
0.09181634336709976,
-0.12921284139156342,
0.13602469861507416,
-0.005322178825736046,
-0.20498058199882507,
0.07565270364284515,
-0.016803644597530365,
0.4890824556350708,
0.23215307295322418,
-0.02597884088754654,
0.2851446270942688,
-0.354024738073349,
0.21252381801605225,
0.2565453052520752,
0.39148786664009094,
-0.3267376720905304,
-0.2725765109062195,
0.39423611760139465,
-0.4358576238155365,
-0.37219110131263733,
-0.1029462218284607,
0.10516533255577087,
0.02943887561559677,
-0.04442455992102623,
0.05712844431400299,
-0.3295972943305969,
0.05410837382078171,
-0.09084348380565643,
-0.17520207166671753,
0.13301944732666016,
0.224800243973732,
-0.26698797941207886,
-0.04010269045829773,
-0.12790319323539734,
0.09605056047439575,
-0.0023123174905776978,
0.13142825663089752,
0.5086548924446106,
-0.24810606241226196,
0.07726961374282837,
0.1404632031917572,
0.2756560444831848,
0.40292391180992126,
0.4460241198539734,
0.049148768186569214,
0.16979750990867615,
0.02271243929862976,
0.08366765081882477,
-0.13092896342277527,
0.28202977776527405,
0.042150162160396576,
-0.12101099640130997,
0.10032165050506592,
0.18470141291618347,
0.33166617155075073,
-0.34148117899894714,
-0.08046337962150574,
-0.09187647700309753,
0.09235559403896332,
-0.06381132453680038,
-0.24431443214416504,
-0.034373775124549866,
-0.05484950542449951,
0.05709163099527359,
-0.09766252338886261,
-0.13494375348091125,
0.3102976977825165,
0.022706955671310425,
0.21679842472076416,
0.1691882163286209,
-0.37488988041877747,
-0.028955137357115746,
-0.3219936788082123,
0.4225342273712158,
0.06536135077476501,
-0.03763532638549805,
0.1324227899312973,
0.06528028845787048,
0.00621332973241806,
-0.2297491878271103,
0.3863006830215454,
0.06365104764699936,
0.21256199479103088,
0.26525598764419556,
-0.22254759073257446,
-0.6708530783653259,
-0.18083666265010834,
-0.3159851133823395,
0.28959229588508606,
0.1978680044412613,
0.02305518463253975,
-0.15612193942070007,
0.08311497420072556,
0.18468429148197174,
-0.028113244101405144,
-0.18701854348182678,
0.04569631069898605,
-0.2581061124801636,
0.009999211877584457,
0.36460068821907043,
-0.22924280166625977,
-0.1427791267633438,
0.4782615602016449,
-0.06073053926229477,
0.3421839475631714,
0.14983788132667542,
-0.21545132994651794,
0.4536169767379761,
0.047774624079465866,
0.27631422877311707,
0.026590503752231598,
-0.20807871222496033,
0.16249088943004608,
-0.09441934525966644,
-0.6795375943183899,
0.33890706300735474,
0.1927538961172104,
-0.5905706882476807,
-0.16465136408805847,
-0.037636782974004745,
0.47643154859542847,
0.05458669364452362,
-0.011679282411932945,
-0.09295854717493057,
-0.48114213347435,
-0.0621471107006073,
-0.5296534299850464,
-0.12390255182981491,
0.2654699385166168,
-0.008956381119787693,
-0.11165179312229156,
-0.3016607165336609,
0.48601317405700684,
0.3428497612476349,
-0.3132480978965759,
0.3125554025173187,
-0.19474510848522186,
-0.20292159914970398,
0.2572427988052368,
0.1027376800775528,
0.8113808631896973,
0.21375523507595062,
0.0021938756108283997,
0.07617828249931335,
-0.35134565830230713,
0.4707513749599457,
-0.7156763672828674,
0.04499911516904831,
-0.26291918754577637,
-0.2532733976840973,
-0.041826069355010986,
0.046717915683984756,
0.04493224620819092,
0.21422642469406128,
0.06681868433952332,
0.5717447400093079,
0.06466993689537048,
-0.1611304134130478,
-0.0035069938749074936,
0.27374058961868286,
0.13994716107845306,
-0.05350300297141075,
-0.14959964156150818,
0.14553578197956085,
-0.12895610928535461,
-0.027124818414449692,
-0.24744370579719543,
0.0909351333975792,
-0.5433633327484131,
0.07716075330972672,
-0.1685914546251297,
-0.12107547372579575,
-0.1406957358121872,
0.11651520431041718,
0.13030724227428436,
-0.39353418350219727,
-0.25777560472488403,
0.6006635427474976,
0.7157094478607178,
0.12420657277107239,
-0.37131816148757935,
0.2642662227153778,
-0.2064560055732727,
0.15178190171718597,
0.10992161184549332,
-0.05415476858615875,
0.045877523720264435,
-0.057032763957977295,
-0.06457622349262238,
0.276641845703125,
0.35905739665031433,
-0.010357465595006943,
-0.2205694317817688,
-0.0072341859340667725,
-0.1653808355331421,
0.07030605524778366,
-0.03975100442767143,
0.20711562037467957,
0.3018413782119751,
0.10604226589202881,
0.08863203227519989,
0.2199646234512329,
-0.5469434261322021,
-0.029552176594734192,
0.24314643442630768,
-0.2311176210641861,
0.16570517420768738,
0.3313015103340149,
0.008900599554181099,
-0.2933350205421448,
-0.25438016653060913,
0.07475247979164124,
0.08233662694692612,
-0.005110431462526321,
-0.03546134755015373,
-0.020485907793045044,
-0.041176121681928635,
0.020232368260622025,
0.25103893876075745,
0.13301165401935577,
0.021783920004963875,
0.434613436460495,
0.30642181634902954,
-0.11115405708551407,
0.23509378731250763,
-0.4188060760498047,
-0.19548580050468445,
0.13808919489383698,
0.0805044174194336,
-0.11472414433956146,
-0.031742505729198456,
-0.15798786282539368,
0.17435529828071594,
0.5180923938751221,
-0.2837792634963989,
-0.18762150406837463,
-0.02894975244998932,
0.15590384602546692,
-0.13453315198421478,
-0.20898255705833435,
-0.20269297063350677,
0.0788305252790451,
0.04642462730407715,
0.06440538167953491,
-0.18087099492549896,
-0.16448324918746948,
-0.23848401010036469,
0.14039763808250427,
-0.1358509361743927,
0.13904498517513275,
-0.09388555586338043,
0.0531131848692894,
0.1827079951763153,
-0.0889543890953064,
-0.07194386422634125,
0.34918099641799927,
0.3699827790260315,
0.4574727714061737,
-0.10201866924762726,
0.08419951796531677,
-0.11546285450458527,
-0.03458692133426666,
0.21736623346805573,
0.22923855483531952,
0.08090734481811523,
-0.02448383718729019,
0.1727311611175537,
-0.03619274124503136,
-0.24741241335868835,
-0.05410424619913101,
-0.20524130761623383,
-0.27699869871139526,
0.20450440049171448,
-0.0031601451337337494,
0.229315847158432,
-0.25947126746177673,
0.4298003911972046,
0.16129784286022186,
-0.09349481761455536,
0.14037218689918518,
-0.18729963898658752,
0.13596060872077942,
-0.11948462575674057,
0.3579462468624115,
0.2065812647342682,
0.2541394531726837,
-0.2403791844844818,
0.223332017660141,
-0.016074348241090775,
0.08376480638980865,
0.06476977467536926,
-0.031833112239837646,
-0.02862314134836197,
-0.32644128799438477,
0.18215462565422058,
-0.42984622716903687,
0.15969720482826233,
-0.10262607038021088,
0.26413482427597046,
-0.1583990901708603,
0.06268270313739777,
0.20385761559009552,
0.11040225625038147,
0.22919906675815582,
0.02511720359325409,
0.42615145444869995,
0.04126839339733124,
0.24798648059368134,
-0.3098810911178589,
0.2689865231513977,
0.07964637875556946,
-0.031282611191272736,
0.10673385113477707,
0.1408994197845459,
0.11347515881061554,
-0.23334597051143646,
-0.1448434293270111,
0.06972706317901611,
0.12309956550598145,
-0.3971679210662842,
-0.3614509701728821,
-0.2509462237358093,
-0.26933151483535767,
-0.017956912517547607,
-0.05178672447800636,
0.12138805538415909,
-0.10855117440223694,
0.10018302500247955,
-0.044841229915618896,
-0.24225075542926788,
-0.37579551339149475,
0.07377775758504868,
0.44615018367767334,
-0.10802555084228516,
0.10562580078840256,
0.1896156370639801,
0.3804336190223694,
0.2985629439353943,
0.33002007007598877,
0.12830069661140442,
0.0885031670331955,
-0.5871762633323669,
0.1041392832994461,
-0.1879848837852478,
-0.0834156721830368,
0.07672026753425598,
0.3212108314037323,
0.17876584827899933,
-0.16076809167861938,
0.3263954818248749,
0.12612119317054749,
-0.06357879936695099,
0.3487561047077179,
-0.11649841070175171,
0.05914187431335449,
-0.39986035227775574,
0.4350467920303345,
0.11445913463830948,
0.211585134267807,
-0.25026389956474304,
0.01833103597164154,
-0.5301827788352966,
-0.18016104400157928,
-0.5192384719848633,
0.1562500298023224,
0.057314030826091766,
-0.33192959427833557,
0.07285404205322266,
0.12624770402908325,
0.07426103204488754,
0.05576527118682861,
0.3771965503692627,
-0.3097309172153473,
-0.2862943410873413,
-0.41255640983581543,
-0.32417938113212585,
0.023713327944278717,
0.07984786480665207,
-0.20767951011657715,
0.22943317890167236,
-0.04843645542860031,
0.5633388161659241,
0.1081700474023819,
0.4685989320278168,
0.05568799376487732,
0.1747456192970276,
-0.24061770737171173,
0.055369362235069275,
-0.0938052386045456,
-0.13297021389007568,
-0.14306612312793732,
0.24368232488632202,
-0.17661771178245544,
-0.18919794261455536,
0.03014836460351944,
-0.12438850104808807,
-0.22878040373325348,
0.21405865252017975,
0.7476032972335815,
0.2672616243362427,
0.3172944486141205,
0.4162449240684509,
-0.002823207527399063,
0.03634314984083176,
-0.007560711354017258,
0.06603831797838211,
0.007561356760561466,
0.2057744264602661,
-0.30258432030677795,
0.2575332224369049,
-0.21722067892551422,
-0.2541283667087555,
0.15533418953418732,
0.6273364424705505,
-0.04024696722626686,
-0.20091114938259125,
-0.35345590114593506,
-0.1567518264055252,
0.05964159220457077,
-0.16473793983459473,
-0.518647313117981,
0.39035049080848694,
-0.04144945740699768,
0.40933364629745483,
-0.0025366097688674927,
-0.08588693290948868,
0.4886842668056488,
-0.33689677715301514,
0.11393262445926666,
0.11974432319402695,
0.3727896213531494,
0.2416967749595642,
-0.11075747758150101,
-0.23718181252479553,
-0.051548443734645844,
0.2927353084087372,
0.16268792748451233,
0.0006722100079059601,
0.20673133432865143,
-0.15648120641708374,
-0.10198025405406952,
-0.17159123718738556,
0.06903013586997986,
0.11228369921445847,
0.060577183961868286,
0.062373917549848557,
-0.1644407957792282
] |
https://github.com/huggingface/datasets/issues/215 | NonMatchingSplitsSizesError when loading blog_authorship_corpus | I just ran it on colab and got this
```
[{'expected': SplitInfo(name='train', num_bytes=610252351, num_examples=532812,
dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='train',
num_bytes=611607465, num_examples=533285, dataset_name='blog_authorship_corpus')},
{'expected': SplitInfo(name='validation', num_bytes=37500394, num_examples=31277,
dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='validation',
num_bytes=35652716, num_examples=30804, dataset_name='blog_authorship_corpus')}]
```
which is different from the `dataset_infos.json` and also different from yours.
It looks like the script for generating examples is not consistent | Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on. | 53 | NonMatchingSplitsSizesError when loading blog_authorship_corpus
Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on.
I just ran it on colab and got this
```
[{'expected': SplitInfo(name='train', num_bytes=610252351, num_examples=532812,
dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='train',
num_bytes=611607465, num_examples=533285, dataset_name='blog_authorship_corpus')},
{'expected': SplitInfo(name='validation', num_bytes=37500394, num_examples=31277,
dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='validation',
num_bytes=35652716, num_examples=30804, dataset_name='blog_authorship_corpus')}]
```
which is different from the `dataset_infos.json` and also different from yours.
It looks like the script for generating examples is not consistent | [
-0.13186068832874298,
0.14030981063842773,
0.05940939113497734,
0.4210398197174072,
-0.10276152193546295,
0.06391056627035141,
-0.09939047694206238,
0.24033156037330627,
-0.16995178163051605,
0.16742539405822754,
-0.002576854545623064,
0.2693632245063782,
0.10592739284038544,
-0.02921498566865921,
-0.06128937005996704,
0.11617531627416611,
-0.07574360817670822,
0.23838576674461365,
0.06643003225326538,
0.009823672473430634,
-0.029608845710754395,
0.4090341627597809,
-0.290790855884552,
-0.08376243710517883,
-0.2635086476802826,
-0.20447701215744019,
-0.007695583626627922,
0.2664903700351715,
-0.028038201853632927,
-0.2925416827201843,
0.27207711338996887,
0.011068349704146385,
0.13318169116973877,
0.1919163018465042,
-0.00012480426812544465,
0.02284415066242218,
0.5506137609481812,
-0.25053170323371887,
-0.21130108833312988,
-0.2491968423128128,
-0.4140856862068176,
-0.28161290287971497,
0.039414264261722565,
-0.3059539496898651,
-0.07530711591243744,
0.13373978435993195,
0.16358286142349243,
-0.052976563572883606,
0.24514071643352509,
0.3204346299171448,
0.11070700734853745,
0.07963929325342178,
-0.2686450183391571,
0.1345806121826172,
0.12662167847156525,
0.08180851489305496,
-0.03699054569005966,
-0.07447116076946259,
-0.18289318680763245,
-0.17931108176708221,
-0.0033599063754081726,
0.4617772102355957,
-0.2776550054550171,
0.13988222181797028,
0.19181618094444275,
0.17948710918426514,
0.348262757062912,
-0.13864782452583313,
0.15919563174247742,
0.3170469105243683,
0.42594918608665466,
0.15770426392555237,
-0.20480979979038239,
-0.42427897453308105,
-0.0219615176320076,
0.10003815591335297,
0.4799433648586273,
0.32488197088241577,
-0.23730987310409546,
0.03319871425628662,
-0.433061808347702,
-0.07635169476270676,
-0.03681832551956177,
0.009392645210027695,
0.15958695113658905,
0.32183772325515747,
0.08606128394603729,
0.07757256180047989,
0.09996238350868225,
0.013011597096920013,
0.3436041474342346,
-0.27978405356407166,
-0.21615895628929138,
0.04208419844508171,
-0.10203404724597931,
-0.19778043031692505,
-0.18273749947547913,
0.06244150549173355,
0.15654721856117249,
0.07547703385353088,
0.37092092633247375,
-0.08625371009111404,
0.17984464764595032,
0.11776173114776611,
0.3715384006500244,
-0.013677000999450684,
-0.028967447578907013,
0.5226830840110779,
0.10686895251274109,
-0.009327450767159462,
0.1176343560218811,
0.04502790421247482,
0.29349997639656067,
-0.1499851495027542,
-0.19445769488811493,
0.12557056546211243,
0.16165246069431305,
-0.6070359349250793,
-0.4450760781764984,
0.016515780240297318,
-0.5715518593788147,
-0.20781360566616058,
-0.055248793214559555,
0.24616670608520508,
-0.36231160163879395,
0.2653512954711914,
-0.18779277801513672,
-0.03759102523326874,
-0.32581865787506104,
-0.01764378882944584,
-0.18110673129558563,
0.1677558720111847,
-0.1367722898721695,
0.25721195340156555,
0.14054302871227264,
-0.18570293486118317,
0.41987064480781555,
-0.17853707075119019,
-0.030709147453308105,
-0.15490424633026123,
0.2606305181980133,
-0.1932949423789978,
0.07086895406246185,
0.22536788880825043,
0.0033082999289035797,
0.16629427671432495,
-0.09200568497180939,
-0.2952803075313568,
-0.35808518528938293,
0.15888839960098267,
-0.2516799569129944,
-0.5216352343559265,
0.10345858335494995,
0.1205809935927391,
-0.47296392917633057,
-0.036487333476543427,
-0.036902524530887604,
0.2329140454530716,
0.4576258659362793,
-0.33405205607414246,
-0.02695993334054947,
-0.1752258688211441,
-0.2176084816455841,
-0.04367905110120773,
-0.2373843491077423,
0.43923449516296387,
0.14354448020458221,
-0.23715516924858093,
0.13986878097057343,
0.06780452281236649,
0.6044769883155823,
0.3637809157371521,
-0.0025907307863235474,
0.07247652113437653,
-0.1579892486333847,
0.33445459604263306,
0.13933111727237701,
-0.3792102336883545,
-0.22019106149673462,
0.47593674063682556,
0.07704773545265198,
0.27838781476020813,
0.26170918345451355,
0.1201210543513298,
0.19283688068389893,
-0.14579878747463226,
0.13192394375801086,
0.3967822790145874,
-0.01601727120578289,
0.06469926238059998,
-0.4757278859615326,
-0.3340061604976654,
0.45108896493911743,
0.10481983423233032,
0.10609757155179977,
0.016658365726470947,
-0.06624103337526321,
0.453386127948761,
0.2774915099143982,
-0.11796833574771881,
-0.03857593238353729,
0.178915336728096,
-0.2975044250488281,
-0.0030195489525794983,
-0.008994619362056255,
0.045939862728118896,
-0.43105632066726685,
-0.06189686805009842,
-0.16155469417572021,
0.2573896646499634,
0.021547138690948486,
-0.3396948575973511,
-0.12602588534355164,
-0.3853745758533478,
-0.012610990554094315,
-0.03815138712525368,
-0.024999532848596573,
0.32791680097579956,
0.38916337490081787,
0.020113889127969742,
0.04731035605072975,
0.5165187120437622,
-0.07561039179563522,
0.19800005853176117,
-0.7434919476509094,
0.24971456825733185,
-0.0970013365149498,
-0.22091659903526306,
0.48767125606536865,
0.29407188296318054,
0.1883361041545868,
-0.20826861262321472,
-0.12820076942443848,
0.4203099310398102,
-0.09913244843482971,
0.41020524501800537,
-0.3028305768966675,
0.009452924132347107,
0.28660088777542114,
-0.21590326726436615,
-0.0950908288359642,
0.3127250373363495,
-0.014362134039402008,
-0.02967958152294159,
-0.08529884368181229,
0.4560617208480835,
-0.35522958636283875,
0.19494345784187317,
0.06018040329217911,
-0.07444212585687637,
0.11264720559120178,
-0.21182698011398315,
-0.2256215363740921,
-0.46470898389816284,
0.5550782680511475,
-0.011282149702310562,
-0.33899542689323425,
0.09569765627384186,
-0.22145242989063263,
0.09830480068922043,
0.471059113740921,
0.09217573702335358,
-0.13324370980262756,
-0.10313469916582108,
0.10757986456155777,
-0.13031743466854095,
0.2442014217376709,
0.2132987231016159,
0.4979696273803711,
0.12661860883235931,
-0.025470968335866928,
0.05887509137392044,
-0.14599889516830444,
-0.3809732496738434,
0.13225601613521576,
-0.017310798168182373,
0.1433498114347458,
0.2880011200904846,
0.09366247802972794,
-0.040374506264925,
-0.2727144658565521,
-0.04973514750599861,
0.1679784059524536,
0.24612028896808624,
-0.2921508848667145,
-0.04091402515769005,
-0.3865091800689697,
-0.47475746273994446,
-0.2583891451358795,
-0.1584344208240509,
-0.21669253706932068,
-0.33608385920524597,
0.16131684184074402,
0.24778471887111664,
-0.1326110064983368,
0.06925041228532791,
-0.16835512220859528,
0.06610099971294403,
-0.31220901012420654,
-0.07321520894765854,
-0.06265108287334442,
-0.28624194860458374,
-0.24312901496887207,
-0.04386451840400696,
0.19816158711910248,
0.37293606996536255,
0.20360085368156433,
-0.4253942668437958,
-0.22502323985099792,
0.14127753674983978,
-0.2914535105228424,
0.14501729607582092,
-0.026525668799877167,
-0.12445494532585144,
0.08017541468143463,
-0.2173847109079361,
0.2646990418434143,
-0.24175013601779938,
0.0449194461107254,
-0.10440611094236374,
-0.33106258511543274,
-0.10031034797430038,
0.12558411061763763,
0.004528342746198177,
-0.21038497984409332,
-0.4195679724216461,
-0.25907838344573975,
-0.34470659494400024,
-0.10632041096687317,
0.28229814767837524,
0.3047817349433899,
0.11865761876106262,
-0.15986120700836182,
-0.11309616267681122,
-0.05772746726870537,
0.21963723003864288,
-0.3405010998249054,
-0.09820809960365295,
0.23921023309230804,
-0.08729145675897598,
-0.11389191448688507,
0.011300381273031235,
-0.05697101354598999,
-0.03342808410525322,
0.15223176777362823,
-0.5655202865600586,
-0.20712752640247345,
-0.1663607358932495,
-0.10165074467658997,
-0.2521023750305176,
-0.2789222300052643,
0.5203965902328491,
-0.05680610239505768,
0.035450875759124756,
0.06587979942560196,
-0.45105597376823425,
0.0322563573718071,
0.16768893599510193,
0.5530168414115906,
-0.18503111600875854,
0.2017785608768463,
-0.059397418051958084,
0.4893559217453003,
0.5270171761512756,
0.0005122683942317963,
-0.1543310284614563,
0.15243995189666748,
0.14646774530410767,
0.07625628262758255,
-0.03768445551395416,
0.3673478066921234,
0.05485774576663971,
-0.22224962711334229,
0.4481472969055176,
-0.0057780202478170395,
-0.22578765451908112,
-0.18706944584846497,
-0.10959067940711975,
-0.26541081070899963,
-0.2833309471607208,
0.13767114281654358,
-0.1600017100572586,
0.13109618425369263,
0.2893316447734833,
0.3210524916648865,
-0.07106977701187134,
-0.5795766711235046,
-0.07721082866191864,
0.39042043685913086,
0.15024107694625854,
0.1212044358253479,
-0.39578667283058167,
0.06771234422922134,
-0.5080149173736572,
0.3432265520095825,
0.24453184008598328,
0.28298795223236084,
-0.15224531292915344,
-0.07150012999773026,
0.10070975124835968,
-0.26286590099334717,
0.2946960926055908,
-0.450811505317688,
-0.10308392345905304,
-0.056670330464839935,
-0.03291384130716324,
-0.3269294798374176,
-0.19002771377563477,
-0.16598448157310486,
0.4601231515407562,
0.47317570447921753,
0.465853214263916,
-0.3707205057144165,
-0.08754470944404602,
0.2038038671016693,
-0.12906353175640106,
-0.13388808071613312,
-0.17332911491394043,
-0.32800331711769104,
-0.4676930606365204,
-0.16358797252178192,
-0.1462998390197754,
-0.12559810280799866,
0.33448296785354614,
-0.013892686925828457,
-0.04778723046183586,
0.08378373831510544,
0.09194675832986832,
0.3580939769744873,
0.34259915351867676,
0.07846525311470032,
0.11075650155544281,
0.10656103491783142,
0.21385885775089264,
0.5311782360076904,
0.12926630675792694,
0.5807284116744995,
0.1455211490392685,
-0.06633424758911133,
-0.019350875169038773,
-0.24416658282279968,
0.14895093441009521,
0.4908931851387024,
0.1351771205663681,
0.053816210478544235,
0.037483520805835724,
-0.08207686245441437,
-0.2781609296798706,
0.07523505389690399,
-0.007691921666264534,
-0.05447133257985115,
-0.4696718752384186,
-0.33327388763427734,
0.2758778929710388,
0.29490888118743896,
-0.14097779989242554,
-0.1551348716020584,
-0.24002976715564728,
-0.3468589782714844,
0.2835216522216797,
0.24371957778930664,
1.0874791145324707,
0.2417486160993576,
-0.02210623398423195,
-0.0018390249460935593,
-0.15207722783088684,
0.9227550625801086,
-0.276262491941452,
0.4379432797431946,
-0.3907809257507324,
-0.2073115110397339,
-0.042194053530693054,
-0.16487109661102295,
0.1221630796790123,
0.022072769701480865,
-0.38290151953697205,
0.3094184696674347,
0.3011414408683777,
0.020166737958788872,
-0.11545133590698242,
0.3871205151081085,
-0.21533185243606567,
-0.14622919261455536,
-0.285542756319046,
-0.02860609069466591,
-0.3070119023323059,
0.4314887821674347,
-0.02508636936545372,
-0.05846847593784332,
-0.21924766898155212,
-0.21921728551387787,
-0.3474550247192383,
0.2333538830280304,
0.03732386976480484,
-0.0337875597178936,
0.26438504457473755,
-0.2253141552209854,
-0.05423031002283096,
0.05196887254714966,
0.3515733480453491,
-0.08515338599681854,
-0.10732707381248474,
-0.0710335522890091,
-0.18470579385757446,
-0.14279161393642426,
0.12849223613739014,
0.014371451921761036,
0.23452402651309967,
-0.08470719307661057,
0.06245040148496628,
0.06788527965545654,
-0.09753068536520004,
-0.3518664836883545,
-0.11455514281988144,
-0.06113250553607941,
-0.20195893943309784,
-0.15386666357517242,
-0.04333508759737015,
0.13102227449417114,
-0.08529549837112427,
-0.03876178339123726,
0.0029937177896499634,
-0.1441469043493271,
-0.22105348110198975,
0.2700084149837494,
-0.06912082433700562,
-0.38187360763549805,
-0.15728235244750977,
0.3526187837123871,
0.44284093379974365,
0.036589257419109344,
0.3667510747909546,
-0.152848020195961,
-0.07765865325927734,
-0.1503259837627411,
-0.15030476450920105,
-0.3644888401031494,
-0.20347857475280762,
0.23492255806922913,
-0.23662817478179932,
-0.12594090402126312,
0.14240820705890656,
0.4553375244140625,
0.18074476718902588,
0.33318740129470825,
-0.06118413060903549,
-0.510886549949646,
-0.008190404623746872,
0.17526480555534363,
0.032078810036182404,
0.05828070640563965,
-0.058064572513103485,
0.5259189605712891,
-0.2515856623649597,
0.21031665802001953,
-0.1909005045890808,
-0.14888900518417358,
-0.44389593601226807,
0.3342974781990051,
0.1320309340953827,
-0.043771445751190186,
-0.00957229919731617,
0.00005443580448627472,
-0.16391296684741974,
0.3139306902885437,
-0.06522475928068161,
-0.005955733358860016,
-0.06145970895886421,
0.20649993419647217,
0.1785380244255066,
-0.1087699830532074,
-0.174637109041214,
0.1248009204864502,
0.07677891105413437,
0.03751734644174576,
0.03463679552078247,
0.2473377287387848,
0.04405125230550766,
0.2818426787853241,
-0.3356453478336334,
0.11022813618183136,
-0.07830432802438736,
0.22765110433101654,
-0.2985169589519501,
0.3604103922843933,
-0.05913567915558815,
0.30647528171539307,
-0.10010340064764023,
0.015594683587551117,
0.15056994557380676,
-0.036064304411411285,
0.0484817698597908,
0.09732745587825775,
0.07677573710680008,
-0.17980913817882538,
0.1473214328289032,
0.18416355550289154,
-0.08916452527046204,
0.6363036036491394,
-0.07548834383487701,
-0.19107255339622498,
0.10431263595819473,
0.04541569575667381,
-0.08597458899021149,
0.0015469093341380358,
0.2222021222114563,
0.025047065690159798,
-0.05612965673208237,
0.5138844847679138,
0.08978398144245148,
-0.13231056928634644,
-0.137436643242836,
0.11166287213563919,
0.33755630254745483,
-0.0757070928812027,
0.10394451022148132,
0.19666683673858643,
-0.20539212226867676,
0.09556091576814651,
0.3046140670776367,
-0.2812727093696594,
0.15195713937282562,
-0.000051431357860565186,
0.027243182063102722,
0.4766053259372711,
0.16119647026062012,
0.3706953227519989,
-0.02431722730398178,
-0.11332204937934875,
0.0299596656113863,
0.6413366794586182,
0.28227782249450684,
0.37167811393737793,
0.2842690348625183,
0.387371689081192,
-0.2766481935977936,
0.02878662385046482,
-0.36788809299468994,
-0.17549064755439758,
-0.06385762989521027,
-0.14051616191864014,
-0.46062153577804565,
-0.04844362661242485,
-0.17240488529205322,
0.20627908408641815,
-0.14023509621620178,
0.12604156136512756,
0.4599732756614685,
-0.07544796168804169,
-0.20757706463336945,
-0.37508833408355713,
0.12007813155651093,
0.028892848640680313,
0.16698630154132843,
-0.2368585765361786,
0.31650424003601074,
-0.07666333019733429,
-0.0866452008485794,
0.32038334012031555,
0.5079480409622192,
0.4745161533355713,
0.30628952383995056,
-0.05767250433564186,
-0.20901255309581757,
0.0815262645483017,
0.11034242808818817,
0.2296566367149353,
0.7636833190917969,
0.2975425124168396,
-0.2571280896663666,
0.3881787657737732,
-0.06476611644029617,
-0.07674150913953781,
0.4682409465312958,
0.07057179510593414,
-0.08752591907978058,
-0.022166043519973755,
0.4095025062561035,
-0.0731789767742157,
0.11578703671693802,
0.021555233746767044,
0.13730394840240479,
-0.2554468810558319,
-0.27098923921585083,
0.06821246445178986,
-0.27079296112060547,
0.30509594082832336,
0.013167710974812508,
0.022203564643859863,
-0.30443084239959717,
0.6118448972702026,
0.3897586166858673,
-0.12752357125282288,
-0.20482808351516724,
-0.07230465114116669,
-0.43062710762023926,
0.34660300612449646,
-0.42263078689575195,
-0.23992247879505157,
-0.29968753457069397,
0.5030856728553772,
-0.22747161984443665,
0.40453994274139404,
-0.2877247929573059,
0.37956419587135315,
-0.06517479568719864,
-0.031675487756729126,
-0.22983890771865845,
-0.06720118224620819,
-0.12271597981452942,
-0.29663899540901184,
0.02004878968000412,
-0.2617557644844055,
0.2225911021232605,
0.07699591666460037,
-0.13086313009262085,
0.0015138424932956696,
-0.01643592119216919,
0.016017727553844452,
0.40780171751976013,
-0.012907572090625763,
0.5090906023979187,
0.39042145013809204,
-0.14212578535079956,
-0.15031196177005768,
-0.005523864179849625,
-0.3197630047798157,
-0.3111400902271271,
0.41492000222206116,
0.2139553278684616,
0.3597555160522461,
-0.174125537276268,
0.6665087342262268,
-0.06747272610664368,
0.3192364275455475,
0.05682755261659622,
0.02263082005083561,
-0.25127550959587097,
-0.057016998529434204,
-0.2459755539894104,
0.03582847863435745,
0.06754429638385773,
0.45341363549232483,
0.15364189445972443,
-0.027757912874221802,
-0.2425970435142517,
-0.3491297662258148,
0.47973042726516724,
-0.3962055742740631,
0.029295947402715683,
-0.006679593585431576,
0.1837034374475479,
0.24500307440757751,
-0.22634100914001465,
-0.7466574907302856,
-0.07005758583545685,
0.25677353143692017,
-0.2124132513999939,
0.05072428658604622,
-0.02079637348651886,
-0.05016607418656349,
-0.2243598997592926,
-0.12880520522594452,
-0.2339140772819519,
0.21499401330947876,
-0.41724684834480286,
0.286338746547699,
-0.1293872594833374
] |
https://github.com/huggingface/datasets/issues/215 | NonMatchingSplitsSizesError when loading blog_authorship_corpus | The files provided by the authors are corrupted and the script seems to ignore the xml files that can't be decoded (it does `try:... except UnicodeDecodeError`). Maybe depending of the environment some files can be opened and some others don't but not sure why | Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on. | 44 | NonMatchingSplitsSizesError when loading blog_authorship_corpus
Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on.
The files provided by the authors are corrupted and the script seems to ignore the xml files that can't be decoded (it does `try:... except UnicodeDecodeError`). Maybe depending of the environment some files can be opened and some others don't but not sure why | [
-0.21565434336662292,
0.12347611784934998,
0.027687493711709976,
0.48136138916015625,
-0.011550076305866241,
0.09883285313844681,
-0.13197048008441925,
0.3685871958732605,
-0.051696889102458954,
0.18515688180923462,
0.07529840618371964,
0.1368841975927353,
0.08542821556329727,
-0.13447432219982147,
-0.032238900661468506,
0.025298824533820152,
-0.09251757711172104,
0.19295063614845276,
0.038546644151210785,
-0.09255413711071014,
-0.1750839650630951,
0.4164971113204956,
-0.3340628147125244,
0.007659561932086945,
-0.2115810513496399,
-0.10277733951807022,
0.08266931772232056,
0.4248708486557007,
0.005414196290075779,
-0.3878881335258484,
0.017097117379307747,
-0.01549144834280014,
0.07717113941907883,
0.20357677340507507,
-0.0001237727265106514,
0.05251894146203995,
0.6025201082229614,
-0.26091182231903076,
-0.15160660445690155,
-0.24732501804828644,
-0.39834678173065186,
-0.3468354344367981,
-0.15325507521629333,
-0.3098127543926239,
0.04340548813343048,
-0.13741998374462128,
0.27026909589767456,
-0.21010427176952362,
0.3015902638435364,
0.3589797019958496,
0.10676811635494232,
0.1728033870458603,
-0.0673220157623291,
0.13837473094463348,
0.278253972530365,
0.06059841811656952,
-0.05707038193941116,
-0.07430325448513031,
-0.030549347400665283,
-0.2105666995048523,
-0.09983684867620468,
0.3154500722885132,
-0.2957831025123596,
-0.004714282229542732,
0.17416709661483765,
0.0982152670621872,
0.3729245960712433,
-0.20413394272327423,
0.17276903986930847,
0.29544177651405334,
0.5296697020530701,
0.13004115223884583,
-0.21195344626903534,
-0.4479368031024933,
-0.15491218864917755,
0.11767435073852539,
0.4065711796283722,
0.4266493618488312,
-0.20510539412498474,
-0.0010265074670314789,
-0.26339811086654663,
-0.034661389887332916,
-0.19299185276031494,
0.06627212464809418,
0.2431643307209015,
0.24165329337120056,
0.08146435022354126,
0.06608115136623383,
-0.02012054994702339,
0.07188792526721954,
0.09668942540884018,
-0.2602767050266266,
-0.14188729226589203,
0.09542854130268097,
0.029838938266038895,
-0.07551892846822739,
-0.1188725158572197,
-0.07541238516569138,
0.20608875155448914,
0.20481674373149872,
0.36635321378707886,
0.019850444048643112,
0.2098536342382431,
0.13504046201705933,
0.33779874444007874,
-0.07288758456707001,
0.048855364322662354,
0.4268062710762024,
0.20002338290214539,
-0.03538358956575394,
0.08910275995731354,
0.01330018974840641,
0.22526928782463074,
-0.2736580967903137,
-0.15773549675941467,
0.17779546976089478,
0.24600408971309662,
-0.49686187505722046,
-0.4554826021194458,
0.14754261076450348,
-0.42383873462677,
-0.2733585834503174,
-0.25034916400909424,
0.26493072509765625,
-0.30463919043540955,
0.3659850060939789,
-0.13079878687858582,
0.08853168785572052,
-0.38467368483543396,
-0.10326562821865082,
-0.13025537133216858,
0.16457189619541168,
-0.1479642242193222,
0.20909681916236877,
0.1741015762090683,
-0.1450197994709015,
0.36790335178375244,
-0.17715896666049957,
-0.06438577175140381,
-0.2138010561466217,
0.36703091859817505,
-0.17966467142105103,
0.04696182161569595,
0.25024035573005676,
0.10622438788414001,
0.17181415855884552,
-0.11795464158058167,
-0.2918159067630768,
-0.285082072019577,
0.09585841745138168,
-0.27959397435188293,
-0.393039733171463,
0.11864625662565231,
0.14444109797477722,
-0.3303492069244385,
-0.04221513122320175,
0.0714513435959816,
0.04952285438776016,
0.41477566957473755,
-0.4803284704685211,
-0.09707238525152206,
-0.22827772796154022,
-0.15888912975788116,
-0.1285473108291626,
-0.2621917724609375,
0.6329419612884521,
0.13807927072048187,
-0.10230564326047897,
0.2826194167137146,
-0.029114600270986557,
0.5553823113441467,
0.3593013286590576,
0.06276628375053406,
0.1281600445508957,
-0.19398050010204315,
0.47451382875442505,
0.11766644567251205,
-0.41009315848350525,
-0.1508031040430069,
0.469144344329834,
-0.04133346676826477,
0.3392702639102936,
0.43024924397468567,
0.10246627032756805,
0.2844761610031128,
-0.17926861345767975,
-0.042457446455955505,
0.3146088123321533,
0.06323046237230301,
-0.028442656621336937,
-0.45213353633880615,
-0.14667300879955292,
0.436776340007782,
0.10489121079444885,
0.18474258482456207,
0.01015954464673996,
0.1415489912033081,
0.4389921724796295,
0.3131595253944397,
-0.10660916566848755,
0.10542171448469162,
0.2982519268989563,
-0.4476800560951233,
0.1695100963115692,
0.10063304007053375,
-0.1074298843741417,
-0.3479068875312805,
-0.07296061515808105,
-0.3559933304786682,
0.14380577206611633,
0.0009279176592826843,
-0.22381561994552612,
-0.17331531643867493,
-0.3992129862308502,
-0.07715778052806854,
-0.003456883132457733,
-0.02226208709180355,
0.3663998246192932,
0.28739380836486816,
0.154518261551857,
-0.059055425226688385,
0.36677902936935425,
-0.033696845173835754,
0.18653325736522675,
-0.8968737721443176,
0.2386501580476761,
-0.15186844766139984,
-0.2217145562171936,
0.4185647666454315,
0.3158281743526459,
0.19127628207206726,
-0.19332465529441833,
-0.0772937685251236,
0.38104304671287537,
-0.10586760938167572,
0.4759340286254883,
-0.2341872751712799,
0.07466614246368408,
0.18912166357040405,
-0.31206458806991577,
-0.020262254402041435,
0.405687540769577,
0.09887292236089706,
-0.1194395050406456,
-0.03732912987470627,
0.422737717628479,
-0.34207528829574585,
0.19422794878482819,
0.1411232054233551,
-0.06570770591497421,
0.06375399231910706,
-0.26771435141563416,
-0.24543547630310059,
-0.52154541015625,
0.6221478581428528,
-0.06730543076992035,
-0.26908358931541443,
0.04679863154888153,
-0.2562190592288971,
0.025931358337402344,
0.5729615092277527,
0.0020754151046276093,
-0.08300849050283432,
-0.06289932131767273,
0.06719455122947693,
-0.06301282346248627,
-0.018116867169737816,
0.1845977008342743,
0.45713484287261963,
0.09094727039337158,
-0.05557703599333763,
0.06711187213659286,
-0.1318192183971405,
-0.4584287405014038,
0.1281435191631317,
-0.04832863807678223,
-0.027972206473350525,
0.5724952816963196,
-0.011887378990650177,
0.06637779623270035,
-0.3477863073348999,
-0.02124866098165512,
0.1145634725689888,
0.13852645456790924,
-0.3325786590576172,
-0.0929332971572876,
-0.32997098565101624,
-0.4057203233242035,
-0.3795689046382904,
-0.07616891711950302,
-0.1871165782213211,
-0.3854970335960388,
0.1835039258003235,
0.21754324436187744,
-0.2500670254230499,
0.02811361849308014,
-0.1977851539850235,
0.005206704139709473,
-0.34196656942367554,
0.04885482043027878,
-0.13127970695495605,
-0.19375471770763397,
-0.21058034896850586,
-0.06514140963554382,
0.2704784572124481,
0.38981252908706665,
0.2202957719564438,
-0.5454668402671814,
-0.2100881040096283,
-0.04477045685052872,
-0.20753580331802368,
0.020225614309310913,
-0.05990787595510483,
-0.17760729789733887,
0.09295939654111862,
-0.15598003566265106,
0.5214743614196777,
-0.16104164719581604,
0.14776454865932465,
-0.12871910631656647,
-0.27084916830062866,
0.12490451335906982,
0.22166506946086884,
-0.14447900652885437,
-0.22062841057777405,
-0.5866003036499023,
-0.17907948791980743,
-0.4568946957588196,
-0.09897778928279877,
0.2818935215473175,
0.29488685727119446,
0.04235469549894333,
-0.16215060651302338,
-0.10634422302246094,
-0.21439433097839355,
0.356164813041687,
-0.16313152015209198,
0.05585532262921333,
0.32341793179512024,
-0.1839478611946106,
-0.27022504806518555,
-0.021707266569137573,
0.1376059502363205,
-0.05147732421755791,
0.14158521592617035,
-0.46213555335998535,
-0.059683170169591904,
-0.18343858420848846,
-0.15344777703285217,
-0.28296756744384766,
-0.11173214018344879,
0.4699302911758423,
-0.03412950783967972,
-0.004535004496574402,
-0.056615859270095825,
-0.2683960199356079,
0.017017774283885956,
0.054796285927295685,
0.300724059343338,
-0.1281159222126007,
0.2338898479938507,
-0.09957724064588547,
0.41609013080596924,
0.5284243822097778,
0.1846238523721695,
-0.06775498390197754,
0.07574257999658585,
0.27277037501335144,
0.16633430123329163,
-0.016635319218039513,
0.33610039949417114,
-0.02377237379550934,
-0.09101869910955429,
0.4331532120704651,
-0.0023463983088731766,
-0.09685909003019333,
-0.14553609490394592,
-0.24594686925411224,
-0.34901532530784607,
-0.19343861937522888,
0.14629052579402924,
-0.1666952669620514,
0.14870798587799072,
0.22088949382305145,
0.3066439926624298,
-0.03872033208608627,
-0.5155571699142456,
0.024541765451431274,
0.45322561264038086,
0.32034769654273987,
0.18500789999961853,
-0.4796754717826843,
0.09125615656375885,
-0.4247417151927948,
0.29793304204940796,
0.14495402574539185,
0.3121426999568939,
-0.18283198773860931,
-0.14990225434303284,
0.10623293370008469,
-0.2515309751033783,
0.2325572371482849,
-0.4161829650402069,
0.019843805581331253,
0.059046562761068344,
-0.0065513551235198975,
-0.3043077290058136,
-0.1795516163110733,
-0.2614225447177887,
0.4053453505039215,
0.3865751028060913,
0.43123432993888855,
-0.3831046223640442,
-0.16495168209075928,
0.09735054522752762,
0.005135940853506327,
-0.10864178836345673,
-0.08253543823957443,
-0.29944607615470886,
-0.3675912618637085,
-0.22960831224918365,
-0.29456833004951477,
-0.08849793672561646,
0.26921510696411133,
-0.09233544021844864,
-0.02708631195127964,
0.03468576818704605,
0.10009204596281052,
0.3609338402748108,
0.27080318331718445,
0.08658649772405624,
-0.10598383843898773,
0.07422317564487457,
0.15665021538734436,
0.5734142065048218,
0.11814229935407639,
0.5895763635635376,
0.06899486482143402,
-0.18111127614974976,
0.024747120216488838,
-0.4304133653640747,
0.19162777066230774,
0.46582555770874023,
0.081842340528965,
0.044300612062215805,
0.12616181373596191,
-0.024200141429901123,
-0.4446394741535187,
-0.05971920117735863,
0.16697165369987488,
-0.08109410107135773,
-0.40408653020858765,
-0.42042431235313416,
0.27812016010284424,
0.20545518398284912,
-0.1348201483488083,
-0.1648535281419754,
-0.13094422221183777,
-0.2597302496433258,
0.3258017897605896,
0.13428542017936707,
1.0393658876419067,
0.2653292715549469,
0.07107443362474442,
-0.06675074994564056,
-0.19366438686847687,
0.7017489671707153,
-0.23345686495304108,
0.4610561728477478,
-0.45273011922836304,
-0.18189243972301483,
-0.09579324722290039,
-0.18577441573143005,
0.2801097333431244,
0.13668379187583923,
-0.21743783354759216,
0.3387278914451599,
0.20434297621250153,
-0.02720646932721138,
-0.10105759650468826,
0.47604691982269287,
-0.2647891044616699,
-0.03463727980852127,
-0.10286451131105423,
-0.05299068242311478,
-0.18343351781368256,
0.456830233335495,
-0.0012250952422618866,
-0.1371757835149765,
-0.1618817299604416,
-0.27150124311447144,
-0.3544192910194397,
0.28696689009666443,
0.11578189581632614,
-0.07829161733388901,
0.18359063565731049,
-0.1999584138393402,
0.05459507927298546,
0.20607027411460876,
0.2277209460735321,
-0.08420178294181824,
-0.03865048289299011,
-0.09670551121234894,
-0.1803741753101349,
-0.1994977593421936,
0.1871034801006317,
0.12525026500225067,
0.3472328186035156,
-0.11429058015346527,
0.062304623425006866,
0.1867659091949463,
-0.1503848284482956,
-0.27849090099334717,
-0.3265236020088196,
0.020360734313726425,
-0.2225656658411026,
-0.1865178346633911,
-0.14518161118030548,
0.015972092747688293,
-0.16698449850082397,
-0.0472404845058918,
-0.0031716078519821167,
-0.0846782922744751,
-0.0963406041264534,
0.19067338109016418,
-0.1776462197303772,
-0.4502430558204651,
-0.1255148947238922,
0.2783941328525543,
0.36409792304039,
-0.030169572681188583,
0.43103885650634766,
-0.0935879498720169,
-0.12448450177907944,
-0.19571992754936218,
-0.1521313637495041,
-0.23456509411334991,
-0.4015829861164093,
0.17225393652915955,
-0.20613950490951538,
-0.10457724332809448,
0.17576433718204498,
0.24396362900733948,
0.08783169090747833,
0.1960269808769226,
-0.12787160277366638,
-0.6653318405151367,
0.12647387385368347,
0.1522238850593567,
0.218843474984169,
-0.019053328782320023,
-0.04890122264623642,
0.32298335433006287,
-0.23107977211475372,
0.1628679484128952,
-0.18060219287872314,
-0.07511378079652786,
-0.30882522463798523,
0.3002735674381256,
0.16600315272808075,
0.04077087715268135,
-0.10946865379810333,
0.029191341251134872,
-0.135566845536232,
0.2487284392118454,
-0.17746086418628693,
0.03926803171634674,
-0.14119011163711548,
0.2227548360824585,
0.15719327330589294,
-0.05965302884578705,
-0.10897029936313629,
0.019748196005821228,
0.09330268204212189,
-0.021798525005578995,
0.033921077847480774,
0.29959672689437866,
-0.0386262983083725,
0.34890031814575195,
-0.3989139795303345,
0.14669688045978546,
-0.09037596732378006,
0.2649862468242645,
-0.3462001085281372,
0.38974738121032715,
-0.20149533450603485,
0.24060280621051788,
-0.03934531658887863,
0.0229201540350914,
-0.09879704564809799,
-0.03177809715270996,
0.12119582295417786,
0.06413545459508896,
0.31527379155158997,
-0.15873874723911285,
0.21573194861412048,
0.2088232785463333,
-0.03734010457992554,
0.7320029139518738,
-0.12561552226543427,
-0.11623473465442657,
0.062017686665058136,
0.05478934198617935,
-0.11067084223031998,
-0.017984287813305855,
0.18334759771823883,
-0.08880674839019775,
-0.08237115293741226,
0.36358341574668884,
0.19489237666130066,
-0.2530840039253235,
-0.1885806769132614,
0.10765566676855087,
0.41206881403923035,
-0.08131382614374161,
0.0942225307226181,
0.23868374526500702,
-0.011601142585277557,
0.017933592200279236,
0.19761022925376892,
-0.1533752828836441,
0.0799495130777359,
0.1149350255727768,
0.09460396319627762,
0.523320734500885,
0.1414513736963272,
0.4351023733615875,
-0.23179784417152405,
-0.1278584599494934,
0.018450116738677025,
0.6700650453567505,
0.19276079535484314,
0.48585203289985657,
0.25121283531188965,
0.3217865824699402,
-0.29630574584007263,
0.15058808028697968,
-0.26697838306427,
-0.17418262362480164,
-0.03776218742132187,
-0.1280360072851181,
-0.4697096347808838,
-0.12692967057228088,
-0.20043063163757324,
0.06337586045265198,
-0.07095864415168762,
0.2730647623538971,
0.3169322609901428,
-0.05591939389705658,
-0.19864140450954437,
-0.29472509026527405,
0.17275679111480713,
-0.15478473901748657,
0.1828123778104782,
-0.3227279484272003,
0.27617940306663513,
0.10261663049459457,
-0.032872408628463745,
0.3759278357028961,
0.5440003871917725,
0.6268026232719421,
0.4050438702106476,
-0.10989484190940857,
-0.12854225933551788,
-0.05433844402432442,
0.047856591641902924,
0.18827101588249207,
0.8659350872039795,
0.21049317717552185,
-0.173279270529747,
0.37000465393066406,
-0.03926464170217514,
-0.08896410465240479,
0.3375842869281769,
0.16805602610111237,
-0.04063234478235245,
0.047046732157468796,
0.3882298171520233,
-0.1983952671289444,
-0.0021037310361862183,
-0.0224141925573349,
0.034169699996709824,
-0.4142058193683624,
-0.2665117383003235,
0.17878387868404388,
-0.14471019804477692,
0.2802107632160187,
-0.15230447053909302,
0.019083548337221146,
-0.17731128633022308,
0.5529252290725708,
0.47746336460113525,
-0.17004427313804626,
-0.09665463119745255,
-0.022314898669719696,
-0.5047860145568848,
0.5072606801986694,
-0.41914352774620056,
-0.3187641203403473,
-0.2432267963886261,
0.3742888867855072,
-0.19792011380195618,
0.26287841796875,
-0.09300824999809265,
0.4435423016548157,
-0.13743431866168976,
0.10049092024564743,
-0.2129075676202774,
-0.019861925393342972,
0.014264997094869614,
-0.15694934129714966,
-0.09848317503929138,
-0.24548834562301636,
0.25242987275123596,
0.04092523828148842,
-0.07209350168704987,
-0.01097242534160614,
0.1572078913450241,
-0.0024539101868867874,
0.274394690990448,
-0.026171691715717316,
0.4778502583503723,
0.44526028633117676,
-0.2909839451313019,
-0.2139376699924469,
-0.11031825840473175,
-0.23036065697669983,
-0.2815762460231781,
0.4010995924472809,
0.22582034766674042,
0.3603361248970032,
-0.20492468774318695,
0.5031101703643799,
-0.09256672859191895,
0.2626860439777374,
-0.15710869431495667,
0.14505548775196075,
-0.2188476175069809,
0.03149867057800293,
-0.23324859142303467,
-0.01633145473897457,
0.15726915001869202,
0.45763304829597473,
0.18879970908164978,
-0.12539446353912354,
-0.23119822144508362,
-0.373332142829895,
0.41276806592941284,
-0.3910871744155884,
-0.07988372445106506,
-0.017234738916158676,
0.19397437572479248,
0.12862254679203033,
-0.041532017290592194,
-0.6443723440170288,
-0.0595877505838871,
0.2283196747303009,
-0.11385009437799454,
0.029822751879692078,
-0.06642253696918488,
-0.15205009281635284,
-0.3520394563674927,
-0.034354664385318756,
-0.2507988512516022,
0.27073606848716736,
-0.41924959421157837,
0.40055108070373535,
-0.10350938886404037
] |
https://github.com/huggingface/datasets/issues/215 | NonMatchingSplitsSizesError when loading blog_authorship_corpus | Feel free to do `ignore_verifications=True` for now... The verifications only include a check on the checksums of the downloaded files, and a check on the number of examples in each splits. | Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on. | 31 | NonMatchingSplitsSizesError when loading blog_authorship_corpus
Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on.
Feel free to do `ignore_verifications=True` for now... The verifications only include a check on the checksums of the downloaded files, and a check on the number of examples in each splits. | [
-0.15917661786079407,
0.061384305357933044,
0.06137007102370262,
0.3985082507133484,
-0.09111974388360977,
0.0681394562125206,
-0.1541566103696823,
0.3743869364261627,
-0.05398889631032944,
0.1291232705116272,
0.09490998089313507,
0.16967818140983582,
0.050891757011413574,
-0.07023631036281586,
-0.02994246408343315,
-0.031388700008392334,
-0.04626775532960892,
0.20410287380218506,
0.04388732090592384,
0.001029621809720993,
-0.019637158140540123,
0.44040247797966003,
-0.30174973607063293,
-0.022966966032981873,
-0.2469935566186905,
-0.16833093762397766,
-0.04212997481226921,
0.32819753885269165,
0.0039550624787807465,
-0.3751760721206665,
0.24395911395549774,
-0.07514706254005432,
0.13529175519943237,
0.19081103801727295,
-0.00012187100219307467,
-0.013404510915279388,
0.5785959959030151,
-0.2156340628862381,
-0.20625445246696472,
-0.25492215156555176,
-0.4047054648399353,
-0.3622797131538391,
-0.08360154926776886,
-0.23551985621452332,
-0.02168666198849678,
-0.055038001388311386,
0.17205533385276794,
-0.08597995340824127,
0.2725290060043335,
0.2854219675064087,
0.11910401284694672,
0.15230633318424225,
-0.1194787472486496,
0.03129195421934128,
0.1314687430858612,
0.11148032546043396,
-0.03822559118270874,
-0.09602130949497223,
-0.0876149833202362,
-0.2862391769886017,
-0.10378170758485794,
0.43996766209602356,
-0.19715236127376556,
0.15519720315933228,
0.2258736789226532,
0.11542969197034836,
0.4008738100528717,
-0.11456099152565002,
0.03758153319358826,
0.3904353976249695,
0.5094952583312988,
0.16033314168453217,
-0.20868922770023346,
-0.5066426992416382,
-0.050456468015909195,
0.19382116198539734,
0.41565215587615967,
0.3648850917816162,
-0.23909999430179596,
0.008471596986055374,
-0.4111096262931824,
-0.07393138110637665,
-0.0905098170042038,
0.10173960030078888,
0.2668370306491852,
0.19856902956962585,
0.11837191134691238,
0.006740126758813858,
0.12967170774936676,
-0.041098929941654205,
0.11463387310504913,
-0.24428820610046387,
-0.13999293744564056,
0.112827830016613,
-0.1838788092136383,
-0.1930742710828781,
-0.1448516845703125,
-0.017406605184078217,
0.2120879590511322,
0.2155565768480301,
0.351828396320343,
-0.054053351283073425,
0.22565490007400513,
0.1119692251086235,
0.42831626534461975,
0.04790709167718887,
-0.010735899209976196,
0.5196449756622314,
0.08321750164031982,
0.0033717905171215534,
0.11515559256076813,
0.059673406183719635,
0.265980988740921,
-0.2190958708524704,
-0.14518535137176514,
0.1199166476726532,
0.15946324169635773,
-0.5667430758476257,
-0.4398612678050995,
0.10815741866827011,
-0.5615882277488708,
-0.24343468248844147,
-0.09248389303684235,
0.17566204071044922,
-0.3614131212234497,
0.3320038616657257,
-0.15387743711471558,
0.04779893159866333,
-0.3616383373737335,
-0.05944567546248436,
-0.2066727578639984,
0.17067909240722656,
-0.19749875366687775,
0.20532439649105072,
0.20146071910858154,
-0.15544496476650238,
0.40264222025871277,
-0.10782983154058456,
-0.05867202579975128,
-0.19689896702766418,
0.4011359214782715,
-0.10814116895198822,
0.020010434091091156,
0.1572449654340744,
-0.029180467128753662,
0.16998447477817535,
-0.0008436329662799835,
-0.216933012008667,
-0.38861730694770813,
0.07954563200473785,
-0.22302427887916565,
-0.5368489027023315,
0.10469014197587967,
0.1530231237411499,
-0.44328850507736206,
-0.06129131466150284,
0.09627173840999603,
0.21096181869506836,
0.36438441276550293,
-0.33245113492012024,
-0.09742449969053268,
-0.22020064294338226,
-0.12947271764278412,
-0.05456848070025444,
-0.20552809536457062,
0.4950895309448242,
0.14020079374313354,
-0.266052782535553,
0.13045363128185272,
-0.018282391130924225,
0.5335451364517212,
0.3493090569972992,
0.034334439784288406,
0.09644124656915665,
-0.1925896555185318,
0.48758596181869507,
0.13571110367774963,
-0.35429847240448,
-0.16301201283931732,
0.5454862713813782,
0.028683774173259735,
0.28070491552352905,
0.25120460987091064,
0.11916983872652054,
0.1942966878414154,
-0.09376268088817596,
0.01077117770910263,
0.408086895942688,
-0.021602002903819084,
0.03519278019666672,
-0.4514918923377991,
-0.3096883296966553,
0.4148997664451599,
0.20669451355934143,
0.11799587309360504,
-0.04226302355527878,
-0.0019413307309150696,
0.4964992105960846,
0.30462905764579773,
-0.13594847917556763,
0.05396605283021927,
0.29197072982788086,
-0.3540269434452057,
0.1288684904575348,
0.038535453379154205,
-0.11504384875297546,
-0.3697326183319092,
-0.023021630942821503,
-0.28698253631591797,
0.2818140387535095,
0.10698975622653961,
-0.2584027945995331,
-0.1996178925037384,
-0.4155747592449188,
-0.025226790457963943,
-0.02996254339814186,
0.010714028030633926,
0.2815219461917877,
0.39745810627937317,
0.05119476094841957,
0.06851144134998322,
0.428454726934433,
-0.06218875199556351,
0.17390741407871246,
-0.796796441078186,
0.23201800882816315,
-0.11876515299081802,
-0.21117733418941498,
0.5127648711204529,
0.3413342833518982,
0.22369951009750366,
-0.16931097209453583,
-0.09573248028755188,
0.4365609586238861,
-0.10373702645301819,
0.40195852518081665,
-0.17406710982322693,
0.010552763938903809,
0.20788681507110596,
-0.29545900225639343,
0.018217746168375015,
0.3747367858886719,
-0.0284036286175251,
-0.06868936866521835,
-0.13359332084655762,
0.4167672395706177,
-0.33828726410865784,
0.16545343399047852,
0.06876222044229507,
0.01500893197953701,
0.07816560566425323,
-0.2387959510087967,
-0.19139666855335236,
-0.45546427369117737,
0.6415620446205139,
-0.0951366126537323,
-0.32226407527923584,
0.042292818427085876,
-0.20106329023838043,
0.03303185850381851,
0.43965309858322144,
0.021865837275981903,
-0.09082555025815964,
-0.0264102965593338,
0.02838919684290886,
-0.1608659327030182,
0.0957215428352356,
0.2750535011291504,
0.5138395428657532,
0.12376817315816879,
0.023313958197832108,
0.015095815993845463,
-0.1677716225385666,
-0.33145835995674133,
0.12296850234270096,
-0.0629400908946991,
0.027277668938040733,
0.36706891655921936,
-0.0033676116727292538,
-0.031910091638565063,
-0.3108045756816864,
-0.012369511649012566,
0.15956242382526398,
0.24881474673748016,
-0.32820871472358704,
-0.13419055938720703,
-0.35838791728019714,
-0.40440231561660767,
-0.3453233242034912,
-0.1350657194852829,
-0.28269660472869873,
-0.36944037675857544,
0.20206354558467865,
0.19996565580368042,
-0.1682591289281845,
0.13886970281600952,
-0.1668083816766739,
0.04333499073982239,
-0.3156355023384094,
-0.05282643437385559,
-0.01851584017276764,
-0.21042899787425995,
-0.27342867851257324,
-0.02624230459332466,
0.22404198348522186,
0.42671772837638855,
0.24252188205718994,
-0.39223507046699524,
-0.15776924788951874,
0.04673943668603897,
-0.2580878734588623,
0.06250384449958801,
-0.05618477612733841,
-0.15136504173278809,
0.1768348515033722,
-0.1386253833770752,
0.37565261125564575,
-0.22181446850299835,
0.10164041817188263,
-0.1899556964635849,
-0.3374048173427582,
0.027316994965076447,
0.17911186814308167,
0.03542134910821915,
-0.19235356152057648,
-0.5341885685920715,
-0.26857152581214905,
-0.36351504921913147,
-0.06236624717712402,
0.28557682037353516,
0.24182623624801636,
0.03172805905342102,
-0.1204400360584259,
-0.13270418345928192,
-0.1704920083284378,
0.2503783702850342,
-0.30170783400535583,
-0.05889040231704712,
0.24042047560214996,
-0.09786741435527802,
-0.16751530766487122,
-0.03147032484412193,
0.0028387531638145447,
-0.05066491290926933,
0.12287375330924988,
-0.5468325018882751,
-0.10958747565746307,
-0.20560337603092194,
-0.07945811003446579,
-0.3269421458244324,
-0.2575342655181885,
0.5263427495956421,
-0.07347503304481506,
-0.024189021438360214,
0.013537459075450897,
-0.3449536859989166,
0.06836865842342377,
0.1019066646695137,
0.5138316750526428,
-0.16110703349113464,
0.18403863906860352,
-0.014320679008960724,
0.5651073455810547,
0.5774591565132141,
0.07665694504976273,
-0.11549916863441467,
0.17679192125797272,
0.09244534373283386,
0.17404824495315552,
0.009827882051467896,
0.37702691555023193,
0.022528842091560364,
-0.1074550524353981,
0.4157789349555969,
0.08360455185174942,
-0.1998012810945511,
-0.11438945680856705,
-0.1578519493341446,
-0.31042420864105225,
-0.1871032863855362,
0.16156162321567535,
-0.2299748659133911,
0.20063230395317078,
0.20180656015872955,
0.23883286118507385,
-0.18510441482067108,
-0.5294701457023621,
-0.012654252350330353,
0.3591078519821167,
0.2272566258907318,
0.17686012387275696,
-0.4701034724712372,
0.14273430407047272,
-0.4302378296852112,
0.2958553731441498,
0.21121390163898468,
0.2849108576774597,
-0.21085688471794128,
-0.15540382266044617,
0.08103788644075394,
-0.19880712032318115,
0.29555171728134155,
-0.4056425988674164,
-0.015020042657852173,
-0.04621124267578125,
-0.03189551830291748,
-0.342242032289505,
-0.2017230987548828,
-0.13815273344516754,
0.3731078505516052,
0.5086655616760254,
0.4213860332965851,
-0.4272281527519226,
-0.12459447234869003,
0.16328121721744537,
-0.05940474942326546,
-0.13091081380844116,
-0.16943767666816711,
-0.25253307819366455,
-0.33338984847068787,
-0.17163142561912537,
-0.14729195833206177,
-0.1254299134016037,
0.30011674761772156,
-0.02195614017546177,
-0.002084653824567795,
0.1447324901819229,
0.12521997094154358,
0.3355754613876343,
0.2571823298931122,
0.16852501034736633,
-0.03306189551949501,
0.10766860842704773,
0.2788693904876709,
0.540444016456604,
0.08358269184827805,
0.5131438374519348,
0.10595917701721191,
-0.058910682797431946,
-0.025092247873544693,
-0.3047671616077423,
0.07861298322677612,
0.43017813563346863,
0.17479118704795837,
0.0852496474981308,
0.14247438311576843,
-0.027434512972831726,
-0.46311166882514954,
-0.025743912905454636,
0.11071310937404633,
-0.07656627148389816,
-0.37168172001838684,
-0.3909304440021515,
0.25883975625038147,
0.26937922835350037,
-0.1429109275341034,
-0.14606890082359314,
-0.19557951390743256,
-0.2553572654724121,
0.23188114166259766,
0.1594078540802002,
0.9950311779975891,
0.26009055972099304,
-0.026021379977464676,
-0.027609582990407944,
-0.22299738228321075,
0.8679138422012329,
-0.25553590059280396,
0.4108973741531372,
-0.42821571230888367,
-0.2512686848640442,
-0.06234835088253021,
-0.20891474187374115,
0.1523512750864029,
0.1181773692369461,
-0.29969677329063416,
0.33157145977020264,
0.2687565088272095,
-0.01166745275259018,
-0.10332239419221878,
0.4452238082885742,
-0.24535900354385376,
-0.07309824228286743,
-0.17734670639038086,
0.01480168104171753,
-0.288422167301178,
0.5008419752120972,
-0.01772240735590458,
-0.12158550322055817,
-0.21846343576908112,
-0.21833479404449463,
-0.4154765009880066,
0.25962021946907043,
0.18067587912082672,
0.005110269412398338,
0.2780006527900696,
-0.1839195191860199,
-0.0008592866361141205,
0.091573067009449,
0.3283592462539673,
-0.1827334463596344,
-0.17481862008571625,
0.006974555552005768,
-0.2024371325969696,
-0.13968569040298462,
0.19291821122169495,
0.07448725402355194,
0.33971625566482544,
-0.12549349665641785,
0.0013905540108680725,
0.05642957240343094,
-0.12228953838348389,
-0.3300777077674866,
-0.3035987317562103,
-0.1133045107126236,
-0.20215778052806854,
-0.18769235908985138,
-0.08816827833652496,
0.07827645540237427,
-0.10347446799278259,
-0.06149611994624138,
0.04047757014632225,
-0.040233857929706573,
-0.21182696521282196,
0.23607870936393738,
-0.09049469232559204,
-0.3304225504398346,
-0.11680580675601959,
0.39779967069625854,
0.3670256733894348,
-0.03411338850855827,
0.44290435314178467,
-0.1041085422039032,
-0.09311012923717499,
-0.20934069156646729,
-0.12919022142887115,
-0.31093570590019226,
-0.34310370683670044,
0.16432727873325348,
-0.268461674451828,
-0.08667010068893433,
0.194707453250885,
0.29301851987838745,
0.23840950429439545,
0.3419274091720581,
-0.001604028046131134,
-0.5291138887405396,
0.016075069084763527,
0.13710251450538635,
-0.024978507310152054,
0.07527955621480942,
-0.1436307728290558,
0.42183154821395874,
-0.20619772374629974,
0.2404181957244873,
-0.21923071146011353,
-0.08254688233137131,
-0.4039372205734253,
0.32245495915412903,
0.11327122896909714,
-0.10176185518503189,
-0.03889915347099304,
0.015869105234742165,
-0.11925475299358368,
0.21726515889167786,
-0.14230133593082428,
0.0013298988342285156,
-0.11548508703708649,
0.20137105882167816,
0.147395059466362,
-0.08197376877069473,
-0.10277969390153885,
0.114006906747818,
0.07142955809831619,
0.02901693433523178,
-0.0539865717291832,
0.2069932222366333,
-0.022113539278507233,
0.32321470975875854,
-0.3484603762626648,
0.04232325404882431,
-0.06938486546278,
0.23659777641296387,
-0.3490239977836609,
0.29365915060043335,
-0.09470129758119583,
0.21986159682273865,
-0.08393579721450806,
-0.00015819072723388672,
-0.03363386169075966,
0.013329416513442993,
0.08372709155082703,
0.07243642210960388,
0.18849554657936096,
-0.17304065823554993,
0.1039828360080719,
0.22139424085617065,
0.021713346242904663,
0.5436677932739258,
-0.07953482121229172,
-0.10975439101457596,
0.07915399968624115,
0.10070711374282837,
-0.12908628582954407,
-0.03161070495843887,
0.2547113597393036,
-0.030462689697742462,
-0.12914377450942993,
0.35050174593925476,
0.14029525220394135,
-0.16056475043296814,
-0.2005099505186081,
0.10796525329351425,
0.3961574137210846,
-0.13299141824245453,
0.12379775941371918,
0.29219895601272583,
-0.16179753839969635,
-0.015710052102804184,
0.23938491940498352,
-0.2638282775878906,
0.13483266532421112,
0.010987766087055206,
0.04418575391173363,
0.4613368809223175,
0.09753677248954773,
0.39205455780029297,
-0.14451506733894348,
-0.13713553547859192,
-0.05386102572083473,
0.7125874757766724,
0.3032740354537964,
0.40754762291908264,
0.23052367568016052,
0.475411981344223,
-0.3398900032043457,
-0.003783765248954296,
-0.35419604182243347,
-0.18464218080043793,
-0.037353575229644775,
-0.10190211236476898,
-0.5155592560768127,
-0.10836469382047653,
-0.2322472631931305,
0.12218470871448517,
-0.08818584680557251,
0.14326107501983643,
0.4093429148197174,
-0.0715935081243515,
-0.18918578326702118,
-0.4787328243255615,
0.05307842046022415,
0.014809217303991318,
0.17545342445373535,
-0.3287905156612396,
0.15796281397342682,
0.036844149231910706,
-0.1626705676317215,
0.39498797059059143,
0.5192059874534607,
0.5169357657432556,
0.30216145515441895,
-0.14195631444454193,
-0.21230356395244598,
0.054576385766267776,
0.151615709066391,
0.23794233798980713,
0.768156886100769,
0.2752503454685211,
-0.2857544720172882,
0.3937153220176697,
-0.05130111426115036,
-0.08288401365280151,
0.40311741828918457,
0.05604337155818939,
-0.06899301707744598,
-0.02687562070786953,
0.44262176752090454,
-0.13705362379550934,
0.11488338559865952,
-0.004703536629676819,
0.11616162210702896,
-0.29875025153160095,
-0.3102468252182007,
0.10357506573200226,
-0.17181900143623352,
0.2889469265937805,
-0.07533550262451172,
0.03425173833966255,
-0.31278958916664124,
0.5959123969078064,
0.43539929389953613,
-0.212471604347229,
-0.21041031181812286,
-0.11609205603599548,
-0.4998016059398651,
0.34542739391326904,
-0.46122199296951294,
-0.2328447550535202,
-0.1896783858537674,
0.47722530364990234,
-0.2099061906337738,
0.29365766048431396,
-0.1712389439344406,
0.46486949920654297,
-0.1285218894481659,
0.0775582417845726,
-0.26981472969055176,
-0.05188273265957832,
-0.0817444771528244,
-0.19109514355659485,
0.021983973681926727,
-0.22614023089408875,
0.19919097423553467,
0.10465008020401001,
-0.08411657810211182,
0.03213798627257347,
0.05748949199914932,
0.026997938752174377,
0.42762643098831177,
-0.08215092122554779,
0.5023901462554932,
0.42900338768959045,
-0.14516234397888184,
-0.21732522547245026,
-0.08768832683563232,
-0.28880035877227783,
-0.29746630787849426,
0.37864717841148376,
0.1362174153327942,
0.4217302203178406,
-0.1751050353050232,
0.6471750736236572,
-0.12871085107326508,
0.3200819194316864,
0.01959068328142166,
0.011846438981592655,
-0.32712477445602417,
-0.03769771009683609,
-0.214523583650589,
0.026058319956064224,
0.15193985402584076,
0.471005916595459,
0.17632994055747986,
-0.017446991056203842,
-0.18155960738658905,
-0.30553677678108215,
0.42345255613327026,
-0.31965968012809753,
0.03429244086146355,
-0.02669631689786911,
0.18106959760189056,
0.20320919156074524,
-0.11101242154836655,
-0.6931034922599792,
-0.0768067017197609,
0.2931540310382843,
-0.11016219109296799,
0.08574353158473969,
-0.035791508853435516,
-0.07137183845043182,
-0.2900952994823456,
-0.022308053448796272,
-0.22079938650131226,
0.23416650295257568,
-0.3639991879463196,
0.384461909532547,
-0.08561214059591293
] |
https://github.com/huggingface/datasets/issues/215 | NonMatchingSplitsSizesError when loading blog_authorship_corpus | I'm getting this same issue when loading the `imdb` corpus via `dataset = load_dataset("imdb")`. When I try `ignore_verifications=True`, no examples are read into the `train` portion of the dataset. | Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on. | 29 | NonMatchingSplitsSizesError when loading blog_authorship_corpus
Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on.
I'm getting this same issue when loading the `imdb` corpus via `dataset = load_dataset("imdb")`. When I try `ignore_verifications=True`, no examples are read into the `train` portion of the dataset. | [
-0.1060912013053894,
0.17192918062210083,
0.08614695072174072,
0.37152886390686035,
-0.07061881572008133,
0.19752010703086853,
-0.08851537108421326,
0.3589627742767334,
-0.07059349119663239,
0.13236775994300842,
0.010963218286633492,
0.1926116794347763,
0.019733257591724396,
-0.13543306291103363,
-0.06135275214910507,
0.001089625060558319,
-0.049684636294841766,
0.151227205991745,
0.08074234426021576,
-0.000766657292842865,
-0.01908314786851406,
0.43668192625045776,
-0.3507993221282959,
-0.06492380797863007,
-0.27976858615875244,
-0.17144758999347687,
0.005060212686657906,
0.30681169033050537,
0.06779033690690994,
-0.33830156922340393,
0.24676106870174408,
-0.08211196959018707,
0.1046873927116394,
0.25874534249305725,
-0.00012322825205046684,
0.03466298431158066,
0.6713199019432068,
-0.23092038929462433,
-0.19163353741168976,
-0.34996122121810913,
-0.33645808696746826,
-0.2255391627550125,
-0.0071844905614852905,
-0.2159276008605957,
0.0023932382464408875,
-0.07125576585531235,
0.19345584511756897,
-0.15920564532279968,
0.17167355120182037,
0.3034624457359314,
0.09692041575908661,
0.1682632714509964,
-0.17914779484272003,
0.05318162962794304,
0.22526121139526367,
0.18425463140010834,
-0.08278965950012207,
-0.08363880217075348,
-0.09633514285087585,
-0.13919712603092194,
-0.13139402866363525,
0.4392056465148926,
-0.243143692612648,
0.1521119922399521,
0.27531176805496216,
0.16114851832389832,
0.2986014783382416,
-0.20217843353748322,
0.018696190789341927,
0.37583062052726746,
0.4876858592033386,
0.10426037013530731,
-0.3134579658508301,
-0.47657036781311035,
-0.02254026010632515,
0.18319030106067657,
0.36662253737449646,
0.3496968448162079,
-0.24039380252361298,
0.03685608133673668,
-0.42643657326698303,
-0.029454322531819344,
-0.13254500925540924,
0.08995271474123001,
0.21369346976280212,
0.10086237639188766,
0.15537028014659882,
-0.0032709985971450806,
0.04466111958026886,
-0.09545892477035522,
0.1590355783700943,
-0.23730173707008362,
-0.11320334672927856,
0.04265632480382919,
-0.13779090344905853,
-0.13386563956737518,
-0.09080664068460464,
0.015388961881399155,
0.1906350553035736,
0.20482176542282104,
0.3135945200920105,
0.05322418361902237,
0.2250058650970459,
0.21918317675590515,
0.47183409333229065,
-0.04583967849612236,
-0.08414595574140549,
0.5593453645706177,
0.24461223185062408,
0.030025452375411987,
0.060235749930143356,
-0.010037921369075775,
0.2779306471347809,
-0.12376952171325684,
-0.08744187653064728,
0.025136426091194153,
0.25217562913894653,
-0.5562329292297363,
-0.4696899950504303,
0.10254070162773132,
-0.4754391312599182,
-0.11085563153028488,
-0.049945469945669174,
0.2599767744541168,
-0.3506721258163452,
0.31802502274513245,
-0.11212270706892014,
0.11180038750171661,
-0.33322635293006897,
-0.0451674610376358,
-0.1908116191625595,
0.1568988561630249,
-0.10932102799415588,
0.18961702287197113,
0.3031001687049866,
-0.09979420900344849,
0.46441444754600525,
-0.1483692228794098,
0.05276651680469513,
-0.16524440050125122,
0.4266863763332367,
-0.176682248711586,
0.12088873237371445,
0.22699227929115295,
0.07362121343612671,
0.23083259165287018,
-0.022406894713640213,
-0.14349472522735596,
-0.3749014735221863,
0.14235332608222961,
-0.1875194013118744,
-0.5286055207252502,
0.11082946509122849,
0.125046044588089,
-0.399397611618042,
-0.05795259028673172,
-0.010794363915920258,
0.19038967788219452,
0.3466760516166687,
-0.38587918877601624,
-0.0868326798081398,
-0.16370455920696259,
-0.07959919422864914,
0.004998224787414074,
-0.1589997410774231,
0.46130794286727905,
0.18528062105178833,
-0.2022431641817093,
0.15319886803627014,
0.05393008887767792,
0.5437243580818176,
0.3525787889957428,
0.02455816976726055,
0.022253315895795822,
-0.14071279764175415,
0.45799392461776733,
0.18906007707118988,
-0.4663136601448059,
-0.12786981463432312,
0.5851624011993408,
0.0991259217262268,
0.3170833885669708,
0.22275221347808838,
0.14682313799858093,
0.23375362157821655,
-0.06082319840788841,
0.040691111236810684,
0.400925874710083,
-0.08982719480991364,
0.07596190273761749,
-0.3674880862236023,
-0.3140704035758972,
0.40807420015335083,
0.17905962467193604,
0.1312665194272995,
0.010799884796142578,
-0.051287077367305756,
0.4866936206817627,
0.26025259494781494,
-0.08486109972000122,
0.09025527536869049,
0.270938515663147,
-0.4059145748615265,
0.13252195715904236,
0.0775730088353157,
-0.09696778655052185,
-0.36799970269203186,
0.0032126829028129578,
-0.18765036761760712,
0.2800235152244568,
0.05730115622282028,
-0.32654303312301636,
-0.15178191661834717,
-0.42282459139823914,
-0.007933657616376877,
0.024887505918741226,
-0.017824368551373482,
0.2539554834365845,
0.32474076747894287,
0.09333169460296631,
-0.019458234310150146,
0.37591367959976196,
-0.026518842205405235,
0.2407076358795166,
-0.8501718044281006,
0.13954225182533264,
-0.176375150680542,
-0.2839401662349701,
0.4763646721839905,
0.276856392621994,
0.18114018440246582,
-0.14808836579322815,
-0.07467490434646606,
0.4480014145374298,
-0.0722123309969902,
0.46613049507141113,
-0.3489922285079956,
0.022523581981658936,
0.31674832105636597,
-0.2829039394855499,
-0.019446251913905144,
0.35974612832069397,
0.012247209437191486,
-0.06112988293170929,
-0.1798420250415802,
0.3726075291633606,
-0.3008643686771393,
0.2264280915260315,
0.10579578578472137,
0.009542830288410187,
0.12567394971847534,
-0.22969752550125122,
-0.2462267428636551,
-0.5783404111862183,
0.5604589581489563,
-0.10399386286735535,
-0.3391011953353882,
-0.001096842810511589,
-0.2969704270362854,
-0.01972806453704834,
0.42888882756233215,
0.11643408238887787,
-0.06571271270513535,
-0.03648044168949127,
-0.00525684654712677,
-0.15044254064559937,
0.19341441988945007,
0.1804913431406021,
0.42518150806427,
0.12823976576328278,
0.08470874279737473,
0.012771890498697758,
-0.17027883231639862,
-0.3577145040035248,
0.1167982891201973,
0.05171636492013931,
0.003451473545283079,
0.38919001817703247,
0.0633619874715805,
0.032328858971595764,
-0.34547922015190125,
-0.027957897633314133,
0.20833459496498108,
0.10395724326372147,
-0.38145801424980164,
-0.12965868413448334,
-0.4263538122177124,
-0.39681047201156616,
-0.2394590675830841,
-0.17718367278575897,
-0.12151668965816498,
-0.376502126455307,
0.2047390192747116,
0.33553194999694824,
-0.20929209887981415,
0.11408486217260361,
-0.2720203697681427,
-0.012221306562423706,
-0.33466166257858276,
-0.06907996535301208,
-0.0707184225320816,
-0.2245490998029709,
-0.2937888503074646,
-0.03721298649907112,
0.1956603080034256,
0.45404261350631714,
0.2249227613210678,
-0.3926709294319153,
-0.16009247303009033,
0.054461658000946045,
-0.26246970891952515,
0.0824066773056984,
-0.08520620316267014,
-0.07174213975667953,
0.11912095546722412,
-0.16228099167346954,
0.37041449546813965,
-0.2849782407283783,
0.02957264706492424,
-0.16127032041549683,
-0.2947843372821808,
0.036483246833086014,
0.153392031788826,
0.03398400545120239,
-0.25572696328163147,
-0.5162034630775452,
-0.21861325204372406,
-0.3656136691570282,
-0.10801637172698975,
0.26958948373794556,
0.18670199811458588,
0.0947457104921341,
-0.15174269676208496,
-0.09986476600170135,
-0.03366941213607788,
0.30374419689178467,
-0.2530960738658905,
-0.11181238293647766,
0.3357352316379547,
-0.22152790427207947,
-0.13774646818637848,
0.054698433727025986,
-0.05541529506444931,
-0.05785643681883812,
0.12819057703018188,
-0.5356529355049133,
-0.11282755434513092,
-0.22534403204917908,
-0.05317845940589905,
-0.21877068281173706,
-0.30812549591064453,
0.4669431746006012,
-0.07963355630636215,
-0.024783868342638016,
-0.03770994395017624,
-0.3831615447998047,
0.07807578146457672,
0.06121492385864258,
0.40866583585739136,
-0.11687021702528,
0.27626001834869385,
-0.001049097627401352,
0.4330562353134155,
0.5189312100410461,
0.0885111540555954,
0.003336705267429352,
0.13722161948680878,
0.12602093815803528,
0.10288116335868835,
0.028162097558379173,
0.303975373506546,
-0.020976334810256958,
-0.12858650088310242,
0.35867953300476074,
0.0653780847787857,
-0.2829357981681824,
-0.1473606377840042,
-0.11749204993247986,
-0.3157091736793518,
-0.26602551341056824,
0.1234094575047493,
-0.34433069825172424,
0.12941250205039978,
0.19345565140247345,
0.3407934308052063,
-0.08182297646999359,
-0.5395622849464417,
-0.018391627818346024,
0.28625598549842834,
0.2730642557144165,
0.13522294163703918,
-0.4073798656463623,
0.15566496551036835,
-0.4685330390930176,
0.2718776762485504,
0.18034248054027557,
0.3475733697414398,
-0.1694795936346054,
-0.15780410170555115,
0.05548808351159096,
-0.20148704946041107,
0.339417964220047,
-0.4746239483356476,
0.013200923800468445,
-0.0041796425357460976,
-0.07114433497190475,
-0.4237631857395172,
-0.189687579870224,
-0.18537120521068573,
0.40302515029907227,
0.4932022988796234,
0.41495800018310547,
-0.37820670008659363,
-0.07719447463750839,
0.24144402146339417,
-0.08462471514940262,
-0.05414053797721863,
-0.15137629210948944,
-0.21289490163326263,
-0.3216528296470642,
-0.27340924739837646,
-0.15363115072250366,
0.005820173770189285,
0.2583274841308594,
-0.10156774520874023,
-0.1375637948513031,
0.09534488618373871,
0.14404428005218506,
0.41291892528533936,
0.2945849299430847,
0.1835898458957672,
0.018144451081752777,
0.14950424432754517,
0.35043197870254517,
0.4505654573440552,
0.17933370172977448,
0.4881417453289032,
0.06032627075910568,
-0.15531286597251892,
0.06298692524433136,
-0.3202924430370331,
0.04378961771726608,
0.4678903818130493,
0.19955551624298096,
0.021901868283748627,
0.1291140466928482,
-0.14375878870487213,
-0.394074410200119,
-0.00532188918441534,
0.06702914088964462,
-0.17417608201503754,
-0.33612456917762756,
-0.36778974533081055,
0.2681983411312103,
0.34013622999191284,
-0.11092524975538254,
-0.16600102186203003,
-0.15098713338375092,
-0.3498978614807129,
0.3399809002876282,
0.17212873697280884,
0.9456440210342407,
0.2882981598377228,
-0.01568662002682686,
-0.0824362263083458,
-0.17538723349571228,
0.8163899183273315,
-0.236005961894989,
0.43048322200775146,
-0.3811832666397095,
-0.24644877016544342,
-0.08875585347414017,
-0.17461098730564117,
0.1384231150150299,
0.1136191338300705,
-0.3597881495952606,
0.32473045587539673,
0.1303011178970337,
0.034613996744155884,
-0.1917153298854828,
0.4030136466026306,
-0.28494516015052795,
-0.19131125509738922,
-0.15553028881549835,
0.023692864924669266,
-0.16818127036094666,
0.38430389761924744,
0.055374160408973694,
-0.07974905520677567,
-0.2306404411792755,
-0.21798528730869293,
-0.4340413808822632,
0.23839318752288818,
0.1523972898721695,
0.041992783546447754,
0.2618045210838318,
-0.211929589509964,
-0.02144467644393444,
0.12297064065933228,
0.33395975828170776,
-0.17732937633991241,
-0.17432652413845062,
-0.0057398416101932526,
-0.10337153822183609,
-0.18696154654026031,
0.14108417928218842,
0.05936410278081894,
0.3844880163669586,
-0.09873633831739426,
-0.011704005300998688,
0.0815645158290863,
-0.15946197509765625,
-0.26500940322875977,
-0.17423103749752045,
-0.1326061338186264,
-0.1864425241947174,
-0.18964163959026337,
-0.16944310069084167,
0.013096466660499573,
-0.06749565899372101,
-0.08927694708108902,
0.013088760897517204,
-0.13440144062042236,
-0.15610651671886444,
0.2143878936767578,
-0.03449402377009392,
-0.3317170739173889,
-0.10979071259498596,
0.4217984080314636,
0.3353780210018158,
-0.0034990832209587097,
0.4691973924636841,
-0.06988655775785446,
-0.11542753130197525,
-0.15430672466754913,
-0.07997772842645645,
-0.14900021255016327,
-0.3325285315513611,
0.209935262799263,
-0.22150230407714844,
-0.08268897235393524,
0.2382514476776123,
0.2852216362953186,
0.13365080952644348,
0.2915157675743103,
-0.12268856167793274,
-0.471201092004776,
-0.00956140086054802,
0.2567778527736664,
-0.019193951040506363,
0.11481359601020813,
-0.1499737948179245,
0.3957260549068451,
-0.1862943321466446,
0.15356986224651337,
-0.19016431272029877,
-0.07312840223312378,
-0.48063111305236816,
0.35391807556152344,
0.09942642599344254,
-0.007975932210683823,
-0.0888342335820198,
-0.027649054303765297,
-0.16565971076488495,
0.28192412853240967,
-0.0191587433218956,
0.0067089758813381195,
-0.13281415402889252,
0.19781990349292755,
0.09791306406259537,
-0.10110466182231903,
-0.1399448961019516,
0.11612597107887268,
0.020546656101942062,
-0.0048479437828063965,
0.03788452595472336,
0.26702621579170227,
-0.008993938565254211,
0.38938796520233154,
-0.36771664023399353,
0.0906316339969635,
-0.0589551106095314,
0.18782053887844086,
-0.3241511881351471,
0.2810356616973877,
-0.12034697830677032,
0.21074873208999634,
-0.044932786375284195,
0.04436337947845459,
0.03362684324383736,
-0.028521068394184113,
0.03280778229236603,
0.04359268397092819,
0.1490325927734375,
-0.16278497874736786,
0.140609472990036,
0.33817797899246216,
-0.02393568679690361,
0.5712108612060547,
-0.06357824057340622,
-0.1615837961435318,
0.030100101605057716,
0.0879780650138855,
-0.08462013304233551,
-0.0033468804322183132,
0.20258064568042755,
-0.060471802949905396,
-0.06835417449474335,
0.3554293215274811,
0.18379716575145721,
-0.10070470720529556,
-0.1846417635679245,
0.11385100334882736,
0.4215511083602905,
-0.17783145606517792,
0.19242455065250397,
0.1978377252817154,
-0.2146584391593933,
-0.01578349992632866,
0.16785669326782227,
-0.20996692776679993,
0.1965465545654297,
0.04577769339084625,
0.020209401845932007,
0.4743586480617523,
0.15783251821994781,
0.3953703045845032,
-0.07260806113481522,
-0.21184641122817993,
-0.06808555126190186,
0.6018927097320557,
0.3082670569419861,
0.4337640404701233,
0.22709372639656067,
0.3257054090499878,
-0.2783255875110626,
-0.00010927417315542698,
-0.3504144549369812,
-0.183759868144989,
-0.011417478322982788,
-0.1646636426448822,
-0.47189947962760925,
-0.0938858762383461,
-0.23944692313671112,
0.09697262942790985,
-0.15479224920272827,
0.15204116702079773,
0.39516106247901917,
-0.04441917687654495,
-0.20598699152469635,
-0.5548534989356995,
0.1378760039806366,
-0.13042554259300232,
0.19311949610710144,
-0.26797130703926086,
0.18461112678050995,
0.05767602100968361,
-0.11533723771572113,
0.43101680278778076,
0.5478075742721558,
0.5472566485404968,
0.32145917415618896,
-0.17351791262626648,
-0.11064151674509048,
0.03344130888581276,
0.032779306173324585,
0.19032762944698334,
0.733572781085968,
0.3221980333328247,
-0.27110177278518677,
0.3745807409286499,
-0.059075117111206055,
-0.05481623113155365,
0.41394397616386414,
0.12746432423591614,
0.015450948849320412,
-0.06342163681983948,
0.5102359056472778,
-0.1708884984254837,
0.10250923782587051,
0.006851306185126305,
0.02524959295988083,
-0.2746659219264984,
-0.3511103689670563,
0.2094680368900299,
-0.3275744616985321,
0.2222515046596527,
-0.030705541372299194,
0.018956240266561508,
-0.25469717383384705,
0.5723084807395935,
0.4384695589542389,
-0.14093264937400818,
-0.21884925663471222,
-0.010653063654899597,
-0.4845343232154846,
0.35602089762687683,
-0.3736163079738617,
-0.16402584314346313,
-0.13282263278961182,
0.5531368851661682,
-0.2862464487552643,
0.23929312825202942,
-0.2779918909072876,
0.38563624024391174,
-0.17468668520450592,
0.16580131649971008,
-0.25717684626579285,
-0.013567924499511719,
-0.10855506360530853,
-0.22183682024478912,
0.006634432822465897,
-0.24003097414970398,
0.14324951171875,
0.042736832052469254,
-0.12452109158039093,
0.03154309093952179,
-0.024334553629159927,
0.06714528799057007,
0.4972288906574249,
-0.0039021968841552734,
0.47871333360671997,
0.4656328856945038,
-0.1569477766752243,
-0.23094283044338226,
-0.16266821324825287,
-0.3780435025691986,
-0.34398841857910156,
0.3681851625442505,
0.17288753390312195,
0.4330157935619354,
-0.17476186156272888,
0.5583014488220215,
-0.04618224874138832,
0.27481594681739807,
-0.04320555180311203,
-0.0047761425375938416,
-0.3202861547470093,
0.012487802654504776,
-0.2711293697357178,
0.025067638605833054,
0.12636426091194153,
0.3703688085079193,
0.1730210781097412,
-0.02074553444981575,
-0.1875908523797989,
-0.4143213629722595,
0.430174857378006,
-0.35417822003364563,
0.05320895090699196,
-0.13932479918003082,
0.15484215319156647,
0.2172609567642212,
-0.14222191274166107,
-0.7538331151008606,
-0.08064009994268417,
0.2726384699344635,
-0.16095545887947083,
0.05061447247862816,
-0.013103971257805824,
-0.014782052487134933,
-0.27094611525535583,
-0.1554519087076187,
-0.25527331233024597,
0.24762418866157532,
-0.37345200777053833,
0.30728623270988464,
-0.09805581718683243
] |
https://github.com/huggingface/datasets/issues/215 | NonMatchingSplitsSizesError when loading blog_authorship_corpus | > I'm getting this same issue when loading the `imdb` corpus via `dataset = load_dataset("imdb")`. When I try `ignore_verifications=True`, no examples are read into the `train` portion of the dataset.
When the checksums don't match, it may mean that the file you downloaded is corrupted. In this case you can try to load the dataset again `load_dataset("imdb", download_mode="force_redownload")`
Also I just checked on my side and it worked fine:
```python
from datasets import load_dataset
dataset = load_dataset("imdb")
print(len(dataset["train"]))
# 25000
```
Let me know if redownloading fixes your issue @EmilyAlsentzer .
If not, feel free to open a separate issue. | Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on. | 100 | NonMatchingSplitsSizesError when loading blog_authorship_corpus
Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on.
> I'm getting this same issue when loading the `imdb` corpus via `dataset = load_dataset("imdb")`. When I try `ignore_verifications=True`, no examples are read into the `train` portion of the dataset.
When the checksums don't match, it may mean that the file you downloaded is corrupted. In this case you can try to load the dataset again `load_dataset("imdb", download_mode="force_redownload")`
Also I just checked on my side and it worked fine:
```python
from datasets import load_dataset
dataset = load_dataset("imdb")
print(len(dataset["train"]))
# 25000
```
Let me know if redownloading fixes your issue @EmilyAlsentzer .
If not, feel free to open a separate issue. | [
-0.17601029574871063,
0.1923229992389679,
0.06580723822116852,
0.415630578994751,
0.012082453817129135,
0.19369161128997803,
-0.060682814568281174,
0.3878972828388214,
-0.05917363613843918,
0.13248199224472046,
-0.07451555132865906,
0.1716667264699936,
0.00934138149023056,
-0.13655923306941986,
-0.07436807453632355,
0.00014028698205947876,
-0.061030514538288116,
0.14836759865283966,
0.07987777143716812,
0.035928815603256226,
-0.06956406682729721,
0.4301077127456665,
-0.3462488055229187,
-0.08884064853191376,
-0.23781460523605347,
-0.11275551468133926,
0.02941947616636753,
0.3264774680137634,
0.04625571146607399,
-0.3628297746181488,
0.2542961537837982,
-0.06689697504043579,
0.12759649753570557,
0.30131080746650696,
-0.00012377803795970976,
0.01873653382062912,
0.6639291048049927,
-0.24313701689243317,
-0.19303658604621887,
-0.38231271505355835,
-0.2983901798725128,
-0.27950337529182434,
-0.031189940869808197,
-0.23511448502540588,
0.00004652142524719238,
-0.045577239245176315,
0.1376456320285797,
-0.17305010557174683,
0.22491493821144104,
0.3440399467945099,
0.0974617749452591,
0.18349336087703705,
-0.09255968779325485,
0.11123840510845184,
0.21578535437583923,
0.12078313529491425,
-0.048925578594207764,
-0.014452159404754639,
-0.017779268324375153,
-0.15842965245246887,
-0.03852691501379013,
0.3862314820289612,
-0.3328869342803955,
0.11739915609359741,
0.25707224011421204,
0.14909526705741882,
0.3444841206073761,
-0.19640594720840454,
0.03148144111037254,
0.38532519340515137,
0.45523858070373535,
0.020421288907527924,
-0.3434726297855377,
-0.4385927617549896,
-0.0033315056934952736,
0.09549721330404282,
0.385768860578537,
0.3656495213508606,
-0.2501451373100281,
0.04120176285505295,
-0.34488174319267273,
0.020254844799637794,
-0.12321119010448456,
0.10563604533672333,
0.1657620221376419,
0.08337247371673584,
0.15274578332901,
-0.013326473534107208,
0.040776655077934265,
-0.03611783683300018,
0.14461666345596313,
-0.2656342089176178,
-0.1059991717338562,
0.09341879934072495,
-0.16324205696582794,
-0.12530268728733063,
-0.18923768401145935,
-0.011101484298706055,
0.16719725728034973,
0.1999482661485672,
0.29252347350120544,
0.010139748454093933,
0.19105952978134155,
0.18825817108154297,
0.469216525554657,
-0.05503105744719505,
-0.10778697580099106,
0.5959746241569519,
0.21419714391231537,
0.08869078755378723,
-0.005386956036090851,
-0.031112052500247955,
0.2485344111919403,
-0.2011575847864151,
0.02705814316868782,
0.12978479266166687,
0.24780960381031036,
-0.5492243766784668,
-0.5105422735214233,
0.178507998585701,
-0.47248125076293945,
-0.1294342279434204,
-0.03337736055254936,
0.2145405113697052,
-0.39336279034614563,
0.32460302114486694,
-0.06497441232204437,
0.12263622879981995,
-0.3191176950931549,
-0.0042855278588831425,
-0.15956468880176544,
0.1274050921201706,
-0.13459908962249756,
0.16218197345733643,
0.2891721725463867,
-0.17284761369228363,
0.4029974639415741,
-0.1103069856762886,
0.06361111253499985,
-0.21592643857002258,
0.3070898950099945,
-0.2068900465965271,
0.065682053565979,
0.2388724982738495,
0.047185469418764114,
0.2478986233472824,
0.0007344074547290802,
-0.20997636020183563,
-0.3573243319988251,
0.13655634224414825,
-0.2047910988330841,
-0.4814677834510803,
0.07134076952934265,
0.12073985487222672,
-0.3954429626464844,
-0.04784272611141205,
-0.07426493614912033,
0.036178454756736755,
0.3651830554008484,
-0.4267297089099884,
-0.09594767540693283,
-0.22851373255252838,
-0.07225896418094635,
-0.035934239625930786,
-0.10529256612062454,
0.5175377726554871,
0.15426748991012573,
-0.16895271837711334,
0.1386125534772873,
0.05945858731865883,
0.5408574342727661,
0.391432523727417,
0.05832092463970184,
0.025509662926197052,
-0.19143261015415192,
0.37669724225997925,
0.20354309678077698,
-0.5307165384292603,
-0.2367611825466156,
0.5350231528282166,
0.13700176775455475,
0.36929187178611755,
0.22536331415176392,
0.14809520542621613,
0.26581189036369324,
-0.06201304867863655,
0.016567617654800415,
0.4239158630371094,
-0.04632773995399475,
0.07779435813426971,
-0.37284496426582336,
-0.29308465123176575,
0.3921940326690674,
0.14195109903812408,
0.1503073275089264,
0.04352620244026184,
-0.02133478969335556,
0.44595351815223694,
0.3237895369529724,
-0.0458550788462162,
0.09353777021169662,
0.2675280272960663,
-0.28064805269241333,
0.25819653272628784,
0.049429990351200104,
-0.22007182240486145,
-0.3241133987903595,
0.027645796537399292,
-0.1992626041173935,
0.299434632062912,
-0.09630544483661652,
-0.2697671949863434,
-0.17187514901161194,
-0.4570290148258209,
-0.042080823332071304,
-0.00748959556221962,
-0.006650581955909729,
0.20860198140144348,
0.28892526030540466,
0.1307036578655243,
-0.06835608929395676,
0.4250880181789398,
-0.09385355561971664,
0.2411915510892868,
-0.8024852871894836,
0.24098919332027435,
-0.19558899104595184,
-0.31735971570014954,
0.4423464238643646,
0.2632880210876465,
0.19873633980751038,
-0.14953134953975677,
-0.14108476042747498,
0.4424898028373718,
-0.031132789328694344,
0.4205712080001831,
-0.3902108371257782,
0.07099071890115738,
0.32512369751930237,
-0.3283196687698364,
-0.013647114858031273,
0.37926772236824036,
0.06837370246648788,
-0.09130765497684479,
-0.09971357136964798,
0.3737080693244934,
-0.3763323724269867,
0.21936804056167603,
0.1308305412530899,
0.029671097174286842,
0.13359251618385315,
-0.21173621714115143,
-0.2728499174118042,
-0.529153048992157,
0.5458309650421143,
-0.06431084871292114,
-0.3128311336040497,
0.004712603986263275,
-0.23172332346439362,
-0.06337665766477585,
0.41675665974617004,
0.039075907319784164,
-0.07154937833547592,
-0.016353987157344818,
-0.005610503256320953,
-0.09737547487020493,
0.0756484791636467,
0.20833925902843475,
0.44202858209609985,
0.09718981385231018,
0.013755030930042267,
0.07849985361099243,
-0.20874279737472534,
-0.3179134726524353,
0.16330751776695251,
0.01875659078359604,
0.0033224241342395544,
0.4489210247993469,
0.013933427631855011,
0.0849306508898735,
-0.2789892554283142,
-0.0302160382270813,
0.11369865387678146,
0.18893904983997345,
-0.42710933089256287,
-0.09499017149209976,
-0.4230707287788391,
-0.38129299879074097,
-0.3252098858356476,
-0.19172726571559906,
-0.15214784443378448,
-0.3741565942764282,
0.10221859812736511,
0.33567163348197937,
-0.09335123002529144,
0.15202751755714417,
-0.27478036284446716,
-0.07710932195186615,
-0.28563809394836426,
-0.16717529296875,
-0.04007302224636078,
-0.25538623332977295,
-0.222213476896286,
-0.06030028685927391,
0.2851209044456482,
0.41625288128852844,
0.21915368735790253,
-0.4314367473125458,
-0.1876332312822342,
-0.003962108865380287,
-0.21282917261123657,
0.047138720750808716,
-0.09212160110473633,
-0.010913737118244171,
0.12462525069713593,
-0.09668281674385071,
0.35306113958358765,
-0.3084551692008972,
0.13665345311164856,
-0.18659070134162903,
-0.28652623295783997,
0.08701904863119125,
0.16549672186374664,
0.005901121534407139,
-0.16749265789985657,
-0.4755880534648895,
-0.2604392468929291,
-0.35200002789497375,
-0.15064652264118195,
0.2697538137435913,
0.1826927661895752,
0.09125352650880814,
-0.12194868177175522,
-0.10851744562387466,
-0.03932376578450203,
0.3502366244792938,
-0.214968740940094,
-0.12616385519504547,
0.2993685305118561,
-0.1570669412612915,
-0.17148832976818085,
0.006665978580713272,
-0.019033823162317276,
-0.028024282306432724,
0.12993308901786804,
-0.5250759720802307,
-0.12667787075042725,
-0.2553532123565674,
-0.01944783329963684,
-0.2235790491104126,
-0.21697384119033813,
0.4017179310321808,
-0.019970007240772247,
0.007223976776003838,
-0.007094044238328934,
-0.3523035943508148,
0.027413323521614075,
0.053191713988780975,
0.38160037994384766,
-0.13469213247299194,
0.30944913625717163,
-0.03444170206785202,
0.4264928102493286,
0.5960376262664795,
0.0360533632338047,
0.02764013409614563,
0.07134276628494263,
0.14365211129188538,
0.07474596798419952,
-0.10545020550489426,
0.26571565866470337,
-0.07296621799468994,
-0.07890313863754272,
0.2505122423171997,
0.008917722851037979,
-0.22383230924606323,
-0.17834460735321045,
-0.12964656949043274,
-0.45140305161476135,
-0.27320659160614014,
0.10059580206871033,
-0.3199053704738617,
0.17668426036834717,
0.13752348721027374,
0.2814924418926239,
-0.055178675800561905,
-0.5646655559539795,
0.029398571699857712,
0.41505634784698486,
0.21458125114440918,
0.11504055559635162,
-0.33853164315223694,
0.1420566290616989,
-0.3411736488342285,
0.26438724994659424,
0.20610526204109192,
0.37408316135406494,
-0.1111692488193512,
-0.11376402527093887,
0.03909432142972946,
-0.19258281588554382,
0.3788115382194519,
-0.4746643006801605,
0.05551697686314583,
-0.00408543087542057,
-0.07041024416685104,
-0.4118961989879608,
-0.21917130053043365,
-0.18260174989700317,
0.3691921532154083,
0.4657864570617676,
0.4691724479198456,
-0.35209381580352783,
-0.061966490000486374,
0.2556946873664856,
0.021391037851572037,
-0.1011052131652832,
-0.174580916762352,
-0.22858764231204987,
-0.3355112373828888,
-0.2618897557258606,
-0.17329686880111694,
-0.04387642443180084,
0.31121692061424255,
-0.07534471899271011,
-0.08241952210664749,
0.04225067049264908,
0.16651961207389832,
0.425326406955719,
0.23124046623706818,
0.20768505334854126,
-0.03240104764699936,
0.22409969568252563,
0.25176823139190674,
0.40947458148002625,
0.2128596007823944,
0.5298258066177368,
-0.0027628839015960693,
-0.19281616806983948,
-0.07655413448810577,
-0.30114465951919556,
0.005492262542247772,
0.43741244077682495,
0.2044098973274231,
-0.030449964106082916,
0.12637130916118622,
-0.13738712668418884,
-0.42967453598976135,
-0.05294419452548027,
0.1266050636768341,
-0.1013169214129448,
-0.38544777035713196,
-0.49731114506721497,
0.29982176423072815,
0.3504994809627533,
-0.11287234723567963,
-0.14339759945869446,
-0.09955067932605743,
-0.3347935676574707,
0.34836745262145996,
0.1721331775188446,
0.9992426037788391,
0.22708752751350403,
-0.02504497393965721,
-0.06836072355508804,
-0.2009786069393158,
0.7844555974006653,
-0.21298271417617798,
0.3598969578742981,
-0.4350261390209198,
-0.2963215112686157,
-0.10601989924907684,
-0.18125872313976288,
0.19104528427124023,
0.10323550552129745,
-0.33262690901756287,
0.3883803188800812,
0.10925772786140442,
-0.01733897253870964,
-0.20386344194412231,
0.4057892858982086,
-0.28847673535346985,
-0.1145377904176712,
-0.15640376508235931,
0.020807690918445587,
-0.1877886950969696,
0.43178772926330566,
0.08245304971933365,
-0.05726049095392227,
-0.2624441087245941,
-0.16835300624370575,
-0.5494994521141052,
0.22166454792022705,
0.14272379875183105,
0.02637326717376709,
0.21180008351802826,
-0.22485177218914032,
-0.013590821996331215,
0.13423489034175873,
0.32788556814193726,
-0.11514613032341003,
-0.10681673884391785,
-0.0016026571393013,
-0.022615842521190643,
-0.15573088824748993,
0.20076419413089752,
0.057710736989974976,
0.4340367317199707,
-0.10155399143695831,
-0.061763565987348557,
0.10912123322486877,
-0.07918648421764374,
-0.2611497640609741,
-0.1338934302330017,
-0.13959364593029022,
-0.18021485209465027,
-0.21085694432258606,
-0.2031717300415039,
0.014056168496608734,
-0.029257072135806084,
-0.09731970727443695,
0.017006656154990196,
-0.059214264154434204,
-0.19780589640140533,
0.25401172041893005,
-0.09184752404689789,
-0.3513319194316864,
-0.09548133611679077,
0.4479711949825287,
0.2841583788394928,
-0.04742593690752983,
0.4655079245567322,
-0.044768765568733215,
-0.11638534069061279,
-0.142870232462883,
-0.07991980016231537,
-0.22824016213417053,
-0.3608661890029907,
0.1705559492111206,
-0.25035595893859863,
0.0032198280096054077,
0.21465757489204407,
0.27662038803100586,
0.23138077557086945,
0.2816075384616852,
-0.09972803294658661,
-0.5418651700019836,
-0.005885621532797813,
0.16270053386688232,
0.09235391020774841,
0.1533018797636032,
-0.19041401147842407,
0.3851987421512604,
-0.2032112181186676,
0.0885583907365799,
-0.18876288831233978,
0.0016788651701062918,
-0.4216451048851013,
0.3190789818763733,
0.0986839234828949,
-0.010334260761737823,
-0.10648006200790405,
-0.05362049490213394,
-0.10954704880714417,
0.23286375403404236,
-0.008623586967587471,
-0.0021029282361268997,
-0.1735309362411499,
0.19913391768932343,
0.07818430662155151,
-0.1462133526802063,
-0.12777991592884064,
0.02929745241999626,
0.07194782793521881,
-0.039905861020088196,
-0.03288396820425987,
0.3182600736618042,
0.016946248710155487,
0.43039947748184204,
-0.2967921495437622,
0.007057413458824158,
-0.05222383886575699,
0.25376251339912415,
-0.37408027052879333,
0.32040339708328247,
-0.06483311206102371,
0.23397673666477203,
-0.0029911978635936975,
0.07607707381248474,
0.005250210408121347,
-0.01093979924917221,
-0.03330609202384949,
0.04425101727247238,
0.26031824946403503,
-0.18230938911437988,
0.15160910785198212,
0.3269649147987366,
0.0630289614200592,
0.66217440366745,
-0.0977916419506073,
-0.14357538521289825,
0.10021911561489105,
0.08938557654619217,
-0.12129510194063187,
0.0176846906542778,
0.2556929588317871,
-0.06330009549856186,
-0.08007554709911346,
0.3751468062400818,
0.16038791835308075,
-0.11737298965454102,
-0.2403324693441391,
0.09514571726322174,
0.5035054087638855,
-0.13529187440872192,
0.18721407651901245,
0.2672545909881592,
-0.05208103731274605,
-0.03511747345328331,
0.11959374696016312,
-0.21357037127017975,
0.11305534839630127,
0.08282115310430527,
-0.016397520899772644,
0.4081759452819824,
0.05979757383465767,
0.3810717761516571,
-0.1107976958155632,
-0.19281329214572906,
-0.016884218901395798,
0.5765299201011658,
0.19954770803451538,
0.4437112510204315,
0.23778961598873138,
0.34543317556381226,
-0.33760300278663635,
0.025902289897203445,
-0.3117019236087799,
-0.1353357583284378,
-0.013288278132677078,
-0.17353425920009613,
-0.44935426115989685,
-0.13270974159240723,
-0.22633275389671326,
0.11731503903865814,
-0.13277365267276764,
0.16289067268371582,
0.32127314805984497,
0.033501870930194855,
-0.20877082645893097,
-0.512785017490387,
0.06974249333143234,
-0.11926928907632828,
0.22779160737991333,
-0.2851017415523529,
0.11935082077980042,
0.12183379381895065,
-0.06800270080566406,
0.38052862882614136,
0.5955421328544617,
0.6343860626220703,
0.3927338123321533,
-0.19025832414627075,
-0.0560276098549366,
0.0363975428044796,
0.05950076878070831,
0.20654883980751038,
0.7163812518119812,
0.2461318075656891,
-0.220201775431633,
0.3402116894721985,
-0.033732496201992035,
-0.06545168161392212,
0.37195467948913574,
0.07000861316919327,
0.0255957692861557,
-0.08627039194107056,
0.5236676335334778,
-0.19162189960479736,
0.11693494766950607,
-0.05106053501367569,
0.0679503083229065,
-0.32060736417770386,
-0.323677659034729,
0.26137760281562805,
-0.26411721110343933,
0.24652719497680664,
-0.0030775396153330803,
0.015305664390325546,
-0.2047778218984604,
0.5182005167007446,
0.5190638303756714,
-0.09691687673330307,
-0.24339550733566284,
-0.01123107224702835,
-0.5534390807151794,
0.3506774604320526,
-0.3848564028739929,
-0.21972526609897614,
-0.14044570922851562,
0.5029476284980774,
-0.2913248836994171,
0.271891713142395,
-0.16698040068149567,
0.4217168986797333,
-0.1999897062778473,
0.23926503956317902,
-0.26129385828971863,
-0.04820116236805916,
-0.08566737174987793,
-0.24912545084953308,
-0.041208043694496155,
-0.23633703589439392,
0.12473779916763306,
0.0006039002910256386,
-0.09424837678670883,
0.030080754309892654,
-0.026399530470371246,
0.06136685982346535,
0.49497443437576294,
0.024868406355381012,
0.4822665750980377,
0.5218864679336548,
-0.1439880132675171,
-0.2633267641067505,
-0.17555569112300873,
-0.33674079179763794,
-0.3082938492298126,
0.43964216113090515,
0.1312471628189087,
0.37442272901535034,
-0.1879602074623108,
0.4798943102359772,
-0.13751064240932465,
0.33619341254234314,
-0.025599170476198196,
-0.1167680025100708,
-0.3755322992801666,
-0.05126340687274933,
-0.22220423817634583,
-0.03113829344511032,
0.09889931231737137,
0.42117664217948914,
0.15882252156734467,
0.08846063911914825,
-0.17987768352031708,
-0.4090624451637268,
0.4370060861110687,
-0.327399343252182,
0.043092552572488785,
-0.11276359856128693,
0.12388109415769577,
0.14992263913154602,
-0.03915152698755264,
-0.7592726349830627,
-0.035973746329545975,
0.3005138337612152,
-0.177036315202713,
-0.02731669321656227,
-0.013707553967833519,
-0.019451463595032692,
-0.22175200283527374,
-0.11064097285270691,
-0.30953407287597656,
0.22752606868743896,
-0.3596225380897522,
0.31355851888656616,
-0.08145659416913986
] |
https://github.com/huggingface/datasets/issues/215 | NonMatchingSplitsSizesError when loading blog_authorship_corpus | I wasn't aware of the "force_redownload" option and manually removed the '/home/me/.cache/huggingface/datasets/' dir, this worked for me (dataset 'cnn_dailymail') | Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on. | 19 | NonMatchingSplitsSizesError when loading blog_authorship_corpus
Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on.
I wasn't aware of the "force_redownload" option and manually removed the '/home/me/.cache/huggingface/datasets/' dir, this worked for me (dataset 'cnn_dailymail') | [
-0.05952122062444687,
0.15316832065582275,
0.0704789012670517,
0.38789206743240356,
-0.015147943049669266,
0.1419079601764679,
-0.09238578379154205,
0.32008153200149536,
-0.04935669153928757,
0.008110485970973969,
-0.08665413409471512,
0.15768729150295258,
0.036548759788274765,
0.0461474284529686,
-0.019717078655958176,
0.08979116380214691,
-0.04565099626779556,
0.20413710176944733,
0.04544687271118164,
0.029078975319862366,
0.000983554869890213,
0.5112385153770447,
-0.24448390305042267,
-0.06453905999660492,
-0.3506300449371338,
-0.14984454214572906,
0.05441678315401077,
0.3629710376262665,
0.010663431137800217,
-0.3910157382488251,
0.319717675447464,
-0.04728415235877037,
0.1141887754201889,
0.24019652605056763,
-0.00012255208275746554,
-0.002842336893081665,
0.4699680805206299,
-0.21914023160934448,
-0.2050269991159439,
-0.2703421115875244,
-0.21681585907936096,
-0.2991623282432556,
-0.04636288434267044,
-0.21825683116912842,
-0.06674200296401978,
-0.06653846800327301,
0.07996359467506409,
-0.05199211835861206,
0.3719485402107239,
0.29745855927467346,
0.125547394156456,
0.09593860059976578,
-0.12729518115520477,
0.10268118977546692,
0.08485596626996994,
0.06652462482452393,
-0.011884946376085281,
-0.04185522720217705,
-0.17200255393981934,
-0.321993887424469,
-0.12819787859916687,
0.5180577635765076,
-0.19157950580120087,
0.12624672055244446,
0.18193864822387695,
0.0800839439034462,
0.2830647826194763,
-0.11941677331924438,
0.06791115552186966,
0.3065376579761505,
0.4064788818359375,
0.10857941955327988,
-0.2249048352241516,
-0.5339201092720032,
0.007108952384442091,
0.05136070400476456,
0.45280009508132935,
0.34143397212028503,
-0.197662353515625,
0.10054163634777069,
-0.41586562991142273,
-0.22632411122322083,
-0.054598119109869,
0.007278576493263245,
0.2139008343219757,
0.20679163932800293,
0.03881848603487015,
-0.010091401636600494,
0.1374928504228592,
-0.037883661687374115,
0.22440919280052185,
-0.09224051982164383,
-0.14465267956256866,
0.08490939438343048,
-0.21261771023273468,
-0.15949317812919617,
-0.12389127165079117,
0.03781522437930107,
0.1740897297859192,
0.153521329164505,
0.2372102290391922,
-0.07823164016008377,
0.14463846385478973,
0.04192858189344406,
0.369392067193985,
0.17495565116405487,
-0.001896597445011139,
0.42824146151542664,
0.14054054021835327,
0.033288851380348206,
0.11029240489006042,
0.003799423575401306,
0.2939819395542145,
-0.15723007917404175,
-0.0670633316040039,
0.045196548104286194,
0.20995980501174927,
-0.543628990650177,
-0.4165376126766205,
0.07986783981323242,
-0.49174922704696655,
-0.20235203206539154,
-0.12295100837945938,
0.13204741477966309,
-0.34991854429244995,
0.35234397649765015,
-0.07884305715560913,
0.03780720755457878,
-0.3732774257659912,
-0.055995743721723557,
-0.2014298439025879,
0.10900092124938965,
-0.19364409148693085,
0.2363349348306656,
0.2714063227176666,
-0.28212133049964905,
0.43705230951309204,
-0.051476895809173584,
-0.09336414933204651,
-0.2561876177787781,
0.2646717131137848,
-0.030780835077166557,
-0.02329244464635849,
0.1904066503047943,
-0.13137565553188324,
0.23993603885173798,
0.00858066976070404,
-0.20084376633167267,
-0.2873159646987915,
0.01637335494160652,
-0.27687519788742065,
-0.6388430595397949,
0.08123864233493805,
0.11715024709701538,
-0.40461617708206177,
-0.05964156240224838,
0.01749790459871292,
0.22032073140144348,
0.3705641031265259,
-0.2604248821735382,
-0.10591349750757217,
-0.16875965893268585,
-0.10133935511112213,
-0.02985317073762417,
-0.16532771289348602,
0.5042769312858582,
0.13272762298583984,
-0.32241421937942505,
0.16070279479026794,
-0.03138468414545059,
0.47419610619544983,
0.4351547956466675,
-0.006501771509647369,
0.10734213143587112,
-0.17257268726825714,
0.3553568720817566,
0.14280344545841217,
-0.3949947953224182,
-0.2550790309906006,
0.4000755250453949,
-0.0010334476828575134,
0.2915744483470917,
0.18328091502189636,
0.13108772039413452,
0.09201548248529434,
-0.0645950585603714,
0.05912280082702637,
0.472974956035614,
0.07429322600364685,
0.0992300882935524,
-0.45281127095222473,
-0.4169975221157074,
0.43306535482406616,
0.16881926357746124,
0.10977046191692352,
0.07702752947807312,
-0.019928500056266785,
0.4880288541316986,
0.31506645679473877,
-0.14438781142234802,
0.06338492035865784,
0.31531858444213867,
-0.33134567737579346,
0.15865163505077362,
0.049391377717256546,
-0.08946045488119125,
-0.5167126059532166,
0.007718347012996674,
-0.2730106711387634,
0.31955772638320923,
0.050448331981897354,
-0.19811005890369415,
-0.23508009314537048,
-0.4627165198326111,
-0.07891352474689484,
-0.1806633174419403,
0.0007563978433609009,
0.23502175509929657,
0.409033864736557,
0.05455164238810539,
-0.018292728811502457,
0.5882975459098816,
-0.09648598730564117,
0.2448498159646988,
-0.8845168948173523,
0.2083265334367752,
-0.12776288390159607,
-0.1689957082271576,
0.41228818893432617,
0.2858721911907196,
0.27037715911865234,
-0.1416531503200531,
-0.13194647431373596,
0.46327081322669983,
-0.22580701112747192,
0.4788298010826111,
-0.22793686389923096,
-0.0022638291120529175,
0.27312564849853516,
-0.2956171929836273,
0.021120639517903328,
0.2180158793926239,
-0.046564821153879166,
-0.055270787328481674,
-0.06619317084550858,
0.3710591197013855,
-0.3695761263370514,
0.13853028416633606,
0.017573252320289612,
-0.04477160423994064,
0.10005359351634979,
-0.2872810363769531,
-0.14379769563674927,
-0.4895384907722473,
0.5787147283554077,
-0.1502460539340973,
-0.2525634467601776,
0.021484743803739548,
-0.1338326781988144,
0.016381271183490753,
0.3793991208076477,
0.06490480899810791,
-0.09646495431661606,
-0.03197631984949112,
-0.01605333387851715,
-0.20027032494544983,
0.05359116196632385,
0.24537457525730133,
0.5202927589416504,
0.136488676071167,
0.026374775916337967,
0.09233323484659195,
-0.16415837407112122,
-0.33067813515663147,
0.15244366228580475,
-0.0643644779920578,
0.08235223591327667,
0.36921730637550354,
0.17514680325984955,
-0.002143767662346363,
-0.5159105062484741,
0.1042155772447586,
0.21197280287742615,
0.24466386437416077,
-0.30409908294677734,
-0.13484103977680206,
-0.3648941218852997,
-0.38661521673202515,
-0.2667771875858307,
-0.1904561072587967,
-0.316261887550354,
-0.3300526738166809,
0.20578353106975555,
0.2855917811393738,
-0.11775757372379303,
0.15927450358867645,
-0.09243506193161011,
0.0607672780752182,
-0.32778340578079224,
0.009110844694077969,
-0.10953319072723389,
-0.2758680284023285,
-0.20552194118499756,
-0.05036255717277527,
0.10383964329957962,
0.3221498429775238,
0.18946270644664764,
-0.356062650680542,
-0.19915348291397095,
-0.07048306614160538,
-0.33795589208602905,
0.04746336489915848,
-0.08756691217422485,
-0.07165685296058655,
0.08050297200679779,
-0.0683811753988266,
0.3928329348564148,
-0.15853354334831238,
0.14054352045059204,
-0.2609803080558777,
-0.3093509078025818,
-0.041610538959503174,
0.1713782101869583,
0.19560803472995758,
-0.16764123737812042,
-0.5419104695320129,
-0.2437303215265274,
-0.36349084973335266,
-0.015157170593738556,
0.2141256183385849,
0.1851952075958252,
0.1718037724494934,
-0.1324823498725891,
-0.20916199684143066,
-0.11133063584566116,
0.2509463429450989,
-0.3925293982028961,
-0.13909894227981567,
0.19587862491607666,
-0.07682523876428604,
-0.13032086193561554,
-0.07141520082950592,
0.10173918306827545,
-0.08580437302589417,
0.07061222195625305,
-0.6237038969993591,
-0.2201807200908661,
-0.24198295176029205,
-0.09389472007751465,
-0.3028300702571869,
-0.17801044881343842,
0.5007232427597046,
-0.04541131854057312,
-0.004132919013500214,
0.08095019310712814,
-0.4596954882144928,
0.01794762909412384,
0.13317060470581055,
0.48731228709220886,
-0.17907088994979858,
0.2381068766117096,
-0.019556019455194473,
0.5533111691474915,
0.5295947194099426,
0.053176093846559525,
-0.009989134967327118,
0.16884203255176544,
0.22626477479934692,
0.040080808103084564,
-0.1329493373632431,
0.3330083191394806,
-0.06891165673732758,
0.037263281643390656,
0.34564948081970215,
0.10086305439472198,
-0.1492968648672104,
-0.1453624665737152,
-0.16622045636177063,
-0.36227425932884216,
-0.1801701933145523,
0.13737726211547852,
-0.13920143246650696,
0.12042494118213654,
0.2959353029727936,
0.14354175329208374,
-0.1756933033466339,
-0.4716580808162689,
-0.008708752691745758,
0.24278505146503448,
0.143654003739357,
0.19786418974399567,
-0.4579145610332489,
0.17113882303237915,
-0.5147838592529297,
0.2657478451728821,
0.15840087831020355,
0.26466140151023865,
-0.13183258473873138,
-0.14703072607517242,
0.09939620643854141,
-0.17282649874687195,
0.39402198791503906,
-0.404949426651001,
-0.07724947482347488,
-0.07967567443847656,
-0.016715524718165398,
-0.33635619282722473,
-0.17841531336307526,
-0.03545089811086655,
0.3083250820636749,
0.4751313626766205,
0.4908388555049896,
-0.39141008257865906,
-0.15796519815921783,
0.1868763118982315,
-0.009669477120041847,
-0.1367054283618927,
-0.13703131675720215,
-0.2299746721982956,
-0.3890259265899658,
-0.2763265073299408,
-0.11392184346914291,
-0.1300937682390213,
0.3114842176437378,
0.02537458948791027,
0.01682465150952339,
0.12226434051990509,
0.0988527312874794,
0.2510795593261719,
0.1897910237312317,
0.13215506076812744,
0.025374535471200943,
0.07778167724609375,
0.3831081986427307,
0.5103031396865845,
0.03691951185464859,
0.6296100616455078,
-0.010878447443246841,
-0.037916332483291626,
-0.08799253404140472,
-0.08143585920333862,
0.02740628272294998,
0.5505662560462952,
0.20019100606441498,
0.05380767583847046,
0.13748937845230103,
0.010431796312332153,
-0.4142747223377228,
-0.04083792492747307,
0.11529917269945145,
-0.08835116773843765,
-0.427870512008667,
-0.2941102385520935,
0.3169788122177124,
0.23538543283939362,
-0.1339426338672638,
-0.13132132589817047,
-0.1356361359357834,
-0.27198246121406555,
0.24533598124980927,
0.055233847349882126,
1.041927695274353,
0.207284614443779,
0.04186401516199112,
-0.055812858045101166,
-0.1492011696100235,
0.9380415678024292,
-0.30007869005203247,
0.4176374673843384,
-0.351711243391037,
-0.17800401151180267,
-0.05750344693660736,
-0.14746718108654022,
0.03603443503379822,
0.0908762663602829,
-0.1540612280368805,
0.3749524652957916,
0.28883594274520874,
0.050439029932022095,
-0.12973631918430328,
0.42349618673324585,
-0.24959737062454224,
-0.15231391787528992,
-0.3030501902103424,
0.01705753430724144,
-0.30228376388549805,
0.5400670766830444,
-0.03814367577433586,
-0.0711965411901474,
-0.08948315680027008,
-0.20423360168933868,
-0.37206488847732544,
0.25258558988571167,
0.024172533303499222,
0.12936845421791077,
0.23180116713047028,
-0.19619151949882507,
-0.07764199376106262,
0.10560862720012665,
0.4005061388015747,
-0.16487471759319305,
-0.12909549474716187,
-0.006210897117853165,
-0.1460067629814148,
-0.12728801369667053,
0.11892835050821304,
0.09156027436256409,
0.28809696435928345,
-0.09807290136814117,
-0.03008083999156952,
-0.013803645968437195,
-0.14492306113243103,
-0.330866277217865,
-0.24841278791427612,
-0.05192255973815918,
-0.16080883145332336,
-0.2244488149881363,
-0.014996785670518875,
0.1725156307220459,
-0.028158828616142273,
-0.1344454139471054,
0.020831778645515442,
-0.04764583706855774,
-0.1695941835641861,
0.11480950564146042,
-0.09480074048042297,
-0.3547867238521576,
-0.1866084635257721,
0.46530085802078247,
0.41192328929901123,
-0.13000470399856567,
0.4889170825481415,
-0.10779237747192383,
-0.04715222120285034,
-0.16125038266181946,
-0.18598607182502747,
-0.2622641324996948,
-0.42547574639320374,
0.20580711960792542,
-0.2105516940355301,
-0.17630591988563538,
0.2077464461326599,
0.26054129004478455,
0.23746593296527863,
0.31274643540382385,
-0.013969458639621735,
-0.4817531108856201,
-0.03925495594739914,
0.13603372871875763,
-0.011188969016075134,
0.09119077026844025,
-0.024539876729249954,
0.3797798752784729,
-0.24098224937915802,
0.318103164434433,
-0.21519368886947632,
0.039288491010665894,
-0.3406312167644501,
0.3029206693172455,
0.19331982731819153,
-0.13923373818397522,
0.06780177354812622,
0.012921538203954697,
-0.14105576276779175,
0.26413536071777344,
-0.10220294445753098,
-0.017113421112298965,
-0.14058807492256165,
0.19693759083747864,
0.15148618817329407,
-0.1118534505367279,
-0.1557074338197708,
0.07982834428548813,
0.06451982259750366,
0.01601596549153328,
0.06329783797264099,
0.2837775647640228,
0.06752502173185349,
0.3050289452075958,
-0.28709176182746887,
-0.03953491151332855,
0.0005170963704586029,
0.19909065961837769,
-0.24377396702766418,
0.22092701494693756,
-0.039350274950265884,
0.21276786923408508,
-0.16374057531356812,
0.05936986207962036,
-0.09963305294513702,
0.0008988901972770691,
0.08639159053564072,
0.08966079354286194,
0.08942975103855133,
-0.25115662813186646,
0.034797344356775284,
0.2602270543575287,
0.05379399657249451,
0.5116792917251587,
-0.08315525203943253,
-0.15430910885334015,
0.1248418316245079,
0.08711467683315277,
-0.14101755619049072,
-0.06204986944794655,
0.3102426528930664,
-0.07737154513597488,
-0.09637980163097382,
0.3810321092605591,
0.17304816842079163,
-0.12971416115760803,
-0.14074625074863434,
0.10686630755662918,
0.45320674777030945,
-0.19162863492965698,
0.15098324418067932,
0.1268135905265808,
-0.10557353496551514,
-0.08674150705337524,
0.37435150146484375,
-0.20107817649841309,
0.12214745581150055,
0.11047141253948212,
0.04505413770675659,
0.3720736503601074,
0.05472875386476517,
0.45312851667404175,
-0.1651650071144104,
-0.15896613895893097,
-0.03961111977696419,
0.6585904955863953,
0.18797153234481812,
0.43030044436454773,
0.14218129217624664,
0.5052541494369507,
-0.3357342779636383,
-0.01521608792245388,
-0.3209925889968872,
0.021360773593187332,
-0.092747263610363,
-0.16650784015655518,
-0.30164259672164917,
-0.11755897104740143,
-0.10489378124475479,
0.15447767078876495,
-0.15096940100193024,
0.055045656859874725,
0.4208003580570221,
-0.06759683787822723,
-0.29463064670562744,
-0.5726760625839233,
-0.003766532987356186,
0.05557895451784134,
0.27704954147338867,
-0.2272971123456955,
0.2844380736351013,
0.0758509635925293,
-0.20439988374710083,
0.319293349981308,
0.6775821447372437,
0.5208287835121155,
0.2321733683347702,
-0.032789599150419235,
-0.07751831412315369,
0.07033324241638184,
0.1269388347864151,
0.2107742726802826,
0.745038628578186,
0.29596900939941406,
-0.31335198879241943,
0.2754243314266205,
-0.038033515214920044,
-0.11196877807378769,
0.3472534716129303,
0.025003623217344284,
0.07327782362699509,
-0.03658036142587662,
0.38708585500717163,
-0.1618291139602661,
0.08336413651704788,
-0.06547261029481888,
0.09793051332235336,
-0.3249247968196869,
-0.2109721601009369,
0.16343875229358673,
-0.17252646386623383,
0.30173978209495544,
-0.08095744252204895,
0.0441569909453392,
-0.2473849654197693,
0.5227413773536682,
0.5025137662887573,
-0.3186624348163605,
-0.15052732825279236,
-0.026378393173217773,
-0.526768684387207,
0.2962951958179474,
-0.3916666507720947,
-0.08135929703712463,
-0.20274899899959564,
0.44821152091026306,
-0.1969209611415863,
0.2801700532436371,
-0.17557315528392792,
0.4149181544780731,
-0.07420146465301514,
-0.018937617540359497,
-0.23684778809547424,
0.0765000432729721,
-0.03134014457464218,
-0.19340305030345917,
0.07157544791698456,
-0.24616384506225586,
0.21737593412399292,
0.1577954888343811,
-0.10438892245292664,
0.03160778433084488,
0.10152055323123932,
-0.016133174300193787,
0.3900722563266754,
-0.07530251145362854,
0.5313584804534912,
0.29228490591049194,
-0.03974778950214386,
-0.28395164012908936,
-0.1452285498380661,
-0.40259096026420593,
-0.31096333265304565,
0.34221339225769043,
0.20279137790203094,
0.4863954484462738,
-0.22398029267787933,
0.47227540612220764,
-0.16622617840766907,
0.31102919578552246,
0.02751193940639496,
-0.061902184039354324,
-0.31948888301849365,
-0.02634221501648426,
-0.1740514636039734,
0.04495802894234657,
0.2053137868642807,
0.5501672625541687,
0.14749205112457275,
0.052830278873443604,
-0.26446664333343506,
-0.41413313150405884,
0.38899165391921997,
-0.38547787070274353,
0.003921061754226685,
0.07362986356019974,
0.23610728979110718,
0.2745177447795868,
-0.2053195834159851,
-0.7636072635650635,
0.04344826191663742,
0.22158850729465485,
-0.13191285729408264,
-0.00814615748822689,
0.06734813749790192,
-0.1885165274143219,
-0.2726271450519562,
-0.014860641211271286,
-0.17716476321220398,
0.36956971883773804,
-0.4083258807659149,
0.41735175251960754,
-0.019796527922153473
] |
https://github.com/huggingface/datasets/issues/215 | NonMatchingSplitsSizesError when loading blog_authorship_corpus | Yes I think this might not be documented well enough. Let’s add it to the doc @lhoestq @SBrandeis.
And everything on how to control the cache behavior better (removing, overriding, changing the path, etc) | Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on. | 34 | NonMatchingSplitsSizesError when loading blog_authorship_corpus
Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`.
```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323,
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation',
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'),
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766,
dataset_name='blog_authorship_corpus')}]
```
Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on.
Yes I think this might not be documented well enough. Let’s add it to the doc @lhoestq @SBrandeis.
And everything on how to control the cache behavior better (removing, overriding, changing the path, etc) | [
-0.04786325991153717,
0.2781369984149933,
0.07765756547451019,
0.39152562618255615,
-0.1035548746585846,
0.036403588950634,
-0.08268314599990845,
0.24596023559570312,
-0.08353319764137268,
0.04618596285581589,
0.08917642384767532,
0.17450417578220367,
0.04060813784599304,
-0.15940970182418823,
0.01790878176689148,
0.05279986560344696,
-0.06446699053049088,
0.1248314157128334,
0.10597938299179077,
0.042897261679172516,
-0.010564025491476059,
0.39612406492233276,
-0.19377824664115906,
-0.040419064462184906,
-0.30533477663993835,
-0.23367762565612793,
0.029022345319390297,
0.23348161578178406,
0.04022801294922829,
-0.4769929349422455,
0.24664773046970367,
0.05662955716252327,
0.10053175687789917,
0.16701549291610718,
-0.00012176283780718222,
-0.06326837837696075,
0.538947582244873,
-0.19484302401542664,
-0.25188663601875305,
-0.029789388179779053,
-0.383603036403656,
-0.27975690364837646,
0.0038727768696844578,
-0.28427672386169434,
0.01517852395772934,
0.023537248373031616,
0.17921487987041473,
-0.1652388870716095,
0.22913643717765808,
0.30275896191596985,
0.12136118113994598,
0.10980746150016785,
-0.18810929358005524,
0.16789482533931732,
0.17320461571216583,
-0.027630262076854706,
-0.06475889682769775,
-0.15657681226730347,
-0.1117100715637207,
-0.28193017840385437,
-0.24037232995033264,
0.4598936438560486,
-0.23572421073913574,
0.1500595211982727,
0.26409223675727844,
0.08830877393484116,
0.32167696952819824,
-0.08726488053798676,
0.013093648478388786,
0.39029115438461304,
0.5862076878547668,
-0.04683353751897812,
-0.28496623039245605,
-0.4985653758049011,
-0.12967389822006226,
0.028640015050768852,
0.5057663321495056,
0.27955061197280884,
-0.15703776478767395,
0.05370159074664116,
-0.46707478165626526,
-0.17777815461158752,
-0.05261141061782837,
-0.0008108243346214294,
0.31687140464782715,
0.19807469844818115,
0.1256277710199356,
-0.05163481831550598,
0.030755802989006042,
-0.010176576673984528,
0.2684495449066162,
-0.18169060349464417,
-0.12499339878559113,
0.08544934540987015,
-0.23216663300991058,
-0.2051638960838318,
-0.02672562748193741,
0.09116505086421967,
0.25675058364868164,
0.2174561768770218,
0.40052518248558044,
0.005886361002922058,
0.21397137641906738,
0.12421661615371704,
0.33585673570632935,
0.2084193080663681,
-0.014871053397655487,
0.3932429850101471,
0.15307927131652832,
-0.0024872946087270975,
0.13732904195785522,
0.05757558345794678,
0.3515794277191162,
-0.20486615598201752,
-0.011022193357348442,
0.20190489292144775,
0.15973474085330963,
-0.4877755641937256,
-0.3507683575153351,
0.100728340446949,
-0.39977967739105225,
-0.26050662994384766,
-0.05867183580994606,
0.24248537421226501,
-0.3720568120479584,
0.3226299285888672,
-0.26906415820121765,
-0.03352269530296326,
-0.4499554932117462,
-0.12790538370609283,
-0.23330028355121613,
0.17981576919555664,
-0.14685563743114471,
0.3382387161254883,
0.23913629353046417,
-0.07944642007350922,
0.3943147361278534,
-0.16760507225990295,
-0.09943628311157227,
-0.13192248344421387,
0.35655441880226135,
-0.1095731258392334,
0.08933661878108978,
0.20857898890972137,
-0.09280383586883545,
0.15524990856647491,
-0.04847044125199318,
-0.09950070828199387,
-0.48516055941581726,
0.041018035262823105,
-0.32748961448669434,
-0.6717569828033447,
0.09786207228899002,
0.11474642902612686,
-0.372028112411499,
-0.0490010529756546,
0.1598801612854004,
0.3045908808708191,
0.5192116498947144,
-0.3798099756240845,
0.0015788823366165161,
-0.08771109580993652,
-0.19829164445400238,
-0.15863703191280365,
-0.1705331802368164,
0.5231292247772217,
0.07261879742145538,
-0.3068561553955078,
0.12426852434873581,
0.011717491783201694,
0.4826216399669647,
0.36976704001426697,
-0.035665083676576614,
0.15336909890174866,
-0.1641877144575119,
0.35587453842163086,
0.17119933664798737,
-0.4163646101951599,
-0.27680954337120056,
0.3803890645503998,
0.1063767820596695,
0.274901419878006,
0.24967363476753235,
0.12377060204744339,
0.24420641362667084,
-0.19297713041305542,
0.016356170177459717,
0.42986148595809937,
-0.06306517869234085,
0.09338276088237762,
-0.5093783736228943,
-0.41878780722618103,
0.4363306760787964,
0.11583659052848816,
0.0694446861743927,
0.036295562982559204,
-0.0036746636033058167,
0.47427088022232056,
0.16346050798892975,
-0.08560024201869965,
0.09851235151290894,
0.25446826219558716,
-0.3477667570114136,
0.13968226313591003,
0.08394390344619751,
-0.07341695576906204,
-0.4933943748474121,
-0.029929041862487793,
-0.2795158624649048,
0.17815431952476501,
0.1481744945049286,
-0.32019758224487305,
-0.0982879176735878,
-0.4774523079395294,
-0.09374035894870758,
-0.13652102649211884,
0.029480785131454468,
0.2034239023923874,
0.5127838253974915,
0.08227682113647461,
0.019414391368627548,
0.5455953478813171,
-0.006968209519982338,
0.16135884821414948,
-0.8287147283554077,
0.06388167291879654,
-0.1368926465511322,
-0.18384507298469543,
0.36261147260665894,
0.35950547456741333,
0.21638250350952148,
-0.05094456672668457,
-0.09464149922132492,
0.5340720415115356,
-0.141417995095253,
0.4370478391647339,
-0.22054386138916016,
0.15210270881652832,
0.24981924891471863,
-0.2066890150308609,
0.1167721226811409,
0.21492500603199005,
-0.13724833726882935,
-0.0022523291409015656,
-0.09489545971155167,
0.3331185579299927,
-0.3746822774410248,
0.08620357513427734,
0.0674547478556633,
-0.10661555081605911,
0.05747620761394501,
-0.2557361125946045,
-0.27272549271583557,
-0.4599677324295044,
0.541471540927887,
-0.05310304835438728,
-0.23666363954544067,
0.013625881634652615,
-0.11991279572248459,
0.10136975347995758,
0.4620301425457001,
0.10436475276947021,
-0.015318512916564941,
-0.06299625337123871,
0.09480446577072144,
-0.2510460615158081,
0.20877355337142944,
0.21671460568904877,
0.4686732888221741,
0.15137289464473724,
0.07372000068426132,
0.019000276923179626,
-0.18847380578517914,
-0.33689552545547485,
0.10088314861059189,
-0.01621163636445999,
-0.024240173399448395,
0.27599823474884033,
0.011330806650221348,
-0.001432274468243122,
-0.3033420741558075,
0.0221082866191864,
0.19120846688747406,
0.1761496663093567,
-0.33251288533210754,
-0.061967164278030396,
-0.3928716778755188,
-0.3234999477863312,
-0.24957427382469177,
-0.1301068663597107,
-0.20251011848449707,
-0.3588606119155884,
0.3024477958679199,
0.16726481914520264,
-0.25919559597969055,
0.1308690905570984,
-0.25159937143325806,
0.18590371310710907,
-0.2763071060180664,
-0.10526414960622787,
-0.07306021451950073,
-0.27786558866500854,
-0.2761032283306122,
-0.06377295404672623,
0.11679285764694214,
0.3153984844684601,
0.3178683817386627,
-0.4152183532714844,
-0.21306505799293518,
0.04067284241318703,
-0.3145899772644043,
0.06718403100967407,
0.05993776023387909,
-0.10611526668071747,
0.10012204945087433,
-0.21414674818515778,
0.3740346431732178,
-0.22101722657680511,
-0.055854637175798416,
-0.22112038731575012,
-0.25211021304130554,
-0.06747736036777496,
0.20162172615528107,
0.24550239741802216,
-0.19950510561466217,
-0.5588045120239258,
-0.32585474848747253,
-0.3663262724876404,
-0.057020142674446106,
0.10900698602199554,
0.29956427216529846,
0.0821918398141861,
-0.21076981723308563,
-0.21016119420528412,
-0.18786519765853882,
0.31254082918167114,
-0.37954747676849365,
-0.16327399015426636,
0.35842156410217285,
-0.1916780322790146,
-0.07630971074104309,
0.04411069676280022,
-0.042466700077056885,
-0.07117582857608795,
0.12719348073005676,
-0.5488820672035217,
-0.1745838224887848,
-0.1155957281589508,
-0.04159938916563988,
-0.21918216347694397,
-0.2206537425518036,
0.6390057802200317,
-0.044646356254816055,
0.04780697077512741,
0.0388738289475441,
-0.36135271191596985,
0.07012835144996643,
0.03474840894341469,
0.5672551393508911,
-0.041620321571826935,
0.23606443405151367,
0.06656758487224579,
0.5585212707519531,
0.4746897220611572,
0.1441454142332077,
-0.024808205664157867,
0.30200421810150146,
0.1700400710105896,
0.08519993722438812,
0.09485109150409698,
0.3581472337245941,
-0.07355281710624695,
-0.20108471810817719,
0.3572823405265808,
0.14081478118896484,
-0.14786866307258606,
-0.08919966965913773,
-0.04618319496512413,
-0.2848127782344818,
-0.26709040999412537,
0.17356158792972565,
-0.32631292939186096,
0.20595723390579224,
0.27358636260032654,
0.18179109692573547,
-0.16912174224853516,
-0.4797634482383728,
0.051178354769945145,
0.3250443935394287,
0.2547907829284668,
0.2598891258239746,
-0.4101262390613556,
0.18531832098960876,
-0.548197865486145,
0.1673709750175476,
0.12330923229455948,
0.26960012316703796,
-0.1897909939289093,
-0.17715877294540405,
0.0442056879401207,
-0.151191845536232,
0.29357317090034485,
-0.5013008713722229,
-0.010341182351112366,
-0.11806616187095642,
-0.018266094848513603,
-0.19106534123420715,
-0.175484761595726,
0.017090920358896255,
0.3075025975704193,
0.4353835880756378,
0.3108360767364502,
-0.47793909907341003,
-0.07290231436491013,
0.11803130060434341,
-0.08828970789909363,
-0.14250580966472626,
-0.22670376300811768,
-0.1783093810081482,
-0.24675950407981873,
-0.1737656444311142,
-0.14634230732917786,
-0.06844387203454971,
0.2047617882490158,
-0.003669668920338154,
0.05763379856944084,
0.07807634025812149,
0.19451922178268433,
0.2609213590621948,
0.23615522682666779,
0.24638855457305908,
-0.07365656644105911,
0.10551030933856964,
0.344176709651947,
0.3810717761516571,
0.0458010733127594,
0.4809633493423462,
-0.04737747088074684,
-0.03335289657115936,
0.03335140272974968,
-0.15820325911045074,
-0.055854521691799164,
0.46437501907348633,
0.1498102843761444,
0.05822744220495224,
0.046125754714012146,
-0.11693403124809265,
-0.37757667899131775,
0.0007064300589263439,
-0.05507602542638779,
-0.14003075659275055,
-0.29990676045417786,
-0.4009559452533722,
0.261601984500885,
0.34820178151130676,
-0.14399400353431702,
-0.1402910351753235,
-0.17629612982273102,
-0.3403513729572296,
0.2590388059616089,
0.23190838098526,
1.041952133178711,
0.2871282398700714,
0.07867705821990967,
-0.14152073860168457,
-0.19598761200904846,
0.8950437307357788,
-0.4584696292877197,
0.3884287476539612,
-0.3797582983970642,
-0.16995228826999664,
-0.049717869609594345,
-0.13921773433685303,
0.06719174981117249,
0.07828167825937271,
-0.34914612770080566,
0.44244837760925293,
0.23112909495830536,
0.06170216202735901,
-0.14359596371650696,
0.3393726348876953,
-0.24981385469436646,
-0.18752291798591614,
-0.19505421817302704,
-0.005369901657104492,
-0.23499362170696259,
0.3488823175430298,
-0.009586093947291374,
-0.0852256715297699,
-0.05986133962869644,
-0.18270446360111237,
-0.3571862578392029,
0.11464259773492813,
0.09397121518850327,
0.012490633875131607,
0.23694093525409698,
-0.20036742091178894,
-0.11602862179279327,
0.09369586408138275,
0.3660138249397278,
-0.1871987134218216,
-0.1647212952375412,
-0.05034508928656578,
-0.13756588101387024,
-0.0733359232544899,
0.11516939103603363,
0.06339465826749802,
0.3432280719280243,
-0.0829625129699707,
0.06117624789476395,
0.1170477643609047,
-0.19855327904224396,
-0.44435131549835205,
-0.21357160806655884,
-0.13070234656333923,
-0.14821791648864746,
-0.11806496232748032,
-0.023201357573270798,
0.08216432482004166,
-0.01390138454735279,
-0.05310804769396782,
0.04212629050016403,
0.003688342869281769,
-0.15956947207450867,
0.3063167929649353,
-0.2527936100959778,
-0.23129945993423462,
-0.16731902956962585,
0.3863880932331085,
0.3539524972438812,
-0.02271563559770584,
0.38353440165519714,
-0.1494131237268448,
-0.16333270072937012,
-0.1423272043466568,
-0.22025412321090698,
-0.24535731971263885,
-0.3556593954563141,
0.11342094093561172,
-0.32436907291412354,
-0.23751303553581238,
0.09655298292636871,
0.19885854423046112,
0.17593811452388763,
0.398185670375824,
-0.05935514718294144,
-0.43293261528015137,
-0.08512742072343826,
0.16189225018024445,
-0.08562631905078888,
0.10745811462402344,
-0.03459126502275467,
0.29530346393585205,
-0.2341655194759369,
0.30818596482276917,
-0.22415944933891296,
-0.2144247442483902,
-0.3940698206424713,
0.27270591259002686,
0.0848626047372818,
-0.03858967125415802,
0.014369315467774868,
0.04511518031358719,
-0.21619164943695068,
0.2673085033893585,
-0.16531917452812195,
0.005659110844135284,
-0.051704272627830505,
0.20624279975891113,
0.13152076303958893,
-0.031795769929885864,
-0.18519622087478638,
0.12904246151447296,
0.09241284430027008,
0.04547378793358803,
0.02897149696946144,
0.2819368839263916,
0.040343932807445526,
0.4037655293941498,
-0.25698018074035645,
0.08450240641832352,
-0.01948448270559311,
0.20341449975967407,
-0.27178576588630676,
0.32474762201309204,
-0.08645592629909515,
0.30650511384010315,
-0.20353427529335022,
0.029180921614170074,
-0.02076466754078865,
0.07677067816257477,
0.12723585963249207,
0.01133882999420166,
0.1532256305217743,
-0.14263533055782318,
0.027951475232839584,
0.27671822905540466,
-0.0762605294585228,
0.5579020977020264,
-0.11840230226516724,
-0.2716977596282959,
0.13532370328903198,
0.07329834997653961,
-0.024312928318977356,
-0.06569484621286392,
0.09087368845939636,
0.02758844569325447,
-0.0758267492055893,
0.4246918857097626,
0.22875291109085083,
-0.1360151767730713,
-0.012512922286987305,
0.23883235454559326,
0.4896003305912018,
-0.26902318000793457,
0.07844099402427673,
0.1427544802427292,
-0.18673284351825714,
0.05787607282400131,
0.3953358829021454,
-0.23366129398345947,
0.14236792922019958,
0.06332097202539444,
0.11303883790969849,
0.4625708758831024,
0.20257914066314697,
0.3750728666782379,
-0.18873688578605652,
-0.10802371799945831,
-0.05696186050772667,
0.623226523399353,
0.27606868743896484,
0.3305191099643707,
0.19891810417175293,
0.3161473870277405,
-0.14343422651290894,
0.010834918357431889,
-0.3369036614894867,
-0.18920423090457916,
-0.0378134548664093,
-0.14686629176139832,
-0.37576279044151306,
-0.09626250714063644,
-0.08604558557271957,
0.08358070254325867,
-0.13657602667808533,
0.10390137881040573,
0.5570069551467896,
-0.17096583545207977,
-0.1825268417596817,
-0.5047012567520142,
0.22231590747833252,
0.003293905407190323,
0.20471422374248505,
-0.22498595714569092,
0.30062878131866455,
-0.04419136047363281,
-0.20166704058647156,
0.28789833188056946,
0.5239021182060242,
0.42503392696380615,
0.2935965657234192,
-0.040379539132118225,
-0.17957088351249695,
0.07012112438678741,
0.17155423760414124,
0.19459757208824158,
0.7336778044700623,
0.22640828788280487,
-0.36697906255722046,
0.2798475921154022,
-0.07750452309846878,
-0.04813341796398163,
0.47493553161621094,
0.010236386209726334,
0.03268764540553093,
-0.02730133756995201,
0.42502889037132263,
0.010576346889138222,
0.11824994534254074,
0.11753836274147034,
0.14925113320350647,
-0.22901606559753418,
-0.2858244776725769,
0.1325470209121704,
-0.17832809686660767,
0.28705668449401855,
-0.1423882246017456,
0.0456337109208107,
-0.20899464190006256,
0.609613835811615,
0.4575616121292114,
-0.2356964647769928,
-0.22168287634849548,
0.0019248947501182556,
-0.5511803030967712,
0.3374861776828766,
-0.3613298833370209,
-0.20019188523292542,
-0.17516092956066132,
0.5507522821426392,
-0.34127503633499146,
0.32878273725509644,
-0.30485665798187256,
0.3189481496810913,
-0.0368739552795887,
0.030296996235847473,
-0.27325257658958435,
-0.09151332080364227,
-0.08998356759548187,
-0.14913113415241241,
0.08855604380369186,
-0.2684873342514038,
0.251039057970047,
0.23709236085414886,
-0.10101060569286346,
-0.020666047930717468,
-0.02704480290412903,
0.17944830656051636,
0.5358684062957764,
-0.028986811637878418,
0.5525883436203003,
0.21866723895072937,
-0.11766823381185532,
-0.17617908120155334,
-0.21538448333740234,
-0.24386943876743317,
-0.3098509609699249,
0.15333756804466248,
0.13062870502471924,
0.3093514144420624,
-0.2756575047969818,
0.49836015701293945,
-0.14632435142993927,
0.41652774810791016,
-0.016830863431096077,
0.008334021084010601,
-0.23042693734169006,
-0.04797782748937607,
-0.09354915469884872,
0.12309993803501129,
0.18964512646198273,
0.412678986787796,
0.17846408486366272,
0.14102651178836823,
-0.19011104106903076,
-0.33226096630096436,
0.3096321225166321,
-0.3596898317337036,
0.08010396361351013,
-0.03542779013514519,
0.2624869644641876,
0.27984440326690674,
-0.24873369932174683,
-0.731859564781189,
-0.06884316354990005,
0.2349817305803299,
-0.12555167078971863,
0.06184437498450279,
0.04573851078748703,
-0.11327065527439117,
-0.2084636092185974,
-0.09276942908763885,
-0.1714310348033905,
0.28795912861824036,
-0.3046322166919708,
0.3468710482120514,
-0.1572411060333252
] |
https://github.com/huggingface/datasets/issues/211 | [Arrow writer, Trivia_qa] Could not convert TagMe with type str: converting to null type | Here the full error trace:
```
ArrowInvalid Traceback (most recent call last)
<ipython-input-1-7aaf3f011358> in <module>
1 import nlp
2 ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
----> 3 ds.map(lambda x: x, load_from_cache_file=False)
~/python_bin/nlp/arrow_dataset.py in map(self, function, with_indices, batched, batch_size, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, arrow_schema, disable_nullable)
549
550 if update_data:
--> 551 writer.finalize() # close_stream=bool(buf_writer is None)) # We only close if we are writing in a file
552
553 # Create new Dataset from buffer or file
~/python_bin/nlp/arrow_writer.py in finalize(self, close_stream)
182 def finalize(self, close_stream=True):
183 if self.pa_writer is not None:
--> 184 self.write_on_file()
185 self.pa_writer.close()
186 if close_stream:
~/python_bin/nlp/arrow_writer.py in write_on_file(self)
104 """
105 if self.current_rows:
--> 106 pa_array = pa.array(self.current_rows, type=self._type)
107 first_example = pa.array(self.current_rows[0:1], type=self._type)[0]
108 # Sanity check
~/hugging_face/venv_3.7/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib.array()
~/hugging_face/venv_3.7/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib._sequence_to_array()
~/hugging_face/venv_3.7/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
ArrowInvalid: Could not convert TagMe with type str: converting to null type
``` | Running the following code
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to null type` error.
On the other hand if we remove a certain column of `trivia_qa` which seems responsible for the bug, it works:
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, remove_columns=["entity_pages"], load_from_cache_file=False)
```
. Seems quite hard to debug what's going on here... @lhoestq @thomwolf - do you have a good first guess what the problem could be?
**Note** BTW: I think this could be a good test to check that the datasets work correctly: Take a tiny portion of the dataset and check that it can be written correctly. | 155 | [Arrow writer, Trivia_qa] Could not convert TagMe with type str: converting to null type
Running the following code
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to null type` error.
On the other hand if we remove a certain column of `trivia_qa` which seems responsible for the bug, it works:
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, remove_columns=["entity_pages"], load_from_cache_file=False)
```
. Seems quite hard to debug what's going on here... @lhoestq @thomwolf - do you have a good first guess what the problem could be?
**Note** BTW: I think this could be a good test to check that the datasets work correctly: Take a tiny portion of the dataset and check that it can be written correctly.
Here the full error trace:
```
ArrowInvalid Traceback (most recent call last)
<ipython-input-1-7aaf3f011358> in <module>
1 import nlp
2 ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
----> 3 ds.map(lambda x: x, load_from_cache_file=False)
~/python_bin/nlp/arrow_dataset.py in map(self, function, with_indices, batched, batch_size, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, arrow_schema, disable_nullable)
549
550 if update_data:
--> 551 writer.finalize() # close_stream=bool(buf_writer is None)) # We only close if we are writing in a file
552
553 # Create new Dataset from buffer or file
~/python_bin/nlp/arrow_writer.py in finalize(self, close_stream)
182 def finalize(self, close_stream=True):
183 if self.pa_writer is not None:
--> 184 self.write_on_file()
185 self.pa_writer.close()
186 if close_stream:
~/python_bin/nlp/arrow_writer.py in write_on_file(self)
104 """
105 if self.current_rows:
--> 106 pa_array = pa.array(self.current_rows, type=self._type)
107 first_example = pa.array(self.current_rows[0:1], type=self._type)[0]
108 # Sanity check
~/hugging_face/venv_3.7/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib.array()
~/hugging_face/venv_3.7/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib._sequence_to_array()
~/hugging_face/venv_3.7/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
ArrowInvalid: Could not convert TagMe with type str: converting to null type
``` | [
0.047822896391153336,
-0.014993414282798767,
0.0999605804681778,
0.48276644945144653,
0.25262296199798584,
0.11827053874731064,
0.12425927817821503,
0.4629979133605957,
0.20459410548210144,
-0.11430197954177856,
0.19549094140529633,
0.5628964900970459,
-0.11228945106267929,
-0.21451006829738617,
-0.06854422390460968,
-0.1865536868572235,
0.11651542037725449,
0.24228183925151825,
-0.003951467573642731,
-0.019452378153800964,
-0.12144695222377777,
0.12436164915561676,
-0.26443976163864136,
0.16095438599586487,
-0.4509822726249695,
-0.1343631148338318,
0.1006031185388565,
0.0705757588148117,
-0.1665283888578415,
-0.45291265845298767,
0.13311639428138733,
-0.38631588220596313,
-0.014494180679321289,
0.267690509557724,
-0.00012025610340060666,
-0.1023913249373436,
0.35268068313598633,
0.04843998700380325,
-0.26101523637771606,
-0.2479172796010971,
-0.4819885492324829,
0.09865820407867432,
0.3085624873638153,
-0.0510614737868309,
0.22519242763519287,
0.0243794247508049,
0.023879460990428925,
-0.5974248647689819,
0.1822831928730011,
0.5890493988990784,
0.1811952143907547,
0.31175121665000916,
-0.058616433292627335,
0.08240842819213867,
0.22701802849769592,
0.08643073588609695,
-0.34749895334243774,
0.15860091149806976,
-0.041865259408950806,
-0.16374878585338593,
-0.09725948423147202,
0.4248977303504944,
-0.17378702759742737,
0.12876734137535095,
0.6042642593383789,
0.1013762578368187,
0.10312234610319138,
-0.3009956479072571,
0.18946436047554016,
0.002262536436319351,
0.2738999128341675,
-0.18591824173927307,
-0.08067543059587479,
0.03091522306203842,
-0.14413130283355713,
-0.3694726824760437,
0.20961233973503113,
0.17653074860572815,
-0.3138512670993805,
0.017662402242422104,
0.011315234936773777,
0.0840630978345871,
-0.06323167681694031,
-0.07367566227912903,
-0.05972215160727501,
0.06742092221975327,
0.013082700781524181,
0.11426423490047455,
-0.05431633070111275,
-0.1860046535730362,
-0.1897270679473877,
-0.22003136575222015,
-0.20488402247428894,
0.24149291217327118,
-0.3378833830356598,
0.04840739071369171,
-0.05792555958032608,
-0.2089127004146576,
-0.16488376259803772,
-0.11893290281295776,
0.2784707546234131,
-0.00025321170687675476,
0.14469991624355316,
0.12964114546775818,
0.3333240747451782,
0.2861374020576477,
0.32042112946510315,
0.24878515303134918,
0.0986189991235733,
-0.3073054552078247,
-0.1854362040758133,
-0.013636887073516846,
-0.011412401683628559,
-0.009702622890472412,
0.5141108632087708,
0.016387635841965675,
0.3002511262893677,
-0.3601059913635254,
-0.3549935519695282,
-0.011049035005271435,
-0.735805332660675,
0.159963920712471,
-0.16902358829975128,
0.10665593296289444,
-0.008254090324044228,
0.4835464060306549,
0.24768327176570892,
0.2814023792743683,
-0.3391999900341034,
-0.19262823462486267,
-0.11420821398496628,
-0.004297148436307907,
-0.29851973056793213,
0.015622427687048912,
0.305298775434494,
-0.03636535629630089,
0.053923748433589935,
0.06570818275213242,
-0.40770697593688965,
-0.20890961587429047,
0.3739098012447357,
-0.42265287041664124,
0.17886768281459808,
-0.008707631379365921,
-0.32873719930648804,
0.41525059938430786,
0.24119050800800323,
-0.4089019298553467,
-0.21291393041610718,
0.1715904176235199,
-0.13049659132957458,
0.0368976853787899,
-0.19280916452407837,
0.12478379905223846,
0.1592133790254593,
-0.21862554550170898,
-0.17026445269584656,
-0.06532660126686096,
0.39254382252693176,
-0.10832788050174713,
0.10371732711791992,
-0.2929549813270569,
-0.0403238981962204,
-0.24107541143894196,
-0.08629386126995087,
0.4788670539855957,
-0.22314198315143585,
0.06661124527454376,
-0.055577293038368225,
0.18355394899845123,
0.3641401529312134,
0.378109872341156,
-0.020373918116092682,
0.1771153062582016,
0.1071867048740387,
0.28203481435775757,
0.4739597737789154,
-0.30076542496681213,
-0.10005518049001694,
0.09920661896467209,
-0.028821874409914017,
-0.007086681202054024,
-0.041806064546108246,
0.12140318751335144,
0.07706896960735321,
-0.1202663853764534,
0.1674463152885437,
0.19477063417434692,
-0.06231947988271713,
0.23532545566558838,
-0.4206896126270294,
-0.10153254866600037,
0.5093355774879456,
-0.17420120537281036,
-0.0756608247756958,
0.026094786822795868,
-0.07687561959028244,
0.05020181089639664,
-0.0676264539361,
-0.013059113174676895,
0.4281765818595886,
0.26007670164108276,
-0.09044051170349121,
-0.08258424699306488,
0.0832560732960701,
-0.1882937252521515,
-0.38731589913368225,
-0.052016731351614,
-0.10536511242389679,
0.13355886936187744,
-0.17240871489048004,
-0.040387071669101715,
-0.3455455005168915,
0.07457055896520615,
-0.02713197097182274,
-0.19891293346881866,
0.1253451704978943,
0.10824747383594513,
0.15891964733600616,
0.05802837386727333,
-0.22786827385425568,
0.1251097172498703,
0.00482417456805706,
0.12739752233028412,
-0.3979262709617615,
-0.14816661179065704,
-0.08023757487535477,
-0.3554534614086151,
-0.09916677325963974,
0.17995890974998474,
0.2376292645931244,
0.16755416989326477,
-0.26986411213874817,
0.1873168647289276,
0.018680404871702194,
0.2171434462070465,
-0.2549818456172943,
0.02990114688873291,
0.01876700296998024,
-0.4021495580673218,
0.2202015370130539,
0.32697343826293945,
0.36164918541908264,
-0.2435903251171112,
-0.3964940011501312,
-0.02146250009536743,
0.01459936611354351,
0.58585524559021,
-0.13255611062049866,
0.10853246599435806,
-0.07677534222602844,
-0.03623274341225624,
0.09410479664802551,
-0.07976377010345459,
0.096011221408844,
-0.11330640316009521,
0.19795340299606323,
0.29243698716163635,
-0.30972325801849365,
0.27264833450317383,
0.42169538140296936,
0.3002501130104065,
0.13427668809890747,
0.15981075167655945,
-0.33452171087265015,
-0.0856642946600914,
0.2644166350364685,
-0.012384925037622452,
0.46109122037887573,
-0.0432867556810379,
0.21456070244312286,
-0.08492761850357056,
-0.15070253610610962,
-0.14859648048877716,
0.35784003138542175,
-0.09661878645420074,
0.01726612262427807,
-0.009265869855880737,
0.4907113313674927,
0.010626139119267464,
-0.17871445417404175,
0.20089170336723328,
0.005513790994882584,
0.2383062243461609,
-0.3552829623222351,
0.3290385901927948,
-0.3391128182411194,
-0.16789516806602478,
-0.38104143738746643,
-0.2544400691986084,
-0.018507950007915497,
-0.502819299697876,
-0.14053601026535034,
0.0792337954044342,
0.006112053990364075,
0.12038955837488174,
-0.2541165053844452,
-0.14185769855976105,
0.018085403367877007,
-0.11071298271417618,
-0.33473554253578186,
-0.3540615737438202,
-0.370501846075058,
-0.06328783929347992,
0.46462759375572205,
0.32319629192352295,
0.1873820722103119,
0.053033873438835144,
-0.0629505142569542,
-0.06901051104068756,
-0.3603874742984772,
0.03056313283741474,
-0.19892199337482452,
0.05718579888343811,
0.12039291858673096,
0.07614035904407501,
-0.13603101670742035,
-0.12729725241661072,
0.42562082409858704,
0.0031829513609409332,
-0.24060222506523132,
0.32919079065322876,
-0.02077130228281021,
0.04902191460132599,
-0.29279494285583496,
-0.48070839047431946,
0.013537148013710976,
-0.46828681230545044,
0.13702994585037231,
-0.11211821436882019,
0.20932060480117798,
0.17763294279575348,
0.12377581000328064,
0.3106841444969177,
-0.0557437539100647,
0.18512554466724396,
0.20702683925628662,
0.3653653860092163,
0.6162764430046082,
-0.13313645124435425,
-0.23794661462306976,
0.20846593379974365,
-0.07696908712387085,
0.3138101398944855,
0.2074880450963974,
-0.17882150411605835,
0.33277010917663574,
-0.42187902331352234,
0.3207613527774811,
-0.16330711543560028,
-0.13050541281700134,
0.2217363715171814,
0.22102117538452148,
-0.048052482306957245,
-0.06043776869773865,
-0.007517026737332344,
0.21831294894218445,
-0.21776598691940308,
0.15179309248924255,
0.12625360488891602,
0.21420934796333313,
-0.05345015227794647,
0.38171952962875366,
0.14399783313274384,
-0.2284076064825058,
0.28303128480911255,
0.016808874905109406,
-0.04759572818875313,
-0.30222105979919434,
-0.27842622995376587,
-0.08813535422086716,
-0.21157032251358032,
0.1277090311050415,
-0.1773894876241684,
0.033944182097911835,
-0.4855811297893524,
-0.022265659645199776,
0.2889741063117981,
-0.18293264508247375,
-0.13431289792060852,
0.3022046387195587,
-0.2138022780418396,
0.2901405990123749,
0.13461044430732727,
0.12581947445869446,
-0.19792313873767853,
-0.41243892908096313,
0.03293651342391968,
-0.024656660854816437,
0.15686127543449402,
0.024755267426371574,
-0.10193738341331482,
-0.05289794132113457,
-0.47397786378860474,
0.28840142488479614,
0.1751556694507599,
0.4326755702495575,
-0.0764363631606102,
-0.1432514786720276,
0.1917077898979187,
-0.11352067440748215,
0.2986406683921814,
-0.14612385630607605,
-0.027595356106758118,
0.3758091628551483,
0.2723763883113861,
-0.4777471125125885,
0.2693077623844147,
-0.23111483454704285,
0.3493022322654724,
0.26166728138923645,
0.2834547162055969,
-0.3896859288215637,
-0.3131132423877716,
0.25790220499038696,
0.16102814674377441,
0.016652081161737442,
0.0899721160531044,
-0.31698015332221985,
-0.00351816788315773,
-0.15553444623947144,
-0.08673816174268723,
0.2757047116756439,
0.3106018602848053,
0.08262214064598083,
0.054902251809835434,
-0.330187052488327,
0.17894992232322693,
0.18064190447330475,
0.026372727006673813,
0.428266704082489,
-0.30367183685302734,
0.137691468000412,
-0.1568317711353302,
0.20898042619228363,
-0.08677200227975845,
0.3240392506122589,
-0.06349006295204163,
-0.19840139150619507,
0.26688045263290405,
-0.05753713473677635,
0.36443638801574707,
0.3292663097381592,
0.03609280288219452,
0.3470538258552551,
-0.12237447500228882,
-0.09592166543006897,
-0.2033008635044098,
0.029605166986584663,
0.16758917272090912,
-0.05280951038002968,
0.04342714324593544,
-0.2120436728000641,
0.4822666347026825,
0.2981495261192322,
-0.033570606261491776,
0.6272773742675781,
0.1370314061641693,
-0.2833763062953949,
0.23740094900131226,
0.1865319013595581,
1.1821577548980713,
0.1512257158756256,
0.1496681571006775,
0.13378293812274933,
-0.4301357865333557,
0.33390843868255615,
0.06193799525499344,
0.32546019554138184,
-0.4628365933895111,
0.3249562978744507,
0.024498580023646355,
-0.1689324676990509,
0.06731470674276352,
-0.03389614075422287,
-0.3024047613143921,
0.0830451101064682,
-0.19603002071380615,
0.3092464506626129,
0.11238547414541245,
0.058071210980415344,
-0.3026752471923828,
-0.31657859683036804,
-0.37491852045059204,
0.08060061186552048,
-0.25055015087127686,
-0.0766252726316452,
0.11036089062690735,
-0.21556557714939117,
-0.49149301648139954,
-0.04550528898835182,
-0.06853950023651123,
0.1147971823811531,
-0.1706717610359192,
0.046522919088602066,
0.23672963678836823,
-0.15768678486347198,
0.1811174750328064,
0.0725666955113411,
-0.10370728373527527,
-0.06586925685405731,
-0.1338338851928711,
-0.08608773350715637,
0.19671598076820374,
0.10096611827611923,
0.12061899900436401,
-0.07572063058614731,
0.011200949549674988,
0.07623331993818283,
0.02482161670923233,
0.2276177704334259,
-0.3680090010166168,
-0.01354152336716652,
-0.06473123282194138,
0.16641730070114136,
0.11926662176847458,
-0.09275055676698685,
-0.08846518397331238,
0.09907546639442444,
-0.06051851063966751,
0.0031132884323596954,
0.0932033360004425,
0.02566814050078392,
0.15167847275733948,
0.08057156950235367,
-0.15691064298152924,
-0.2600077986717224,
0.26901620626449585,
0.34133127331733704,
0.04775969684123993,
0.24060404300689697,
0.7169973850250244,
0.0595085434615612,
-0.18554146587848663,
-0.17794457077980042,
0.07761091738939285,
-0.052395571023225784,
-0.7310899496078491,
0.3293781280517578,
-0.33141714334487915,
-0.22107812762260437,
0.03403424471616745,
0.4544679522514343,
-0.202938050031662,
0.08033965528011322,
-0.1594124734401703,
-0.2330784797668457,
-0.21894444525241852,
0.17904852330684662,
-0.030600447207689285,
0.03467164188623428,
-0.45244812965393066,
-0.057528574019670486,
0.09664352983236313,
0.1214955747127533,
-0.22719335556030273,
-0.010041768662631512,
-0.17429344356060028,
0.3713476061820984,
0.09213243424892426,
0.03296457976102829,
-0.050732433795928955,
-0.18051032721996307,
-0.011443930678069592,
0.515113115310669,
-0.09715501219034195,
-0.14438799023628235,
-0.26212018728256226,
0.14715488255023956,
0.07113237679004669,
-0.16618289053440094,
0.07055415213108063,
0.024171963334083557,
0.0784350335597992,
-0.21286910772323608,
-0.15107877552509308,
-0.10288618505001068,
-0.18629826605319977,
0.05603841319680214,
-0.08770027756690979,
0.2029782235622406,
-0.17871850728988647,
0.09925535321235657,
-0.14713366329669952,
0.05682013928890228,
-0.24345897138118744,
0.10793513804674149,
0.2107045203447342,
0.057123005390167236,
-0.2081969976425171,
0.04877771437168121,
-0.0946367084980011,
-0.15886461734771729,
0.3047354519367218,
-0.37726426124572754,
-0.166188046336174,
0.056550346314907074,
-0.1906721591949463,
0.41663122177124023,
-0.0920555517077446,
0.0020520929247140884,
-0.08149725943803787,
0.09775548428297043,
0.07033410668373108,
0.31662482023239136,
-0.17869526147842407,
-0.1631123125553131,
-0.11346417665481567,
0.1911708414554596,
-0.023984402418136597,
-0.1549658477306366,
-0.030290916562080383,
0.09489049762487411,
0.033047355711460114,
-0.4421166777610779,
-0.16407272219657898,
0.13605383038520813,
-0.025477886199951172,
-0.07160672545433044,
0.3569367825984955,
-0.10453945398330688,
0.021537616848945618,
0.02030269056558609,
0.36647793650627136,
0.334046334028244,
0.43646442890167236,
0.20343390107154846,
-0.06764330714941025,
0.11950598657131195,
-0.02497245743870735,
0.38919922709465027,
0.24424739181995392,
0.15110091865062714,
0.17533531785011292,
0.5244446992874146,
-0.298078715801239,
-0.32812410593032837,
0.06573379039764404,
0.10832846164703369,
-0.27272334694862366,
-0.08761180937290192,
-0.5703158378601074,
-0.11522654443979263,
-0.4419068396091461,
-0.08809848129749298,
-0.19053779542446136,
0.25448960065841675,
0.692865252494812,
0.23379063606262207,
0.016697607934474945,
-0.5845615863800049,
-0.12988480925559998,
0.13295458257198334,
0.39208438992500305,
-0.2488599270582199,
0.40359482169151306,
0.10868524014949799,
-0.0760030746459961,
-0.13055269420146942,
0.49973490834236145,
0.4683450162410736,
0.5678133368492126,
-0.2883794605731964,
-0.06765200197696686,
0.05808182805776596,
-0.18258091807365417,
0.23777779936790466,
0.5766581892967224,
0.33824294805526733,
0.14017975330352783,
0.03504382073879242,
-0.03796571493148804,
-0.1073760911822319,
-0.09008006751537323,
-0.029721643775701523,
0.277446985244751,
-0.16376112401485443,
0.2949458956718445,
-0.23841068148612976,
-0.22263887524604797,
-0.046252354979515076,
-0.21092990040779114,
-0.3650149405002594,
-0.04621872305870056,
0.20551665127277374,
0.0495741181075573,
0.01566902920603752,
-0.33418184518814087,
0.05742139369249344,
0.20212304592132568,
0.5171065926551819,
0.27114230394363403,
0.13861316442489624,
-0.47538450360298157,
-0.11695388704538345,
-0.7315421104431152,
0.1763940453529358,
-0.3149000406265259,
-0.1567133218050003,
-0.014518678188323975,
0.3632786273956299,
0.04523162543773651,
0.31469881534576416,
-0.034921616315841675,
0.2289496809244156,
0.25130152702331543,
0.30536097288131714,
-0.3416901230812073,
-0.11979328095912933,
0.35304325819015503,
-0.3037296235561371,
0.023086491972208023,
-0.5888969302177429,
0.26860255002975464,
0.051241569221019745,
0.06511207669973373,
-0.008692510426044464,
-0.2844811677932739,
0.29853957891464233,
0.48924562335014343,
0.27550697326660156,
0.2637924551963806,
0.2856045365333557,
0.24758201837539673,
-0.5557767748832703,
-0.21760618686676025,
-0.1734553575515747,
-0.20772723853588104,
-0.020305626094341278,
0.08986908197402954,
0.5805659294128418,
-0.14044833183288574,
0.062437351793050766,
-0.3035687804222107,
0.3277711570262909,
-0.22651728987693787,
0.034377943724393845,
-0.17557282745838165,
0.06700552254915237,
-0.3490554690361023,
0.16302508115768433,
0.07218987494707108,
0.1204005628824234,
0.1978316456079483,
0.24254406988620758,
-0.5347840189933777,
-0.38742899894714355,
0.30438604950904846,
-0.5194072723388672,
-0.4466894865036011,
0.2931904196739197,
0.14298835396766663,
0.44685134291648865,
-0.012415779754519463,
-0.7071853280067444,
-0.2688806653022766,
0.21321886777877808,
-0.09643738716840744,
0.025330565869808197,
0.023005280643701553,
0.02659551426768303,
0.07402946054935455,
-0.19160304963588715,
0.3619847893714905,
0.00830192118883133,
0.049281045794487,
0.04832902178168297,
-0.22841106355190277
] |
https://github.com/huggingface/datasets/issues/211 | [Arrow writer, Trivia_qa] Could not convert TagMe with type str: converting to null type | Actually thinking a bit more about it, it's probably a data sample that is not correct in `trivia_qa`. But I'm a bit surprised though that we managed to write it in .arrow format and now cannot write it anymore after an "identity" mapping. | Running the following code
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to null type` error.
On the other hand if we remove a certain column of `trivia_qa` which seems responsible for the bug, it works:
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, remove_columns=["entity_pages"], load_from_cache_file=False)
```
. Seems quite hard to debug what's going on here... @lhoestq @thomwolf - do you have a good first guess what the problem could be?
**Note** BTW: I think this could be a good test to check that the datasets work correctly: Take a tiny portion of the dataset and check that it can be written correctly. | 43 | [Arrow writer, Trivia_qa] Could not convert TagMe with type str: converting to null type
Running the following code
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to null type` error.
On the other hand if we remove a certain column of `trivia_qa` which seems responsible for the bug, it works:
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, remove_columns=["entity_pages"], load_from_cache_file=False)
```
. Seems quite hard to debug what's going on here... @lhoestq @thomwolf - do you have a good first guess what the problem could be?
**Note** BTW: I think this could be a good test to check that the datasets work correctly: Take a tiny portion of the dataset and check that it can be written correctly.
Actually thinking a bit more about it, it's probably a data sample that is not correct in `trivia_qa`. But I'm a bit surprised though that we managed to write it in .arrow format and now cannot write it anymore after an "identity" mapping. | [
0.1208232045173645,
0.08130066096782684,
0.08892324566841125,
0.4082986116409302,
0.2814409136772156,
0.05460158735513687,
0.11376447230577469,
0.33654892444610596,
0.18600942194461823,
-0.18695004284381866,
0.24845752120018005,
0.5634832978248596,
0.0009862612932920456,
-0.07831837981939316,
-0.023558761924505234,
-0.11811482906341553,
0.07306350767612457,
0.2508920431137085,
0.050629690289497375,
-0.1244528666138649,
-0.09246085584163666,
0.1616436094045639,
-0.18193918466567993,
0.22253037989139557,
-0.5130985379219055,
-0.15872830152511597,
0.1441274732351303,
0.08026709407567978,
-0.11963669210672379,
-0.4990118741989136,
0.01551610417664051,
-0.34734246134757996,
0.03081813082098961,
0.20836132764816284,
-0.00011913953494513407,
-0.16594409942626953,
0.3734931945800781,
-0.052215129137039185,
-0.1960316151380539,
-0.21079610288143158,
-0.5531389117240906,
0.16648231446743011,
0.3032819926738739,
-0.06724217534065247,
0.23992854356765747,
-0.10213456302881241,
0.0658058375120163,
-0.5268751382827759,
0.09618109464645386,
0.49537739157676697,
0.19496870040893555,
0.15002773702144623,
0.11893051862716675,
0.08554054796695709,
0.26706463098526,
0.11917148530483246,
-0.28745442628860474,
0.0432623028755188,
-0.13040462136268616,
-0.22419467568397522,
-0.06938833743333817,
0.3475063741207123,
-0.04919649660587311,
-0.0045446306467056274,
0.5662893056869507,
0.044567935168743134,
0.19759419560432434,
-0.18642769753932953,
0.25648245215415955,
0.058506954461336136,
0.3549572825431824,
-0.061708323657512665,
-0.1086406335234642,
0.09885508567094803,
-0.12332411855459213,
-0.3633821904659271,
0.28847557306289673,
0.22252202033996582,
-0.2659066617488861,
-0.012292016297578812,
0.11637657880783081,
0.06312420964241028,
0.009714841842651367,
-0.12463657557964325,
-0.15653665363788605,
0.1494547575712204,
0.018611852079629898,
0.11266791820526123,
-0.05011356249451637,
-0.1976815164089203,
-0.1804715394973755,
-0.07938490062952042,
-0.30318981409072876,
0.2140204757452011,
-0.28308483958244324,
0.011638686060905457,
-0.05160389840602875,
-0.16387298703193665,
-0.20187893509864807,
-0.08790966868400574,
0.41374561190605164,
-0.0001445319503545761,
-0.005352219566702843,
0.06754866987466812,
0.3144073188304901,
0.42886194586753845,
0.46972113847732544,
0.098272405564785,
0.13660791516304016,
-0.30488911271095276,
-0.18265269696712494,
-0.03447582572698593,
-0.025242093950510025,
-0.009739932604134083,
0.43271714448928833,
0.024083491414785385,
0.07819658517837524,
-0.3047500550746918,
-0.25904086232185364,
0.026841796934604645,
-0.7115640044212341,
0.2219676673412323,
-0.21643343567848206,
0.13746324181556702,
0.06488527357578278,
0.4073716700077057,
0.29524290561676025,
0.2960963249206543,
-0.2042863816022873,
-0.20120768249034882,
-0.11234623193740845,
-0.09873443841934204,
-0.3487413823604584,
-0.1523420810699463,
0.19270963966846466,
-0.0855012834072113,
0.08561816811561584,
0.02165371924638748,
-0.5190795063972473,
-0.22347429394721985,
0.29673436284065247,
-0.2855612337589264,
0.2961820662021637,
0.06044945493340492,
-0.27452200651168823,
0.45916247367858887,
0.21227796375751495,
-0.5164345502853394,
-0.09735013544559479,
0.0927971601486206,
-0.204600989818573,
0.07067333161830902,
-0.18194742500782013,
0.1397913545370102,
0.03730938956141472,
-0.2744908034801483,
-0.20205318927764893,
-0.0635196715593338,
0.3884657919406891,
-0.16859491169452667,
0.09392964094877243,
-0.2046530842781067,
-0.012688685208559036,
-0.28410348296165466,
-0.14891177415847778,
0.383408784866333,
-0.18657824397087097,
0.10843682289123535,
-0.0751800686120987,
0.1669815629720688,
0.3044077157974243,
0.34559154510498047,
0.0228829775005579,
0.19979768991470337,
0.10551220178604126,
0.3500438332557678,
0.39273685216903687,
-0.2295798361301422,
-0.009729590266942978,
-0.0022537419572472572,
-0.017602205276489258,
-0.007658632472157478,
-0.05828159302473068,
-0.0028016925789415836,
0.042020607739686966,
-0.11749880015850067,
0.08269516378641129,
0.12329777330160141,
0.01209910400211811,
0.259146511554718,
-0.3936404287815094,
-0.06219422072172165,
0.4800755977630615,
-0.31273168325424194,
-0.2060406655073166,
-0.030394628643989563,
0.016499511897563934,
0.10142692923545837,
-0.02642885595560074,
-0.09374566376209259,
0.30804821848869324,
0.17479312419891357,
-0.07066208124160767,
-0.14800602197647095,
0.15718470513820648,
-0.04129200056195259,
-0.3996149003505707,
-0.05961373448371887,
-0.11000104248523712,
0.1341487169265747,
-0.051153406500816345,
0.0029529668390750885,
-0.2747977077960968,
0.05228060483932495,
-0.007796440273523331,
-0.25278154015541077,
0.14248062670230865,
0.06316795945167542,
0.16465048491954803,
0.12633134424686432,
-0.21560579538345337,
0.06162596493959427,
0.021692467853426933,
0.12927879393100739,
-0.36722826957702637,
-0.2625303566455841,
0.010546255856752396,
-0.3314328193664551,
-0.19128312170505524,
0.23127031326293945,
0.2290375530719757,
0.13432130217552185,
-0.2543701231479645,
0.19253799319267273,
-0.009426010772585869,
0.3920418620109558,
-0.21428406238555908,
0.07450925558805466,
-0.01363501138985157,
-0.5046822428703308,
0.19313804805278778,
0.4102119505405426,
0.2995215952396393,
-0.2957395613193512,
-0.4034363925457001,
-0.053517699241638184,
-0.03167383745312691,
0.5904877781867981,
-0.09309862554073334,
0.25580811500549316,
-0.02029421180486679,
-0.06831356883049011,
0.07016144692897797,
-0.12563331425189972,
0.19013722240924835,
-0.16906914114952087,
0.17845749855041504,
0.2348817139863968,
-0.23076646029949188,
0.31589844822883606,
0.38045749068260193,
0.32732710242271423,
0.21452650427818298,
0.03870785981416702,
-0.3840383291244507,
-0.060156673192977905,
0.27095603942871094,
0.06697294116020203,
0.3688619136810303,
-0.059140823781490326,
0.22426293790340424,
-0.13389982283115387,
-0.15443645417690277,
-0.17635606229305267,
0.321090430021286,
-0.20176978409290314,
0.07100464403629303,
0.06617754697799683,
0.5125985145568848,
0.017989778891205788,
-0.18942219018936157,
0.3008752167224884,
-0.016682380810379982,
0.23172098398208618,
-0.41760358214378357,
0.2389870434999466,
-0.31163686513900757,
-0.05878400430083275,
-0.34087467193603516,
-0.2117820829153061,
-0.0825006514787674,
-0.565778911113739,
-0.030333183705806732,
-0.033450912684202194,
-0.07007120549678802,
0.03609158471226692,
-0.11940206587314606,
-0.14799292385578156,
-0.10889899730682373,
-0.07129647582769394,
-0.3734090328216553,
-0.4300118386745453,
-0.25979503989219666,
-0.04753976687788963,
0.3729802370071411,
0.23948872089385986,
0.10474350303411484,
-0.012625178322196007,
-0.07535828649997711,
0.00032676197588443756,
-0.4714282155036926,
-0.004124712198972702,
-0.22297047078609467,
0.06794367730617523,
0.18282291293144226,
0.02107103168964386,
-0.030382610857486725,
-0.014437520876526833,
0.36036163568496704,
-0.06673955172300339,
-0.27643465995788574,
0.3501123785972595,
0.06635912507772446,
0.054407998919487,
-0.2934790253639221,
-0.31152215600013733,
0.08216521143913269,
-0.466784805059433,
0.3006454408168793,
-0.09647873044013977,
0.24163854122161865,
0.2114756554365158,
-0.017977159470319748,
0.2288760095834732,
-0.0653318464756012,
0.1617140769958496,
0.18838946521282196,
0.4239365756511688,
0.5407384634017944,
-0.22937588393688202,
-0.3174418807029724,
0.29581257700920105,
-0.03764570504426956,
0.3881964087486267,
0.1468108892440796,
-0.04843839257955551,
0.4057908058166504,
-0.384377658367157,
0.131942018866539,
-0.14741839468479156,
-0.07091417163610458,
0.1809772104024887,
0.2352914959192276,
-0.05996190011501312,
-0.1455630660057068,
0.033156804740428925,
0.21858522295951843,
-0.03075641393661499,
0.24850612878799438,
0.09110978245735168,
0.004534488543868065,
-0.11354295909404755,
0.3820229172706604,
0.30407604575157166,
-0.15708638727664948,
0.26299142837524414,
0.006089884787797928,
-0.06353563070297241,
-0.230089008808136,
-0.27072858810424805,
-0.1288834810256958,
-0.17353969812393188,
0.15583141148090363,
-0.15172062814235687,
0.033583350479602814,
-0.38190969824790955,
-0.031434834003448486,
0.33778005838394165,
-0.18510079383850098,
-0.1455889195203781,
0.2932654917240143,
-0.2784809470176697,
0.23703891038894653,
0.08548419177532196,
0.19006088376045227,
-0.12471485137939453,
-0.40733543038368225,
0.12500068545341492,
-0.0006934851408004761,
0.1178487092256546,
0.036328915506601334,
-0.19866199791431427,
-0.12969739735126495,
-0.4102337658405304,
0.31972992420196533,
0.03993400186300278,
0.36018651723861694,
-0.1612703651189804,
-0.1563730239868164,
0.1840427666902542,
-0.15219661593437195,
0.4350284934043884,
-0.3664802610874176,
-0.05906306952238083,
0.30513784289360046,
0.3421058654785156,
-0.4739355742931366,
0.34191980957984924,
-0.22176426649093628,
0.24682141840457916,
0.1647558957338333,
0.1495353877544403,
-0.32348155975341797,
-0.23489397764205933,
0.17474141716957092,
0.02016613818705082,
0.023735221475362778,
0.17043368518352509,
-0.3350865840911865,
0.02666223794221878,
-0.07697559148073196,
-0.17390739917755127,
0.20773641765117645,
0.24202145636081696,
0.018690072000026703,
0.07589267194271088,
-0.4179534316062927,
0.19375517964363098,
0.2174443006515503,
0.08719144761562347,
0.39977794885635376,
-0.24007312953472137,
0.011527381837368011,
-0.020229674875736237,
0.1994381695985794,
-0.07045424729585648,
0.45299166440963745,
-0.04165391996502876,
-0.17850881814956665,
0.25579360127449036,
-0.08369375020265579,
0.4723662734031677,
0.3834895193576813,
0.08568917214870453,
0.32462573051452637,
-0.27232176065444946,
-0.22830970585346222,
-0.3209863603115082,
0.006949512753635645,
0.04117930680513382,
0.00267807487398386,
0.14303763210773468,
-0.10382363200187683,
0.5234213471412659,
0.24864955246448517,
-0.07634901255369186,
0.5133987665176392,
0.16703101992607117,
-0.3357831835746765,
0.323159396648407,
0.2279377579689026,
1.1573790311813354,
0.058490168303251266,
0.10378345847129822,
-0.058251798152923584,
-0.46720439195632935,
0.44061124324798584,
0.06488735228776932,
0.2514752745628357,
-0.47175145149230957,
0.35401394963264465,
0.004888011142611504,
-0.2005733847618103,
0.04434853419661522,
-0.051942937076091766,
-0.30089566111564636,
0.11113596707582474,
-0.21602872014045715,
0.24487365782260895,
0.09667222946882248,
0.09772033989429474,
-0.3100961744785309,
-0.3052619397640228,
-0.2676105201244354,
0.09327099472284317,
-0.1876256912946701,
-0.007991142570972443,
0.11706545203924179,
-0.2904031276702881,
-0.5326499938964844,
-0.05518368259072304,
-0.08857408165931702,
0.19176533818244934,
-0.1987987458705902,
-0.07285838574171066,
0.25250235199928284,
-0.2095436453819275,
0.23995491862297058,
0.23208938539028168,
0.08816669881343842,
-0.06347925961017609,
-0.17391392588615417,
-0.04728449508547783,
0.29204028844833374,
0.15689215064048767,
0.12021410465240479,
-0.033129528164863586,
0.014185480773448944,
0.10079529136419296,
0.04560539871454239,
0.25179731845855713,
-0.4120064377784729,
0.04076303541660309,
-0.08722396194934845,
0.20695391297340393,
0.09257963299751282,
-0.05611642822623253,
0.058333199471235275,
0.056927867233753204,
-0.05763889104127884,
-0.024936577305197716,
0.10847321152687073,
0.013143669813871384,
0.16904377937316895,
0.03570611774921417,
-0.11537586152553558,
-0.2564198076725006,
0.31084921956062317,
0.31110742688179016,
-0.011715319007635117,
0.26380234956741333,
0.7341855764389038,
0.027994778007268906,
-0.15276385843753815,
-0.19830745458602905,
0.02862986922264099,
-0.02416124939918518,
-0.7314627766609192,
0.3125096559524536,
-0.3160664141178131,
-0.36789238452911377,
0.020079785957932472,
0.5516512989997864,
-0.23535113036632538,
0.1846444010734558,
-0.185321643948555,
-0.2600320875644684,
-0.1918117254972458,
0.2942541241645813,
-0.06804841756820679,
0.0068130940198898315,
-0.4693588614463806,
-0.10694636404514313,
0.029502471908926964,
0.1694573611021042,
-0.2477700561285019,
0.035324156284332275,
-0.11774788051843643,
0.36261871457099915,
-0.046685829758644104,
-0.005117494612932205,
-0.004681721329689026,
-0.25742170214653015,
0.010051561519503593,
0.5666002035140991,
-0.12076975405216217,
-0.1419093906879425,
-0.28333717584609985,
0.14587776362895966,
0.08442181348800659,
-0.1702071577310562,
0.16537953913211823,
-0.017817551270127296,
0.06224697083234787,
-0.2151457965373993,
-0.07266784459352493,
-0.2080886960029602,
-0.18448589742183685,
0.07484998553991318,
-0.021099571138620377,
0.24461886286735535,
-0.2342158854007721,
0.08050147444009781,
-0.07008995115756989,
0.06816443800926208,
-0.3697085678577423,
0.007148392498493195,
-0.014693065546452999,
0.0024236664175987244,
-0.035316575318574905,
0.15229377150535583,
-0.1864626258611679,
-0.11169946938753128,
0.2823203206062317,
-0.2953430414199829,
-0.12911133468151093,
-0.005005622282624245,
-0.19424118101596832,
0.3379955291748047,
-0.15246900916099548,
0.0480976402759552,
-0.04230756685137749,
0.11493928730487823,
0.1366555243730545,
0.35715654492378235,
-0.2620999217033386,
0.021108441054821014,
-0.08318209648132324,
0.27575427293777466,
0.12450669705867767,
-0.22823961079120636,
-0.1093328595161438,
0.06607528775930405,
-0.06436733156442642,
-0.36997437477111816,
-0.13122707605361938,
0.1212930977344513,
-0.1415523886680603,
-0.0027165487408638,
0.3157489597797394,
-0.15956252813339233,
-0.039288513362407684,
-0.002072412520647049,
0.3984375298023224,
0.3103441596031189,
0.5081055760383606,
0.20689107477664948,
0.0034972578287124634,
0.09589074552059174,
0.008702009916305542,
0.24191135168075562,
0.34572988748550415,
0.36158615350723267,
0.2970229983329773,
0.6127428412437439,
-0.3836427628993988,
-0.2681463360786438,
-0.026009079068899155,
0.10279293358325958,
-0.2622458040714264,
-0.1417003720998764,
-0.5835599303245544,
-0.12105023860931396,
-0.44204020500183105,
-0.08055077493190765,
-0.2170771062374115,
0.19709840416908264,
0.5802704095840454,
0.21965691447257996,
-0.04547487199306488,
-0.6290245056152344,
-0.20984312891960144,
0.058179207146167755,
0.5017368197441101,
-0.2239837348461151,
0.45599672198295593,
0.016069352626800537,
-0.05682431161403656,
-0.018257025629281998,
0.5782515406608582,
0.43931031227111816,
0.5464798808097839,
-0.3213457763195038,
-0.013242482207715511,
0.05908244475722313,
-0.17023105919361115,
0.28284281492233276,
0.6259995102882385,
0.37193670868873596,
0.07206597179174423,
0.049773093312978745,
-0.028637081384658813,
-0.09993836283683777,
-0.26097196340560913,
0.021830879151821136,
0.4561338722705841,
-0.009454039856791496,
0.21890728175640106,
-0.29675382375717163,
-0.13070404529571533,
-0.07994214445352554,
-0.24563893675804138,
-0.30123287439346313,
-0.07740287482738495,
0.13583429157733917,
0.01643802411854267,
0.020510993897914886,
-0.34253883361816406,
0.07126212120056152,
0.16037490963935852,
0.5518673062324524,
0.2615603506565094,
0.12667232751846313,
-0.4171103239059448,
-0.11879702657461166,
-0.5855780243873596,
0.2008875161409378,
-0.23853275179862976,
-0.1507560908794403,
-0.09952849894762039,
0.3261135518550873,
0.10537063330411911,
0.24450406432151794,
-0.027682185173034668,
0.20349770784378052,
0.33210206031799316,
0.3179226815700531,
-0.3015897274017334,
-0.06234607473015785,
0.3174629807472229,
-0.3273674547672272,
0.00846301019191742,
-0.5750225186347961,
0.2966243624687195,
0.06786385178565979,
0.06840582191944122,
0.1313176155090332,
-0.301472008228302,
0.20186860859394073,
0.4438701570034027,
0.3714682459831238,
0.2160162627696991,
0.25399476289749146,
0.25643861293792725,
-0.4523237645626068,
-0.26916107535362244,
-0.20937898755073547,
-0.23863396048545837,
0.10153631865978241,
0.10521870851516724,
0.5344887971878052,
-0.08086100220680237,
0.12656208872795105,
-0.25590893626213074,
0.1533980369567871,
-0.17736376821994781,
0.1092863604426384,
-0.2637517750263214,
0.1466660499572754,
-0.3174295723438263,
0.08098757266998291,
0.12022750079631805,
0.12272705882787704,
0.15131545066833496,
0.14416126906871796,
-0.4850180745124817,
-0.4537811875343323,
0.3317626416683197,
-0.3799084722995758,
-0.334623783826828,
0.3907817304134369,
0.21516934037208557,
0.43962419033050537,
-0.1042729839682579,
-0.7881215214729309,
-0.35706236958503723,
0.1472138911485672,
-0.13919532299041748,
-0.050900354981422424,
-0.11611431837081909,
-0.05664430931210518,
-0.005235496908426285,
-0.21112194657325745,
0.3439016342163086,
-0.008731506764888763,
0.0837300568819046,
0.09028655290603638,
-0.16827616095542908
] |
https://github.com/huggingface/datasets/issues/211 | [Arrow writer, Trivia_qa] Could not convert TagMe with type str: converting to null type | Actually, I know what the problem is...I'm quite sure it's a bug. Here we take some test inputs: https://github.com/huggingface/nlp/blob/0e0ef12c14d2175e0b0bd7d8aa814b09e2cd7e1f/src/nlp/arrow_dataset.py#L472
It might be that in the test inputs, a `Sequence` type value is an emtpy list. So in my case I have `ds[0]["entity_pages']["wiki_context"] = []`. => this leads to an `arrow_schema` equal to `null` for `["entity_pages']["wiki_context"]` => see line: https://github.com/huggingface/nlp/blob/0e0ef12c14d2175e0b0bd7d8aa814b09e2cd7e1f/src/nlp/arrow_dataset.py#L501 instead of list of string which it should for other examples.
Guess it's an edge case, but it can happen. | Running the following code
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to null type` error.
On the other hand if we remove a certain column of `trivia_qa` which seems responsible for the bug, it works:
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, remove_columns=["entity_pages"], load_from_cache_file=False)
```
. Seems quite hard to debug what's going on here... @lhoestq @thomwolf - do you have a good first guess what the problem could be?
**Note** BTW: I think this could be a good test to check that the datasets work correctly: Take a tiny portion of the dataset and check that it can be written correctly. | 79 | [Arrow writer, Trivia_qa] Could not convert TagMe with type str: converting to null type
Running the following code
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to null type` error.
On the other hand if we remove a certain column of `trivia_qa` which seems responsible for the bug, it works:
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, remove_columns=["entity_pages"], load_from_cache_file=False)
```
. Seems quite hard to debug what's going on here... @lhoestq @thomwolf - do you have a good first guess what the problem could be?
**Note** BTW: I think this could be a good test to check that the datasets work correctly: Take a tiny portion of the dataset and check that it can be written correctly.
Actually, I know what the problem is...I'm quite sure it's a bug. Here we take some test inputs: https://github.com/huggingface/nlp/blob/0e0ef12c14d2175e0b0bd7d8aa814b09e2cd7e1f/src/nlp/arrow_dataset.py#L472
It might be that in the test inputs, a `Sequence` type value is an emtpy list. So in my case I have `ds[0]["entity_pages']["wiki_context"] = []`. => this leads to an `arrow_schema` equal to `null` for `["entity_pages']["wiki_context"]` => see line: https://github.com/huggingface/nlp/blob/0e0ef12c14d2175e0b0bd7d8aa814b09e2cd7e1f/src/nlp/arrow_dataset.py#L501 instead of list of string which it should for other examples.
Guess it's an edge case, but it can happen. | [
0.09355707466602325,
-0.05218075215816498,
0.09173013269901276,
0.49227476119995117,
0.2525184750556946,
0.1492106020450592,
0.10871350765228271,
0.4077000319957733,
0.1446879804134369,
-0.0935792624950409,
0.3454059362411499,
0.5846510529518127,
-0.12629714608192444,
-0.08148074150085449,
-0.03906689211726189,
-0.18967239558696747,
0.15724416077136993,
0.2686881422996521,
0.08629145473241806,
-0.06003156676888466,
-0.14310383796691895,
0.15054133534431458,
-0.27892497181892395,
0.1321714222431183,
-0.4200155735015869,
-0.10315186530351639,
0.07676132768392563,
0.0571163073182106,
-0.08841769397258759,
-0.45285388827323914,
0.07614743709564209,
-0.3256979286670685,
-0.00657503679394722,
0.2591463327407837,
-0.00012003633310087025,
-0.12074834853410721,
0.41301560401916504,
-0.04033137857913971,
-0.26557812094688416,
-0.24955396354198456,
-0.435833215713501,
0.03188975900411606,
0.33162352442741394,
-0.04249082878232002,
0.18057310581207275,
-0.06374594569206238,
0.02380255237221718,
-0.5875162482261658,
0.20610764622688293,
0.5833624601364136,
0.17648330330848694,
0.2174154371023178,
-0.06840868294239044,
0.130262553691864,
0.29421332478523254,
0.05315934866666794,
-0.33830970525741577,
-0.08270286023616791,
0.022632073611021042,
-0.12178804725408554,
-0.13316559791564941,
0.3214312493801117,
-0.06175166368484497,
0.058570221066474915,
0.6247357726097107,
0.0932791531085968,
0.13128316402435303,
-0.3116700053215027,
0.14749667048454285,
0.14453640580177307,
0.39628151059150696,
-0.08866610378026962,
-0.08990984410047531,
-0.01776956021785736,
-0.1631641685962677,
-0.3528531789779663,
0.2785201370716095,
0.18064822256565094,
-0.29843685030937195,
-0.0033445656299591064,
0.07484915107488632,
0.14837554097175598,
-0.08723288029432297,
-0.06426304578781128,
-0.11870856583118439,
0.15310712158679962,
0.039316605776548386,
0.06686507165431976,
-0.10409830510616302,
-0.20409660041332245,
-0.10837486386299133,
-0.23340731859207153,
-0.2524468004703522,
0.3161037564277649,
-0.4382798671722412,
0.037972576916217804,
-0.0514424592256546,
-0.13796302676200867,
-0.14761598408222198,
0.06295932829380035,
0.38411492109298706,
0.09981708228588104,
0.027438730001449585,
0.0716606080532074,
0.3587127923965454,
0.3659059405326843,
0.31820422410964966,
0.13503791391849518,
0.06323648989200592,
-0.22235745191574097,
-0.08160152286291122,
0.017592262476682663,
0.01670028269290924,
-0.03930993750691414,
0.40901291370391846,
0.009138813242316246,
0.14973634481430054,
-0.33181336522102356,
-0.2487674355506897,
0.058740902692079544,
-0.7114651799201965,
0.2303270548582077,
-0.19834312796592712,
0.09589575976133347,
-0.024717159569263458,
0.5226476788520813,
0.2696346640586853,
0.3240772485733032,
-0.2275407910346985,
-0.10159376263618469,
-0.14699961245059967,
-0.13756303489208221,
-0.24351471662521362,
-0.04535190016031265,
0.21126894652843475,
-0.07352477312088013,
0.16572391986846924,
0.024609260261058807,
-0.4914286732673645,
-0.20295216143131256,
0.26686957478523254,
-0.3210102915763855,
0.17625238001346588,
0.0648171454668045,
-0.32960668206214905,
0.45327848196029663,
0.1861165463924408,
-0.39012306928634644,
-0.18190482258796692,
0.10338769853115082,
-0.19294854998588562,
0.09501944482326508,
-0.15740565955638885,
0.12872956693172455,
0.024879056960344315,
-0.14852550625801086,
-0.30236488580703735,
-0.032280486077070236,
0.3422371447086334,
-0.11202162504196167,
0.15281787514686584,
-0.24676944315433502,
-0.10657308995723724,
-0.2501501142978668,
-0.06317590177059174,
0.40901368856430054,
-0.19291436672210693,
0.08677572011947632,
-0.018419388681650162,
0.14051750302314758,
0.2578383982181549,
0.2855258882045746,
0.016143830493092537,
0.12157110869884491,
0.06346698850393295,
0.39460426568984985,
0.43152397871017456,
-0.27908146381378174,
0.00753962155431509,
0.13285386562347412,
-0.03557674586772919,
-0.01185564324259758,
0.0022213980555534363,
0.106452576816082,
0.033090755343437195,
-0.2236127406358719,
0.10748087614774704,
0.19908706843852997,
-0.06461169570684433,
0.2510938048362732,
-0.4027029275894165,
-0.06630875915288925,
0.49514514207839966,
-0.20197103917598724,
-0.18115761876106262,
-0.05476035922765732,
-0.05374499410390854,
0.1514836549758911,
-0.014162302017211914,
-0.028817620128393173,
0.38277533650398254,
0.3288469910621643,
-0.14390335977077484,
-0.16071803867816925,
0.1006358191370964,
-0.10738269984722137,
-0.46785426139831543,
0.011794470250606537,
-0.18902337551116943,
0.2026108205318451,
-0.08662518858909607,
0.028060778975486755,
-0.3410986661911011,
0.12534892559051514,
-0.10165326297283173,
-0.2273106873035431,
0.14942359924316406,
0.054173775017261505,
0.16102643311023712,
0.14653602242469788,
-0.12235642969608307,
0.11216219514608383,
0.013422539457678795,
0.08212637901306152,
-0.46395158767700195,
-0.08359160274267197,
0.0000034905970096588135,
-0.2866653800010681,
-0.08776189386844635,
0.2652673125267029,
0.27048325538635254,
0.11229990422725677,
-0.2972472012042999,
0.21523022651672363,
0.11378934979438782,
0.27887803316116333,
-0.40211978554725647,
0.07179568707942963,
0.06320392340421677,
-0.42975902557373047,
0.1421480029821396,
0.4353228509426117,
0.36861947178840637,
-0.34248340129852295,
-0.38880297541618347,
-0.04157602787017822,
0.022348709404468536,
0.680326521396637,
-0.13089539110660553,
0.14410719275474548,
-0.03299497812986374,
-0.03734292834997177,
0.07075367867946625,
-0.05491744726896286,
0.16543735563755035,
0.01798594556748867,
0.12332215905189514,
0.3098255395889282,
-0.24867242574691772,
0.29118919372558594,
0.37837231159210205,
0.2824706435203552,
0.11098349094390869,
0.12216784060001373,
-0.385292649269104,
-0.21817061305046082,
0.31259840726852417,
0.025050241500139236,
0.375763863325119,
-0.05269097909331322,
0.18641407787799835,
-0.05416803061962128,
-0.1827584058046341,
-0.17576918005943298,
0.35379332304000854,
-0.05842497944831848,
0.1938471794128418,
0.03641253709793091,
0.5011975765228271,
-0.015893951058387756,
-0.13138148188591003,
0.24980765581130981,
-0.008867017924785614,
0.20772449672222137,
-0.4109279215335846,
0.3374977111816406,
-0.4077056050300598,
-0.13143034279346466,
-0.37055841088294983,
-0.15277180075645447,
-0.02439647540450096,
-0.6165551543235779,
-0.04489489644765854,
-0.018378648906946182,
-0.030627353116869926,
0.12242846935987473,
-0.28436070680618286,
-0.13166259229183197,
0.013293301686644554,
-0.0776517242193222,
-0.4024278521537781,
-0.42999592423439026,
-0.4094288945198059,
-0.04795015603303909,
0.43011704087257385,
0.392078697681427,
0.10363443940877914,
0.03218571096658707,
-0.10713545233011246,
-0.03624807298183441,
-0.412510484457016,
0.03437487781047821,
-0.2577618956565857,
0.09031230211257935,
0.15104316174983978,
0.06090404838323593,
0.01968567818403244,
-0.0868513435125351,
0.32464173436164856,
0.0006716586649417877,
-0.3420940041542053,
0.39525100588798523,
0.053129956126213074,
0.14244522154331207,
-0.3051873445510864,
-0.4616950452327728,
0.039699941873550415,
-0.4655473232269287,
0.1820293664932251,
0.006348218768835068,
0.18158909678459167,
0.23612701892852783,
0.05442696437239647,
0.28018122911453247,
-0.04302285239100456,
0.1691674292087555,
0.19449341297149658,
0.47960275411605835,
0.5730381011962891,
-0.14828313887119293,
-0.36124667525291443,
0.2676405906677246,
-0.13377967476844788,
0.2956109642982483,
0.17932796478271484,
-0.15094295144081116,
0.3191587030887604,
-0.3194129765033722,
0.15346959233283997,
-0.13758273422718048,
-0.12629760801792145,
0.2398141473531723,
0.1834496110677719,
-0.04229190945625305,
-0.10745668411254883,
0.03156432509422302,
0.25976672768592834,
-0.18653300404548645,
0.1925482153892517,
0.1195826455950737,
0.20338138937950134,
-0.0464816614985466,
0.3153981566429138,
0.1880693882703781,
-0.2586812973022461,
0.33788976073265076,
-0.03515106439590454,
-0.008244846016168594,
-0.28940531611442566,
-0.10925959050655365,
-0.08718876540660858,
-0.14598098397254944,
0.15237297117710114,
-0.08302415907382965,
0.07133284211158752,
-0.4544132947921753,
-0.02870737574994564,
0.2991611063480377,
-0.1059684082865715,
-0.14508497714996338,
0.250357985496521,
-0.2715938091278076,
0.2326233685016632,
0.07304367423057556,
0.15341895818710327,
-0.11898380517959595,
-0.5184164047241211,
0.04418310150504112,
-0.031994059681892395,
0.09283921867609024,
-0.020921939983963966,
-0.20190303027629852,
0.017810538411140442,
-0.4196455180644989,
0.28542864322662354,
0.168317511677742,
0.4798279106616974,
-0.04797328636050224,
-0.19165828824043274,
0.1719038486480713,
-0.15335027873516083,
0.3857506513595581,
-0.2743549942970276,
-0.01348680630326271,
0.36245664954185486,
0.36000773310661316,
-0.48109689354896545,
0.26782646775245667,
-0.2580377459526062,
0.26213786005973816,
0.17987318336963654,
0.19627155363559723,
-0.41516295075416565,
-0.30158761143684387,
0.14041119813919067,
0.19144894182682037,
-0.021241571754217148,
0.16336633265018463,
-0.2792511582374573,
-0.023450009524822235,
-0.06628596782684326,
-0.17773979902267456,
0.2659930884838104,
0.3581661880016327,
0.03981295973062515,
-0.0013968013226985931,
-0.433009535074234,
0.11331077665090561,
0.1220482736825943,
0.020940713584423065,
0.4554500877857208,
-0.29696622490882874,
0.12399284541606903,
-0.20001757144927979,
0.16423341631889343,
-0.06789224594831467,
0.34366923570632935,
-0.06636166572570801,
-0.0957203358411789,
0.30548208951950073,
-0.12876884639263153,
0.3905342221260071,
0.3394402861595154,
-0.02647443488240242,
0.3637796938419342,
-0.17648416757583618,
-0.1536535620689392,
-0.2444365918636322,
-0.025315474718809128,
0.14097058773040771,
-0.0874008983373642,
0.10841048508882523,
-0.19618093967437744,
0.5411815643310547,
0.3007131814956665,
-0.03165445849299431,
0.4439757466316223,
0.18964070081710815,
-0.32779401540756226,
0.3507964611053467,
0.21915343403816223,
1.112839698791504,
0.11890722066164017,
0.17537809908390045,
0.08425121009349823,
-0.3473072648048401,
0.4513011574745178,
0.022426187992095947,
0.25419673323631287,
-0.48580291867256165,
0.25739234685897827,
-0.03554876148700714,
-0.1875910460948944,
0.040305718779563904,
0.02434402145445347,
-0.28639018535614014,
0.1932094246149063,
-0.17377714812755585,
0.26287317276000977,
0.12903322279453278,
0.01991180330514908,
-0.2860623300075531,
-0.33544138073921204,
-0.4839944839477539,
0.07514122128486633,
-0.15866316854953766,
-0.0643378347158432,
0.10971181094646454,
-0.2614781856536865,
-0.4933289885520935,
-0.09190820157527924,
-0.1271524727344513,
0.14361169934272766,
-0.24136842787265778,
-0.062289826571941376,
0.25829100608825684,
-0.17976704239845276,
0.22817057371139526,
0.16256220638751984,
-0.04886312782764435,
-0.0574195496737957,
-0.18875814974308014,
-0.11977651715278625,
0.20588132739067078,
0.09073035418987274,
0.1580936759710312,
-0.019870396703481674,
0.14279145002365112,
0.058030568063259125,
0.09111496061086655,
0.2642859220504761,
-0.40775418281555176,
-0.0016342736780643463,
0.06845372915267944,
0.16408002376556396,
0.03515498340129852,
-0.021138448268175125,
-0.12933418154716492,
0.10254503041505814,
-0.01636495254933834,
-0.03418709710240364,
0.0898296982049942,
0.04698125272989273,
0.08257467299699783,
0.05820866674184799,
-0.10640527307987213,
-0.22666838765144348,
0.2634595036506653,
0.3531939685344696,
0.05719932168722153,
0.14272743463516235,
0.7486613988876343,
0.1637575626373291,
-0.1326281875371933,
-0.19221460819244385,
0.08599641174077988,
0.018571345135569572,
-0.7875833511352539,
0.28427761793136597,
-0.27142956852912903,
-0.3222104012966156,
0.03584709018468857,
0.6465661525726318,
-0.23184804618358612,
0.08952032029628754,
-0.16638681292533875,
-0.2611517906188965,
-0.17477571964263916,
0.17243973910808563,
-0.03713047131896019,
0.061161190271377563,
-0.509809136390686,
-0.18457816541194916,
0.10252305865287781,
0.131935253739357,
-0.21777275204658508,
0.0001780930906534195,
-0.2947481870651245,
0.3535666763782501,
-0.01486620306968689,
0.10168533027172089,
0.005318854004144669,
-0.17168745398521423,
-0.004655670374631882,
0.4534410834312439,
-0.1637963354587555,
-0.1482589691877365,
-0.23846150934696198,
0.15354639291763306,
0.11453447490930557,
-0.11689335107803345,
0.06979884952306747,
-0.02155900187790394,
0.0305703766644001,
-0.21219202876091003,
-0.10736984014511108,
-0.2103567123413086,
-0.17519178986549377,
-0.013519302941858768,
0.0763074979186058,
0.26232606172561646,
-0.27176356315612793,
0.12272563576698303,
-0.17236706614494324,
0.07838184386491776,
-0.3097918927669525,
0.02072773315012455,
0.11779609322547913,
0.02143005281686783,
-0.14642228186130524,
0.10597573220729828,
-0.16352449357509613,
-0.2105933129787445,
0.3242960274219513,
-0.3493191599845886,
-0.2074197381734848,
0.04359646514058113,
-0.15914978086948395,
0.39598068594932556,
-0.10549262166023254,
0.002634037286043167,
-0.07950562983751297,
0.0834643617272377,
0.05427968502044678,
0.322162389755249,
-0.19346070289611816,
-0.11521845310926437,
-0.04124796763062477,
0.2851087749004364,
0.1726256161928177,
-0.21538770198822021,
-0.026877500116825104,
0.11490350216627121,
0.02829228714108467,
-0.41845881938934326,
-0.08133640885353088,
0.18888001143932343,
-0.048989567905664444,
0.01914885640144348,
0.26837441325187683,
-0.19589760899543762,
0.02850089967250824,
-0.07040534913539886,
0.43938636779785156,
0.4198613166809082,
0.4042418301105499,
0.16703370213508606,
-0.024891190230846405,
0.08554995059967041,
0.054913394153118134,
0.3567952811717987,
0.34315094351768494,
0.21554216742515564,
0.25422748923301697,
0.5395474433898926,
-0.17617838084697723,
-0.26875847578048706,
-0.05656963586807251,
0.12042126059532166,
-0.22145402431488037,
-0.13927096128463745,
-0.4548976421356201,
-0.15396666526794434,
-0.48004013299942017,
-0.2001102864742279,
-0.16493968665599823,
0.13815337419509888,
0.568152666091919,
0.2202722281217575,
0.04264826327562332,
-0.5250182747840881,
-0.13786688446998596,
0.10644260793924332,
0.3856297731399536,
-0.17447832226753235,
0.46047085523605347,
0.006540074944496155,
-0.0706382691860199,
-0.030537154525518417,
0.42286744713783264,
0.42817622423171997,
0.5327762961387634,
-0.3272397220134735,
-0.06885861605405807,
0.1260795146226883,
-0.16419416666030884,
0.240712970495224,
0.5911158323287964,
0.2477376013994217,
0.06603623181581497,
0.06582185626029968,
-0.05595836788415909,
-0.08274547755718231,
-0.10225661098957062,
-0.022089514881372452,
0.34112438559532166,
-0.12443605065345764,
0.421477735042572,
-0.27773118019104004,
-0.14602136611938477,
-0.10044369101524353,
-0.1861693561077118,
-0.2864457666873932,
0.032042890787124634,
0.10367287695407867,
0.03099707141518593,
0.07790986448526382,
-0.3275088369846344,
0.06784392893314362,
0.18376044929027557,
0.5826796889305115,
0.2241734117269516,
0.10328647494316101,
-0.3924229145050049,
-0.09169905632734299,
-0.7618374824523926,
0.1753283143043518,
-0.2416837513446808,
-0.21087603271007538,
0.10276053845882416,
0.302072137594223,
0.08311302959918976,
0.30485838651657104,
-0.04291003942489624,
0.27844712138175964,
0.252066433429718,
0.28670433163642883,
-0.38265180587768555,
-0.1970774233341217,
0.34452682733535767,
-0.28109580278396606,
-0.052883341908454895,
-0.5603267550468445,
0.23074865341186523,
0.016348760575056076,
0.058767423033714294,
0.03245602548122406,
-0.2147497981786728,
0.18569090962409973,
0.44472193717956543,
0.20759908854961395,
0.18357205390930176,
0.17585764825344086,
0.27285701036453247,
-0.4320273995399475,
-0.3502245247364044,
-0.2179291844367981,
-0.19331367313861847,
0.03420940786600113,
0.03560404106974602,
0.4834500849246979,
-0.16845622658729553,
0.03575201705098152,
-0.27571359276771545,
0.12094943970441818,
-0.13554725050926208,
0.13369105756282806,
-0.2686518430709839,
0.1832183301448822,
-0.41397562623023987,
0.19967903196811676,
0.22928164899349213,
0.022406067699193954,
0.1284518539905548,
0.14924879372119904,
-0.4297788143157959,
-0.49896374344825745,
0.2569379210472107,
-0.4704397916793823,
-0.3264240026473999,
0.28185033798217773,
0.1456383913755417,
0.3511766791343689,
-0.06056024134159088,
-0.740278959274292,
-0.2556817829608917,
0.2354605495929718,
-0.12984564900398254,
0.017962586134672165,
-0.04342929646372795,
-0.0465824231505394,
0.026109915226697922,
-0.23466283082962036,
0.23958729207515717,
0.0006647706031799316,
0.1402987837791443,
0.033131200820207596,
-0.2577146291732788
] |
https://github.com/huggingface/datasets/issues/211 | [Arrow writer, Trivia_qa] Could not convert TagMe with type str: converting to null type | Good point, I think the schema should be infered at the writing stage where we have a `writer_batch_size` number of examples (typically 10k) so it's even less likely to run into this scenario. | Running the following code
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to null type` error.
On the other hand if we remove a certain column of `trivia_qa` which seems responsible for the bug, it works:
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, remove_columns=["entity_pages"], load_from_cache_file=False)
```
. Seems quite hard to debug what's going on here... @lhoestq @thomwolf - do you have a good first guess what the problem could be?
**Note** BTW: I think this could be a good test to check that the datasets work correctly: Take a tiny portion of the dataset and check that it can be written correctly. | 33 | [Arrow writer, Trivia_qa] Could not convert TagMe with type str: converting to null type
Running the following code
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to null type` error.
On the other hand if we remove a certain column of `trivia_qa` which seems responsible for the bug, it works:
```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, remove_columns=["entity_pages"], load_from_cache_file=False)
```
. Seems quite hard to debug what's going on here... @lhoestq @thomwolf - do you have a good first guess what the problem could be?
**Note** BTW: I think this could be a good test to check that the datasets work correctly: Take a tiny portion of the dataset and check that it can be written correctly.
Good point, I think the schema should be infered at the writing stage where we have a `writer_batch_size` number of examples (typically 10k) so it's even less likely to run into this scenario. | [
-0.06821640580892563,
0.06093105673789978,
0.1053825318813324,
0.4737013578414917,
0.2520800828933716,
0.10438019782304764,
0.09826843440532684,
0.3812301754951477,
0.22328925132751465,
-0.06250713765621185,
0.32705157995224,
0.4799831509590149,
-0.08507631719112396,
-0.022185668349266052,
-0.04573952779173851,
-0.1310695856809616,
0.16129447519779205,
0.32369378209114075,
0.06354093551635742,
-0.12184248864650726,
-0.1438349485397339,
0.08432061970233917,
-0.23519453406333923,
0.07620376348495483,
-0.5430987477302551,
-0.16950677335262299,
0.05933573842048645,
0.10318537801504135,
-0.15469522774219513,
-0.4448223412036896,
0.014604160562157631,
-0.2505454123020172,
0.13717079162597656,
0.31009209156036377,
-0.00011774222366511822,
-0.13116741180419922,
0.38236409425735474,
-0.04525517672300339,
-0.21709251403808594,
-0.1553119570016861,
-0.4626956284046173,
0.060809992253780365,
0.26330962777137756,
-0.06844918429851532,
0.19009876251220703,
-0.0022964784875512123,
0.06410683691501617,
-0.4999206066131592,
0.10783122479915619,
0.5157179832458496,
0.2082083821296692,
0.2796901762485504,
-0.01879967376589775,
0.03328923508524895,
0.32798734307289124,
0.021057460457086563,
-0.36564770340919495,
0.0005636103451251984,
-0.028315484523773193,
-0.15549598634243011,
-0.16190847754478455,
0.3987066149711609,
-0.08816113322973251,
0.05234827101230621,
0.6084595322608948,
0.09695272892713547,
0.11834555864334106,
-0.2912595272064209,
0.1959603726863861,
0.12539079785346985,
0.4451828598976135,
-0.10498585551977158,
-0.1137467697262764,
-0.003936167806386948,
-0.134548157453537,
-0.39042460918426514,
0.23909559845924377,
0.19062307476997375,
-0.25099968910217285,
-0.0031804293394088745,
0.05959666147828102,
0.10651848465204239,
-0.03581857308745384,
-0.19298137724399567,
-0.06624897569417953,
0.20389685034751892,
0.06159105896949768,
0.0426708459854126,
-0.10467115044593811,
-0.15812568366527557,
-0.01255903672426939,
-0.23138535022735596,
-0.3124716281890869,
0.2501974403858185,
-0.3363650441169739,
0.042031340301036835,
0.009231436997652054,
-0.10786857455968857,
-0.1433403491973877,
-0.07465694099664688,
0.3727552592754364,
0.023687565699219704,
0.13817401230335236,
0.1114930510520935,
0.3602553904056549,
0.3803686499595642,
0.3734177052974701,
0.13893957436084747,
0.172773540019989,
-0.25541582703590393,
-0.20996034145355225,
-0.018515706062316895,
-0.025886449962854385,
-0.026921186596155167,
0.4833763837814331,
-0.018194954842329025,
0.1269228756427765,
-0.34274405241012573,
-0.2864153981208801,
0.037969790399074554,
-0.6072550415992737,
0.1798172891139984,
-0.216493159532547,
0.1809121072292328,
0.014957142062485218,
0.44045618176460266,
0.1411498636007309,
0.31975412368774414,
-0.2866179943084717,
-0.2129357010126114,
-0.16906782984733582,
-0.06719328463077545,
-0.35299694538116455,
-0.047406695783138275,
0.23163442313671112,
0.025345204398036003,
0.1709941029548645,
0.045751430094242096,
-0.5268831253051758,
-0.19393058121204376,
0.27525487542152405,
-0.33649227023124695,
0.1010013073682785,
0.09800000488758087,
-0.1817556768655777,
0.3801156282424927,
0.15239638090133667,
-0.39502614736557007,
-0.20507794618606567,
0.07577154040336609,
-0.14228400588035583,
-0.014657892286777496,
-0.14263604581356049,
0.16258682310581207,
0.019487731158733368,
-0.22843661904335022,
-0.28548699617385864,
-0.04417174682021141,
0.37683555483818054,
-0.08247704803943634,
0.033103182911872864,
-0.19425195455551147,
-0.07683172076940536,
-0.2546737790107727,
-0.14971096813678741,
0.49143582582473755,
-0.17050649225711823,
0.16371475160121918,
0.052067410200834274,
0.1588343381881714,
0.32009202241897583,
0.34647512435913086,
-0.05128083378076553,
0.23606014251708984,
0.07445212453603745,
0.32859450578689575,
0.4783320128917694,
-0.27670979499816895,
0.05458474159240723,
0.14386886358261108,
-0.04974491149187088,
-0.014119445346295834,
0.0557805560529232,
0.004746994003653526,
0.1131347045302391,
-0.186081200838089,
0.11334642767906189,
0.17492221295833588,
-0.10872144997119904,
0.2992888391017914,
-0.44598719477653503,
-0.049678459763526917,
0.3986054062843323,
-0.2075345367193222,
-0.08162309229373932,
0.059087470173835754,
0.010010667145252228,
0.055392369627952576,
0.017926130443811417,
-0.08591845631599426,
0.3454481363296509,
0.2982359528541565,
-0.12419264018535614,
-0.10706953704357147,
0.08703393489122391,
-0.0994408056139946,
-0.4447139501571655,
0.03243211656808853,
-0.15776506066322327,
0.12304919958114624,
0.05034473165869713,
-0.09754765033721924,
-0.294474333524704,
0.09615029394626617,
-0.03822718933224678,
-0.25051984190940857,
0.15453094244003296,
0.023196179419755936,
0.1731850802898407,
0.05925080552697182,
-0.20210525393486023,
0.0661349892616272,
-0.015744267031550407,
0.10741614550352097,
-0.3512536287307739,
-0.17887350916862488,
-0.04425763338804245,
-0.3509325087070465,
-0.03988923504948616,
0.2398829162120819,
0.23701804876327515,
0.10021079331636429,
-0.2585672438144684,
0.23891958594322205,
-0.0016572964377701283,
0.3618732690811157,
-0.24295124411582947,
0.08757425099611282,
-0.04195791482925415,
-0.26053377985954285,
0.1956302523612976,
0.2751908302307129,
0.35893163084983826,
-0.2975814938545227,
-0.4221460223197937,
-0.006539434194564819,
0.03794514760375023,
0.5811728835105896,
-0.044700462371110916,
0.1357862651348114,
0.03368104249238968,
-0.07959751784801483,
0.13727305829524994,
-0.10519817471504211,
0.17800775170326233,
-0.07357253134250641,
0.06387844681739807,
0.3371363878250122,
-0.2674139440059662,
0.31074604392051697,
0.42854443192481995,
0.2990175485610962,
0.11164859682321548,
0.057120949029922485,
-0.29339706897735596,
-0.13686709105968475,
0.35193371772766113,
0.13247989118099213,
0.4555588364601135,
-0.015705600380897522,
0.20980580151081085,
-0.07270664721727371,
-0.16493405401706696,
-0.20099247992038727,
0.31755495071411133,
-0.14931783080101013,
0.19674572348594666,
0.06621268391609192,
0.45941370725631714,
0.02002319134771824,
-0.21954345703125,
0.21167489886283875,
0.03651811182498932,
0.21878327429294586,
-0.37831512093544006,
0.28381994366645813,
-0.2859777808189392,
-0.0772416889667511,
-0.4313698709011078,
-0.042443785816431046,
-0.046468060463666916,
-0.5650829076766968,
-0.03836654871702194,
0.007924221456050873,
-0.09303827583789825,
0.03654531389474869,
-0.32838574051856995,
-0.11925627291202545,
-0.12170131504535675,
-0.06536591798067093,
-0.2936857044696808,
-0.4041465222835541,
-0.3502984941005707,
-0.05848420411348343,
0.4213869571685791,
0.38563215732574463,
0.1997774988412857,
0.016428174450993538,
-0.005452672950923443,
-0.028151260688900948,
-0.4237631857395172,
0.04701822251081467,
-0.22188512980937958,
0.04329712688922882,
0.16059285402297974,
-0.005856461822986603,
0.05179901421070099,
-0.10299589484930038,
0.3697010576725006,
-0.05113134905695915,
-0.25189265608787537,
0.3521765470504761,
0.02231493405997753,
-0.03763393312692642,
-0.26293817162513733,
-0.4058386981487274,
0.11667194962501526,
-0.5667976140975952,
0.10078822076320648,
-0.04693658649921417,
0.20174640417099,
0.171672061085701,
0.08207504451274872,
0.2255024015903473,
-0.06525570154190063,
0.19515232741832733,
0.2803915739059448,
0.37839382886886597,
0.5403062105178833,
-0.22598065435886383,
-0.32307562232017517,
0.29508623480796814,
-0.1108960509300232,
0.3608185052871704,
0.23071272671222687,
-0.1520203948020935,
0.4052870571613312,
-0.4103546440601349,
0.17004787921905518,
-0.0837431252002716,
-0.11723372340202332,
0.31236863136291504,
0.19045503437519073,
-0.06837323307991028,
-0.09682268649339676,
0.017994578927755356,
0.21361678838729858,
-0.20148390531539917,
0.1650698333978653,
0.008490161970257759,
0.199805349111557,
-0.10333198308944702,
0.3400725722312927,
0.12449967861175537,
-0.1656520813703537,
0.3614374101161957,
0.01160019263625145,
0.012079384177923203,
-0.25102946162223816,
-0.14403466880321503,
0.019972141832113266,
-0.21486935019493103,
0.06162186712026596,
-0.04792577028274536,
0.056543897837400436,
-0.4713309407234192,
-0.034646663814783096,
0.23681128025054932,
-0.14764034748077393,
-0.16390953958034515,
0.322564959526062,
-0.3387589156627655,
0.2803706228733063,
0.09475952386856079,
0.1365748643875122,
-0.11946560442447662,
-0.4064585566520691,
0.023601878434419632,
-0.05851206183433533,
0.1087665855884552,
-0.016414202749729156,
-0.26465630531311035,
0.0026100880932062864,
-0.534706175327301,
0.24957682192325592,
0.05217341333627701,
0.39608776569366455,
-0.04335755109786987,
-0.18558365106582642,
0.18215234577655792,
-0.22928622364997864,
0.40755343437194824,
-0.3126874268054962,
0.018774807453155518,
0.2859611511230469,
0.2986101806163788,
-0.4982847571372986,
0.18487998843193054,
-0.2240564525127411,
0.330209344625473,
0.22574888169765472,
0.18554359674453735,
-0.37205302715301514,
-0.32857340574264526,
0.22981742024421692,
0.04473920911550522,
-0.0006509236991405487,
0.10367845743894577,
-0.35246750712394714,
-0.05329139903187752,
-0.06974142789840698,
-0.14215591549873352,
0.2665811777114868,
0.3564813733100891,
-0.07092612981796265,
0.0079500712454319,
-0.4361250102519989,
0.1583191156387329,
0.15794898569583893,
0.13093774020671844,
0.3880293667316437,
-0.3398948907852173,
0.12485630810260773,
-0.16583502292633057,
0.19165833294391632,
-0.04550173133611679,
0.42883315682411194,
-0.2038113921880722,
-0.1900620460510254,
0.3096029460430145,
-0.174551859498024,
0.48622891306877136,
0.37902361154556274,
0.0421503409743309,
0.31145578622817993,
-0.2637413740158081,
-0.17829649150371552,
-0.2773716449737549,
-0.043513596057891846,
0.13077571988105774,
-0.08891058713197708,
0.09123104065656662,
-0.23243579268455505,
0.5531400442123413,
0.30162313580513,
-0.05554824322462082,
0.4027084708213806,
0.18881957232952118,
-0.35648322105407715,
0.4658268094062805,
0.2532043159008026,
1.1186977624893188,
0.10575829446315765,
0.22237133979797363,
0.025404172018170357,
-0.40893757343292236,
0.35305461287498474,
-0.03306626155972481,
0.2725175619125366,
-0.49555620551109314,
0.2272232323884964,
0.027789248153567314,
-0.1229366809129715,
0.07964393496513367,
0.05283215641975403,
-0.27910733222961426,
0.15774770081043243,
-0.1973516345024109,
0.3361303210258484,
0.07588654011487961,
0.12650950253009796,
-0.4026109278202057,
-0.34524786472320557,
-0.48598968982696533,
0.08268747478723526,
-0.083915576338768,
-0.08008445799350739,
0.026806198060512543,
-0.2240903526544571,
-0.40694770216941833,
-0.13697338104248047,
-0.13860897719860077,
0.13444149494171143,
-0.15800276398658752,
-0.11935241520404816,
0.2568897604942322,
-0.154481440782547,
0.1984211951494217,
0.22811612486839294,
0.0449160672724247,
-0.050611916929483414,
-0.16760903596878052,
-0.014997154474258423,
0.27013760805130005,
0.11929114162921906,
0.14295688271522522,
-0.027162950485944748,
0.0714477002620697,
0.04230794310569763,
0.08588605374097824,
0.2309129536151886,
-0.4100569188594818,
0.011083267629146576,
-0.12113723158836365,
0.20614740252494812,
-0.023422762751579285,
-0.13388662040233612,
-0.08782537281513214,
0.11561565101146698,
-0.034164153039455414,
-0.08314493298530579,
0.11682294309139252,
0.02967080846428871,
0.11227241158485413,
0.09994056075811386,
-0.15056638419628143,
-0.2468956857919693,
0.22061574459075928,
0.3188552260398865,
0.05649012699723244,
0.23681804537773132,
0.6745470762252808,
0.08035561442375183,
-0.14073994755744934,
-0.23257210850715637,
0.04807336628437042,
0.051203567534685135,
-0.7669647932052612,
0.33888331055641174,
-0.2679664194583893,
-0.40249454975128174,
0.13678410649299622,
0.5917763113975525,
-0.1855551302433014,
0.013741280883550644,
-0.09446403384208679,
-0.2665630280971527,
-0.09995357692241669,
0.19291746616363525,
0.03185880184173584,
0.07356494665145874,
-0.4767534136772156,
-0.12634290754795074,
0.07701265066862106,
0.22448205947875977,
-0.2680851221084595,
-0.04891285300254822,
-0.23274098336696625,
0.37962889671325684,
0.014470759779214859,
0.08027612417936325,
-0.0298212468624115,
-0.15083584189414978,
-0.006759891286492348,
0.4313046336174011,
-0.14375334978103638,
-0.151163250207901,
-0.27181369066238403,
0.1370278000831604,
0.07310191541910172,
-0.02483992651104927,
0.1579185277223587,
0.029813691973686218,
-0.01240551471710205,
-0.2556418180465698,
-0.0019757207483053207,
-0.1860363781452179,
-0.2229127734899521,
-0.028440099209547043,
0.05852131545543671,
0.2825692296028137,
-0.2086717188358307,
0.12727847695350647,
-0.1877681314945221,
0.07987599074840546,
-0.33941370248794556,
0.07165061682462692,
0.07958433032035828,
0.015731222927570343,
0.03195758908987045,
0.09080922603607178,
-0.14252540469169617,
-0.07515721768140793,
0.31408578157424927,
-0.3454221487045288,
-0.10453855246305466,
0.11357147991657257,
-0.11710676550865173,
0.3987210690975189,
-0.08429927378892899,
0.014218473806977272,
-0.026213794946670532,
0.13289308547973633,
0.07714072614908218,
0.257689893245697,
-0.2710583806037903,
-0.12639226019382477,
-0.05107753723859787,
0.30452218651771545,
0.17767737805843353,
-0.21350863575935364,
-0.04058536887168884,
0.12846454977989197,
0.05426420271396637,
-0.3916771411895752,
-0.14858072996139526,
0.08976948261260986,
-0.09947685152292252,
0.007058609277009964,
0.33671271800994873,
-0.11197775602340698,
0.021539010107517242,
0.08279454708099365,
0.49896591901779175,
0.4582202136516571,
0.39912155270576477,
0.16864843666553497,
-0.11093109101057053,
-0.001728832721710205,
0.021545136347413063,
0.31710419058799744,
0.31534647941589355,
0.3045441806316376,
0.15489012002944946,
0.5104095935821533,
-0.3058182895183563,
-0.26720643043518066,
-0.09200514853000641,
0.06214548274874687,
-0.2543644905090332,
-0.14574915170669556,
-0.5064579248428345,
-0.14190487563610077,
-0.42316168546676636,
-0.10091476142406464,
-0.1865212768316269,
0.2660888731479645,
0.5050715208053589,
0.17831434309482574,
0.0029863715171813965,
-0.5828507542610168,
-0.056132711470127106,
0.031109150499105453,
0.3965829312801361,
-0.24684061110019684,
0.501538097858429,
-0.03485250473022461,
-0.09850385785102844,
-0.09822677075862885,
0.5166679620742798,
0.46027395129203796,
0.6580979228019714,
-0.27573996782302856,
-0.07016037404537201,
0.07553207874298096,
-0.1338510811328888,
0.15214858949184418,
0.5606761574745178,
0.3276126980781555,
0.15973082184791565,
0.11919431388378143,
-0.03441876545548439,
-0.09463390707969666,
-0.11874830722808838,
-0.03437354043126106,
0.2678053081035614,
-0.09244757890701294,
0.35593241453170776,
-0.15395544469356537,
-0.2433713674545288,
-0.08671636879444122,
-0.15515628457069397,
-0.28839296102523804,
-0.05635576695203781,
0.13199466466903687,
-0.0714786946773529,
0.05464477092027664,
-0.4272519052028656,
0.07915197312831879,
0.20936818420886993,
0.6322185397148132,
0.2378581017255783,
0.16091462969779968,
-0.4584116041660309,
-0.07986677438020706,
-0.7588373422622681,
0.1408190131187439,
-0.39341655373573303,
-0.1612657904624939,
0.026848401874303818,
0.35101792216300964,
-0.014347352087497711,
0.2293814867734909,
-0.05591113865375519,
0.32126232981681824,
0.17826001346111298,
0.2982586920261383,
-0.3454146683216095,
-0.17916637659072876,
0.2205488085746765,
-0.34437063336372375,
-0.049058496952056885,
-0.6017604470252991,
0.32700303196907043,
0.050085149705410004,
0.08173493295907974,
-0.0072828978300094604,
-0.2222326546907425,
0.3362940847873688,
0.2882280945777893,
0.32577580213546753,
0.16702570021152496,
0.2884238064289093,
0.19261911511421204,
-0.45870640873908997,
-0.39807483553886414,
-0.19980329275131226,
-0.30666303634643555,
-0.09984276443719864,
0.13190922141075134,
0.469083696603775,
-0.17963804304599762,
0.11805972456932068,
-0.2406577318906784,
0.25994157791137695,
-0.10598036646842957,
0.1154140830039978,
-0.15053386986255646,
0.13514043390750885,
-0.3236255943775177,
0.11830688267946243,
0.2612653076648712,
0.16057133674621582,
0.1331453025341034,
0.1277531236410141,
-0.47373223304748535,
-0.4435843527317047,
0.28088921308517456,
-0.3823678195476532,
-0.38338327407836914,
0.25261789560317993,
0.22172556817531586,
0.3979001045227051,
-0.09128394722938538,
-0.7310698628425598,
-0.3031177520751953,
0.13606199622154236,
-0.08944415301084518,
0.0044166408479213715,
0.06323646008968353,
0.07703427970409393,
-0.0773245319724083,
-0.21661366522312164,
0.28396859765052795,
-0.055230170488357544,
0.026483627036213875,
0.05415119603276253,
-0.25348347425460815
] |
https://github.com/huggingface/datasets/issues/207 | Remove test set from NLP viewer | Appears that [two thirds of those polled on Twitter](https://twitter.com/srush_nlp/status/1265734497632477185) are in favor of _some_ mechanism for averting eyeballs from the test data. | While the new [NLP viewer](https://huggingface.co/nlp/viewer/) is a great tool, I think it would be best to outright remove the option of looking at the test sets. At the very least, a warning should be displayed to users before showing the test set. Newcomers to the field might not be aware of best practices, and small things like this can help increase awareness. | 22 | Remove test set from NLP viewer
While the new [NLP viewer](https://huggingface.co/nlp/viewer/) is a great tool, I think it would be best to outright remove the option of looking at the test sets. At the very least, a warning should be displayed to users before showing the test set. Newcomers to the field might not be aware of best practices, and small things like this can help increase awareness.
Appears that [two thirds of those polled on Twitter](https://twitter.com/srush_nlp/status/1265734497632477185) are in favor of _some_ mechanism for averting eyeballs from the test data. | [
-0.13736289739608765,
0.17048227787017822,
-0.1900717169046402,
-0.2922053933143616,
-0.17911425232887268,
0.044915564358234406,
0.2525577247142792,
0.5567147731781006,
0.055269014090299606,
0.05124489217996597,
0.014377285726368427,
0.17538653314113617,
-0.3614470660686493,
0.08514592051506042,
0.07604803889989853,
0.1644962877035141,
-0.30261021852493286,
0.5070188045501709,
-0.1310981959104538,
0.1275256872177124,
-0.22304917871952057,
-0.20796175301074982,
0.0001344829797744751,
0.24395689368247986,
0.18622954189777374,
-0.39478161931037903,
0.18797406554222107,
-0.16565582156181335,
-0.019231760874390602,
-0.5875657796859741,
-0.10718861222267151,
0.20037740468978882,
-0.17094139754772186,
-0.11505144089460373,
-0.00009701006638351828,
0.0429435595870018,
0.16814804077148438,
0.12773200869560242,
-0.289050430059433,
0.10696420818567276,
-0.12031254917383194,
-0.05883173644542694,
0.2786576449871063,
-0.13759134709835052,
-0.08296464383602142,
-0.22412899136543274,
0.1421549767255783,
-0.22430917620658875,
0.10305432975292206,
0.3524733781814575,
0.3387940526008606,
0.3524862229824066,
-0.30852365493774414,
0.43407294154167175,
0.13730277121067047,
-0.011704564094543457,
-0.27527016401290894,
0.04518921300768852,
0.03301137313246727,
0.015701495110988617,
-0.39855605363845825,
0.5405020117759705,
-0.06409768760204315,
-0.007953528314828873,
-0.038286879658699036,
-0.17734374105930328,
0.3933626711368561,
-0.2694503664970398,
-0.30618664622306824,
0.0869026929140091,
0.1984504759311676,
-0.19477087259292603,
-0.06235070526599884,
-0.41920164227485657,
0.23830965161323547,
0.04672989994287491,
0.09231428802013397,
0.2671627700328827,
-0.05867631360888481,
0.23186297714710236,
-0.5527652502059937,
-0.41144225001335144,
-0.1109342873096466,
0.0838954895734787,
0.14198283851146698,
-0.10454480350017548,
0.08363662660121918,
-0.05657775700092316,
0.3543230891227722,
-0.08692210912704468,
0.17274439334869385,
-0.05581090599298477,
-0.2580600678920746,
0.014445632696151733,
-0.005055133253335953,
-0.5017728805541992,
0.0999649241566658,
-0.01905730366706848,
-0.03359732776880264,
0.20497824251651764,
0.08029212802648544,
0.10392996668815613,
-0.20463961362838745,
0.06354296207427979,
0.10912415385246277,
0.12340101599693298,
0.35100409388542175,
0.062386415898799896,
0.2597549855709076,
0.24740107357501984,
0.2432093620300293,
0.30436408519744873,
0.33762866258621216,
-0.251872718334198,
-0.2752167880535126,
0.12666171789169312,
0.354028582572937,
-0.23466157913208008,
-0.3460922837257385,
0.003445904701948166,
-0.5296180248260498,
0.014234960079193115,
0.014480089768767357,
0.10928130894899368,
-0.0006174850277602673,
0.12058684229850769,
0.03531207889318466,
0.03173815459012985,
-0.3619564175605774,
-0.35781922936439514,
-0.0544237419962883,
0.10798418521881104,
-0.09068240970373154,
0.11934177577495575,
0.4057035446166992,
0.04340828210115433,
0.16046184301376343,
-0.0342019721865654,
0.09332332015037537,
0.04058919847011566,
0.3698306381702423,
0.024624507874250412,
0.346337229013443,
-0.05756784602999687,
-0.1173800528049469,
-0.21008704602718353,
-0.2158709615468979,
-0.14201414585113525,
-0.18773341178894043,
0.15288540720939636,
0.09354298561811447,
-0.20848321914672852,
0.05266881734132767,
0.3505091369152069,
-0.4395666718482971,
-0.014217622578144073,
0.09178121387958527,
0.234715074300766,
-0.3213294446468353,
-0.04506167769432068,
0.14012736082077026,
-0.17458771169185638,
-0.13457608222961426,
0.07385968416929245,
-0.17334511876106262,
0.29054293036460876,
-0.09705110639333725,
-0.08341526985168457,
-0.03997647017240524,
-0.09570494294166565,
-0.207576185464859,
-0.02417227253317833,
-0.4004930555820465,
0.17513087391853333,
-0.20396791398525238,
-0.06718962639570236,
0.36196768283843994,
-0.2131473869085312,
-0.10236697643995285,
0.20034706592559814,
-0.23160767555236816,
0.016960090026259422,
-0.14347735047340393,
0.07153680175542831,
-0.16221846640110016,
-0.4502266049385071,
-0.47924771904945374,
0.07163726538419724,
0.060160815715789795,
0.14337174594402313,
-0.44935938715934753,
-0.4256094694137573,
0.49176400899887085,
0.045784737914800644,
-0.05306442454457283,
-0.13597598671913147,
-0.1581975519657135,
0.25878408551216125,
0.43748700618743896,
0.028907788917422295,
-0.039323121309280396,
-0.23834066092967987,
0.20831498503684998,
-0.3265897035598755,
-0.2815675735473633,
0.007924303412437439,
-0.1326737105846405,
-0.16728752851486206,
-0.08347122371196747,
0.1869812160730362,
0.42072296142578125,
-0.28292417526245117,
-0.0900668129324913,
-0.09678641706705093,
-0.15172302722930908,
-0.09776139259338379,
0.29000505805015564,
-0.1413697898387909,
-0.09831617772579193,
0.1374543309211731,
0.09653125703334808,
-0.15791693329811096,
-0.17216792702674866,
0.03815504163503647,
0.02072005905210972,
-0.17654575407505035,
-0.05305419862270355,
0.10111168771982193,
0.3118337094783783,
0.3026479482650757,
0.07121899724006653,
0.06072896346449852,
0.07649918645620346,
0.17240792512893677,
0.06634168326854706,
0.10490579158067703,
0.2324661910533905,
0.2782416343688965,
0.07447272539138794,
-0.44166046380996704,
-0.014351686462759972,
0.1355339139699936,
-0.151292085647583,
0.23665392398834229,
-0.31678566336631775,
0.2563723921775818,
0.16144399344921112,
-0.07265856117010117,
0.0031079649925231934,
-0.029503941535949707,
0.04893171787261963,
-0.3398032486438751,
-0.13817624747753143,
-0.337873250246048,
-0.026473138481378555,
0.2268938571214676,
-0.18623097240924835,
0.23691917955875397,
-0.33784234523773193,
0.17116916179656982,
0.09643452614545822,
-0.015973366796970367,
-0.0260864719748497,
0.10548362880945206,
0.20493507385253906,
-0.35236141085624695,
0.23605813086032867,
0.07625585794448853,
0.10919326543807983,
0.3495016396045685,
0.22472359240055084,
0.17186972498893738,
-0.21009546518325806,
-0.27264276146888733,
0.3151495158672333,
0.3302733898162842,
0.2265135943889618,
-0.024842336773872375,
0.24631303548812866,
-0.166645348072052,
-0.2424010932445526,
0.07095293700695038,
-0.10728862881660461,
-0.05060543864965439,
-0.3737708628177643,
0.02483482100069523,
-0.1493522822856903,
-0.5540044903755188,
-0.1692960262298584,
0.19525045156478882,
-0.0923478901386261,
-0.25069016218185425,
0.5380775332450867,
-0.028283800929784775,
-0.3674883246421814,
0.2202185094356537,
-0.2902728021144867,
0.6584694981575012,
-0.20973871648311615,
0.22307725250720978,
-0.06582289189100266,
-0.020816585049033165,
-0.36914482712745667,
0.30891114473342896,
0.17983661592006683,
0.060834262520074844,
0.522704541683197,
0.10138292610645294,
-0.17568466067314148,
-0.1762026697397232,
-0.27201029658317566,
0.08650858700275421,
-0.03296918421983719,
0.3253641426563263,
-0.0012542828917503357,
-0.1657099574804306,
-0.04760973900556564,
-0.14837469160556793,
-0.4186188578605652,
-0.22404444217681885,
-0.00045916810631752014,
-0.15232473611831665,
0.14578016102313995,
0.38489559292793274,
-0.24102428555488586,
-0.46456465125083923,
0.0017172731459140778,
-0.2199234515428543,
0.020160745829343796,
-0.014971038326621056,
0.2074323296546936,
0.20418484508991241,
-0.26563623547554016,
0.0050034308806061745,
-0.14018674194812775,
-0.05355343222618103,
-0.11937104165554047,
0.04450136795639992,
0.01233486458659172,
-0.27020204067230225,
-0.28076624870300293,
0.019245881587266922,
-0.2571013271808624,
0.1463606357574463,
-0.1737016886472702,
-0.6786444783210754,
-0.32688552141189575,
0.18293766677379608,
-0.09719103574752808,
-0.045817092061042786,
-0.5455358624458313,
-0.11407436430454254,
0.17513547837734222,
-0.2621878385543823,
0.1255512535572052,
0.08653382956981659,
0.25623390078544617,
0.00540316104888916,
0.14536041021347046,
-0.10717704147100449,
-0.10614816099405289,
0.267967164516449,
0.15631680190563202,
0.2747737765312195,
0.11752210557460785,
-0.007231287658214569,
0.0892392173409462,
0.26060837507247925,
-0.008756168186664581,
-0.035113535821437836,
0.04626890644431114,
0.12895257771015167,
0.015699461102485657,
0.33214300870895386,
-0.11922281235456467,
-0.313361257314682,
0.05188624560832977,
0.08164504170417786,
-0.2134508490562439,
-0.4037645161151886,
0.14978067576885223,
-0.40173640847206116,
0.13901287317276,
0.12182234227657318,
0.04311314970254898,
0.06124310567975044,
-0.5748977065086365,
0.05878446623682976,
-0.19712994992733002,
0.2268815040588379,
-0.06648248434066772,
-0.20710493624210358,
-0.013696662150323391,
-0.2750268280506134,
-0.011230707168579102,
0.14623209834098816,
0.3845880925655365,
0.010643396526575089,
-0.2336488664150238,
0.24429184198379517,
0.1683444231748581,
0.21813812851905823,
0.06173047423362732,
0.20189140737056732,
0.13025835156440735,
-0.12362942099571228,
-0.3014462888240814,
0.1879303902387619,
-0.21928927302360535,
-0.09623371809720993,
0.15762069821357727,
-0.027110785245895386,
0.02971985936164856,
-0.24706478416919708,
0.36989444494247437,
0.12154660373926163,
-0.23160691559314728,
0.024665754288434982,
-0.013284511864185333,
0.010629601776599884,
-0.037181828171014786,
0.2463870644569397,
-0.1701396256685257,
-0.02812224254012108,
-0.36340099573135376,
-0.10158498585224152,
-0.024530136957764626,
-0.20282796025276184,
0.37643951177597046,
0.28827911615371704,
-0.01591498777270317,
0.2726737856864929,
0.0973345935344696,
0.21220341324806213,
0.039156991988420486,
-0.19112005829811096,
0.1898479163646698,
0.247857928276062,
0.3424505591392517,
-0.04484070837497711,
-0.20925547182559967,
0.34741029143333435,
0.41228631138801575,
0.13903403282165527,
0.0013980045914649963,
-0.3875180780887604,
0.057237036526203156,
-0.2808181643486023,
0.2900629937648773,
0.07467538118362427,
-0.174647718667984,
0.053832121193408966,
-0.12565749883651733,
0.24363866448402405,
-0.1218833178281784,
-0.3639516234397888,
0.000638376921415329,
0.11595022678375244,
-0.18264447152614594,
0.20929919183254242,
0.4568058252334595,
0.7854485511779785,
0.04531314969062805,
0.19970180094242096,
0.47228047251701355,
-0.15780213475227356,
0.43638378381729126,
-0.15434899926185608,
0.2508730888366699,
-0.13412988185882568,
0.09534639865159988,
0.05953202396631241,
-0.11783868074417114,
0.11199340224266052,
0.20780609548091888,
0.002054903656244278,
0.0006368251051753759,
0.26226550340652466,
-0.35835036635398865,
-0.1193864494562149,
0.32153481245040894,
0.04634018987417221,
-0.021235276013612747,
-0.30379799008369446,
0.2726384997367859,
-0.16115741431713104,
-0.20504175126552582,
0.10787323862314224,
0.028086042031645775,
0.3095525801181793,
0.04540547728538513,
0.18522445857524872,
0.13581514358520508,
0.11219034343957901,
0.1330631673336029,
-0.13726158440113068,
-0.18840216100215912,
0.39658981561660767,
0.23549309372901917,
-0.17092248797416687,
0.12436376512050629,
-0.08929335325956345,
-0.012547902762889862,
-0.1636733114719391,
0.29650095105171204,
0.2138882428407669,
0.2833039164543152,
0.3150736391544342,
-0.19931212067604065,
-0.1702399104833603,
0.26491525769233704,
0.19701620936393738,
0.05972404032945633,
-0.08262807130813599,
-0.0058592259883880615,
0.2142532765865326,
-0.47217684984207153,
0.03237347677350044,
0.039203714579343796,
0.11395150423049927,
-0.1505127102136612,
0.28724610805511475,
0.04401278495788574,
-0.03829532116651535,
0.043228570371866226,
0.3496764302253723,
-0.23045490682125092,
0.10065092146396637,
0.05798114836215973,
0.09893631935119629,
0.10476025938987732,
0.43976637721061707,
-0.16813921928405762,
-0.24870668351650238,
-0.4134778082370758,
0.25973135232925415,
-0.12139610201120377,
-0.2759031653404236,
0.1033058911561966,
0.12412773072719574,
-0.05992032587528229,
-0.036587972193956375,
0.2192913293838501,
-0.10416138172149658,
-0.006942488253116608,
-0.09856215864419937,
0.004728846251964569,
0.002826118841767311,
0.16214457154273987,
-0.13531595468521118,
0.2648948132991791,
0.23671147227287292,
0.1758655607700348,
-0.07974191009998322,
0.16821028292179108,
-0.45865800976753235,
-0.2357047200202942,
-0.3629606366157532,
0.16979244351387024,
-0.33876797556877136,
0.16333013772964478,
0.025976408272981644,
0.0013712691143155098,
0.131124347448349,
-0.2586054801940918,
-0.23900258541107178,
-0.3924419581890106,
-0.11555568873882294,
0.0577705055475235,
-0.014545109122991562,
-0.1714857965707779,
0.020736847072839737,
0.011869490146636963,
0.10929164290428162,
0.05694784224033356,
-0.11095632612705231,
-0.36126941442489624,
0.18716436624526978,
0.654991865158081,
-0.22639794647693634,
-0.37684378027915955,
0.04805293679237366,
0.0021645687520503998,
-0.3364020586013794,
0.1804552525281906,
0.19234485924243927,
0.2569877505302429,
0.07886850833892822,
-0.07736150175333023,
0.09211748093366623,
0.14207780361175537,
-0.0038993731141090393,
0.2430170774459839,
-0.22079411149024963,
0.05613260716199875,
0.016851454973220825,
-0.029933013021945953,
-0.025893239304423332,
-0.027973540127277374,
-0.30157986283302307,
-0.29457831382751465,
0.2904887795448303,
0.3381895124912262,
-0.3103622794151306,
0.027729328721761703,
0.32519036531448364,
0.048447202891111374,
0.07958593964576721,
0.2135290503501892,
0.08040469884872437,
0.029684752225875854,
0.29514917731285095,
0.0309763140976429,
-0.00004234188236296177,
-0.3247302174568176,
0.08860582113265991,
0.16464705765247345,
-0.41913896799087524,
-0.2750462591648102,
0.12339773774147034,
0.12206247448921204,
0.17781221866607666,
-0.01930566132068634,
0.19298282265663147,
0.6014686822891235,
-0.04290518909692764,
0.3327934443950653,
-0.029134601354599,
-0.04987681284546852,
-0.06779876351356506,
0.006361827254295349,
-0.1729620099067688,
0.08005881309509277,
0.37211331725120544,
0.37689298391342163,
0.2283657193183899,
-0.12036129087209702,
-0.06467597186565399,
0.04856038838624954,
0.017171749845147133,
0.17235639691352844,
-0.27359190583229065,
0.11902842670679092,
-0.09038843214511871,
0.13026049733161926,
0.07079996168613434,
-0.2096400409936905,
0.10960590839385986,
0.11861185729503632,
-0.10826557874679565,
-0.10142333060503006,
0.1704074740409851,
-0.036531589925289154,
0.2522592842578888,
-0.09298397600650787,
-0.19044820964336395,
-0.0768471509218216,
0.3444373309612274,
0.1669951230287552,
0.3699305057525635,
-0.14906473457813263,
-0.18440492451190948,
-0.02608916535973549,
-0.18871204555034637,
-0.09965525567531586,
-0.009150639176368713,
-0.3066669702529907,
0.2665650248527527,
0.07575131207704544,
0.1416868269443512,
0.25459739565849304,
0.21736104786396027,
-0.09045848995447159,
0.0599961057305336,
0.3468180298805237,
-0.22026780247688293,
-0.26668524742126465,
0.26403459906578064,
0.5363548994064331,
-0.33223026990890503,
-0.06163088232278824,
-0.11595634371042252,
0.05984329432249069,
0.10731910169124603,
0.27525317668914795,
-0.24124692380428314,
0.09731181710958481,
-0.2812128961086273,
0.15977293252944946,
0.27768322825431824,
0.43047958612442017,
0.0057656243443489075,
0.1721988022327423,
-0.09262100607156754,
-0.07269566506147385,
-0.5211904644966125,
0.18362881243228912,
0.22089821100234985,
-0.14337538182735443,
0.259044885635376,
-0.026720775291323662,
-0.18254798650741577,
0.2621276378631592,
-0.3430914878845215,
0.19633996486663818,
-0.03144615888595581,
-0.22313153743743896,
-0.2514569163322449,
0.035640161484479904,
-0.03186886012554169,
0.2519475817680359,
-0.1788475662469864,
-0.10400594770908356,
0.20293313264846802,
-0.18828251957893372,
0.15878048539161682,
0.06955939531326294,
0.08495213091373444,
0.14256064593791962,
0.28576359152793884,
0.281242311000824,
0.1692962348461151,
0.12046939134597778,
-0.03955983370542526,
0.09596652537584305,
0.000599101185798645,
-0.018906811252236366,
-0.18427985906600952,
-0.2055191695690155,
0.09908117353916168,
0.19717489182949066,
-0.0958147719502449,
0.27070245146751404,
0.12599588930606842,
0.1675502359867096,
-0.02738126367330551,
0.22046245634555817,
-0.11364427953958511,
0.1647748202085495,
0.032816462218761444,
0.2928231358528137,
-0.1284547597169876,
0.22897553443908691,
-0.09584259986877441,
-0.14297911524772644,
-0.07893221825361252,
-0.19231939315795898,
0.25615233182907104,
-0.2987458407878876,
-0.04730776697397232,
0.028888415545225143,
0.372744083404541,
0.00969204306602478,
-0.31185051798820496,
-0.45354217290878296,
-0.2849319577217102,
0.24580822885036469,
-0.08283773809671402,
0.24263238906860352,
0.44049474596977234,
-0.11160415410995483,
-0.14189913868904114,
-0.08976626396179199,
0.3100309371948242,
0.0736428052186966,
0.13642023503780365,
0.07103091478347778,
-0.3468834161758423
] |
https://github.com/huggingface/datasets/issues/206 | [Question] Combine 2 datasets which have the same columns | We are thinking about ways to combine datasets for T5 in #217, feel free to share your thoughts about this. | Hi,
I am using ``nlp`` to load personal datasets. I created summarization datasets in multi-languages based on wikinews. I have one dataset for english and one for german (french is getting to be ready as well). I want to keep these datasets independent because they need different pre-processing (add different task-specific prefixes for T5 : *summarize:* for english and *zusammenfassen:* for german)
My issue is that I want to train T5 on the combined english and german datasets to see if it improves results. So I would like to combine 2 datasets (which have the same columns) to make one and train T5 on it. I was wondering if there is a proper way to do it? I assume that it can be done by combining all examples of each dataset but maybe you have a better solution.
Hoping this is clear enough,
Thanks a lot 😊
Best | 20 | [Question] Combine 2 datasets which have the same columns
Hi,
I am using ``nlp`` to load personal datasets. I created summarization datasets in multi-languages based on wikinews. I have one dataset for english and one for german (french is getting to be ready as well). I want to keep these datasets independent because they need different pre-processing (add different task-specific prefixes for T5 : *summarize:* for english and *zusammenfassen:* for german)
My issue is that I want to train T5 on the combined english and german datasets to see if it improves results. So I would like to combine 2 datasets (which have the same columns) to make one and train T5 on it. I was wondering if there is a proper way to do it? I assume that it can be done by combining all examples of each dataset but maybe you have a better solution.
Hoping this is clear enough,
Thanks a lot 😊
Best
We are thinking about ways to combine datasets for T5 in #217, feel free to share your thoughts about this. | [
-0.24451451003551483,
0.06389839947223663,
0.024110831320285797,
0.36282336711883545,
0.10962121933698654,
0.4387524425983429,
0.26998746395111084,
0.3603740930557251,
0.044979143887758255,
-0.11644783616065979,
-0.381481409072876,
0.12374326586723328,
0.003628678619861603,
0.2719852328300476,
0.27131691575050354,
-0.5642147064208984,
0.05804482102394104,
0.21875345706939697,
-0.5200099945068359,
0.18503700196743011,
0.007575150579214096,
0.005126262083649635,
-0.16544681787490845,
0.012677192687988281,
-0.20304375886917114,
0.2349441945552826,
-0.3422628939151764,
-0.22793927788734436,
0.04638442397117615,
0.15664580464363098,
0.3019716739654541,
0.16707965731620789,
0.21462075412273407,
0.31491559743881226,
-0.00011992744111921638,
-0.07949517667293549,
-0.016488976776599884,
-0.09052366763353348,
0.14189808070659637,
-0.19872920215129852,
0.09682495146989822,
-0.36194995045661926,
-0.06335476040840149,
-0.15658241510391235,
0.08227722346782684,
-0.23953083157539368,
-0.23318354785442352,
0.03752853721380234,
0.26808595657348633,
-0.16602979600429535,
0.05411152169108391,
-0.188320592045784,
-0.251149445772171,
0.3409510850906372,
-0.07127415388822556,
-0.16056816279888153,
0.0614653155207634,
-0.06943392753601074,
0.08189091831445694,
-0.31951451301574707,
0.5779258608818054,
0.2133333683013916,
-0.03511062264442444,
-0.11987727880477905,
0.08233247697353363,
0.14248356223106384,
0.1433926224708557,
-0.1095086932182312,
0.05533512309193611,
0.19000259041786194,
0.7741914987564087,
-0.05964938551187515,
0.008376194164156914,
-0.29153186082839966,
0.4038733243942261,
-0.1315470039844513,
-0.19321182370185852,
0.1430453211069107,
0.017043307423591614,
0.025498170405626297,
-0.25481942296028137,
-0.15632006525993347,
-0.0164065882563591,
0.3023141622543335,
-0.04316413402557373,
0.33158251643180847,
0.11024920642375946,
0.27707964181900024,
-0.06372199952602386,
-0.1514376997947693,
0.16603240370750427,
-0.33642664551734924,
0.000991474837064743,
0.15475766360759735,
-0.3073637783527374,
-0.4046189486980438,
-0.3330455422401428,
-0.18422913551330566,
0.27262577414512634,
-0.1534881740808487,
-0.15438945591449738,
-0.006971031427383423,
-0.1090388372540474,
0.13872379064559937,
0.30268222093582153,
0.15827219188213348,
0.13861002027988434,
0.21253788471221924,
-0.18847210705280304,
-0.31628331542015076,
-0.3603151738643646,
0.16161024570465088,
0.07011684775352478,
-0.0728301927447319,
-0.1233942061662674,
-0.2811368703842163,
-0.058452386409044266,
-0.34144553542137146,
0.1455402374267578,
-0.19353191554546356,
-0.27553874254226685,
-0.2310830056667328,
-0.10256724059581757,
-0.15160977840423584,
-0.0181959867477417,
0.3452557921409607,
-0.1489933580160141,
0.3091169595718384,
-0.10607438534498215,
-0.013937316834926605,
-0.025030506774783134,
0.07381550967693329,
-0.17078666388988495,
0.12827026844024658,
0.09456299245357513,
0.1703295111656189,
-0.13089489936828613,
0.41861796379089355,
-0.18310464918613434,
0.10155941545963287,
0.32089948654174805,
-0.19957442581653595,
-0.07107561081647873,
-0.24224181473255157,
0.3129124045372009,
0.16381879150867462,
0.1630842238664627,
0.1007986068725586,
-0.30066731572151184,
0.167317733168602,
-0.173665851354599,
-0.08247645199298859,
0.015731103718280792,
0.059499677270650864,
-0.08394315838813782,
-0.3012196719646454,
-0.12381046265363693,
0.6368820667266846,
0.23763468861579895,
-0.31690338253974915,
-0.14158743619918823,
0.09555449336767197,
-0.46418440341949463,
-0.04789269343018532,
0.2085668444633484,
0.02511993795633316,
-0.3501126766204834,
-0.13585302233695984,
0.0010477718897163868,
-0.006365634500980377,
-0.05010829120874405,
0.28892162442207336,
-0.2664487659931183,
0.20656630396842957,
0.09581834822893143,
0.0672091692686081,
0.6602531671524048,
0.017082706093788147,
-0.21449172496795654,
0.22153334319591522,
-0.15071627497673035,
0.13258711993694305,
-0.10475029796361923,
0.11741265654563904,
-0.37669920921325684,
-0.047003574669361115,
0.18447914719581604,
0.8385096788406372,
-0.2917744815349579,
-0.15610283613204956,
-0.06377512961626053,
-0.3239149749279022,
0.3379635214805603,
0.15537415444850922,
0.10215353965759277,
-0.2498815953731537,
-0.14259573817253113,
0.16948066651821136,
0.16629913449287415,
-0.356065958738327,
0.16821666061878204,
0.18711219727993011,
-0.02912452444434166,
0.11733973026275635,
-0.22763407230377197,
-0.2857434153556824,
-0.26597312092781067,
-0.13448573648929596,
0.1124015748500824,
0.04761628434062004,
0.4460560083389282,
-0.45091044902801514,
0.06634527444839478,
-0.6603160500526428,
-0.02074446901679039,
0.09107711911201477,
-0.0005951300263404846,
0.3114056885242462,
0.10588116943836212,
-0.2892327904701233,
-0.175703763961792,
0.3350963890552521,
-0.0520145557820797,
-0.16662995517253876,
-0.15280741453170776,
0.4420304596424103,
0.038530878722667694,
0.07375138998031616,
0.009351879358291626,
0.5092471837997437,
0.048488471657037735,
0.034645307809114456,
0.149419367313385,
-0.12538093328475952,
-0.5496699213981628,
0.1898004114627838,
0.183569997549057,
0.02857401967048645,
-0.15538746118545532,
-0.068069227039814,
0.3543192744255066,
-0.3344201147556305,
-0.0053182621486485004,
-0.1602422446012497,
-0.07414629310369492,
0.4110819697380066,
-0.24898143112659454,
0.36992499232292175,
-0.020390696823596954,
-0.11749587208032608,
0.016925035044550896,
-0.15341848134994507,
0.021901724860072136,
-0.10193338245153427,
0.21405470371246338,
-0.007762245833873749,
0.013551242649555206,
0.34956735372543335,
-0.387805700302124,
0.2461588978767395,
0.28392383456230164,
0.10369329154491425,
-0.046701379120349884,
-0.014283496886491776,
-0.14048606157302856,
-0.047391608357429504,
0.03492948040366173,
0.17373257875442505,
0.5730593800544739,
0.19658580422401428,
0.201826810836792,
0.23324695229530334,
-0.15427251160144806,
0.12579293549060822,
0.014814585447311401,
0.1872757375240326,
0.06608593463897705,
0.30791279673576355,
0.0905812680721283,
0.22131584584712982,
0.18971002101898193,
0.39874452352523804,
0.20331734418869019,
-0.09153177589178085,
-0.1926695704460144,
-0.005747830495238304,
-0.2850164473056793,
-0.6398731470108032,
-0.5628815293312073,
-0.1282135248184204,
-0.2211204171180725,
-0.05306980013847351,
-0.09376570582389832,
-0.0052847787737846375,
0.00872943177819252,
0.1844758689403534,
-0.11454105377197266,
0.42126092314720154,
-0.47502192854881287,
-0.2778404951095581,
0.2787609398365021,
0.041623201221227646,
-0.18180063366889954,
0.0709051787853241,
0.4079386293888092,
0.21213699877262115,
0.2545481026172638,
-0.057418711483478546,
-0.23279772698879242,
-0.06010568141937256,
-0.5316919088363647,
0.05019490793347359,
-0.36541086435317993,
-0.14889386296272278,
-0.2518877685070038,
-0.10150045156478882,
-0.21497701108455658,
-0.3766782879829407,
0.051559530198574066,
0.3118175268173218,
0.05274157226085663,
-0.1287008374929428,
0.05726409703493118,
0.2869410514831543,
-0.10500974953174591,
-0.29453229904174805,
-0.42148053646087646,
-0.05987602099776268,
0.042383067309856415,
-0.16191205382347107,
-0.020818598568439484,
-0.36425983905792236,
-0.05395589396357536,
-0.036509353667497635,
-0.2672067880630493,
-0.011379342526197433,
-0.2016235589981079,
0.0008076950907707214,
0.1787797063589096,
-0.13474710285663605,
-0.12834623456001282,
-0.08461089432239532,
-0.1897968202829361,
0.29974430799484253,
-0.030816208571195602,
-0.10249122232198715,
-0.15170343220233917,
-0.1399437040090561,
-0.0023920759558677673,
-0.14289137721061707,
0.3774227499961853,
0.17890051007270813,
0.017672274261713028,
0.14856798946857452,
0.07189612090587616,
-0.2294684201478958,
0.021115601062774658,
0.09855327755212784,
0.45749837160110474,
-0.1967516839504242,
0.25292760133743286,
-0.14573286473751068,
0.6077174544334412,
0.5213463306427002,
0.16695120930671692,
0.06605766713619232,
0.25551122426986694,
0.14240209758281708,
0.0633198544383049,
-0.20977532863616943,
0.2008449137210846,
0.19462987780570984,
0.05766982585191727,
0.2699241042137146,
0.10378659516572952,
-0.053352147340774536,
-0.3339765965938568,
0.09006898105144501,
-0.3042641878128052,
-0.11738692224025726,
0.37775230407714844,
-0.272573858499527,
0.11911562830209732,
0.011026915162801743,
-0.464156836271286,
-0.3556422293186188,
-0.13096469640731812,
-0.21647487580776215,
0.11839114129543304,
-0.2585562467575073,
0.13618622720241547,
-0.5622233748435974,
-0.10364512354135513,
-0.140688955783844,
0.32386571168899536,
0.1514759510755539,
0.3083507716655731,
0.04973016306757927,
0.055047936737537384,
-0.24609489738941193,
-0.04382070153951645,
0.0648692399263382,
-0.4924119710922241,
-0.13473451137542725,
0.0649791806936264,
0.014051701873540878,
-0.23107802867889404,
-0.17589332163333893,
0.017375919967889786,
-0.09139548987150192,
-0.18299786746501923,
0.3364602327346802,
-0.31847766041755676,
-0.15623880922794342,
0.6944684982299805,
0.43872055411338806,
-0.07578420639038086,
-0.3850887417793274,
0.046434272080659866,
-0.1232314258813858,
-0.14339585602283478,
-0.26000726222991943,
-0.04751051962375641,
0.16320359706878662,
-0.3689451813697815,
0.15044571459293365,
0.01641192100942135,
0.08038859069347382,
0.4504481554031372,
0.10332688689231873,
0.0721358209848404,
0.352663516998291,
0.3876456320285797,
-0.24028700590133667,
-0.0815337598323822,
-0.2526187300682068,
0.4975552558898926,
-0.07558071613311768,
-0.3227156698703766,
-0.1711563766002655,
-0.14382445812225342,
0.7155787944793701,
-0.06854936480522156,
0.15113170444965363,
0.231692373752594,
-0.3995974361896515,
-0.361508846282959,
0.001953156664967537,
0.20284631848335266,
0.2826133668422699,
0.32211485505104065,
-0.3971283733844757,
-0.4497554302215576,
0.6233009696006775,
0.4106392562389374,
-0.020718932151794434,
0.2541210949420929,
-0.25738000869750977,
-0.17415764927864075,
0.09945577383041382,
-0.10148287564516068,
0.8141263127326965,
0.021813631057739258,
0.3815930485725403,
-0.00047905556857585907,
-0.16811984777450562,
0.7002723217010498,
-0.09663334488868713,
0.019921768456697464,
0.020172063261270523,
-0.1437639445066452,
-0.035385921597480774,
-0.03009585104882717,
-0.12921613454818726,
0.37022101879119873,
-0.2077862173318863,
0.3171713054180145,
-0.0004519149661064148,
-0.00524304062128067,
0.0035987719893455505,
0.40919193625450134,
0.06669454276561737,
-0.25877243280410767,
-0.39313653111457825,
-0.0303385891020298,
-0.30272597074508667,
-0.05387930944561958,
-0.1444966197013855,
0.07147341966629028,
-0.13137845695018768,
0.07047849893569946,
-0.1482681930065155,
0.29996389150619507,
0.5066030025482178,
0.044584959745407104,
-0.41170385479927063,
-0.44156980514526367,
0.29387804865837097,
0.1413809210062027,
0.3556130528450012,
0.02908967062830925,
0.029953598976135254,
0.014914780855178833,
-0.3565634787082672,
-0.015754686668515205,
-0.11483734846115112,
-0.29389649629592896,
0.2594217360019684,
0.020187336951494217,
-0.2533405125141144,
0.06901317089796066,
0.41276517510414124,
-0.08236521482467651,
-0.25440287590026855,
-0.17855213582515717,
0.3314897418022156,
-0.059461019933223724,
-0.5873781442642212,
0.6571646928787231,
0.15120764076709747,
-0.07791917026042938,
0.010054625570774078,
-0.11371757090091705,
-0.2892296314239502,
0.3845168650150299,
-0.27283975481987,
-0.25546637177467346,
0.060183294117450714,
0.1803913712501526,
0.3060007393360138,
-0.36582598090171814,
0.4701862335205078,
0.1839190125465393,
0.2744100093841553,
0.02297355979681015,
-0.06155161187052727,
0.26224833726882935,
-0.07377277314662933,
-0.3581317663192749,
0.10253649204969406,
0.20453248918056488,
0.11256218701601028,
0.1527307629585266,
0.1633155196905136,
0.12227499485015869,
0.20673184096813202,
-0.06777942925691605,
-0.3782421946525574,
0.2728555202484131,
0.200240820646286,
0.26178988814353943,
0.25701823830604553,
0.31280267238616943,
0.06446360796689987,
0.6031780242919922,
-0.1696951985359192,
-0.019097788259387016,
0.13622340559959412,
0.28524187207221985,
0.34651583433151245,
0.08450741320848465,
-0.40706947445869446,
0.014368634670972824,
-0.04422113299369812,
0.0018224380910396576,
0.11410652101039886,
-0.14427253603935242,
-0.07686243951320648,
0.17597177624702454,
0.34493160247802734,
0.001123265828937292,
0.06023344025015831,
-0.2807413935661316,
-0.011823095381259918,
-0.022508585825562477,
0.06651268899440765,
-0.09257775545120239,
-0.00026310235261917114,
0.38064053654670715,
-0.07365313172340393,
0.03403807058930397,
-0.28564876317977905,
0.26426970958709717,
-0.1323501467704773,
-0.03567935526371002,
0.25900283455848694,
0.10173744708299637,
0.3916667401790619,
-0.044483136385679245,
-0.25726914405822754,
-0.26786476373672485,
0.21714022755622864,
0.06505507230758667,
-0.34551671147346497,
-0.03496948629617691,
0.046090368181467056,
-0.06114388257265091,
0.15212295949459076,
0.3250305950641632,
-0.10721445083618164,
-0.025068938732147217,
0.23458319902420044,
0.0007479563355445862,
-0.1970008909702301,
0.07210490852594376,
0.23050764203071594,
-0.06402743607759476,
-0.14158520102500916,
0.21958449482917786,
0.09061235189437866,
0.3772614300251007,
-0.3111916780471802,
-0.012799031101167202,
-0.007480906322598457,
-0.03604806959629059,
0.3243543207645416,
0.5464572310447693,
-0.032420575618743896,
-0.10312484204769135,
-0.012002123519778252,
0.08090406656265259,
0.058864183723926544,
-0.05017808824777603,
-0.14656272530555725,
-0.0674607902765274,
-0.0896884873509407,
-0.07963159680366516,
0.23124241828918457,
-0.08268290758132935,
0.06398656964302063,
0.29144909977912903,
0.22425898909568787,
0.13219547271728516,
0.059876590967178345,
0.27598100900650024,
0.005738468840718269,
-0.4656766653060913,
0.027942942455410957,
0.41669270396232605,
-0.07972194254398346,
0.0029158368706703186,
-0.39661499857902527,
-0.0038863271474838257,
-0.1403137445449829,
0.20574165880680084,
-0.12469911575317383,
-0.33381330966949463,
0.5012160539627075,
0.09291692078113556,
-0.14959858357906342,
-0.22758518159389496,
0.1266917884349823,
0.5161339640617371,
-0.03509516268968582,
-0.048462413251399994,
0.0520235076546669,
0.16546931862831116,
-0.1280071884393692,
0.037699319422245026,
0.25175678730010986,
0.11086656898260117,
0.029335781931877136,
0.0011414103209972382,
0.024302955716848373,
0.1404404491186142,
0.12212355434894562,
0.1034310832619667,
0.019177988171577454,
0.08414570987224579,
-0.01620527356863022,
0.2771753966808319,
0.10079756379127502,
-0.06125646084547043,
0.07313267886638641,
-0.12367571890354156,
0.0440765842795372,
-0.588858962059021,
0.26579609513282776,
0.31551527976989746,
-0.023779835551977158,
-0.05252765864133835,
0.17175768315792084,
-0.32935717701911926,
-0.18782618641853333,
0.5251398682594299,
0.2926930785179138,
-0.15609651803970337,
-0.15337051451206207,
0.03533812612295151,
-0.02974071353673935,
0.31862959265708923,
0.3571052551269531,
0.08333572745323181,
-0.42110368609428406,
-0.1852589249610901,
-0.7274479866027832,
0.11188363283872604,
-0.1998959630727768,
-0.11876031011343002,
-0.26006925106048584,
0.0404849499464035,
0.26376107335090637,
0.2332354187965393,
0.06438417732715607,
0.43237608671188354,
0.14185306429862976,
0.1557856947183609,
-0.43412360548973083,
-0.15743917226791382,
0.08547855913639069,
0.18689313530921936,
0.05970897525548935,
-0.11151805520057678,
0.024231597781181335,
0.35462501645088196,
-0.1866980493068695,
-0.06368330121040344,
0.01978754997253418,
0.13367462158203125,
-0.04021917283535004,
0.2397705316543579,
0.03683649003505707,
0.6354694366455078,
-0.16606959700584412,
0.09476259350776672,
0.1124473363161087,
-0.050969451665878296,
-0.5395124554634094,
0.35593634843826294,
-0.15957559645175934,
0.019293449819087982,
-0.6011696457862854,
0.6696318984031677,
0.12462136149406433,
-0.28975358605384827,
-0.08932241797447205,
0.12198374420404434,
-0.053985126316547394,
-0.13608352839946747,
0.2872995138168335,
0.0695641040802002,
0.2895844280719757,
0.6231246590614319,
0.044806335121393204,
0.08362887054681778,
-0.18011710047721863,
-0.09812998026609421,
0.2389068305492401,
0.10177017748355865,
-0.4384743273258209,
-0.09930215030908585,
-0.1474403738975525,
0.0205276720225811,
-0.08745379000902176,
-0.5327368378639221,
-0.03613046929240227,
0.3234035074710846,
-0.17692339420318604,
0.3889912962913513,
0.5019958019256592,
0.01669117622077465,
0.0657181590795517,
-0.2933851182460785,
-0.06997093558311462,
-0.07178293913602829,
-0.07720504701137543,
-0.1236257553100586,
-0.2613339424133301
] |
https://github.com/huggingface/datasets/issues/197 | Scientific Papers only downloading Pubmed | Hi so there are indeed two configurations in the datasets as you can see [here](https://github.com/huggingface/nlp/blob/master/datasets/scientific_papers/scientific_papers.py#L81-L82).
You can load either one with:
```python
dataset = nlp.load_dataset('scientific_papers', 'pubmed')
dataset = nlp.load_dataset('scientific_papers', 'arxiv')
```
This issues is actually related to a similar user-experience issue with GLUE. When several configurations are available and the first configuration is loaded by default (see issue #152 and #130), it seems to be unexpected for users.
I think we should maybe raise a (very explicit) error when there are several configurations available and the user doesn't specify one.
What do you think @lhoestq @patrickvonplaten @mariamabarham ? | Hi!
I have been playing around with this module, and I am a bit confused about the `scientific_papers` dataset. I thought that it would download two separate datasets, arxiv and pubmed. But when I run the following:
```
dataset = nlp.load_dataset('scientific_papers', data_dir='.', cache_dir='.')
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5.05k/5.05k [00:00<00:00, 2.66MB/s]
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4.90k/4.90k [00:00<00:00, 2.42MB/s]
Downloading and preparing dataset scientific_papers/pubmed (download: 4.20 GiB, generated: 2.33 GiB, total: 6.53 GiB) to ./scientific_papers/pubmed/1.1.1...
Downloading: 3.62GB [00:40, 90.5MB/s]
Downloading: 880MB [00:08, 101MB/s]
Dataset scientific_papers downloaded and prepared to ./scientific_papers/pubmed/1.1.1. Subsequent calls will reuse this data.
```
only a pubmed folder is created. There doesn't seem to be something for arxiv. Are these two datasets merged? Or have I misunderstood something?
Thanks! | 98 | Scientific Papers only downloading Pubmed
Hi!
I have been playing around with this module, and I am a bit confused about the `scientific_papers` dataset. I thought that it would download two separate datasets, arxiv and pubmed. But when I run the following:
```
dataset = nlp.load_dataset('scientific_papers', data_dir='.', cache_dir='.')
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5.05k/5.05k [00:00<00:00, 2.66MB/s]
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4.90k/4.90k [00:00<00:00, 2.42MB/s]
Downloading and preparing dataset scientific_papers/pubmed (download: 4.20 GiB, generated: 2.33 GiB, total: 6.53 GiB) to ./scientific_papers/pubmed/1.1.1...
Downloading: 3.62GB [00:40, 90.5MB/s]
Downloading: 880MB [00:08, 101MB/s]
Dataset scientific_papers downloaded and prepared to ./scientific_papers/pubmed/1.1.1. Subsequent calls will reuse this data.
```
only a pubmed folder is created. There doesn't seem to be something for arxiv. Are these two datasets merged? Or have I misunderstood something?
Thanks!
Hi so there are indeed two configurations in the datasets as you can see [here](https://github.com/huggingface/nlp/blob/master/datasets/scientific_papers/scientific_papers.py#L81-L82).
You can load either one with:
```python
dataset = nlp.load_dataset('scientific_papers', 'pubmed')
dataset = nlp.load_dataset('scientific_papers', 'arxiv')
```
This issues is actually related to a similar user-experience issue with GLUE. When several configurations are available and the first configuration is loaded by default (see issue #152 and #130), it seems to be unexpected for users.
I think we should maybe raise a (very explicit) error when there are several configurations available and the user doesn't specify one.
What do you think @lhoestq @patrickvonplaten @mariamabarham ? | [
0.34102776646614075,
-0.050783343613147736,
0.04983740672469139,
0.20578475296497345,
-0.012494008988142014,
-0.09158316254615784,
0.13143377006053925,
0.24781447649002075,
0.07514068484306335,
-0.21932382881641388,
-0.1656389683485031,
0.10058028995990753,
0.06382811069488525,
-0.29008498787879944,
0.24017472565174103,
0.0783972442150116,
0.0976623147726059,
0.11659547686576843,
0.14824892580509186,
-0.1969805359840393,
-0.11032861471176147,
0.46621453762054443,
-0.11777040362358093,
-0.12418785691261292,
0.02648148499429226,
0.05782896280288696,
-0.25497737526893616,
0.22920289635658264,
-0.17581428587436676,
-0.2693144679069519,
0.22969691455364227,
0.46074485778808594,
0.01064758375287056,
0.24424946308135986,
-0.00012602117203641683,
-0.026637017726898193,
0.4085165858268738,
0.03749188035726547,
-0.07534395158290863,
-0.12848345935344696,
0.15254196524620056,
-0.31279507279396057,
0.39784446358680725,
-0.10654234141111374,
0.04228166490793228,
-0.393091082572937,
0.17608490586280823,
-0.046389978379011154,
0.17987260222434998,
0.0012874174863100052,
0.08718021214008331,
0.12423442304134369,
0.06380897760391235,
0.06727617979049683,
0.4933621883392334,
0.01011587679386139,
0.06612028926610947,
0.41989225149154663,
0.2697266936302185,
-0.16339382529258728,
0.13654892146587372,
0.24459709227085114,
-0.11495184898376465,
0.1563953310251236,
0.17969712615013123,
0.4194623827934265,
0.05964410677552223,
-0.4671778976917267,
-0.20219320058822632,
0.34553930163383484,
0.014854662120342255,
0.013018671423196793,
-0.04609832167625427,
-0.4677787721157074,
-0.01220071129500866,
0.0002346821129322052,
0.20772784948349,
0.45637431740760803,
-0.16081520915031433,
-0.0648922324180603,
0.08118142932653427,
-0.2500704526901245,
-0.060462795197963715,
0.5617239475250244,
0.16432194411754608,
0.048341281712055206,
-0.19733892381191254,
0.3637370467185974,
0.4003930985927582,
0.16857296228408813,
-0.26249799132347107,
-0.2875668406486511,
0.19754011929035187,
0.18750794231891632,
-0.3029335141181946,
0.008081495761871338,
0.0892409011721611,
-0.0668543353676796,
0.24016210436820984,
0.3428828716278076,
0.0869828388094902,
-0.04315388202667236,
0.19389544427394867,
0.12176162004470825,
0.529692530632019,
-0.06093313917517662,
-0.020973533391952515,
0.1862221211194992,
0.3687583804130554,
-0.016591491177678108,
0.0886765867471695,
0.09830331802368164,
0.09169559925794601,
-0.025422867387533188,
-0.23397573828697205,
-0.598155677318573,
0.287977397441864,
-0.2756761908531189,
0.24873152375221252,
-0.023607876151800156,
-0.011190991848707199,
-0.05599594488739967,
-0.2106602042913437,
0.004625678062438965,
0.018986862152814865,
0.2226305902004242,
0.11902976036071777,
0.28089165687561035,
-0.20559236407279968,
0.20877200365066528,
-0.0782691240310669,
0.005981238558888435,
-0.3656753599643707,
0.03970438241958618,
0.27115416526794434,
-0.27817502617836,
0.1672438383102417,
0.09166526049375534,
-0.11322474479675293,
-0.1840112805366516,
0.17918317019939423,
-0.13153216242790222,
0.0667213574051857,
0.3698318600654602,
0.27781257033348083,
0.508072555065155,
-0.0019681155681610107,
-0.2545323967933655,
-0.27548736333847046,
-0.06114349514245987,
-0.2797984778881073,
-0.16831763088703156,
-0.18680988252162933,
0.029858209192752838,
-0.39023643732070923,
0.16661079227924347,
0.00011780112981796265,
0.28824135661125183,
0.1552387923002243,
-0.17051096260547638,
-0.11550761014223099,
-0.004567872732877731,
-0.08512463420629501,
-0.37034308910369873,
0.12198788672685623,
0.34375470876693726,
0.19060109555721283,
-0.1056913435459137,
-0.12709030508995056,
-0.1005403995513916,
0.08209993690252304,
0.311158686876297,
-0.2761954665184021,
0.14208726584911346,
-0.24165396392345428,
0.2310815006494522,
0.5904173254966736,
-0.27101388573646545,
-0.452669233083725,
0.31155821681022644,
-0.024965107440948486,
0.07489564269781113,
0.15223035216331482,
0.2749258577823639,
-0.1387363225221634,
-0.02256181463599205,
0.16591569781303406,
0.3668280839920044,
0.09084153175354004,
-0.1462748646736145,
-0.30497613549232483,
-0.194266214966774,
0.30231988430023193,
-0.09074105322360992,
0.11595368385314941,
0.005938924849033356,
-0.008974798023700714,
0.06970684230327606,
0.30660560727119446,
0.2294960767030716,
0.18607574701309204,
0.24630224704742432,
-0.07493281364440918,
-0.009011022746562958,
0.07086265832185745,
-0.2000008523464203,
-0.33421590924263,
0.05639561265707016,
-0.3555225133895874,
0.2431671917438507,
0.26221126317977905,
-0.042365819215774536,
-0.23279789090156555,
-0.4931893050670624,
-0.1797831803560257,
-0.26830679178237915,
0.004727199673652649,
0.21896950900554657,
0.12241218984127045,
0.16072684526443481,
-0.26788291335105896,
0.17435473203659058,
0.009839585050940514,
0.08805970847606659,
-0.8079344034194946,
0.3179464042186737,
-0.017846236005425453,
-0.07045114785432816,
0.0631343349814415,
0.1433001160621643,
0.001261923462152481,
-0.16912347078323364,
0.32444727420806885,
0.43658122420310974,
-0.13749289512634277,
0.22820736467838287,
0.22558555006980896,
0.05751761049032211,
0.2537793219089508,
-0.11084961891174316,
0.15133501589298248,
-0.1257915049791336,
0.11191115528345108,
-0.23113122582435608,
-0.3042531907558441,
0.11682837456464767,
-0.0770876556634903,
0.37470802664756775,
0.14695371687412262,
-0.011496390216052532,
0.010349219664931297,
-0.23012566566467285,
-0.47462472319602966,
-0.21605578064918518,
0.20148727297782898,
0.22801299393177032,
-0.1119728833436966,
0.14593082666397095,
-0.2998264729976654,
0.07807661592960358,
0.07013916224241257,
0.017232604324817657,
-0.020467184484004974,
0.17367807030677795,
-0.27142301201820374,
-0.2440958023071289,
-0.18221423029899597,
0.516252338886261,
0.8718119859695435,
0.19785284996032715,
0.3229740858078003,
0.10880731791257858,
-0.17633862793445587,
-0.1969754993915558,
0.08697985857725143,
0.033732831478118896,
-0.12805841863155365,
0.21404004096984863,
0.17132708430290222,
-0.008642091415822506,
-0.42317691445350647,
0.3805907964706421,
0.16046586632728577,
0.021289855241775513,
-0.37637463212013245,
-0.1903132200241089,
-0.40123867988586426,
-0.3012843132019043,
-0.6075862050056458,
-0.18438860774040222,
-0.36245566606521606,
-0.34663310647010803,
-0.06475569307804108,
0.13995036482810974,
-0.05048669874668121,
0.02463909424841404,
-0.2065402865409851,
0.15557387471199036,
-0.23960019648075104,
0.06841801851987839,
0.141157329082489,
0.1248280256986618,
-0.3013819754123688,
-0.080742746591568,
0.03651655092835426,
0.38875484466552734,
0.518622100353241,
0.054689645767211914,
-0.2073940485715866,
-0.08984847366809845,
-0.4579673111438751,
0.25336790084838867,
-0.2039085477590561,
0.4136425256729126,
0.2852550745010376,
0.0983385220170021,
0.36341434717178345,
-0.08333992213010788,
0.2817317247390747,
-0.14543606340885162,
0.030420979484915733,
0.008215336129069328,
0.08342495560646057,
-0.020247697830200195,
-0.2850768268108368,
-0.5693515539169312,
-0.3060920238494873,
-0.2529955804347992,
-0.11007168889045715,
-0.05502310022711754,
0.12144863605499268,
0.24505096673965454,
-0.0811234563589096,
0.12399712204933167,
-0.4648562967777252,
-0.045524708926677704,
-0.36400437355041504,
-0.08933573216199875,
0.24169158935546875,
-0.22708259522914886,
-0.4088027775287628,
-0.04336240887641907,
-0.02477332204580307,
-0.09826163947582245,
0.15945127606391907,
-0.38081425428390503,
-0.41890549659729004,
-0.21503809094429016,
-0.5069783329963684,
0.17532096803188324,
0.41701313853263855,
0.30164095759391785,
-0.3365061581134796,
-0.10329846292734146,
-0.08495710790157318,
-0.1637304276227951,
0.18865779042243958,
0.2175230085849762,
0.3610684871673584,
0.20806372165679932,
-0.09732384234666824,
-0.015406223013997078,
0.5112146735191345,
0.45359480381011963,
0.1888437420129776,
0.2588818669319153,
-0.030591147020459175,
0.6296035647392273,
0.08015412092208862,
-0.352665513753891,
0.0025883882772177458,
-0.023501619696617126,
0.2995643615722656,
0.3215644955635071,
0.2464163601398468,
-0.17453664541244507,
-0.09905517101287842,
0.1481444090604782,
-0.35031506419181824,
-0.3976816236972809,
0.22064201533794403,
-0.11810313165187836,
0.03348477929830551,
0.21164000034332275,
-0.3735966980457306,
0.05672074481844902,
-0.05050106719136238,
-0.3561001718044281,
0.39024847745895386,
-0.13153076171875,
0.12844499945640564,
-0.599489688873291,
0.11785094439983368,
-0.43639665842056274,
0.13917550444602966,
-0.12238942086696625,
0.16424347460269928,
0.11637763679027557,
-0.06740288436412811,
0.3922004699707031,
0.028027335181832314,
0.5079417824745178,
-0.1339224874973297,
-0.21793539822101593,
0.1831878274679184,
-0.09627951681613922,
-0.8417407274246216,
-0.16880621016025543,
-0.07770348340272903,
-0.11526864767074585,
0.2761756479740143,
0.30282431840896606,
-0.5176626443862915,
-0.25081342458724976,
0.2035353183746338,
0.1481359899044037,
-0.17218632996082306,
-0.2493516206741333,
-0.263827383518219,
-0.4485575556755066,
-0.3102776110172272,
-0.3914089500904083,
-0.12274369597434998,
-0.05234157666563988,
-0.11759019643068314,
-0.1287962943315506,
0.1574462354183197,
-0.1702951192855835,
0.1424727588891983,
-0.16090027987957,
0.2610478401184082,
-0.020965980365872383,
0.03182746842503548,
0.465202271938324,
0.13367360830307007,
-0.575064480304718,
0.5631838440895081,
-0.18785931169986725,
0.2896803617477417,
0.1397072970867157,
-0.17257237434387207,
0.3634226322174072,
0.53404700756073,
-0.06888536363840103,
0.06709124147891998,
0.03953199088573456,
-0.07136170566082001,
-0.11491309851408005,
0.25564396381378174,
0.5111374258995056,
-0.3491494655609131,
-0.13880009949207306,
-0.3376767933368683,
0.5596760511398315,
0.08166489005088806,
-0.4084247350692749,
0.19925884902477264,
0.26665204763412476,
-0.24415437877178192,
0.28216004371643066,
-0.3538729250431061,
1.0832160711288452,
0.04487142711877823,
0.31874552369117737,
0.08139197528362274,
-0.20796729624271393,
0.891269862651825,
-0.019846737384796143,
0.025093605741858482,
-0.2386833131313324,
-0.04003006964921951,
0.016051342710852623,
-0.18522723019123077,
0.05906523019075394,
0.0831565335392952,
-0.026412058621644974,
0.29316970705986023,
0.22072936594486237,
0.09865710139274597,
-0.10229625552892685,
0.5956615805625916,
0.04097191244363785,
-0.08230295777320862,
-0.3292580842971802,
0.04090885818004608,
-0.013093538582324982,
0.31515443325042725,
0.06848505884408951,
-0.14593453705310822,
-0.22294293344020844,
-0.4063076972961426,
-0.26716148853302,
0.04904662072658539,
0.05897710099816322,
0.13230887055397034,
0.102867990732193,
-0.11787711083889008,
-0.29500049352645874,
0.02908182516694069,
-0.04239260405302048,
0.019790973514318466,
-0.25581473112106323,
-0.0875733494758606,
0.003971949219703674,
-0.3073880076408386,
-0.13085803389549255,
-0.22023822367191315,
0.2706191837787628,
-0.1288914680480957,
-0.18283438682556152,
-0.23630553483963013,
0.04053318500518799,
-0.15919379889965057,
-0.46210959553718567,
0.31663966178894043,
0.2644232213497162,
-0.0829138308763504,
-0.29635560512542725,
0.3617565333843231,
0.11170418560504913,
-0.0023642703890800476,
0.029360253363847733,
0.3525853753089905,
0.0783948078751564,
0.36199334263801575,
0.1353423148393631,
-0.19166700541973114,
-0.06823709607124329,
0.3341466188430786,
0.5289828777313232,
-0.09188312292098999,
0.2554863691329956,
-0.115418940782547,
0.051908038556575775,
-0.05099864304065704,
-0.16937878727912903,
-0.08383148908615112,
-0.3399846851825714,
0.12293001264333725,
-0.01236810814589262,
0.06921026110649109,
0.1314322054386139,
0.043052248656749725,
0.09093345701694489,
-0.21702653169631958,
-0.10895167291164398,
-0.45283451676368713,
0.06527463346719742,
0.29334086179733276,
-0.1723695993423462,
0.40974053740501404,
0.0405631959438324,
-0.12469850480556488,
0.25025713443756104,
0.31264162063598633,
-0.16058337688446045,
0.2575591206550598,
0.0629950612783432,
0.24463985860347748,
0.6299228668212891,
0.01803286001086235,
0.08861178159713745,
-0.11040416359901428,
-0.08225207775831223,
-0.057102978229522705,
-0.17737193405628204,
-0.09637583792209625,
-0.2691378593444824,
0.22645141184329987,
0.14458200335502625,
0.05872973054647446,
0.0979403629899025,
-0.23562291264533997,
0.0319424606859684,
0.008571362122893333,
0.20746645331382751,
-0.06657180190086365,
-0.039421163499355316,
-0.025018073618412018,
-0.16160482168197632,
0.03848223015666008,
0.11174441874027252,
0.34071171283721924,
-0.36419492959976196,
-0.04273565113544464,
0.3421165347099304,
0.008133165538311005,
-0.21149592101573944,
-0.09788179397583008,
-0.28521832823753357,
-0.030537590384483337,
0.1042071133852005,
-0.04821782559156418,
0.11100776493549347,
0.006433602422475815,
-0.02997584268450737,
-0.1822148710489273,
0.3628309667110443,
0.5864512324333191,
-0.26623332500457764,
0.08765033632516861,
-0.05240938067436218,
0.02447781339287758,
-0.1797003597021103,
-0.038482461124658585,
0.22309213876724243,
0.2693849802017212,
-0.08858191221952438,
0.268466055393219,
0.3248119652271271,
0.025378338992595673,
-0.12275771796703339,
-0.019717741757631302,
0.6393313407897949,
-0.19335435330867767,
0.08591987192630768,
-0.2401423454284668,
-0.04187872260808945,
-0.11093232035636902,
-0.017787883058190346,
-0.033447396010160446,
0.007564239203929901,
-0.09867122769355774,
0.20377245545387268,
0.20150569081306458,
-0.03543471544981003,
0.05255989357829094,
0.23083460330963135,
-0.1845744103193283,
0.016510192304849625,
0.7022262811660767,
0.20640385150909424,
0.30672264099121094,
0.14233775436878204,
0.7357051968574524,
-0.11739077419042587,
-0.05003523454070091,
-0.13992121815681458,
0.5564060211181641,
0.26854610443115234,
-0.2376047670841217,
0.06799222528934479,
-0.11369521915912628,
-0.142375648021698,
0.048237983137369156,
-0.04404212161898613,
-0.328213632106781,
0.27146100997924805,
-0.027660518884658813,
-0.19461427628993988,
-0.735490083694458,
0.16255098581314087,
0.07861082255840302,
0.1073671504855156,
-0.15201492607593536,
0.18626035749912262,
-0.07005301117897034,
-0.050073251128196716,
0.2191651314496994,
0.5182143449783325,
0.2908780872821808,
0.3593866229057312,
-0.0064812470227479935,
-0.16204549372196198,
0.24868381023406982,
0.17708560824394226,
-0.20950044691562653,
0.15459448099136353,
0.34004947543144226,
0.0780133605003357,
0.32010093331336975,
0.042092397809028625,
-0.10348362475633621,
-0.06722696125507355,
0.0774071142077446,
0.02938055619597435,
-0.3207195997238159,
0.5537846684455872,
-0.2837353050708771,
0.08010008186101913,
-0.017824001610279083,
0.06254686415195465,
-0.6169645190238953,
-0.1906488686800003,
0.21398423612117767,
0.005209197290241718,
0.16936859488487244,
-0.46065640449523926,
0.01407582312822342,
0.17706599831581116,
0.5300928354263306,
0.04728832468390465,
0.06634972244501114,
-0.15457892417907715,
-0.24412712454795837,
-0.7898312211036682,
0.13781481981277466,
-0.2290433943271637,
0.14415255188941956,
-0.048181138932704926,
0.3934709429740906,
0.032874125987291336,
0.31124621629714966,
-0.02222028374671936,
0.1306430697441101,
-0.539971113204956,
-0.13637644052505493,
-0.17598344385623932,
-0.04879867658019066,
-0.21684114634990692,
-0.058267854154109955,
0.005118973553180695,
-0.11321879178285599,
0.10097970068454742,
-0.2996004521846771,
-0.07709407806396484,
0.09741338342428207,
0.0709075927734375,
0.0748334527015686,
0.05449429154396057,
0.40695086121559143,
0.23451271653175354,
0.41267135739326477,
-0.000277101993560791,
-0.2844558656215668,
-0.5316896438598633,
0.04555456340312958,
-0.416957288980484,
0.09936391562223434,
0.021548980847001076,
0.20746108889579773,
-0.4415888488292694,
0.15417622029781342,
-0.11783294379711151,
-0.07033371180295944,
0.13117671012878418,
0.056523412466049194,
0.03648348152637482,
-0.008407427929341793,
0.14452460408210754,
0.1382405012845993,
0.23347686231136322,
0.4183560013771057,
-0.22531282901763916,
0.13117742538452148,
-0.19558241963386536,
-0.2739400565624237,
0.28979170322418213,
-0.36235570907592773,
-0.134887233376503,
0.12069552391767502,
0.24682091176509857,
0.07022978365421295,
0.06666940450668335,
-0.6980173587799072,
-0.2639472186565399,
0.3107894957065582,
-0.04248134046792984,
-0.1835707724094391,
0.2500549554824829,
-0.13164961338043213,
-0.4783773422241211,
-0.0227043479681015,
0.044105131179094315,
0.15658116340637207,
-0.3813154399394989,
0.011634185910224915,
-0.23016799986362457
] |
https://github.com/huggingface/datasets/issues/197 | Scientific Papers only downloading Pubmed | Now if you don't specify which part you want, it raises an error:
```
ValueError: Config name is missing.
Please pick one among the available configs: ['pubmed', 'arxiv']
Example of usage:
`load_dataset('scientific_papers', 'pubmed')`
``` | Hi!
I have been playing around with this module, and I am a bit confused about the `scientific_papers` dataset. I thought that it would download two separate datasets, arxiv and pubmed. But when I run the following:
```
dataset = nlp.load_dataset('scientific_papers', data_dir='.', cache_dir='.')
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5.05k/5.05k [00:00<00:00, 2.66MB/s]
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4.90k/4.90k [00:00<00:00, 2.42MB/s]
Downloading and preparing dataset scientific_papers/pubmed (download: 4.20 GiB, generated: 2.33 GiB, total: 6.53 GiB) to ./scientific_papers/pubmed/1.1.1...
Downloading: 3.62GB [00:40, 90.5MB/s]
Downloading: 880MB [00:08, 101MB/s]
Dataset scientific_papers downloaded and prepared to ./scientific_papers/pubmed/1.1.1. Subsequent calls will reuse this data.
```
only a pubmed folder is created. There doesn't seem to be something for arxiv. Are these two datasets merged? Or have I misunderstood something?
Thanks! | 34 | Scientific Papers only downloading Pubmed
Hi!
I have been playing around with this module, and I am a bit confused about the `scientific_papers` dataset. I thought that it would download two separate datasets, arxiv and pubmed. But when I run the following:
```
dataset = nlp.load_dataset('scientific_papers', data_dir='.', cache_dir='.')
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5.05k/5.05k [00:00<00:00, 2.66MB/s]
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4.90k/4.90k [00:00<00:00, 2.42MB/s]
Downloading and preparing dataset scientific_papers/pubmed (download: 4.20 GiB, generated: 2.33 GiB, total: 6.53 GiB) to ./scientific_papers/pubmed/1.1.1...
Downloading: 3.62GB [00:40, 90.5MB/s]
Downloading: 880MB [00:08, 101MB/s]
Dataset scientific_papers downloaded and prepared to ./scientific_papers/pubmed/1.1.1. Subsequent calls will reuse this data.
```
only a pubmed folder is created. There doesn't seem to be something for arxiv. Are these two datasets merged? Or have I misunderstood something?
Thanks!
Now if you don't specify which part you want, it raises an error:
```
ValueError: Config name is missing.
Please pick one among the available configs: ['pubmed', 'arxiv']
Example of usage:
`load_dataset('scientific_papers', 'pubmed')`
``` | [
0.3337518572807312,
0.15182587504386902,
0.04038216546177864,
0.12209126353263855,
-0.01158253476023674,
0.07017669826745987,
0.10876737534999847,
0.386903315782547,
-0.11695444583892822,
-0.22115789353847504,
-0.12466732412576675,
0.3359684348106384,
0.04204697906970978,
-0.3219139277935028,
0.3353402316570282,
0.059789542108774185,
0.17052797973155975,
0.11987831443548203,
0.24696116149425507,
-0.3221699595451355,
-0.15091925859451294,
0.36268121004104614,
-0.20078310370445251,
-0.07502949237823486,
0.17173171043395996,
0.17042206227779388,
-0.13634681701660156,
0.2355842888355255,
-0.28036168217658997,
-0.2833782732486725,
0.3049052655696869,
0.41182857751846313,
0.12482453882694244,
0.3285561501979828,
-0.0001224009320139885,
-0.051074616611003876,
0.3996657729148865,
-0.1145327091217041,
-0.12407520413398743,
-0.2439044862985611,
0.025619491934776306,
-0.27727824449539185,
0.36111241579055786,
-0.15762539207935333,
0.10323167592287064,
-0.5018042922019958,
0.22668275237083435,
-0.1019296795129776,
0.002705581486225128,
0.2615557014942169,
0.12145350873470306,
-0.0823289230465889,
0.13635185360908508,
0.003647378645837307,
0.32640424370765686,
0.01863134279847145,
0.09062426537275314,
0.30791085958480835,
0.17882341146469116,
0.08364862948656082,
0.19623708724975586,
0.2178083211183548,
-0.12764735519886017,
0.07411863654851913,
0.3337646722793579,
0.3773285150527954,
0.04918483644723892,
-0.4533298909664154,
-0.0953766331076622,
0.2512941360473633,
0.4695168435573578,
-0.08259274810552597,
0.03704769164323807,
-0.20686852931976318,
-0.04010636359453201,
-0.08870531618595123,
0.10810987651348114,
0.39001116156578064,
-0.2233264446258545,
-0.04825706407427788,
0.021009482443332672,
-0.38639745116233826,
-0.1963813453912735,
0.58647620677948,
0.16923373937606812,
0.15303432941436768,
-0.08709702640771866,
0.3638680875301361,
0.21774187684059143,
0.13750764727592468,
0.033936306834220886,
-0.32258543372154236,
0.25541025400161743,
0.2819863557815552,
-0.2922053337097168,
-0.007908500730991364,
-0.035040438175201416,
-0.2091566026210785,
0.18896672129631042,
0.326124370098114,
0.07502581179141998,
-0.06704697757959366,
0.2005782276391983,
0.12096545845270157,
0.4643363952636719,
-0.1520892232656479,
0.08678402006626129,
0.35399243235588074,
0.21561071276664734,
-0.18660415709018707,
0.03401936963200569,
0.018244968727231026,
-0.07721927762031555,
0.0717441588640213,
-0.22967693209648132,
-0.6142798066139221,
0.14092868566513062,
-0.40558966994285583,
0.44782310724258423,
-0.025238938629627228,
0.21384793519973755,
-0.10629229247570038,
-0.23445358872413635,
0.08172988146543503,
0.10517358034849167,
0.20921194553375244,
0.0853356346487999,
0.17645776271820068,
-0.1176484003663063,
0.09517573565244675,
-0.08684973418712616,
0.01650475151836872,
-0.36104920506477356,
-0.05815677344799042,
0.23637695610523224,
-0.0132148377597332,
0.261093407869339,
-0.09314660727977753,
0.07390698045492172,
-0.090160071849823,
0.24405556917190552,
-0.059681836515665054,
0.14490285515785217,
0.49642643332481384,
0.3115929663181305,
0.5195353627204895,
-0.0001559816300868988,
-0.19920705258846283,
-0.27722200751304626,
0.1592060625553131,
-0.3895842730998993,
-0.12449295818805695,
-0.11835961043834686,
0.07398621737957001,
-0.3111487627029419,
-0.06145257502794266,
0.10784704983234406,
0.2107418328523636,
0.18148663640022278,
-0.35827332735061646,
-0.10828778892755508,
0.02562979981303215,
0.04021844640374184,
-0.3753201961517334,
0.17049986124038696,
0.1312364786863327,
0.06589071452617645,
-0.038904186338186264,
-0.285993754863739,
-0.0642908364534378,
0.2266976237297058,
0.07826383411884308,
-0.3078138828277588,
0.1558774709701538,
-0.12100686132907867,
0.05395705997943878,
0.8645718097686768,
-0.21998487412929535,
-0.40715402364730835,
0.27943742275238037,
0.05443707853555679,
-0.14355961978435516,
0.0917615070939064,
0.3109305799007416,
-0.2846710681915283,
0.051498785614967346,
0.09130990505218506,
0.2885000705718994,
-0.012590447440743446,
-0.2461199164390564,
-0.14480474591255188,
-0.11279940605163574,
0.30863797664642334,
-0.07593360543251038,
0.2943570017814636,
0.16808997094631195,
-0.015602990984916687,
0.14979888498783112,
0.4100167155265808,
0.18755675852298737,
0.21378695964813232,
0.22659926116466522,
-0.1147899329662323,
-0.10925041139125824,
0.20860177278518677,
-0.17600110173225403,
-0.16421037912368774,
0.06642287224531174,
-0.4373759329319,
0.2642475664615631,
0.3202393054962158,
0.0615609809756279,
-0.29039326310157776,
-0.520103931427002,
-0.06402754783630371,
-0.31061503291130066,
-0.012993888929486275,
0.2909797132015228,
-0.001455383375287056,
0.07865075767040253,
-0.3556828796863556,
0.04744647443294525,
-0.1270780712366104,
0.014778020791709423,
-0.7680270075798035,
0.15683011710643768,
-0.0025865230709314346,
-0.014122537337243557,
0.08916129171848297,
-0.030356526374816895,
-0.04141630977392197,
-0.0181819386780262,
0.2261602282524109,
0.41557687520980835,
-0.03188009187579155,
0.3567318320274353,
0.3559616804122925,
-0.10024566948413849,
0.11630096286535263,
-0.2353438436985016,
0.15720008313655853,
-0.10833920538425446,
0.2621355652809143,
-0.2087302803993225,
-0.34462541341781616,
0.10563212633132935,
-0.15303215384483337,
0.3154360055923462,
0.15342338383197784,
-0.002797182649374008,
0.06230337917804718,
-0.12727221846580505,
-0.40658944845199585,
-0.14812877774238586,
0.17097873985767365,
0.27738890051841736,
-0.3150275647640228,
0.0903300791978836,
-0.26422256231307983,
0.03734511509537697,
0.12562444806098938,
0.006545018404722214,
-0.17453709244728088,
0.1829851269721985,
-0.3114658296108246,
-0.218950092792511,
-0.13686047494411469,
0.4669196307659149,
0.9032633900642395,
0.25674009323120117,
0.3886660039424896,
0.09151758253574371,
-0.05875265598297119,
-0.16813614964485168,
0.18907034397125244,
0.13167817890644073,
0.012559568509459496,
0.16735856235027313,
-0.06914028525352478,
-0.048744987696409225,
-0.4017599821090698,
0.2793743312358856,
0.16855449974536896,
0.06223824620246887,
-0.30279770493507385,
-0.03771195560693741,
-0.37835752964019775,
-0.1974485218524933,
-0.5116115212440491,
-0.2571055591106415,
-0.2551203668117523,
-0.3293740749359131,
-0.16789837181568146,
0.010062027722597122,
0.05495510622859001,
0.01971004530787468,
-0.5319440364837646,
0.04521992802619934,
-0.13294251263141632,
-0.15076608955860138,
0.1229516863822937,
-0.02294669859111309,
-0.24956735968589783,
0.007366064935922623,
-0.06586247682571411,
0.38983431458473206,
0.48786187171936035,
-0.07025723159313202,
-0.04292710870504379,
0.052866771817207336,
-0.4029851257801056,
0.2302953153848648,
-0.24395574629306793,
0.2364078313112259,
0.2415207326412201,
0.1290687620639801,
0.2934618592262268,
-0.0029640784487128258,
0.15736204385757446,
-0.18025970458984375,
0.024904688820242882,
-0.04032796248793602,
0.10109657049179077,
-0.10888008028268814,
-0.27549323439598083,
-0.8172608017921448,
-0.3088199496269226,
-0.18090634047985077,
-0.23882095515727997,
0.18941515684127808,
0.1692734807729721,
0.3574632704257965,
0.020866934210062027,
0.1280636340379715,
-0.32717815041542053,
0.057699061930179596,
-0.36877599358558655,
-0.1524684578180313,
0.4007762670516968,
-0.27363458275794983,
-0.37948542833328247,
0.10961058735847473,
0.14097359776496887,
0.038805801421403885,
0.14969386160373688,
-0.27083054184913635,
-0.05013028904795647,
-0.007900236174464226,
-0.5291979908943176,
0.1509532630443573,
0.33623063564300537,
0.2992240786552429,
-0.3369194269180298,
-0.11374468356370926,
-0.13982738554477692,
-0.06552587449550629,
0.11963070183992386,
0.24273642897605896,
0.5703086853027344,
0.13668487966060638,
-0.06114605814218521,
-0.18792985379695892,
0.47023582458496094,
0.3327806293964386,
0.2193659096956253,
0.13947364687919617,
-0.08077389746904373,
0.5153934955596924,
0.07098846882581711,
-0.2541893422603607,
0.17766226828098297,
0.03409871459007263,
0.11521978676319122,
0.4011799693107605,
0.14756056666374207,
-0.31791743636131287,
-0.2271197885274887,
0.029213115572929382,
-0.3635048270225525,
-0.29176682233810425,
0.22638431191444397,
-0.16411001980304718,
0.1019243597984314,
0.26066869497299194,
-0.41129791736602783,
-0.10925649106502533,
-0.021790388971567154,
-0.42039117217063904,
0.4306926727294922,
-0.15378358960151672,
0.1531316041946411,
-0.6548850536346436,
0.16735491156578064,
-0.4477037787437439,
0.11611578613519669,
-0.2242058366537094,
0.17975777387619019,
0.013182636350393295,
-0.10940734297037125,
0.20083558559417725,
0.07203806191682816,
0.3785322904586792,
-0.09238990396261215,
-0.27775925397872925,
0.16358672082424164,
0.11103224754333496,
-0.6928816437721252,
-0.05451362580060959,
0.03548400476574898,
0.06715419888496399,
0.07046359777450562,
0.15606406331062317,
-0.32216528058052063,
-0.2182283103466034,
0.2806127667427063,
0.12941719591617584,
-0.2067832499742508,
-0.23308983445167542,
-0.3231203854084015,
-0.5719004273414612,
-0.23541997373104095,
-0.4505121111869812,
-0.14295253157615662,
-0.04531502351164818,
-0.13631458580493927,
-0.09380374848842621,
0.21509875357151031,
-0.1203148365020752,
0.25403082370758057,
-0.06086587905883789,
0.26602500677108765,
-0.037856221199035645,
-0.03367999196052551,
0.4772062599658966,
0.09539496898651123,
-0.27915599942207336,
0.4296419620513916,
-0.14281487464904785,
0.2030206024646759,
0.13304805755615234,
-0.372006893157959,
0.4784090220928192,
0.30285537242889404,
-0.10998030006885529,
-0.00590573251247406,
0.19600863754749298,
-0.25283539295196533,
-0.008956448175013065,
0.14065776765346527,
0.4020999073982239,
-0.34685513377189636,
-0.32030215859413147,
-0.5828097462654114,
0.5492743253707886,
0.003125932067632675,
-0.36882954835891724,
0.2551993131637573,
-0.010728076100349426,
-0.33157041668891907,
0.23260772228240967,
-0.2238222360610962,
1.1526602506637573,
0.12742339074611664,
0.3265940845012665,
-0.0009182412177324295,
-0.10209798812866211,
0.82244473695755,
-0.05445804446935654,
0.08067631721496582,
-0.10956190526485443,
-0.04315526783466339,
-0.13305158913135529,
-0.20595550537109375,
0.16717343032360077,
0.12997116148471832,
-0.0915985256433487,
0.30789634585380554,
0.17555038630962372,
0.0021262802183628082,
0.07282951474189758,
0.47516173124313354,
0.1268334835767746,
0.004292736761271954,
-0.35017240047454834,
0.06220252811908722,
0.031312499195337296,
0.15649764239788055,
0.04731954261660576,
-0.23766162991523743,
-0.48491808772087097,
-0.41060131788253784,
-0.09666375815868378,
0.09266923367977142,
0.3221284747123718,
0.07424497604370117,
-0.07986213266849518,
-0.1980777382850647,
-0.2268858104944229,
0.20781366527080536,
-0.008842572569847107,
-0.05847974494099617,
-0.33503925800323486,
0.17607887089252472,
-0.14393207430839539,
-0.27947548031806946,
-0.20071381330490112,
-0.1652783304452896,
0.26254016160964966,
-0.25820496678352356,
-0.2651193141937256,
-0.010710440576076508,
-0.07903056591749191,
-0.2800616919994354,
-0.3210082948207855,
0.29311150312423706,
0.42605656385421753,
0.010683368891477585,
-0.2837388813495636,
0.40910011529922485,
-0.024119526147842407,
-0.004243135452270508,
0.056246668100357056,
0.40378648042678833,
0.024780165404081345,
0.47836121916770935,
0.1997634917497635,
-0.30778151750564575,
-0.11372819542884827,
0.30474233627319336,
0.7428837418556213,
-0.07022078335285187,
0.3021067976951599,
-0.09806780517101288,
-0.011663965880870819,
-0.10569634288549423,
-0.10398510098457336,
-0.2096780389547348,
-0.1769353449344635,
0.03281928226351738,
0.031270582228899,
0.2512499690055847,
0.21842877566814423,
0.011708710342645645,
-0.011573165655136108,
-0.1802452802658081,
-0.18839296698570251,
-0.4614045023918152,
-0.13243600726127625,
0.08870525658130646,
-0.37249791622161865,
0.4005108177661896,
0.07215963304042816,
-0.13302437961101532,
0.3243177533149719,
0.1654851734638214,
-0.20654752850532532,
0.15494365990161896,
-0.035978857427835464,
0.27045345306396484,
0.4610447287559509,
0.1112743392586708,
0.05570754408836365,
-0.20335344970226288,
-0.0635242611169815,
-0.19280771911144257,
-0.1160019040107727,
-0.1025906354188919,
-0.27869704365730286,
0.22386646270751953,
0.12650951743125916,
0.04898825287818909,
0.013911639340221882,
-0.23256486654281616,
-0.19723469018936157,
0.10693582147359848,
0.012789525091648102,
-0.0910220593214035,
0.04635275900363922,
0.12139242887496948,
-0.13883911073207855,
0.014663740992546082,
0.04517371952533722,
0.31722262501716614,
-0.28538018465042114,
0.11752559244632721,
0.328976571559906,
0.11331665515899658,
-0.2091713845729828,
-0.13677528500556946,
-0.2675720751285553,
-0.014869920909404755,
0.12046246230602264,
-0.17886057496070862,
0.309526264667511,
0.02365928888320923,
0.06650537252426147,
-0.21033525466918945,
0.23484084010124207,
0.7377378344535828,
-0.2688868045806885,
0.13990581035614014,
-0.07228117436170578,
0.026591014117002487,
-0.26007381081581116,
-0.03565461188554764,
0.14888788759708405,
0.2221623808145523,
-0.16084370017051697,
0.157526895403862,
0.1493343561887741,
-0.07433685660362244,
-0.1829710453748703,
0.010846085846424103,
0.7443419694900513,
-0.16752219200134277,
0.10861487686634064,
-0.13933515548706055,
-0.006555989384651184,
0.04117734730243683,
-0.015504902228713036,
0.17375347018241882,
0.021766699850559235,
0.10402995347976685,
0.09909937530755997,
0.29588207602500916,
0.046929530799388885,
-0.08133494853973389,
0.156587153673172,
-0.1968528926372528,
-0.023894090205430984,
0.708240270614624,
0.10019351541996002,
0.3292528986930847,
0.21454080939292908,
0.5007230043411255,
0.04617156460881233,
0.08842470496892929,
-0.15246064960956573,
0.45210152864456177,
0.30750763416290283,
-0.12500478327274323,
-0.1658221185207367,
-0.2766610383987427,
-0.06631577759981155,
-0.10191549360752106,
0.004147782921791077,
-0.2759506106376648,
0.16210857033729553,
0.013707369565963745,
-0.20408134162425995,
-0.619045615196228,
0.3473252058029175,
0.028992461040616035,
-0.0881718322634697,
-0.15126639604568481,
0.05593831092119217,
-0.051576077938079834,
-0.10623002052307129,
0.3673670291900635,
0.33350253105163574,
0.24257759749889374,
0.2939143478870392,
0.06989099830389023,
-0.1643190234899521,
0.35103273391723633,
0.030839597806334496,
-0.18330976366996765,
0.199112206697464,
0.3185024857521057,
0.09088282287120819,
0.3007443845272064,
0.10069775581359863,
-0.036437030881643295,
0.03841108828783035,
0.27434471249580383,
0.0016558682546019554,
-0.25471341609954834,
0.49166321754455566,
-0.14734365046024323,
0.06510015577077866,
-0.0114300437271595,
0.11638021469116211,
-0.6328656673431396,
-0.22419331967830658,
0.2930052578449249,
0.09583322703838348,
0.1150798574090004,
-0.3418160080909729,
0.014299340546131134,
0.09833107888698578,
0.6334848403930664,
-0.07817037403583527,
0.12740150094032288,
-0.12272877246141434,
-0.3408302068710327,
-0.684195876121521,
0.22655139863491058,
-0.11939598619937897,
0.13815149664878845,
0.0011202073656022549,
0.2716941237449646,
0.2850784659385681,
0.24463215470314026,
0.08168907463550568,
0.0556468740105629,
-0.6260473728179932,
0.019000347703695297,
-0.043697748333215714,
-0.2273305505514145,
-0.27663105726242065,
0.2152407020330429,
-0.08741721510887146,
-0.03948530554771423,
0.10128570348024368,
-0.3512215316295624,
-0.028956817463040352,
-0.0786876305937767,
-0.08384843170642853,
0.29225456714630127,
0.16823866963386536,
0.5404806137084961,
0.1115911453962326,
0.5250939130783081,
-0.18571817874908447,
-0.2845458388328552,
-0.38820579648017883,
0.117737777531147,
-0.37535855174064636,
0.10256737470626831,
-0.0020772889256477356,
0.06304667145013809,
-0.46579107642173767,
0.32165244221687317,
-0.07286262512207031,
0.013991950079798698,
-0.048585690557956696,
-0.22922445833683014,
-0.0022873161360621452,
-0.051074616611003876,
0.07794699817895889,
0.1083177849650383,
0.18994644284248352,
0.2920578718185425,
-0.20192834734916687,
0.07437711209058762,
-0.18357303738594055,
-0.13972805440425873,
0.38617220520973206,
-0.20822550356388092,
-0.194026380777359,
0.09874100238084793,
0.018720127642154694,
-0.1719149947166443,
0.16188180446624756,
-0.7090767621994019,
-0.06251832842826843,
0.3703853189945221,
-0.08114277571439743,
-0.1896420121192932,
0.10166247189044952,
-0.08538301289081573,
-0.34090688824653625,
-0.10702259838581085,
0.20711614191532135,
0.011787373572587967,
-0.27496469020843506,
-0.19342853128910065,
-0.18986105918884277
] |
https://github.com/huggingface/datasets/issues/193 | [Tensorflow] Use something else than `from_tensor_slices()` | `from_generator` is not working on TPU, I met the following error :
```
File "/usr/local/lib/python3.6/contextlib.py", line 88, in __exit__
next(self.gen)
File "/home/usr/.venv/bart/lib/python3.6/site-packages/tensorflow_core/python/eager/context.py", line 1900, in execution_mode
executor_new.wait()
File "/home/usr/.venv/bart/lib/python3.6/site-packages/tensorflow_core/python/eager/executor.py", line 67, in wait
pywrap_tensorflow.TFE_ExecutorWaitForAllPendingNodes(self._handle)
tensorflow.python.framework.errors_impl.NotFoundError: No registered 'PyFunc' OpKernel for 'CPU' devices compatible with node {{node PyFunc}}
. Registered: <no registered kernels>
[[PyFunc]]
```
---
@lhoestq It seems you merged some changes that allow lazy-loading. **Can you give an example of how to use ?** Maybe the Colab notebook should be updated with this method as well. | In the example notebook, the TF Dataset is built using `from_tensor_slices()` :
```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
labels = {"output_1": train_tf_dataset["start_positions"]}
labels["output_2"] = train_tf_dataset["end_positions"]
tfdataset = tf.data.Dataset.from_tensor_slices((features, labels)).batch(8)
```
But according to [official tensorflow documentation](https://www.tensorflow.org/guide/data#consuming_numpy_arrays), this will load the entire dataset to memory.
**This defeats one purpose of this library, which is lazy loading.**
Is there any other way to load the `nlp` dataset into TF dataset lazily ?
---
For example, is it possible to use [Arrow dataset](https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowDataset) ? If yes, is there any code example ? | 87 | [Tensorflow] Use something else than `from_tensor_slices()`
In the example notebook, the TF Dataset is built using `from_tensor_slices()` :
```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
labels = {"output_1": train_tf_dataset["start_positions"]}
labels["output_2"] = train_tf_dataset["end_positions"]
tfdataset = tf.data.Dataset.from_tensor_slices((features, labels)).batch(8)
```
But according to [official tensorflow documentation](https://www.tensorflow.org/guide/data#consuming_numpy_arrays), this will load the entire dataset to memory.
**This defeats one purpose of this library, which is lazy loading.**
Is there any other way to load the `nlp` dataset into TF dataset lazily ?
---
For example, is it possible to use [Arrow dataset](https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowDataset) ? If yes, is there any code example ?
`from_generator` is not working on TPU, I met the following error :
```
File "/usr/local/lib/python3.6/contextlib.py", line 88, in __exit__
next(self.gen)
File "/home/usr/.venv/bart/lib/python3.6/site-packages/tensorflow_core/python/eager/context.py", line 1900, in execution_mode
executor_new.wait()
File "/home/usr/.venv/bart/lib/python3.6/site-packages/tensorflow_core/python/eager/executor.py", line 67, in wait
pywrap_tensorflow.TFE_ExecutorWaitForAllPendingNodes(self._handle)
tensorflow.python.framework.errors_impl.NotFoundError: No registered 'PyFunc' OpKernel for 'CPU' devices compatible with node {{node PyFunc}}
. Registered: <no registered kernels>
[[PyFunc]]
```
---
@lhoestq It seems you merged some changes that allow lazy-loading. **Can you give an example of how to use ?** Maybe the Colab notebook should be updated with this method as well. | [
-0.1073198914527893,
-0.08736070990562439,
0.05800746753811836,
0.19675154983997345,
0.21142977476119995,
0.09753540903329849,
0.28022220730781555,
0.37640857696533203,
-0.15019194781780243,
0.0037060528993606567,
-0.06849081069231033,
0.5348143577575684,
-0.11443067342042923,
0.0036037880927324295,
0.32549747824668884,
-0.17846299707889557,
-0.03447549790143967,
0.2562466263771057,
-0.06642463803291321,
-0.06997586786746979,
-0.04355182498693466,
-0.02456831745803356,
-0.09649714827537537,
-0.026774592697620392,
0.05681774765253067,
0.018075238913297653,
0.08552540838718414,
-0.14649775624275208,
0.40811312198638916,
0.04641713947057724,
0.38986966013908386,
0.02334488183259964,
-0.033621031790971756,
0.15604394674301147,
-0.00011474287020973861,
0.40614014863967896,
0.035418152809143066,
-0.19170302152633667,
0.07188375294208527,
-0.11593537032604218,
0.16804373264312744,
-0.16358737647533417,
0.1652325987815857,
-0.2180953472852707,
-0.05620696395635605,
0.02299460396170616,
0.21298514306545258,
-0.06016510725021362,
0.2803554832935333,
0.13797186315059662,
0.09116256982088089,
0.5434460639953613,
-0.17063158750534058,
0.26339152455329895,
0.14321106672286987,
-0.15265360474586487,
-0.23502619564533234,
-0.25438031554222107,
-0.19450947642326355,
0.020992005243897438,
0.11463582515716553,
0.08944624662399292,
-0.23712721467018127,
0.1298714429140091,
0.46162647008895874,
0.16119210422039032,
-0.06941086798906326,
-0.36647167801856995,
-0.2092972993850708,
0.4291154742240906,
0.26164674758911133,
-0.06549926102161407,
-0.17502015829086304,
-0.446580171585083,
-0.23368878662586212,
-0.3110027611255646,
-0.1049039289355278,
0.12665338814258575,
-0.2806468904018402,
0.22548311948776245,
-0.09822195768356323,
-0.0873730480670929,
-0.25664621591567993,
0.17651858925819397,
0.19647055864334106,
-0.04481390118598938,
0.12743717432022095,
0.1107761561870575,
0.20774662494659424,
0.15451118350028992,
0.40833669900894165,
0.02135753631591797,
0.3032936751842499,
0.4022805988788605,
-0.28941798210144043,
0.029115810990333557,
0.1779962182044983,
-0.5676333904266357,
-0.06889715045690536,
-0.23024220764636993,
0.3916994631290436,
0.1674436330795288,
-0.30582019686698914,
0.251703143119812,
-0.01072559505701065,
-0.09433722496032715,
-0.4143868684768677,
0.1737426221370697,
-0.1531386822462082,
-0.5154545903205872,
0.05342916026711464,
0.044939037412405014,
-0.254041850566864,
-0.010109532624483109,
0.02233666554093361,
-0.5388681292533875,
-0.17005741596221924,
0.22495564818382263,
-0.3130665421485901,
-0.425286203622818,
-0.25239044427871704,
-0.049549102783203125,
0.0026699593290686607,
0.2106463611125946,
-0.12489939481019974,
0.5658942461013794,
0.14857403934001923,
-0.137321338057518,
-0.3045380115509033,
-0.0486360602080822,
-0.19958896934986115,
0.08693213760852814,
-0.06759446859359741,
-0.08612370491027832,
0.1349666565656662,
-0.175648033618927,
0.17783555388450623,
-0.15483301877975464,
-0.16657809913158417,
0.13682587444782257,
0.2998948097229004,
-0.10216791927814484,
0.09434030205011368,
0.2443123757839203,
0.04629768803715706,
-0.0560595765709877,
0.04743875190615654,
0.07257132232189178,
-0.21072903275489807,
0.36221182346343994,
-0.5235639810562134,
-0.30007055401802063,
-0.04146762937307358,
0.09681671112775803,
0.026772238314151764,
-0.19203853607177734,
-0.3231533169746399,
0.2882840931415558,
0.1580442488193512,
-0.13978272676467896,
-0.17260849475860596,
-0.17757444083690643,
-0.43399563431739807,
-0.2991335690021515,
0.3465137779712677,
0.07501198351383209,
-0.5027421116828918,
-0.12278881669044495,
-0.01291557028889656,
-0.05792718753218651,
0.2622867822647095,
0.42779242992401123,
-0.22205686569213867,
0.538048267364502,
-0.08767727762460709,
-0.027470942586660385,
0.801042914390564,
-0.07477029412984848,
-0.171042799949646,
0.24721184372901917,
-0.11224529147148132,
0.16722844541072845,
0.02871318906545639,
0.3875944912433624,
-0.0019190041348338127,
-0.03081868588924408,
0.38124793767929077,
0.6379417181015015,
-0.15168501436710358,
0.02548329345881939,
-0.10614646971225739,
-0.34956642985343933,
0.27074897289276123,
0.24196375906467438,
0.10449346899986267,
-0.030045397579669952,
-0.23651066422462463,
0.3986966013908386,
0.1312621533870697,
-0.024340886622667313,
-0.1928764283657074,
0.1461460292339325,
-0.1458994448184967,
0.02518763765692711,
-0.18390010297298431,
0.10199633985757828,
-0.6190453767776489,
0.23352786898612976,
0.14448203146457672,
0.08388835191726685,
0.23681887984275818,
-0.044368527829647064,
0.3555765450000763,
0.12261108309030533,
0.05143428593873978,
0.15910980105400085,
-0.04666578024625778,
0.12642867863178253,
-0.05838803946971893,
-0.04362756758928299,
-0.3507680296897888,
0.13079914450645447,
-0.35051771998405457,
-0.09408803284168243,
-0.3933817148208618,
0.2961205840110779,
0.3782658278942108,
-0.03691055625677109,
-0.11612765491008759,
0.257525771856308,
-0.33689430356025696,
-0.10079985857009888,
0.05960436910390854,
0.2039336860179901,
0.008492151275277138,
0.3252086639404297,
-0.7214286923408508,
0.4762921929359436,
0.057510197162628174,
-0.017924971878528595,
-0.08479515463113785,
0.13055159151554108,
0.009945487603545189,
-0.2209624946117401,
-0.018168173730373383,
0.2750522494316101,
-0.23169951140880585,
0.1988259106874466,
0.28876668214797974,
-0.28769582509994507,
0.14816169440746307,
0.0720500499010086,
0.1864931881427765,
-0.1110144853591919,
0.47623977065086365,
0.17128829658031464,
0.17858904600143433,
0.3287806212902069,
-0.5321705937385559,
0.20310641825199127,
0.6362370252609253,
-0.01515454612672329,
-0.1437099575996399,
0.17936590313911438,
0.018021419644355774,
-0.2019813060760498,
-0.03624867647886276,
-0.07885129749774933,
0.2486165463924408,
0.10557541996240616,
0.04468761384487152,
-0.018213583156466484,
-0.09769757837057114,
-0.28492289781570435,
0.21820439398288727,
0.10028055310249329,
0.4032105505466461,
-0.09976091235876083,
0.026069751009345055,
0.23116254806518555,
-0.17332789301872253,
0.08780363202095032,
0.249880850315094,
0.17551709711551666,
-0.24388746917247772,
0.01786116696894169,
-0.2885760962963104,
-0.2792428433895111,
-0.05579949915409088,
0.08746685087680817,
0.13963860273361206,
-0.16931785643100739,
-0.09134820103645325,
0.38729098439216614,
-0.009227089583873749,
-0.08408628404140472,
-0.14456327259540558,
0.2974509596824646,
0.14736483991146088,
-0.4759064018726349,
-0.10680673271417618,
-0.06507281959056854,
-0.21300122141838074,
0.031523361802101135,
0.37497052550315857,
0.19188150763511658,
0.222330704331398,
0.0081336610019207,
-0.13919644057750702,
0.18115459382534027,
-0.08397331088781357,
0.2416813224554062,
-0.031938329339027405,
0.13781845569610596,
-0.046962663531303406,
0.11223617196083069,
-0.0727233737707138,
-0.26345980167388916,
-0.061837464570999146,
-0.429096519947052,
0.03967159241437912,
0.18683330714702606,
0.01748155802488327,
0.1602577567100525,
-0.23621909320354462,
-0.13863727450370789,
-0.289046972990036,
-0.39600279927253723,
-0.01829865574836731,
0.18625009059906006,
0.32266682386398315,
0.4042637348175049,
0.003960270434617996,
0.2540595233440399,
0.3930632770061493,
0.06724469363689423,
0.08527881652116776,
-0.15549039840698242,
0.49338218569755554,
-0.27669817209243774,
-0.266829252243042,
-0.14344805479049683,
-0.14479805529117584,
0.24469909071922302,
0.36844587326049805,
-0.6950926184654236,
0.21136067807674408,
-0.09673400223255157,
0.14602124691009521,
-0.09841294586658478,
-0.01586531288921833,
0.22807864844799042,
-0.2083779126405716,
0.06874667853116989,
-0.01793697476387024,
0.09904526174068451,
0.13033005595207214,
0.02588054910302162,
-0.1436578333377838,
0.42202189564704895,
0.4722154438495636,
0.3167874217033386,
0.7827593088150024,
-0.12301819026470184,
-0.24631236493587494,
0.2838461399078369,
-0.22802242636680603,
0.2599782943725586,
-0.19186261296272278,
-0.01625453680753708,
0.06628713756799698,
0.04867049306631088,
-0.0657784715294838,
0.23008973896503448,
-0.10858777165412903,
-0.13981178402900696,
-0.15558448433876038,
0.22440415620803833,
0.0955587700009346,
-0.22741472721099854,
0.22539538145065308,
-0.20803266763687134,
0.21618545055389404,
0.0942547470331192,
0.22961732745170593,
-0.33768606185913086,
-0.42883235216140747,
-0.025798311457037926,
-0.17720972001552582,
0.4478469789028168,
-0.05506230518221855,
-0.28194907307624817,
0.13209481537342072,
-0.693756639957428,
0.09473717957735062,
0.04768528416752815,
0.3188590705394745,
0.0776636004447937,
-0.24230387806892395,
0.004208177328109741,
0.0652078166604042,
0.6028183698654175,
0.04434838145971298,
-0.08510814607143402,
0.21417254209518433,
-0.19752860069274902,
-0.5001963376998901,
0.02252393588423729,
-0.03151191025972366,
-0.08884158730506897,
0.2648521661758423,
0.12026447057723999,
-0.2928028106689453,
-0.5042575597763062,
-0.07943674921989441,
-0.00020402553491294384,
-0.3595188856124878,
-0.09357305616140366,
-0.2238897979259491,
-0.26167458295822144,
-0.02819342352449894,
-0.3826901614665985,
0.021888190880417824,
0.3010372817516327,
-0.12246362119913101,
0.0201726071536541,
-0.17321881651878357,
0.0016045160591602325,
0.23391839861869812,
0.011684682220220566,
0.14289602637290955,
0.4014410674571991,
0.040681470185518265,
-0.061452604830265045,
-0.0342998281121254,
-0.09876605868339539,
0.2059071809053421,
-0.09806300699710846,
-0.16123175621032715,
0.03657034784555435,
0.15343116223812103,
0.3691772520542145,
0.03178824484348297,
0.023263178765773773,
0.12791937589645386,
-0.14821909368038177,
0.03830118477344513,
-0.14445967972278595,
0.37864598631858826,
0.09082312881946564,
-0.34533339738845825,
-0.07255448400974274,
-0.5526954531669617,
0.5314421653747559,
0.2988010346889496,
0.15192611515522003,
0.48851919174194336,
-0.1953694373369217,
-0.35578614473342896,
0.4916248321533203,
0.3968748152256012,
0.5634973645210266,
-0.37892574071884155,
0.488278329372406,
0.7028648853302002,
0.5218997597694397,
0.9219175577163696,
-0.38402408361434937,
0.2837420105934143,
-0.11130359023809433,
-0.3852221369743347,
-0.0714365616440773,
-0.2753489315509796,
-0.3265306055545807,
0.13125737011432648,
0.13309474289417267,
0.2455313801765442,
0.126722514629364,
0.2848149836063385,
0.24128463864326477,
0.35134434700012207,
0.3585633337497711,
-0.4072931408882141,
-0.21222932636737823,
0.013731896877288818,
0.051649563014507294,
-0.14455965161323547,
-0.11486605554819107,
-0.20799045264720917,
0.21388474106788635,
0.05818121135234833,
-0.014009371399879456,
0.15659651160240173,
-0.2624652683734894,
0.2152727097272873,
0.13642607629299164,
-0.13545162975788116,
0.06786555051803589,
0.2597355842590332,
0.1231052577495575,
-0.18345579504966736,
-0.07790296524763107,
-0.07857638597488403,
0.061042480170726776,
-0.011666816659271717,
0.14572271704673767,
-0.04938455671072006,
0.6279585957527161,
-0.05613863840699196,
0.1945367157459259,
0.16612496972084045,
-0.08871294558048248,
-0.5715486407279968,
-0.1340985894203186,
-0.14428310096263885,
0.07634425908327103,
0.18374980986118317,
-0.5355894565582275,
0.2812327444553375,
-0.2824206054210663,
0.20707973837852478,
0.05103122815489769,
0.13851380348205566,
-0.2297205924987793,
0.039810460060834885,
0.01662156917154789,
-0.19243469834327698,
0.20765329897403717,
0.03500457480549812,
0.09302018582820892,
0.031202398240566254,
0.3733731806278229,
0.22355763614177704,
0.020717144012451172,
-0.017776809632778168,
0.0854412093758583,
0.2849075496196747,
-0.07938229292631149,
0.08008500933647156,
0.026714550331234932,
0.2016976922750473,
0.07773049175739288,
0.3733219504356384,
-0.18203888833522797,
0.06518024951219559,
-0.29214492440223694,
-0.16977250576019287,
-0.2766077518463135,
0.339433491230011,
-0.08160261809825897,
0.12775243818759918,
-0.04945923388004303,
0.21621188521385193,
-0.1064225435256958,
0.24101118743419647,
-0.18489307165145874,
-0.053981855511665344,
0.0022446569055318832,
0.04347361624240875,
-0.14907661080360413,
-0.017295964062213898,
0.04800468310713768,
0.11890891194343567,
0.027415594086050987,
0.12441618740558624,
-0.32206061482429504,
-0.14280161261558533,
-0.02780255489051342,
0.20201469957828522,
0.051952119916677475,
-0.25063204765319824,
-0.023800689727067947,
-0.37163621187210083,
-0.33128997683525085,
-0.20353341102600098,
0.11228162050247192,
-0.11092804372310638,
-0.2844444513320923,
0.022438805550336838,
-0.0787317305803299,
0.36041101813316345,
-0.25190919637680054,
0.06195436790585518,
-0.08628301322460175,
0.34060928225517273,
-0.09359625726938248,
0.25554755330085754,
0.15018978714942932,
-0.022436991333961487,
-0.37363651394844055,
-0.12177456170320511,
0.17380215227603912,
-0.15421348810195923,
0.12140513956546783,
-0.328571081161499,
-0.07203707098960876,
-0.257598340511322,
0.02463843673467636,
0.31406277418136597,
-0.19655224680900574,
0.12919332087039948,
0.22686833143234253,
0.0630623996257782,
-0.10534346848726273,
-0.1104499027132988,
0.21441768109798431,
0.026152312755584717,
-0.03034992143511772,
0.22932729125022888,
0.07449840009212494,
0.15259431302547455,
-0.10686443746089935,
-0.030716732144355774,
0.04046764224767685,
-0.5724344253540039,
-0.18100467324256897,
0.4083300232887268,
-0.07960902899503708,
0.06841670721769333,
-0.17246660590171814,
0.10472419857978821,
0.1336464285850525,
0.13838425278663635,
0.3073665499687195,
0.17160212993621826,
-0.10191697627305984,
-0.08759215474128723,
-0.04754035919904709,
-0.3773829936981201,
-0.4539465606212616,
0.48343297839164734,
-0.041963785886764526,
0.571456253528595,
-0.2652560770511627,
0.001651465892791748,
0.11766763031482697,
-0.16160371899604797,
-0.17609857022762299,
0.28459814190864563,
-0.10150378197431564,
-0.018113423138856888,
-0.25577735900878906,
0.05828007310628891,
-0.16195760667324066,
0.2735612988471985,
-0.0926429033279419,
-0.23047123849391937,
-0.21142840385437012,
0.3268531560897827,
0.1237487941980362,
0.169804647564888,
0.08803112804889679,
0.08871430158615112,
0.20860150456428528,
-0.14125806093215942,
0.24054531753063202,
-0.28913414478302,
-0.09723284840583801,
-0.3500290811061859,
0.015348119661211967,
0.08870019018650055,
0.3145703375339508,
-0.30286291241645813,
0.1288619339466095,
0.10812981426715851,
-0.06667671352624893,
-0.015008230693638325,
0.2600981891155243,
0.23029488325119019,
0.11595521867275238,
0.24547173082828522,
-0.045211441814899445,
-0.025874607264995575,
0.14597786962985992,
0.180082306265831,
0.16942837834358215,
-0.5887806415557861,
0.6027829647064209,
0.18034836649894714,
-0.0968208760023117,
-0.008341532200574875,
0.18996262550354004,
-0.05924639478325844,
-0.03979812189936638,
0.489726185798645,
-0.26842519640922546,
0.03991950303316116,
0.056890394538640976,
0.01327614113688469,
-0.18620270490646362,
0.6324126124382019,
0.08844924718141556,
0.49170365929603577,
-0.10871750861406326,
0.026488706469535828,
-0.4697314500808716,
0.12125231325626373,
-0.11352185904979706,
0.1386706531047821,
0.2599012553691864,
0.2758069932460785,
0.15131691098213196,
0.17945997416973114,
-0.4360817074775696,
-0.18453650176525116,
0.00546585489064455,
0.09761235117912292,
-0.12733064591884613,
-0.1538161337375641,
-0.49346429109573364,
0.120275117456913,
-0.15698720514774323,
-0.49851176142692566,
0.054586682468652725,
-0.4139026403427124,
-0.10423582792282104,
-0.09382889419794083,
0.253180593252182,
0.3283693194389343,
0.46398043632507324,
0.28149116039276123,
-0.033510975539684296,
-0.04955582320690155,
0.04295963793992996,
-0.0872577354311943,
-0.11083066463470459,
-0.028888264670968056,
-0.3553536832332611,
-0.0496390163898468,
-0.17677126824855804,
0.07457371056079865,
-0.27969491481781006,
-0.025637540966272354,
-0.3028118908405304,
-0.2440079003572464,
0.01799812912940979,
-0.08510939031839371,
-0.12512291967868805,
0.07936549186706543,
-0.29182329773902893,
0.18006496131420135,
0.32479479908943176,
0.39626315236091614,
-0.1290537714958191,
-0.13008853793144226,
-0.2926555275917053,
0.14886412024497986,
0.3681568503379822,
-0.6422930955886841,
-0.17142197489738464,
0.04930239915847778,
-0.15187057852745056,
0.24562564492225647,
0.0641329288482666,
-0.27930429577827454,
-0.20046266913414001,
0.3068371117115021,
-0.12597054243087769,
-0.19656680524349213,
0.19951152801513672,
0.3359585702419281,
-0.05168163776397705,
-0.1160435825586319,
0.27684786915779114,
-0.03130447492003441,
-0.4617123305797577,
-0.23161359131336212,
-0.43983322381973267
] |
https://github.com/huggingface/datasets/issues/193 | [Tensorflow] Use something else than `from_tensor_slices()` | Could you send me the code you used to run create the dataset using `.from_generator` ? What version of tensorflow are you using ? | In the example notebook, the TF Dataset is built using `from_tensor_slices()` :
```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
labels = {"output_1": train_tf_dataset["start_positions"]}
labels["output_2"] = train_tf_dataset["end_positions"]
tfdataset = tf.data.Dataset.from_tensor_slices((features, labels)).batch(8)
```
But according to [official tensorflow documentation](https://www.tensorflow.org/guide/data#consuming_numpy_arrays), this will load the entire dataset to memory.
**This defeats one purpose of this library, which is lazy loading.**
Is there any other way to load the `nlp` dataset into TF dataset lazily ?
---
For example, is it possible to use [Arrow dataset](https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowDataset) ? If yes, is there any code example ? | 24 | [Tensorflow] Use something else than `from_tensor_slices()`
In the example notebook, the TF Dataset is built using `from_tensor_slices()` :
```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
labels = {"output_1": train_tf_dataset["start_positions"]}
labels["output_2"] = train_tf_dataset["end_positions"]
tfdataset = tf.data.Dataset.from_tensor_slices((features, labels)).batch(8)
```
But according to [official tensorflow documentation](https://www.tensorflow.org/guide/data#consuming_numpy_arrays), this will load the entire dataset to memory.
**This defeats one purpose of this library, which is lazy loading.**
Is there any other way to load the `nlp` dataset into TF dataset lazily ?
---
For example, is it possible to use [Arrow dataset](https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowDataset) ? If yes, is there any code example ?
Could you send me the code you used to run create the dataset using `.from_generator` ? What version of tensorflow are you using ? | [
-0.1686098277568817,
-0.09398830682039261,
0.011844169348478317,
0.16997693479061127,
0.27237045764923096,
0.0823572501540184,
0.2256460040807724,
0.38973069190979004,
-0.050376541912555695,
0.005149416625499725,
-0.08119415491819382,
0.6080824732780457,
-0.14292097091674805,
-0.014412950724363327,
0.2508256435394287,
-0.21652516722679138,
-0.10149351507425308,
0.2596185803413391,
-0.1496252566576004,
-0.0935942679643631,
-0.014412535354495049,
-0.03481736034154892,
-0.14135733246803284,
-0.027524136006832123,
-0.06012880802154541,
-0.08392547070980072,
0.07913264632225037,
-0.09566854685544968,
0.3711802363395691,
0.03904271125793457,
0.2916146218776703,
0.0025849156081676483,
-0.02442087233066559,
0.16511137783527374,
-0.00010320143337594345,
0.32157468795776367,
0.03437269479036331,
-0.1477328985929489,
0.04883991926908493,
-0.07913137972354889,
0.1653173267841339,
-0.2739705741405487,
0.19196182489395142,
-0.3028233051300049,
-0.054379045963287354,
0.008168972097337246,
0.19384194910526276,
-0.02881579101085663,
0.3141268789768219,
0.1588185429573059,
0.21697206795215607,
0.4294997453689575,
-0.11771450936794281,
0.3017027974128723,
0.11722411215305328,
-0.17708152532577515,
-0.19004741311073303,
-0.22906650602817535,
-0.21755391359329224,
-0.014429546892642975,
0.03290630131959915,
0.26630115509033203,
-0.2041044682264328,
0.13051089644432068,
0.4554975926876068,
0.1430780291557312,
-0.11107172816991806,
-0.3703576326370239,
-0.26494020223617554,
0.378965824842453,
0.22448182106018066,
-0.08395039290189743,
-0.1515456736087799,
-0.4547223746776581,
-0.17095226049423218,
-0.30649858713150024,
-0.15057682991027832,
0.11813399940729141,
-0.2600310742855072,
0.12261305749416351,
-0.10149882733821869,
-0.0880129337310791,
-0.23205605149269104,
0.1448359191417694,
0.16639269888401031,
-0.042912617325782776,
0.08226311951875687,
0.10815662145614624,
0.15611283481121063,
0.04901379719376564,
0.24615411460399628,
0.05889111012220383,
0.35808175802230835,
0.36975133419036865,
-0.34041744470596313,
0.05369757115840912,
0.17792092263698578,
-0.5166316032409668,
-0.0021290257573127747,
-0.2505266070365906,
0.32315099239349365,
0.17214274406433105,
-0.24499277770519257,
0.1835710108280182,
-0.07256843149662018,
0.01231042668223381,
-0.41781705617904663,
0.1140064001083374,
-0.11787016689777374,
-0.4833918809890747,
-0.02392812818288803,
0.021701965481042862,
-0.23941385746002197,
-0.04856516048312187,
0.11936338245868683,
-0.46755555272102356,
-0.03389650210738182,
0.2352789044380188,
-0.3758569359779358,
-0.37095242738723755,
-0.19662556052207947,
0.056530844420194626,
0.01388191431760788,
0.27162668108940125,
-0.18506407737731934,
0.42958906292915344,
0.15240806341171265,
-0.1067647784948349,
-0.3398880064487457,
0.004123427905142307,
-0.28825172781944275,
0.12291799485683441,
-0.128438800573349,
-0.11231770366430283,
0.14382165670394897,
-0.07857148349285126,
0.202426016330719,
-0.08083003759384155,
-0.17189085483551025,
0.13403822481632233,
0.28055456280708313,
-0.10108020901679993,
0.08383195102214813,
0.21504929661750793,
0.05136341229081154,
-0.013148441910743713,
0.04464422166347504,
0.0967692881822586,
-0.16510331630706787,
0.3000507652759552,
-0.5144059062004089,
-0.24342922866344452,
-0.03408610820770264,
0.20138007402420044,
0.11621686816215515,
-0.14932671189308167,
-0.25425857305526733,
0.3058803975582123,
0.13064295053482056,
-0.05816652625799179,
-0.17962652444839478,
-0.16915199160575867,
-0.41828644275665283,
-0.32790136337280273,
0.31852301955223083,
0.058431752026081085,
-0.44932541251182556,
-0.07593970000743866,
-0.02289440482854843,
-0.00007997453212738037,
0.2840339243412018,
0.41180548071861267,
-0.2025938779115677,
0.4759204685688019,
-0.06604333221912384,
0.06232486665248871,
0.72726970911026,
-0.0797073096036911,
-0.2046176642179489,
0.24727146327495575,
-0.18754437565803528,
0.16651341319084167,
-0.05649483948945999,
0.3881370425224304,
0.014578795060515404,
0.006611668039113283,
0.38259804248809814,
0.6268607378005981,
-0.13027739524841309,
0.1262756735086441,
-0.16897960007190704,
-0.26857030391693115,
0.30446285009384155,
0.2909621000289917,
0.05505335330963135,
-0.09941775351762772,
-0.2690315246582031,
0.3530552089214325,
0.14091569185256958,
-0.04823555424809456,
-0.1705198884010315,
0.17430956661701202,
-0.10140752792358398,
0.0338936410844326,
-0.19647005200386047,
0.02353718876838684,
-0.6025984883308411,
0.2567143738269806,
0.21885161101818085,
0.11899276822805405,
0.14820294082164764,
-0.09703925251960754,
0.27089357376098633,
0.1100616380572319,
0.03228224813938141,
0.1563066691160202,
0.11244985461235046,
0.11767585575580597,
-0.01731005497276783,
-0.010448114946484566,
-0.25076234340667725,
0.2139793187379837,
-0.3762323558330536,
-0.16274914145469666,
-0.35741373896598816,
0.2085111141204834,
0.30177509784698486,
-0.035390328615903854,
0.004790168255567551,
0.2599482834339142,
-0.2557673454284668,
-0.11474455147981644,
0.05725495144724846,
0.27530282735824585,
-0.028167078271508217,
0.23908807337284088,
-0.626108705997467,
0.3982264995574951,
-0.01640932820737362,
-0.06816980242729187,
-0.05593923479318619,
0.14532607793807983,
0.04535271227359772,
-0.17168757319450378,
0.016372691839933395,
0.22037409245967865,
-0.1982620507478714,
0.0816420316696167,
0.21227948367595673,
-0.25049859285354614,
0.1703198403120041,
0.02143106237053871,
0.17781007289886475,
-0.09024903178215027,
0.3996802568435669,
0.05171949043869972,
0.12820933759212494,
0.2929065525531769,
-0.5027151107788086,
0.24715286493301392,
0.6455687284469604,
0.0017064344137907028,
-0.060609929263591766,
0.2191503643989563,
-0.0046081021428108215,
-0.18649226427078247,
-0.11462296545505524,
-0.0755285769701004,
0.22046300768852234,
0.23334906995296478,
0.004561223089694977,
-0.04915616661310196,
-0.17390264570713043,
-0.23643594980239868,
0.22989504039287567,
0.10348096489906311,
0.3950205445289612,
-0.09640935808420181,
0.04655270650982857,
0.15590442717075348,
-0.21102258563041687,
0.05060579255223274,
0.22332820296287537,
0.2867368757724762,
-0.20513232052326202,
-0.03855033963918686,
-0.2432168871164322,
-0.2629225552082062,
-0.07050161063671112,
0.01839357614517212,
0.10047151148319244,
-0.17765039205551147,
-0.06376825273036957,
0.32688218355178833,
-0.005278110504150391,
-0.0022929199039936066,
-0.10702614486217499,
0.2660936713218689,
0.25394612550735474,
-0.36759284138679504,
-0.048126786947250366,
-0.09654653817415237,
-0.25975215435028076,
0.12326259911060333,
0.3457806706428528,
0.26507654786109924,
0.3060998022556305,
0.04240216314792633,
-0.029359718784689903,
0.15714672207832336,
-0.029308415949344635,
0.16931912302970886,
-0.18968917429447174,
0.12898249924182892,
-0.0720650851726532,
0.20253294706344604,
-0.10920309275388718,
-0.2199781984090805,
-0.04013655334711075,
-0.42298492789268494,
0.04551757872104645,
0.19250144064426422,
0.016064487397670746,
0.05312595143914223,
-0.22644716501235962,
-0.22007009387016296,
-0.2942710816860199,
-0.4235444664955139,
-0.011317901313304901,
0.11504678428173065,
0.2867080271244049,
0.46687254309654236,
-0.032427191734313965,
0.2744038701057434,
0.35955268144607544,
0.13477610051631927,
0.02100229822099209,
-0.13184306025505066,
0.5142495632171631,
-0.2914406657218933,
-0.2923903167247772,
-0.12593911588191986,
-0.15778809785842896,
0.21387837827205658,
0.2645535469055176,
-0.6998733878135681,
0.16331243515014648,
-0.18016740679740906,
0.09063294529914856,
-0.17192870378494263,
-0.023034224286675453,
0.2796552777290344,
-0.18283775448799133,
-0.037739407271146774,
-0.06421390175819397,
0.12822078168392181,
0.1593089997768402,
-0.0026168711483478546,
-0.17444071173667908,
0.2911268472671509,
0.43631649017333984,
0.2932071387767792,
0.6823476552963257,
-0.049521900713443756,
-0.24725846946239471,
0.24511629343032837,
-0.20342181622982025,
0.17989686131477356,
-0.15880486369132996,
-0.12973527610301971,
0.06918278336524963,
0.04686060547828674,
-0.019307183101773262,
0.2627427577972412,
-0.07913021743297577,
-0.19225265085697174,
-0.08546385169029236,
0.19333986937999725,
0.02322906255722046,
-0.2450512796640396,
0.2765367925167084,
-0.19784586131572723,
0.1782020926475525,
0.10248073935508728,
0.17246127128601074,
-0.38271018862724304,
-0.43289726972579956,
-0.02819056063890457,
-0.2183409184217453,
0.36756956577301025,
-0.05496903136372566,
-0.3525266945362091,
0.12331695854663849,
-0.6885601878166199,
0.07143362611532211,
0.09516589343547821,
0.2950817942619324,
0.044007617980241776,
-0.26446810364723206,
0.02743583917617798,
0.06361382454633713,
0.5770883560180664,
0.08534595370292664,
-0.0374402180314064,
0.19421914219856262,
-0.06062142550945282,
-0.5440307259559631,
0.027683336287736893,
-0.083886057138443,
-0.02656669169664383,
0.25266408920288086,
0.13720032572746277,
-0.3163083791732788,
-0.5172994136810303,
-0.05490119010210037,
0.011884225532412529,
-0.32387733459472656,
-0.10303252935409546,
-0.25590822100639343,
-0.24362275004386902,
-0.012446063570678234,
-0.29287317395210266,
0.0692630335688591,
0.26373085379600525,
-0.11182914674282074,
-0.007646054029464722,
-0.10520246624946594,
-0.001755502074956894,
0.2264765202999115,
0.021024271845817566,
0.21798670291900635,
0.49741891026496887,
0.09195971488952637,
-0.006784416735172272,
0.044760119169950485,
-0.1746143400669098,
0.21001891791820526,
-0.10321353375911713,
-0.1212226003408432,
-0.0029215235263109207,
0.11823958158493042,
0.3274335265159607,
0.04370652884244919,
0.04576556012034416,
0.08590245991945267,
-0.2112955003976822,
0.11721108853816986,
-0.2157902717590332,
0.4107756018638611,
0.16171136498451233,
-0.28921425342559814,
-0.10195816308259964,
-0.45165905356407166,
0.4895883798599243,
0.22257594764232635,
0.10899336636066437,
0.4912770986557007,
-0.17228461802005768,
-0.36280930042266846,
0.4391489624977112,
0.33841994404792786,
0.5404884219169617,
-0.3218809962272644,
0.4336530864238739,
0.7526194453239441,
0.48587948083877563,
0.8558774590492249,
-0.3515866994857788,
0.28582507371902466,
-0.15107737481594086,
-0.3399323523044586,
0.00625995360314846,
-0.22546721994876862,
-0.40141764283180237,
0.06774863600730896,
0.068091481924057,
0.1856304109096527,
0.08648006618022919,
0.22489555180072784,
0.17575769126415253,
0.3943643271923065,
0.36009690165519714,
-0.4310414791107178,
-0.214525043964386,
0.14980143308639526,
-0.03654587268829346,
-0.15512952208518982,
-0.05978808179497719,
-0.20871591567993164,
0.18185418844223022,
0.06399624794721603,
0.0220143124461174,
0.15056127309799194,
-0.18615037202835083,
0.2835206985473633,
0.05520600080490112,
-0.06650624424219131,
-0.013074557296931744,
0.2632400691509247,
0.12207894027233124,
-0.17733296751976013,
-0.0984831377863884,
-0.057642001658678055,
0.02004125714302063,
0.0036127837374806404,
0.08650209754705429,
-0.05334336310625076,
0.6400724053382874,
-0.049178384244441986,
0.13697367906570435,
0.10900606215000153,
-0.07215587794780731,
-0.48971885442733765,
-0.1959056705236435,
-0.11551913619041443,
0.0858885869383812,
0.08319633454084396,
-0.547953724861145,
0.23642683029174805,
-0.20112018287181854,
0.18663056194782257,
0.1621534526348114,
0.12269800156354904,
-0.19497346878051758,
0.09241079539060593,
0.09988820552825928,
-0.21338355541229248,
0.2217307984828949,
0.03510220721364021,
0.10077407956123352,
0.0912485271692276,
0.3558182120323181,
0.2210889607667923,
-0.025953620672225952,
-0.07953093945980072,
0.08418352156877518,
0.3034347891807556,
-0.06420763581991196,
0.035456523299217224,
0.04730710759758949,
0.288316011428833,
0.07017548382282257,
0.3478030860424042,
-0.22790850698947906,
0.014587372541427612,
-0.1992013156414032,
-0.18210981786251068,
-0.30683788657188416,
0.3347513675689697,
-0.06750883162021637,
0.12765052914619446,
-0.025996500626206398,
0.2155904620885849,
-0.07443252205848694,
0.25938680768013,
-0.3228645324707031,
-0.04293408989906311,
-0.022495359182357788,
0.0756106972694397,
-0.10007309913635254,
-0.12442082911729813,
0.09797748923301697,
0.09842254221439362,
0.14724940061569214,
0.1296602487564087,
-0.358987033367157,
-0.2738020122051239,
-0.02206329256296158,
0.11938446760177612,
0.021814584732055664,
-0.2305416762828827,
-0.02456890419125557,
-0.388022243976593,
-0.3245272636413574,
-0.17464721202850342,
0.10038813948631287,
-0.14644457399845123,
-0.29161930084228516,
0.05987213924527168,
-0.11217352747917175,
0.27732694149017334,
-0.09360376000404358,
0.00846327655017376,
-0.17180174589157104,
0.28409406542778015,
-0.06256428360939026,
0.1911998987197876,
0.13741609454154968,
-0.07968723773956299,
-0.3882512152194977,
-0.13485881686210632,
0.1281261146068573,
-0.10049576312303543,
-0.0008420981466770172,
-0.3645164370536804,
-0.08045905828475952,
-0.20343463122844696,
0.09064093977212906,
0.24004027247428894,
-0.25075528025627136,
0.034920692443847656,
0.21327045559883118,
0.20128269493579865,
-0.12772279977798462,
-0.10396610200405121,
0.19983381032943726,
0.023196738213300705,
0.06183870509266853,
0.12107584625482559,
-0.021087300032377243,
0.1645384281873703,
-0.10702909529209137,
0.015114806592464447,
0.051866620779037476,
-0.5421467423439026,
-0.26469677686691284,
0.3222053050994873,
-0.15680630505084991,
-0.034058090299367905,
-0.08664076775312424,
0.13565927743911743,
0.12472369521856308,
0.2581653892993927,
0.31806832551956177,
0.23370836675167084,
-0.07991020381450653,
-0.07542462646961212,
-0.10472934693098068,
-0.3642435371875763,
-0.4094371497631073,
0.4181023836135864,
-0.13467052578926086,
0.5021536350250244,
-0.251481294631958,
0.0272148959338665,
0.1200004518032074,
-0.2684727907180786,
-0.1701836735010147,
0.30529215931892395,
-0.21323728561401367,
-0.01148919016122818,
-0.24748308956623077,
0.0629420056939125,
-0.1118248999118805,
0.22725602984428406,
-0.06825117766857147,
-0.19298408925533295,
-0.18089815974235535,
0.29027456045150757,
0.0493139810860157,
0.19488759338855743,
0.07147763669490814,
0.18252313137054443,
0.23883718252182007,
-0.12766583263874054,
0.2389977127313614,
-0.2271493822336197,
-0.09096384048461914,
-0.40485456585884094,
0.02497946098446846,
0.10322326421737671,
0.33521679043769836,
-0.3399101495742798,
0.12908819317817688,
0.0999295562505722,
-0.10254407674074173,
-0.06795084476470947,
0.2378438413143158,
0.2075454592704773,
0.1221877932548523,
0.29464390873908997,
0.07240201532840729,
-0.12988510727882385,
0.14953750371932983,
0.19643737375736237,
0.17680440843105316,
-0.46683070063591003,
0.49007347226142883,
0.19497531652450562,
-0.020242858678102493,
-0.10694965720176697,
0.1463768184185028,
-0.1831081211566925,
-0.089093416929245,
0.521966814994812,
-0.24887987971305847,
0.04972730576992035,
-0.088209368288517,
0.07930800318717957,
-0.22433125972747803,
0.6939452290534973,
0.033030711114406586,
0.46245676279067993,
-0.1568174660205841,
0.01007494330406189,
-0.4859360158443451,
0.09705594927072525,
-0.19249571859836578,
0.15192368626594543,
0.24726279079914093,
0.3328301012516022,
0.10673506557941437,
0.18085797131061554,
-0.4369942545890808,
-0.18489594757556915,
-0.05393590033054352,
0.11275489628314972,
-0.20269322395324707,
-0.06505998969078064,
-0.5096170902252197,
0.11405152827501297,
-0.07577045261859894,
-0.4709782004356384,
0.1125391274690628,
-0.43344634771347046,
0.05631042271852493,
-0.09103848785161972,
0.2783651649951935,
0.2807081639766693,
0.41367271542549133,
0.33369937539100647,
-0.041489891707897186,
-0.04722532629966736,
-0.01979193463921547,
-0.10569283366203308,
-0.12665528059005737,
0.02345750294625759,
-0.34460675716400146,
-0.07571867853403091,
-0.05020666494965553,
0.21799996495246887,
-0.23613232374191284,
-0.0374738909304142,
-0.23950162529945374,
-0.20596855878829956,
0.09328204393386841,
-0.11421603709459305,
-0.09886123985052109,
0.11413223296403885,
-0.1716415286064148,
0.18321622908115387,
0.1843816041946411,
0.43261075019836426,
-0.09274697303771973,
-0.05656100809574127,
-0.2720027565956116,
-0.037574395537376404,
0.46004101634025574,
-0.5970888733863831,
-0.23472294211387634,
0.09746084362268448,
-0.06007564067840576,
0.22572439908981323,
0.04289388656616211,
-0.29877716302871704,
-0.15917867422103882,
0.29100289940834045,
-0.1312485933303833,
-0.24028590321540833,
0.27734342217445374,
0.3229195475578308,
-0.08262727409601212,
-0.08083811402320862,
0.29049015045166016,
-0.0606854110956192,
-0.3934634029865265,
-0.15429000556468964,
-0.45488864183425903
] |
https://github.com/huggingface/datasets/issues/193 | [Tensorflow] Use something else than `from_tensor_slices()` | I'm using TF2.2
Here is my code :
```
import nlp
from transformers import BartTokenizer
tokenizer = BartTokenizer.from_pretrained('bart-large')
def encode(sample):
article_inputs = tokenizer.encode_plus(sample["article"], max_length=tokenizer.model_max_length, pad_to_max_length=True)
summary_inputs = tokenizer.encode_plus(sample["highlights"], max_length=tokenizer.model_max_length, pad_to_max_length=True)
article_inputs.update({"lm_labels": summary_inputs['input_ids']})
return article_inputs
cnn_dm = nlp.load_dataset('cnn_dailymail', '3.0.0', split='test')
cnn_dm = cnn_dm.map(encode)
def gen():
for sample in cnn_dm:
s = {}
s['input_ids'] = sample['input_ids']
s['attention_mask'] = sample['attention_mask']
s['lm_labels'] = sample['lm_labels']
yield s
dataset = tf.data.Dataset.from_generator(gen, output_types={k: tf.int32 for k in ['input_ids', 'attention_mask', 'lm_labels']}, output_shapes={k: tf.TensorShape([tokenizer.model_max_length]) for k in ['input_ids', 'attention_mask', 'lm_labels']}
``` | In the example notebook, the TF Dataset is built using `from_tensor_slices()` :
```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
labels = {"output_1": train_tf_dataset["start_positions"]}
labels["output_2"] = train_tf_dataset["end_positions"]
tfdataset = tf.data.Dataset.from_tensor_slices((features, labels)).batch(8)
```
But according to [official tensorflow documentation](https://www.tensorflow.org/guide/data#consuming_numpy_arrays), this will load the entire dataset to memory.
**This defeats one purpose of this library, which is lazy loading.**
Is there any other way to load the `nlp` dataset into TF dataset lazily ?
---
For example, is it possible to use [Arrow dataset](https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowDataset) ? If yes, is there any code example ? | 82 | [Tensorflow] Use something else than `from_tensor_slices()`
In the example notebook, the TF Dataset is built using `from_tensor_slices()` :
```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
labels = {"output_1": train_tf_dataset["start_positions"]}
labels["output_2"] = train_tf_dataset["end_positions"]
tfdataset = tf.data.Dataset.from_tensor_slices((features, labels)).batch(8)
```
But according to [official tensorflow documentation](https://www.tensorflow.org/guide/data#consuming_numpy_arrays), this will load the entire dataset to memory.
**This defeats one purpose of this library, which is lazy loading.**
Is there any other way to load the `nlp` dataset into TF dataset lazily ?
---
For example, is it possible to use [Arrow dataset](https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowDataset) ? If yes, is there any code example ?
I'm using TF2.2
Here is my code :
```
import nlp
from transformers import BartTokenizer
tokenizer = BartTokenizer.from_pretrained('bart-large')
def encode(sample):
article_inputs = tokenizer.encode_plus(sample["article"], max_length=tokenizer.model_max_length, pad_to_max_length=True)
summary_inputs = tokenizer.encode_plus(sample["highlights"], max_length=tokenizer.model_max_length, pad_to_max_length=True)
article_inputs.update({"lm_labels": summary_inputs['input_ids']})
return article_inputs
cnn_dm = nlp.load_dataset('cnn_dailymail', '3.0.0', split='test')
cnn_dm = cnn_dm.map(encode)
def gen():
for sample in cnn_dm:
s = {}
s['input_ids'] = sample['input_ids']
s['attention_mask'] = sample['attention_mask']
s['lm_labels'] = sample['lm_labels']
yield s
dataset = tf.data.Dataset.from_generator(gen, output_types={k: tf.int32 for k in ['input_ids', 'attention_mask', 'lm_labels']}, output_shapes={k: tf.TensorShape([tokenizer.model_max_length]) for k in ['input_ids', 'attention_mask', 'lm_labels']}
``` | [
-0.12176664173603058,
-0.02593163400888443,
0.047091420739889145,
0.1898202747106552,
0.19800370931625366,
0.15442749857902527,
0.24837557971477509,
0.45679691433906555,
-0.037150345742702484,
-0.05661487579345703,
-0.14168617129325867,
0.6093761324882507,
-0.1823762059211731,
-0.03136494383215904,
0.24518440663814545,
-0.16024306416511536,
-0.05153343826532364,
0.2101798951625824,
-0.08378109335899353,
-0.05111920088529587,
0.04143429547548294,
-0.10304632782936096,
-0.11337640881538391,
-0.08961835503578186,
-0.08411601930856705,
0.037810683250427246,
0.02680412121117115,
-0.15933364629745483,
0.4063459038734436,
-0.015848200768232346,
0.34805411100387573,
0.0354810431599617,
-0.061999354511499405,
0.10191073268651962,
-0.00011394677858334035,
0.38300830125808716,
0.03163420408964157,
-0.1697196662425995,
0.005115790292620659,
-0.04868346452713013,
0.18722325563430786,
-0.22094641625881195,
0.24761855602264404,
-0.2797371447086334,
0.022960029542446136,
-0.04330676421523094,
0.228247731924057,
0.02149239182472229,
0.274108350276947,
0.05634458735585213,
0.11358040571212769,
0.4625847637653351,
-0.22616219520568848,
0.3665572702884674,
0.15347087383270264,
-0.10670578479766846,
-0.13823066651821136,
-0.2763128876686096,
-0.21094036102294922,
0.041313812136650085,
0.0462956503033638,
0.2148604542016983,
-0.2967182695865631,
0.10010874271392822,
0.48837122321128845,
0.13461041450500488,
-0.11587323993444443,
-0.29013538360595703,
-0.20416900515556335,
0.3537537455558777,
0.1901262253522873,
-0.07160364091396332,
-0.176860049366951,
-0.5691706538200378,
-0.2341982126235962,
-0.21981756389141083,
-0.214105486869812,
0.04874373972415924,
-0.1875368356704712,
0.1386624127626419,
-0.21671627461910248,
-0.09149636328220367,
-0.19212813675403595,
0.16961535811424255,
0.17300380766391754,
0.08847001194953918,
0.15939004719257355,
0.1527353972196579,
0.16368268430233002,
0.0402703583240509,
0.27683913707733154,
-0.011180374771356583,
0.29415324330329895,
0.4132719337940216,
-0.3397204875946045,
-0.0049701593816280365,
0.14997586607933044,
-0.5529506206512451,
-0.002599624916911125,
-0.21910403668880463,
0.31478384137153625,
0.21479743719100952,
-0.25012966990470886,
0.17884549498558044,
-0.006411362439393997,
-0.06401263177394867,
-0.396527498960495,
0.14390519261360168,
-0.17764908075332642,
-0.5946309566497803,
0.0709008276462555,
0.02544734627008438,
-0.29087966680526733,
0.09226294606924057,
0.05414499714970589,
-0.5405896306037903,
-0.0903407409787178,
0.227428138256073,
-0.3082317113876343,
-0.45655399560928345,
-0.24953967332839966,
0.03222159296274185,
0.02825886756181717,
0.26590344309806824,
-0.17248530685901642,
0.4949045777320862,
0.0468011274933815,
-0.12600718438625336,
-0.2357965111732483,
0.07146383821964264,
-0.20548024773597717,
0.08548416197299957,
-0.05327289551496506,
-0.0908421128988266,
0.18941828608512878,
-0.0446491502225399,
0.23619991540908813,
-0.18066555261611938,
-0.15809719264507294,
0.1609501838684082,
0.2584719657897949,
-0.09254209697246552,
0.07164009660482407,
0.2176823914051056,
-0.014462517574429512,
0.06174687296152115,
0.047353651374578476,
0.11339722573757172,
-0.23381265997886658,
0.35670915246009827,
-0.5510233640670776,
-0.22753360867500305,
-0.004840852692723274,
0.08490916341543198,
0.10352516174316406,
-0.23398065567016602,
-0.3640980124473572,
0.35490846633911133,
0.10241933912038803,
-0.12468791007995605,
-0.14371708035469055,
-0.14855515956878662,
-0.4110416769981384,
-0.26339447498321533,
0.2886543869972229,
0.11818336695432663,
-0.37230175733566284,
-0.1996258646249771,
0.013992603868246078,
0.03928866237401962,
0.2183590829372406,
0.44404229521751404,
-0.22877204418182373,
0.4910328686237335,
-0.06854419410228729,
0.17658208310604095,
0.7466118335723877,
-0.1683417558670044,
-0.21639244258403778,
0.2665832042694092,
-0.10920847207307816,
0.20277346670627594,
0.007078424096107483,
0.4875006675720215,
0.05561169609427452,
-0.028244778513908386,
0.327843576669693,
0.6070598363876343,
-0.11004224419593811,
0.09091212600469589,
-0.06263850629329681,
-0.35401713848114014,
0.38336843252182007,
0.22360147535800934,
0.04943356290459633,
-0.08908843249082565,
-0.24513199925422668,
0.48383060097694397,
0.15792742371559143,
0.006073672324419022,
-0.18220338225364685,
0.1302788257598877,
-0.18597282469272614,
0.005775615572929382,
-0.22100533545017242,
0.0439634770154953,
-0.626213550567627,
0.2945079207420349,
0.2898067235946655,
0.019800759851932526,
0.2248508483171463,
-0.1320510059595108,
0.3046323359012604,
0.08697177469730377,
0.05847340449690819,
0.15581576526165009,
-0.03637566789984703,
0.15324527025222778,
-0.008286310359835625,
-0.05614299327135086,
-0.3398273289203644,
0.2135774791240692,
-0.35561296343803406,
-0.08592253923416138,
-0.2873382270336151,
0.26861265301704407,
0.4462813138961792,
0.006337590515613556,
-0.13960552215576172,
0.2558356821537018,
-0.23948130011558533,
-0.09090784192085266,
0.09431416541337967,
0.22145769000053406,
-0.03742823749780655,
0.3102300763130188,
-0.6426635384559631,
0.5175512433052063,
-0.00729936920106411,
-0.05198519304394722,
-0.03803402930498123,
0.15125687420368195,
0.04083907604217529,
-0.22987133264541626,
-0.04504137486219406,
0.20381388068199158,
-0.18118439614772797,
0.252112478017807,
0.22757010161876678,
-0.29739847779273987,
0.08644019067287445,
0.09497058391571045,
0.14749155938625336,
-0.10604110360145569,
0.38184425234794617,
0.0820869654417038,
0.2589591443538666,
0.29437315464019775,
-0.4201216995716095,
0.20113766193389893,
0.5873521566390991,
-0.03383904695510864,
-0.08823416382074356,
0.2429153025150299,
-0.08980477601289749,
-0.21951758861541748,
-0.04968205839395523,
-0.1579289585351944,
0.23874813318252563,
0.15569506585597992,
0.04756339266896248,
-0.01836027018725872,
-0.08513352274894714,
-0.189578115940094,
0.23301160335540771,
0.13817881047725677,
0.34429094195365906,
-0.10489457100629807,
0.07945506274700165,
0.24394959211349487,
-0.20069316029548645,
0.12063638865947723,
0.20413264632225037,
0.16148771345615387,
-0.18216632306575775,
0.020874956622719765,
-0.2740585505962372,
-0.3233441710472107,
-0.06881661713123322,
-0.01563415303826332,
0.11983832716941833,
-0.1766922026872635,
-0.08395637571811676,
0.35642576217651367,
0.03898804262280464,
-0.026908492669463158,
-0.12038229405879974,
0.3014894723892212,
0.1829606145620346,
-0.4852120280265808,
-0.1409328579902649,
-0.0722895935177803,
-0.1876290738582611,
0.012351103127002716,
0.341431200504303,
0.24763786792755127,
0.21397319436073303,
0.1156187579035759,
-0.10640104860067368,
0.09337572008371353,
-0.13714498281478882,
0.22248098254203796,
-0.14118948578834534,
0.07441708445549011,
-0.09138825535774231,
0.0858772024512291,
-0.13170884549617767,
-0.23741337656974792,
-0.13842526078224182,
-0.4001227915287018,
0.015284059569239616,
0.178102508187294,
0.04398305341601372,
0.14078150689601898,
-0.17305465042591095,
-0.054111726582050323,
-0.31138139963150024,
-0.368055135011673,
0.025136403739452362,
0.164383202791214,
0.2630552053451538,
0.42665642499923706,
-0.09771574288606644,
0.2875244617462158,
0.2841937243938446,
0.05660056322813034,
0.0843755453824997,
-0.059109944850206375,
0.5510886907577515,
-0.21195615828037262,
-0.20756618678569794,
-0.1972452700138092,
-0.1682773232460022,
0.12386772036552429,
0.2879939675331116,
-0.7350272536277771,
0.25820624828338623,
-0.14762330055236816,
0.05228989198803902,
-0.136073037981987,
-0.04323390871286392,
0.3010389506816864,
-0.24622800946235657,
0.05798213928937912,
-0.01921362616121769,
0.042981427162885666,
0.07409325987100601,
0.015041571110486984,
-0.21246114373207092,
0.2835451662540436,
0.42533111572265625,
0.35637781023979187,
0.8198503255844116,
-0.08152447640895844,
-0.19571217894554138,
0.21599642932415009,
-0.2431856095790863,
0.2042168378829956,
-0.2124851942062378,
-0.07977622747421265,
0.073217011988163,
0.014921128749847412,
-0.019206777215003967,
0.30555546283721924,
-0.1208544597029686,
-0.2351139485836029,
-0.06570623815059662,
0.16245457530021667,
0.07112404704093933,
-0.18955563008785248,
0.2537774443626404,
-0.23828265070915222,
0.12286156415939331,
0.14369387924671173,
0.2271645963191986,
-0.39819368720054626,
-0.5145755410194397,
-0.052926596254110336,
-0.19155599176883698,
0.34394755959510803,
-0.038793012499809265,
-0.40476492047309875,
0.18230606615543365,
-0.7144542932510376,
0.13730914890766144,
0.05638710781931877,
0.3346385359764099,
0.10766465961933136,
-0.2996092736721039,
0.02329104393720627,
0.07969065755605698,
0.6119204759597778,
0.16484849154949188,
-0.07098306715488434,
0.17361631989479065,
-0.15104737877845764,
-0.5380707383155823,
0.012870658189058304,
-0.05156503990292549,
0.03713851794600487,
0.2749985158443451,
0.1597067415714264,
-0.30154356360435486,
-0.5077016949653625,
-0.04973512887954712,
0.006742892786860466,
-0.35283520817756653,
-0.06370021402835846,
-0.22928370535373688,
-0.15957221388816833,
-0.036567918956279755,
-0.31081509590148926,
0.07019171863794327,
0.2330520749092102,
-0.05486302077770233,
0.035344574600458145,
-0.23602719604969025,
-0.07313291728496552,
0.2959987223148346,
-0.007531940471380949,
0.17190706729888916,
0.555413544178009,
0.0686982125043869,
-0.05782347917556763,
0.028072133660316467,
-0.2228824645280838,
0.2243756800889969,
-0.046551648527383804,
-0.17790314555168152,
0.020541710779070854,
0.13925306499004364,
0.4212951064109802,
0.0915336161851883,
0.04267314821481705,
0.1779651641845703,
-0.18196235597133636,
0.02648220583796501,
-0.23252315819263458,
0.45168939232826233,
0.10564132034778595,
-0.2878836691379547,
-0.11276016384363174,
-0.41713830828666687,
0.5051949620246887,
0.26663684844970703,
0.09778295457363129,
0.4054182767868042,
-0.1845548301935196,
-0.37959763407707214,
0.474712610244751,
0.3681877851486206,
0.5930814146995544,
-0.3568763732910156,
0.522830069065094,
0.6306702494621277,
0.513515293598175,
0.9229066967964172,
-0.36990708112716675,
0.25785937905311584,
-0.10761429369449615,
-0.2891255021095276,
-0.03414952754974365,
-0.270114004611969,
-0.36774057149887085,
0.09762480854988098,
0.14890345931053162,
0.2554055154323578,
0.05960749089717865,
0.3281601369380951,
0.22872522473335266,
0.4213240146636963,
0.400400310754776,
-0.4190787374973297,
-0.1393458992242813,
0.04883725941181183,
-0.0004682987928390503,
-0.1998964101076126,
-0.08649679273366928,
-0.13067443668842316,
0.22034922242164612,
-0.03784758970141411,
-0.06312507390975952,
0.09271541237831116,
-0.19131918251514435,
0.27331072092056274,
0.08860552310943604,
-0.022878140211105347,
-0.030652809888124466,
0.2359609305858612,
0.05160657316446304,
-0.16254596412181854,
-0.07398046553134918,
-0.07821480929851532,
0.020682163536548615,
0.012831945903599262,
0.13242071866989136,
-0.0732160210609436,
0.5777001976966858,
-0.0037469007074832916,
0.23270893096923828,
0.20195773243904114,
-0.07018744200468063,
-0.6475852727890015,
-0.2420337200164795,
-0.0774628072977066,
0.16460154950618744,
0.12083669006824493,
-0.5740079283714294,
0.27751532196998596,
-0.216440349817276,
0.20163749158382416,
0.04024412855505943,
0.05791104584932327,
-0.18905197083950043,
0.057202037423849106,
0.08815030008554459,
-0.22422657907009125,
0.23804382979869843,
0.07987484335899353,
0.080214723944664,
0.00434209406375885,
0.4003141224384308,
0.09414893388748169,
0.026444852352142334,
0.0004956014454364777,
0.140666663646698,
0.318990558385849,
-0.053173262625932693,
-0.035519614815711975,
-0.03209904208779335,
0.22842811048030853,
-0.0022147579584270716,
0.31702908873558044,
-0.2210991531610489,
0.04519498348236084,
-0.3271239399909973,
-0.22691549360752106,
-0.27978166937828064,
0.40973973274230957,
-0.03227889910340309,
0.17035385966300964,
-0.029661305248737335,
0.23653820157051086,
-0.21207377314567566,
0.25990185141563416,
-0.19452978670597076,
-0.00035261688753962517,
0.055743128061294556,
0.06459634006023407,
-0.20630134642124176,
-0.037182509899139404,
0.08591098338365555,
0.1474553346633911,
0.029786797240376472,
0.14584200084209442,
-0.28631365299224854,
-0.16016757488250732,
-0.05519580841064453,
0.21042361855506897,
0.06889985501766205,
-0.18370765447616577,
-0.07681185752153397,
-0.35104912519454956,
-0.30541983246803284,
-0.21098463237285614,
0.07133463025093079,
-0.11096087098121643,
-0.2526506781578064,
-0.01770791783928871,
-0.016698386520147324,
0.3033115565776825,
-0.18731701374053955,
0.05895691365003586,
-0.03881070017814636,
0.3205208480358124,
-0.06789536029100418,
0.2631838917732239,
0.17212143540382385,
-0.016811057925224304,
-0.3609761893749237,
-0.11104582995176315,
0.2617635130882263,
-0.12928399443626404,
-0.019321009516716003,
-0.354259192943573,
-0.028004365041851997,
-0.24651046097278595,
0.019432909786701202,
0.38171759247779846,
-0.2598596215248108,
0.011901510879397392,
0.25529196858406067,
0.0760611817240715,
-0.069309301674366,
-0.13709065318107605,
0.289845734834671,
0.0156412310898304,
-0.01702931523323059,
0.21574857831001282,
0.01905597373843193,
0.23018860816955566,
-0.07639765739440918,
-0.059450481086969376,
0.05092654377222061,
-0.45813047885894775,
-0.24831125140190125,
0.3442261219024658,
-0.14797531068325043,
-0.04453134164214134,
-0.156599760055542,
0.1595495194196701,
0.1588200032711029,
0.20096920430660248,
0.268885999917984,
0.27205371856689453,
-0.13097810745239258,
-0.08041979372501373,
-0.10907384008169174,
-0.29884976148605347,
-0.41599294543266296,
0.4332541525363922,
-0.030950263142585754,
0.5543476343154907,
-0.3014596402645111,
-0.04429031163454056,
0.21874772012233734,
-0.2889840006828308,
-0.14263536036014557,
0.28795987367630005,
-0.1215730682015419,
-0.09826506674289703,
-0.18458379805088043,
0.0626409575343132,
-0.2162010222673416,
0.2093060165643692,
-0.12552742660045624,
-0.24214600026607513,
-0.18847361207008362,
0.28286221623420715,
0.12130404263734818,
0.14187608659267426,
0.03304450586438179,
0.13925668597221375,
0.26242363452911377,
-0.1684403270483017,
0.28532490134239197,
-0.3038650155067444,
-0.023454107344150543,
-0.30802375078201294,
0.05243360996246338,
0.030013471841812134,
0.32330068945884705,
-0.34771162271499634,
0.13549581170082092,
0.07323811948299408,
-0.05230707302689552,
-0.021849362179636955,
0.25487399101257324,
0.21410419046878815,
0.11187854409217834,
0.24433214962482452,
-0.04741958528757095,
-0.038062963634729385,
0.1554596871137619,
0.13566061854362488,
0.10434865951538086,
-0.6335431337356567,
0.5223554968833923,
0.2589547038078308,
-0.03485376015305519,
0.04822508245706558,
0.2361012101173401,
-0.1764226257801056,
-0.11756715178489685,
0.49291664361953735,
-0.26624596118927,
0.07922807335853577,
0.08962001651525497,
0.02324390783905983,
-0.23603755235671997,
0.6891621947288513,
0.015659432858228683,
0.5115365982055664,
-0.12947995960712433,
0.08085672557353973,
-0.4833618402481079,
0.04604011029005051,
-0.13137918710708618,
0.13447974622249603,
0.24390091001987457,
0.28714609146118164,
0.154861181974411,
0.21748216450214386,
-0.37715381383895874,
-0.2930711507797241,
-0.07903548330068588,
0.005899231880903244,
-0.12049275636672974,
-0.09162646532058716,
-0.4695655107498169,
0.20530220866203308,
-0.06458187103271484,
-0.4875369668006897,
0.05354753136634827,
-0.31423690915107727,
-0.10486914962530136,
-0.06824911385774612,
0.20545005798339844,
0.27082759141921997,
0.3716528117656708,
0.3245227336883545,
-0.05926666408777237,
0.002298116683959961,
0.06226669251918793,
-0.10009273886680603,
-0.1329045593738556,
-0.028408346697688103,
-0.3497496247291565,
-0.08344780653715134,
-0.16258271038532257,
0.16817989945411682,
-0.33418509364128113,
0.013359403237700462,
-0.21613335609436035,
-0.3234879970550537,
0.05041768401861191,
-0.2010858803987503,
-0.14042305946350098,
0.09030617028474808,
-0.30964651703834534,
0.31978514790534973,
0.13747623562812805,
0.47105610370635986,
-0.1315186321735382,
-0.038961559534072876,
-0.19754278659820557,
0.1254427134990692,
0.47626370191574097,
-0.696999192237854,
-0.18452942371368408,
0.08059538900852203,
-0.13366712629795074,
0.28647270798683167,
0.08193138241767883,
-0.34681081771850586,
-0.21591895818710327,
0.36738553643226624,
-0.0630364716053009,
-0.2189217507839203,
0.23914088308811188,
0.3046948313713074,
-0.10874490439891815,
-0.11808691918849945,
0.30738404393196106,
-0.08267609775066376,
-0.3657676577568054,
-0.19985421001911163,
-0.5045340657234192
] |
https://github.com/huggingface/datasets/issues/193 | [Tensorflow] Use something else than `from_tensor_slices()` | Apparently we'll have to wait for the next tensorflow release to use `.from_generator` and TPU. See https://github.com/tensorflow/tensorflow/issues/34346#issuecomment-598262489 | In the example notebook, the TF Dataset is built using `from_tensor_slices()` :
```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
labels = {"output_1": train_tf_dataset["start_positions"]}
labels["output_2"] = train_tf_dataset["end_positions"]
tfdataset = tf.data.Dataset.from_tensor_slices((features, labels)).batch(8)
```
But according to [official tensorflow documentation](https://www.tensorflow.org/guide/data#consuming_numpy_arrays), this will load the entire dataset to memory.
**This defeats one purpose of this library, which is lazy loading.**
Is there any other way to load the `nlp` dataset into TF dataset lazily ?
---
For example, is it possible to use [Arrow dataset](https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowDataset) ? If yes, is there any code example ? | 17 | [Tensorflow] Use something else than `from_tensor_slices()`
In the example notebook, the TF Dataset is built using `from_tensor_slices()` :
```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
labels = {"output_1": train_tf_dataset["start_positions"]}
labels["output_2"] = train_tf_dataset["end_positions"]
tfdataset = tf.data.Dataset.from_tensor_slices((features, labels)).batch(8)
```
But according to [official tensorflow documentation](https://www.tensorflow.org/guide/data#consuming_numpy_arrays), this will load the entire dataset to memory.
**This defeats one purpose of this library, which is lazy loading.**
Is there any other way to load the `nlp` dataset into TF dataset lazily ?
---
For example, is it possible to use [Arrow dataset](https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowDataset) ? If yes, is there any code example ?
Apparently we'll have to wait for the next tensorflow release to use `.from_generator` and TPU. See https://github.com/tensorflow/tensorflow/issues/34346#issuecomment-598262489 | [
-0.1305495947599411,
-0.03085968643426895,
0.03630451485514641,
0.12274200469255447,
0.22812069952487946,
0.09177563339471817,
0.27305594086647034,
0.4065890908241272,
-0.11111760139465332,
0.0027905330061912537,
-0.08880870044231415,
0.5513769388198853,
-0.15211911499500275,
0.04721108078956604,
0.3196074664592743,
-0.26276540756225586,
-0.06650402396917343,
0.24885836243629456,
-0.1298072785139084,
-0.014312822371721268,
-0.04055114462971687,
-0.053230561316013336,
-0.09556209295988083,
-0.016439586877822876,
0.015059834346175194,
-0.03353513032197952,
0.051149748265743256,
-0.1520296335220337,
0.4169294536113739,
0.021076910197734833,
0.35533690452575684,
0.0021883435547351837,
-0.03409393131732941,
0.11227062344551086,
-0.00010922730143647641,
0.38452446460723877,
0.03214535117149353,
-0.14960576593875885,
0.06209937110543251,
-0.07406571507453918,
0.20812636613845825,
-0.22736459970474243,
0.1988503485918045,
-0.2661628723144531,
-0.04680870845913887,
-0.005252291448414326,
0.23685553669929504,
-0.03428581357002258,
0.257424920797348,
0.11936882883310318,
0.15609541535377502,
0.5252828598022461,
-0.173379048705101,
0.2786279022693634,
0.1325308084487915,
-0.15955960750579834,
-0.21689723432064056,
-0.27933022379875183,
-0.13236470520496368,
-0.010954213328659534,
0.06574587523937225,
0.14796696603298187,
-0.22829397022724152,
0.09629996120929718,
0.4325977861881256,
0.15464548766613007,
-0.11124914139509201,
-0.3790856897830963,
-0.2610156834125519,
0.4085841774940491,
0.2015363872051239,
-0.07298093289136887,
-0.17706947028636932,
-0.4851957857608795,
-0.17577533423900604,
-0.2934437394142151,
-0.17836517095565796,
0.08686387538909912,
-0.2625954747200012,
0.18190957605838776,
-0.10118096321821213,
-0.12041530758142471,
-0.21891944110393524,
0.12010437995195389,
0.21201223134994507,
-0.03557460010051727,
0.16041889786720276,
0.11686260998249054,
0.22441290318965912,
0.1082771047949791,
0.349454402923584,
0.08066010475158691,
0.354869544506073,
0.36756548285484314,
-0.2840503752231598,
-0.011491380631923676,
0.16927161812782288,
-0.5806731581687927,
-0.044434115290641785,
-0.25259649753570557,
0.35710659623146057,
0.18533852696418762,
-0.29192599654197693,
0.21650972962379456,
-0.013307638466358185,
-0.07356643676757812,
-0.4224946200847626,
0.1319459229707718,
-0.13990892469882965,
-0.5050941705703735,
0.04702812060713768,
0.04630619287490845,
-0.22082199156284332,
-0.01992803066968918,
0.060599204152822495,
-0.5112510323524475,
-0.14770323038101196,
0.2690739929676056,
-0.2849743962287903,
-0.4418402910232544,
-0.2301689088344574,
0.028392238542437553,
-0.01433276291936636,
0.1737464815378189,
-0.12791681289672852,
0.5364341735839844,
0.13731825351715088,
-0.12483684718608856,
-0.2813413143157959,
-0.02957770600914955,
-0.23230744898319244,
0.1130899041891098,
-0.06146424263715744,
-0.09602802246809006,
0.15568780899047852,
-0.16067297756671906,
0.17979377508163452,
-0.12268876284360886,
-0.12777183949947357,
0.181620255112648,
0.2595548629760742,
-0.08195087313652039,
0.1001741960644722,
0.257914662361145,
0.014886215329170227,
-0.06456946581602097,
0.0382283553481102,
0.07491455972194672,
-0.21613088250160217,
0.3539184033870697,
-0.5225857496261597,
-0.28902292251586914,
-0.048797063529491425,
0.13496698439121246,
0.08778078109025955,
-0.2136901319026947,
-0.3331679701805115,
0.3261956572532654,
0.12096337974071503,
-0.1192808598279953,
-0.18521875143051147,
-0.20750415325164795,
-0.42386937141418457,
-0.3011671304702759,
0.30410706996917725,
0.04064252972602844,
-0.46133387088775635,
-0.11523310840129852,
0.006508614402264357,
-0.01659354940056801,
0.2493128478527069,
0.44560661911964417,
-0.23294807970523834,
0.4801928400993347,
-0.05343689024448395,
0.0012748390436172485,
0.7598667144775391,
-0.08542155474424362,
-0.16154108941555023,
0.22563154995441437,
-0.12333734333515167,
0.20281225442886353,
-0.004924893379211426,
0.40537595748901367,
0.00034402497112751007,
-0.029118189588189125,
0.3868638575077057,
0.6318569183349609,
-0.15841248631477356,
0.07676413655281067,
-0.10929078608751297,
-0.3459326922893524,
0.30011415481567383,
0.279721200466156,
0.09528972208499908,
-0.05658244341611862,
-0.26506099104881287,
0.3954322636127472,
0.13062487542629242,
-0.0343218557536602,
-0.18207566440105438,
0.0670047253370285,
-0.1286899298429489,
0.00043360888957977295,
-0.17078568041324615,
0.06576729565858841,
-0.6022964119911194,
0.2533167898654938,
0.1912776380777359,
0.09608078002929688,
0.1893984079360962,
-0.11190374940633774,
0.36263155937194824,
0.10908060520887375,
0.11826247721910477,
0.15904927253723145,
0.019094761461019516,
0.0754808783531189,
-0.028345119208097458,
-0.011725282296538353,
-0.34432217478752136,
0.1589709371328354,
-0.37544140219688416,
-0.12695880234241486,
-0.34896767139434814,
0.26449695229530334,
0.37324219942092896,
0.01796679198741913,
-0.08456045389175415,
0.30133238434791565,
-0.3664577305316925,
-0.12099925428628922,
0.11764286458492279,
0.21522921323776245,
-0.030569130554795265,
0.29321372509002686,
-0.6672239303588867,
0.4424225687980652,
0.05159900337457657,
-0.022755734622478485,
-0.10921411961317062,
0.12416113913059235,
0.0025713806971907616,
-0.19744905829429626,
0.010840348899364471,
0.28054291009902954,
-0.22586210072040558,
0.1471133828163147,
0.2610127925872803,
-0.2442212700843811,
0.15271605551242828,
0.0638124942779541,
0.1342633068561554,
-0.11270657181739807,
0.3706355690956116,
0.09925232827663422,
0.13777045905590057,
0.2951819598674774,
-0.5292934775352478,
0.23122292757034302,
0.6706404685974121,
-0.022198140621185303,
-0.11366260796785355,
0.21687638759613037,
0.03733411058783531,
-0.21183159947395325,
-0.08162235468626022,
-0.08116958290338516,
0.20193099975585938,
0.1457822173833847,
0.041635867208242416,
0.0004894677549600601,
-0.1641395390033722,
-0.25839439034461975,
0.24762287735939026,
0.13116759061813354,
0.38085076212882996,
-0.1395995318889618,
0.030044760555028915,
0.20352737605571747,
-0.19155406951904297,
0.08323949575424194,
0.2106477916240692,
0.17547309398651123,
-0.2056153416633606,
0.03021705336868763,
-0.27456989884376526,
-0.30668652057647705,
-0.08983340859413147,
0.035019807517528534,
0.14405672252178192,
-0.18368183076381683,
-0.049924641847610474,
0.3294704854488373,
-0.04942644387483597,
-0.05361642688512802,
-0.11888295412063599,
0.3149208426475525,
0.16494840383529663,
-0.4449191689491272,
-0.06582370400428772,
-0.105502188205719,
-0.18507158756256104,
0.09022971987724304,
0.36076802015304565,
0.17744196951389313,
0.2429792881011963,
0.026393840089440346,
-0.08753322809934616,
0.168130025267601,
-0.07798132300376892,
0.2226693034172058,
-0.11164140701293945,
0.11009330302476883,
-0.04960907995700836,
0.07181691378355026,
-0.12877157330513,
-0.2588932514190674,
-0.11553194373846054,
-0.4312821328639984,
0.053853221237659454,
0.1550912708044052,
-0.0024249479174613953,
0.14857839047908783,
-0.2426670342683792,
-0.17587366700172424,
-0.30553802847862244,
-0.39437296986579895,
0.018097572028636932,
0.16430489718914032,
0.3020918369293213,
0.42609962821006775,
-0.029929064214229584,
0.28222182393074036,
0.38556820154190063,
0.05240762233734131,
0.08026604354381561,
-0.13831505179405212,
0.47845780849456787,
-0.27619481086730957,
-0.25517192482948303,
-0.15608848631381989,
-0.17423512041568756,
0.1930471509695053,
0.3186531066894531,
-0.7124727964401245,
0.14556282758712769,
-0.08327458798885345,
0.08658705651760101,
-0.08990909159183502,
-0.04109260439872742,
0.2317248433828354,
-0.2033177763223648,
0.020511122420430183,
0.004608724266290665,
0.1650746613740921,
0.14517617225646973,
0.024806426838040352,
-0.20415616035461426,
0.370391309261322,
0.423714816570282,
0.33127135038375854,
0.7575738430023193,
-0.08429160714149475,
-0.21429266035556793,
0.23427140712738037,
-0.1822497695684433,
0.1970280408859253,
-0.23281565308570862,
-0.06427554786205292,
0.042938943952322006,
-0.013692915439605713,
-0.005353173241019249,
0.22368408739566803,
-0.10000864416360855,
-0.1953769326210022,
-0.11733990907669067,
0.22071102261543274,
0.11836301535367966,
-0.23836761713027954,
0.25822973251342773,
-0.21444028615951538,
0.1831321120262146,
0.1111203283071518,
0.21261000633239746,
-0.3299848735332489,
-0.39972004294395447,
-0.019310519099235535,
-0.23272426426410675,
0.4178357422351837,
-0.04035956785082817,
-0.3286675810813904,
0.10396482050418854,
-0.7131766676902771,
0.06532415747642517,
0.11960602551698685,
0.3085826337337494,
0.08994682133197784,
-0.29901477694511414,
-0.0069963932037353516,
0.0677560344338417,
0.54835045337677,
0.0983370915055275,
-0.08745630085468292,
0.2097495198249817,
-0.17732767760753632,
-0.4892943799495697,
0.034078385680913925,
-0.05583801865577698,
-0.0789330005645752,
0.24943751096725464,
0.14017444849014282,
-0.2619260549545288,
-0.49131250381469727,
-0.024556774646043777,
-0.01641920953989029,
-0.33952704071998596,
-0.048820044845342636,
-0.1868024468421936,
-0.2434476912021637,
0.0010784752666950226,
-0.3156525492668152,
0.05761398375034332,
0.2791344225406647,
-0.1710854470729828,
0.020696353167295456,
-0.15080365538597107,
-0.0014762766659259796,
0.21223333477973938,
0.0035507548600435257,
0.16318711638450623,
0.46328669786453247,
0.0473945327103138,
-0.04891367256641388,
-0.008087970316410065,
-0.13080638647079468,
0.22405441105365753,
-0.09222035109996796,
-0.15226924419403076,
0.01875913515686989,
0.15853534638881683,
0.3719961941242218,
0.04845401644706726,
0.036095090210437775,
0.12852442264556885,
-0.17415043711662292,
0.0331273153424263,
-0.19866780936717987,
0.36705324053764343,
0.08676327019929886,
-0.34173792600631714,
-0.08246486634016037,
-0.5109409093856812,
0.5615847706794739,
0.29596754908561707,
0.12883765995502472,
0.4830287992954254,
-0.19704554975032806,
-0.36169514060020447,
0.5212909579277039,
0.38263067603111267,
0.5099002718925476,
-0.3703688383102417,
0.5261975526809692,
0.7229405045509338,
0.4783591032028198,
0.9239943027496338,
-0.3590673804283142,
0.271091103553772,
-0.12388913333415985,
-0.35866448283195496,
-0.028797602280974388,
-0.2556568682193756,
-0.37506231665611267,
0.07888748496770859,
0.10311451554298401,
0.21673324704170227,
0.13108590245246887,
0.27752795815467834,
0.2179107964038849,
0.3121587336063385,
0.3466190695762634,
-0.4222288429737091,
-0.1941184550523758,
0.06759946048259735,
0.029670272022485733,
-0.23409509658813477,
-0.08185210824012756,
-0.1964038461446762,
0.23074984550476074,
0.06485637277364731,
0.02035634219646454,
0.12005943804979324,
-0.18482458591461182,
0.28192728757858276,
0.13958941400051117,
-0.09903085976839066,
0.0404784195125103,
0.2417283058166504,
0.12007851898670197,
-0.20490717887878418,
-0.10917830467224121,
-0.08963549137115479,
0.06531937420368195,
0.010170526802539825,
0.14681871235370636,
-0.044765181839466095,
0.6814284920692444,
-0.021972253918647766,
0.19641372561454773,
0.16399000585079193,
-0.07861166447401047,
-0.5933405160903931,
-0.18238696455955505,
-0.11446219682693481,
0.08533680438995361,
0.16856367886066437,
-0.5447580814361572,
0.2875629663467407,
-0.19816642999649048,
0.18102926015853882,
0.0979793518781662,
0.11959955096244812,
-0.20461025834083557,
0.054966479539871216,
0.05523791164159775,
-0.18702730536460876,
0.22112686932086945,
0.02921537682414055,
0.12724709510803223,
0.03463389724493027,
0.3529255986213684,
0.22735239565372467,
0.004736330360174179,
-0.025911346077919006,
0.10443621128797531,
0.2849634885787964,
-0.04618552699685097,
0.06443589180707932,
0.03664505109190941,
0.22891287505626678,
0.06418915092945099,
0.3598421514034271,
-0.22694502770900726,
0.031078461557626724,
-0.2919079661369324,
-0.17317941784858704,
-0.3018862009048462,
0.36624377965927124,
-0.05979655310511589,
0.1284087598323822,
-0.0037668123841285706,
0.21896661818027496,
-0.12371939420700073,
0.22889870405197144,
-0.24168671667575836,
-0.02274310775101185,
0.005892595276236534,
0.06760427355766296,
-0.12601542472839355,
-0.0586392804980278,
0.06964524835348129,
0.13090012967586517,
0.06438510864973068,
0.1422179788351059,
-0.3747166693210602,
-0.20188695192337036,
-0.04005315527319908,
0.16559568047523499,
0.032665714621543884,
-0.23869407176971436,
-0.004422037396579981,
-0.34728121757507324,
-0.33256155252456665,
-0.16482393443584442,
0.1165752112865448,
-0.12507416307926178,
-0.2715752124786377,
0.060311850160360336,
-0.059461016207933426,
0.2978954017162323,
-0.13933756947517395,
0.03453737124800682,
-0.1070035994052887,
0.313271164894104,
-0.0834675282239914,
0.24981437623500824,
0.09919039905071259,
-0.05009351670742035,
-0.3136667013168335,
-0.11679358035326004,
0.13764718174934387,
-0.11599984019994736,
0.06822923570871353,
-0.31335949897766113,
-0.07454542815685272,
-0.2488783597946167,
0.042872995138168335,
0.2715889811515808,
-0.23715418577194214,
0.09041175246238708,
0.2457917034626007,
0.11498203873634338,
-0.09760560840368271,
-0.1507219523191452,
0.20687197148799896,
0.08234623819589615,
-0.02431715466082096,
0.20025314390659332,
0.08809411525726318,
0.1603432446718216,
-0.06396119296550751,
-0.040288254618644714,
0.010186681523919106,
-0.5695468187332153,
-0.1938687264919281,
0.4081520438194275,
-0.13632269203662872,
-0.01425013318657875,
-0.1612708568572998,
0.09546278417110443,
0.1648012101650238,
0.21101638674736023,
0.2794186770915985,
0.22885382175445557,
-0.071799635887146,
-0.09621991217136383,
-0.06139986962080002,
-0.35142725706100464,
-0.42889073491096497,
0.4405210316181183,
-0.061253905296325684,
0.5847461819648743,
-0.2274622917175293,
0.03551597520709038,
0.1482982188463211,
-0.21972991526126862,
-0.16932755708694458,
0.2957035303115845,
-0.14875149726867676,
-0.06481284648180008,
-0.23912541568279266,
0.06481736153364182,
-0.15066874027252197,
0.2991454601287842,
-0.10230936110019684,
-0.21432216465473175,
-0.16765889525413513,
0.2694036364555359,
0.09658157080411911,
0.22632597386837006,
0.11800218373537064,
0.07471579313278198,
0.24854061007499695,
-0.11725829541683197,
0.19789016246795654,
-0.2634506821632385,
-0.10788576304912567,
-0.3696136176586151,
0.011613085865974426,
0.0912146270275116,
0.2826961874961853,
-0.333754301071167,
0.12661029398441315,
0.07012587785720825,
-0.045848943293094635,
-0.02080637589097023,
0.2440701723098755,
0.2368536740541458,
0.09861889481544495,
0.30468040704727173,
-0.0035823434591293335,
-0.05681198090314865,
0.1515500694513321,
0.15705440938472748,
0.1753876507282257,
-0.5788911581039429,
0.5717279314994812,
0.2261790782213211,
-0.055577121675014496,
-0.005985397845506668,
0.20326685905456543,
-0.08927394449710846,
-0.12076389789581299,
0.5214148759841919,
-0.2620495855808258,
0.0367177277803421,
-0.00250809732824564,
0.046714432537555695,
-0.19307464361190796,
0.6902192234992981,
0.05742118880152702,
0.4553859531879425,
-0.08694545924663544,
0.04564303159713745,
-0.44194960594177246,
0.09158547222614288,
-0.10719521343708038,
0.211973637342453,
0.2606280446052551,
0.2983134686946869,
0.1464911252260208,
0.20516307651996613,
-0.45577120780944824,
-0.2137388437986374,
-0.016207600012421608,
0.04839964210987091,
-0.1488637924194336,
-0.10379485785961151,
-0.5044936537742615,
0.12454164028167725,
-0.13039083778858185,
-0.442399799823761,
0.08776954561471939,
-0.42137792706489563,
-0.034125976264476776,
-0.08691303431987762,
0.2229066789150238,
0.32336729764938354,
0.4466139078140259,
0.3336485028266907,
-0.039631858468055725,
-0.10491986572742462,
0.049597591161727905,
-0.0795430913567543,
-0.1129736453294754,
-0.027450663968920708,
-0.31767064332962036,
-0.07864468544721603,
-0.1492992490530014,
0.1286468505859375,
-0.2904026210308075,
-0.047470126301050186,
-0.22104136645793915,
-0.26274269819259644,
0.025212854146957397,
-0.10299608111381531,
-0.13584566116333008,
0.09924516826868057,
-0.26050934195518494,
0.17538069188594818,
0.2303081601858139,
0.4477683901786804,
-0.14069747924804688,
-0.1299131214618683,
-0.21534103155136108,
0.08180087059736252,
0.38260042667388916,
-0.6043994426727295,
-0.20278362929821014,
0.06831440329551697,
-0.16580957174301147,
0.25549808144569397,
0.06379912793636322,
-0.27773869037628174,
-0.21997889876365662,
0.27987343072891235,
-0.12841495871543884,
-0.21454517543315887,
0.25627386569976807,
0.3233982026576996,
-0.10076102614402771,
-0.12213346362113953,
0.2780953645706177,
-0.061141014099121094,
-0.43306151032447815,
-0.21358869969844818,
-0.4865185022354126
] |
https://github.com/huggingface/datasets/issues/192 | [Question] Create Apache Arrow dataset from raw text file | We store every dataset in the Arrow format. This is convenient as it supports nested types and memory mapping. If you are curious feel free to check the [pyarrow documentation](https://arrow.apache.org/docs/python/)
You can use this library to load your covid papers by creating a dataset script. You can find inspiration from the ones we've already written in `/datasets`. Here is a link to the steps to [add a dataset](https://github.com/huggingface/nlp/blob/master/CONTRIBUTING.md#how-to-add-a-dataset) | Hi guys, I have gathered and preprocessed about 2GB of COVID papers from CORD dataset @ Kggle. I have seen you have a text dataset as "Crime and punishment" in Apache arrow format. Do you have any script to do it from a raw txt file (preprocessed as for BERT like) or any guide?
Is the worth of send it to you and add it to the NLP library?
Thanks, Manu
| 68 | [Question] Create Apache Arrow dataset from raw text file
Hi guys, I have gathered and preprocessed about 2GB of COVID papers from CORD dataset @ Kggle. I have seen you have a text dataset as "Crime and punishment" in Apache arrow format. Do you have any script to do it from a raw txt file (preprocessed as for BERT like) or any guide?
Is the worth of send it to you and add it to the NLP library?
Thanks, Manu
We store every dataset in the Arrow format. This is convenient as it supports nested types and memory mapping. If you are curious feel free to check the [pyarrow documentation](https://arrow.apache.org/docs/python/)
You can use this library to load your covid papers by creating a dataset script. You can find inspiration from the ones we've already written in `/datasets`. Here is a link to the steps to [add a dataset](https://github.com/huggingface/nlp/blob/master/CONTRIBUTING.md#how-to-add-a-dataset) | [
-0.1738838404417038,
-0.06410497426986694,
-0.045787423849105835,
0.06958923488855362,
-0.3965015411376953,
0.13637560606002808,
0.06761038303375244,
0.40038391947746277,
-0.068243607878685,
-0.3222419023513794,
0.13134296238422394,
0.18338912725448608,
-0.08250486105680466,
0.07896033674478531,
0.39143094420433044,
-0.04079137742519379,
-0.0588856115937233,
0.2828744053840637,
-0.03286244720220566,
-0.03655622899532318,
0.16092781722545624,
-0.0212873462587595,
-0.10444429516792297,
0.007256589829921722,
-0.19171856343746185,
-0.34966567158699036,
-0.16615350544452667,
0.15690958499908447,
-0.1471918672323227,
-0.4131222069263458,
0.11186324059963226,
0.0859130322933197,
0.5545092821121216,
0.1522887796163559,
-0.00012087303912267089,
-0.46484100818634033,
0.1461741030216217,
-0.07211586833000183,
-0.15252892673015594,
-0.20889602601528168,
-0.232600599527359,
-0.09182374179363251,
0.17215833067893982,
-0.3390498459339142,
0.0773116946220398,
-0.4477842450141907,
0.17121951282024384,
-0.2712026834487915,
0.6657806634902954,
0.3493711054325104,
0.07335950434207916,
-0.1018950417637825,
0.18934036791324615,
0.2285752296447754,
0.47995370626449585,
0.542945146560669,
-0.3052915334701538,
0.1529545933008194,
0.26077890396118164,
-0.20762118697166443,
-0.28251877427101135,
0.15879952907562256,
-0.09765521436929703,
-0.23909716308116913,
0.33057811856269836,
0.1180301383137703,
-0.2703995108604431,
-0.33307674527168274,
0.048938315361738205,
0.39643773436546326,
0.36962535977363586,
-0.4938056766986847,
0.048539161682128906,
-0.05016287416219711,
0.18940657377243042,
-0.48908114433288574,
-0.14875277876853943,
0.6180800795555115,
-0.5020691752433777,
0.3597387969493866,
0.3344428539276123,
-0.38164591789245605,
-0.43398380279541016,
0.1284179389476776,
0.45758846402168274,
-0.07156996428966522,
-0.04713990166783333,
-0.07582772523164749,
-0.050290171056985855,
0.17449459433555603,
0.21123643219470978,
-0.24556133151054382,
-0.14875848591327667,
0.3470054566860199,
-0.1437053680419922,
-0.16275882720947266,
-0.4877951145172119,
-0.20781898498535156,
0.2758224308490753,
-0.029754452407360077,
0.3700706660747528,
-0.1301804780960083,
-0.03909512981772423,
-0.09167703241109848,
0.039463020861148834,
-0.09501941502094269,
0.4510572552680969,
0.20620964467525482,
-0.009002260863780975,
-0.26278287172317505,
0.16223491728305817,
-0.0809464082121849,
-0.20558717846870422,
0.0966666042804718,
-0.1564088761806488,
0.03321831673383713,
0.04962415248155594,
-0.1927904188632965,
0.011112412437796593,
0.006019183434545994,
-0.4366477131843567,
-0.024570120498538017,
-0.2640628516674042,
0.23352792859077454,
0.18255864083766937,
-0.09135620296001434,
0.22798101603984833,
0.3980581760406494,
0.002583298832178116,
-0.1910053789615631,
0.12297531217336655,
0.07351367920637131,
-0.2823683023452759,
0.28089261054992676,
0.24723418056964874,
0.04876583814620972,
-0.002006618771702051,
-0.09525186568498611,
0.04778182506561279,
-0.3019627630710602,
0.19040703773498535,
-0.011526014655828476,
0.16694147884845734,
-0.1192820817232132,
0.2679125964641571,
0.04077550023794174,
-0.14994093775749207,
-0.12755176424980164,
-0.10135650634765625,
0.3692103326320648,
-0.3687538504600525,
-0.1211438775062561,
-0.13666413724422455,
-0.0014926977455615997,
0.055035948753356934,
-0.14150623977184296,
-0.2777971029281616,
0.25129154324531555,
0.13343475759029388,
0.19284114241600037,
0.05564342439174652,
0.2801027297973633,
-0.013974577188491821,
-0.25124961137771606,
0.034251868724823,
0.47603195905685425,
-0.23271846771240234,
0.1828201711177826,
-0.1303548663854599,
0.4220266342163086,
0.04189300164580345,
0.19998136162757874,
-0.25090548396110535,
0.3373119533061981,
0.028532909229397774,
0.37845587730407715,
0.7308472394943237,
-0.07829384505748749,
0.22644926607608795,
0.40336307883262634,
0.18155469000339508,
-0.3522214889526367,
0.14907340705394745,
-0.043225377798080444,
0.10294309258460999,
-0.09913067519664764,
-0.30004069209098816,
0.49250930547714233,
0.11881767213344574,
0.03809336572885513,
-0.07898508757352829,
-0.2024594098329544,
-0.18061646819114685,
0.013829093426465988,
-0.14248503744602203,
-0.1521226167678833,
0.09050919860601425,
-0.45889031887054443,
0.4787382483482361,
-0.29847607016563416,
0.4021228551864624,
0.2903975248336792,
0.041525423526763916,
-0.014199167490005493,
0.24639397859573364,
-0.11176923662424088,
-0.18240374326705933,
-0.31211769580841064,
-0.40653055906295776,
0.29062819480895996,
-0.2542751431465149,
-0.2743143141269684,
-0.25395360589027405,
-0.11944717168807983,
0.07688561081886292,
-0.030594658106565475,
-0.03145664557814598,
-0.24361345171928406,
-0.21933585405349731,
0.017764132469892502,
-0.20738831162452698,
0.2594844698905945,
-0.2797715365886688,
0.13498452305793762,
-0.23029448091983795,
0.21568074822425842,
0.08199449628591537,
-0.19584107398986816,
0.24660933017730713,
0.23807460069656372,
-0.2799947261810303,
0.14895713329315186,
0.0656597912311554,
0.1418319046497345,
-0.05355462804436684,
0.20256268978118896,
0.4277292490005493,
-0.28081637620925903,
0.08477296680212021,
-0.6659767031669617,
0.30370938777923584,
-0.04134868085384369,
0.22573737800121307,
-0.11210650950670242,
-0.3082040846347809,
0.44492775201797485,
-0.06242334470152855,
0.19242992997169495,
-0.16103288531303406,
0.018283164128661156,
-0.07411972433328629,
-0.030854687094688416,
-0.08382117003202438,
0.17987780272960663,
0.055171363055706024,
0.43464672565460205,
0.156639963388443,
-0.15134316682815552,
0.027362637221813202,
0.08514806628227234,
-0.12751756608486176,
-0.17111240327358246,
0.2346557080745697,
0.23757702112197876,
-0.3029535114765167,
-0.10359880328178406,
-0.1672840416431427,
0.04839325323700905,
0.09259171783924103,
0.18483607470989227,
-0.15063875913619995,
-0.04035823792219162,
0.08050712198019028,
-0.09687428176403046,
0.3708855211734772,
-0.030180826783180237,
0.2931443750858307,
-0.16108748316764832,
-0.0907881110906601,
-0.02335536479949951,
-0.17951402068138123,
-0.28069770336151123,
-0.04755205661058426,
0.1384667009115219,
-0.2195429801940918,
0.028408849611878395,
-0.06600518524646759,
-0.37388554215431213,
-0.3311775028705597,
0.12961038947105408,
-0.04142492637038231,
0.25273483991622925,
0.012834236025810242,
-0.24280181527137756,
0.16066354513168335,
0.0032888036221265793,
-0.015388000756502151,
0.5403857231140137,
0.09072727710008621,
0.07187342643737793,
-0.18865998089313507,
-0.5223940014839172,
-0.18206366896629333,
0.05640018358826637,
0.24623338878154755,
0.42041847109794617,
0.3654952347278595,
-0.18795721232891083,
0.12019790709018707,
-0.037212222814559937,
-0.015586551278829575,
0.03923356533050537,
-0.17580151557922363,
-0.27563244104385376,
-0.18567413091659546,
0.12907779216766357,
-0.5696601867675781,
-0.10519050806760788,
-0.2161608785390854,
0.04164506494998932,
-0.17576496303081512,
-0.21181301772594452,
-0.07265765964984894,
-0.040174324065446854,
0.19620949029922485,
-0.5246601104736328,
-0.15463665127754211,
-0.1268382966518402,
0.35743266344070435,
0.30721616744995117,
0.2926774024963379,
-0.024484626948833466,
0.23975211381912231,
0.11661984771490097,
-0.3075913190841675,
-0.05353686213493347,
0.19105185568332672,
-0.06540259718894958,
0.37870287895202637,
-0.3172715902328491,
-0.5370230078697205,
0.011981863528490067,
-0.05331190302968025,
-0.07275433838367462,
0.31094807386398315,
-0.3548154830932617,
0.4196316599845886,
0.08230727165937424,
0.02953271195292473,
-0.1032710075378418,
-0.012858429923653603,
0.24516265094280243,
-0.00042297039180994034,
0.06135670840740204,
-0.05839308723807335,
0.09048902988433838,
0.356862872838974,
-0.1284237802028656,
0.3276352286338806,
0.34489214420318604,
0.1456562876701355,
-0.046614307910203934,
0.5362757444381714,
0.25174787640571594,
0.06070580333471298,
0.17636626958847046,
-0.11871372908353806,
0.07755326479673386,
0.10546062886714935,
0.03186950832605362,
-0.07428266108036041,
0.12698684632778168,
0.037481941282749176,
0.18022382259368896,
0.31824931502342224,
-0.3227258324623108,
-0.20063084363937378,
-0.24340973794460297,
-0.37224990129470825,
-0.19315633177757263,
0.39509591460227966,
-0.2958453595638275,
0.2528686821460724,
-0.11756265163421631,
-0.21010136604309082,
-0.17794978618621826,
-0.47201061248779297,
-0.10274523496627808,
0.23868027329444885,
0.2641415596008301,
0.17290504276752472,
-0.04200541228055954,
0.36136147379875183,
-0.6206266283988953,
0.2994306683540344,
0.18296527862548828,
-0.11638809740543365,
0.1148841381072998,
0.053787678480148315,
0.21332398056983948,
0.08678186684846878,
-0.116925448179245,
0.1683700680732727,
-0.05905257165431976,
-0.014313681051135063,
0.33650946617126465,
-0.3689159154891968,
0.3253720700740814,
-0.28265267610549927,
0.037240538746118546,
0.22013762593269348,
-0.11274115741252899,
-0.4396894872188568,
-0.22016751766204834,
0.17403529584407806,
0.14907994866371155,
-0.11088638007640839,
-0.4020352065563202,
0.12999650835990906,
0.005802426487207413,
-0.3960942029953003,
-0.14598968625068665,
0.39685720205307007,
-0.016033083200454712,
-0.12497647851705551,
-0.15539239346981049,
-0.0196640957146883,
0.10079912096261978,
0.22278183698654175,
-0.23059993982315063,
0.2011769711971283,
-0.2508758008480072,
0.02177169919013977,
-0.08185725659132004,
0.3278181254863739,
0.06736361235380173,
-0.001511555165052414,
0.18697330355644226,
-0.22211626172065735,
-0.0643140897154808,
-0.3994571268558502,
0.5800670385360718,
0.1728685200214386,
0.11208881437778473,
0.15619589388370514,
0.1852518916130066,
-0.3044200539588928,
-0.11992905288934708,
-0.011086886748671532,
0.13509565591812134,
-0.11089462041854858,
-0.4100247919559479,
-0.3892832100391388,
0.5749382376670837,
0.04820920154452324,
-0.03414585441350937,
0.2953094244003296,
0.05651567503809929,
-0.29029685258865356,
0.6706217527389526,
0.20020261406898499,
1.225579023361206,
-0.1759890615940094,
0.2871074974536896,
0.05487573891878128,
-0.10766854882240295,
0.5923519134521484,
-0.42020469903945923,
-0.21309912204742432,
-0.5059723258018494,
0.30423209071159363,
-0.11025388538837433,
-0.1454433649778366,
0.15465322136878967,
0.33180296421051025,
-0.06618227809667587,
0.1046360656619072,
0.2753223776817322,
-0.045742105692625046,
0.1352178156375885,
0.32489001750946045,
-0.21979480981826782,
-0.4144164025783539,
-0.15021663904190063,
-0.09407122433185577,
-0.12854498624801636,
0.04692883789539337,
0.11305602639913559,
-0.4174148440361023,
-0.32015812397003174,
0.07482137531042099,
-0.42436736822128296,
0.10035192221403122,
-0.00813352968543768,
-0.22221902012825012,
-0.26612773537635803,
-0.6077929139137268,
0.3085108697414398,
0.3429756462574005,
0.09421686083078384,
-0.0077797845005989075,
-0.285155713558197,
0.09172770380973816,
-0.2546539306640625,
-0.3908626437187195,
0.27973127365112305,
-0.12988488376140594,
0.07501401752233505,
-0.15044385194778442,
-0.20562174916267395,
0.15109014511108398,
0.05339084565639496,
-0.2871481776237488,
-0.006581559777259827,
-0.2250330001115799,
0.4990307092666626,
-0.12148292362689972,
-0.06034606322646141,
0.32706499099731445,
-0.41001591086387634,
0.005483098328113556,
0.07348687946796417,
0.3840419054031372,
0.10894711315631866,
0.05277860164642334,
0.26296380162239075,
-0.2531402111053467,
-0.04520687088370323,
0.17500489950180054,
0.3665909469127655,
-0.22578546404838562,
0.500103235244751,
0.41960784792900085,
-0.15374994277954102,
-0.2953294515609741,
0.276152640581131,
0.3888964056968689,
-0.8429332971572876,
-0.1055259183049202,
-0.008339785039424896,
0.09867812693119049,
0.016229508444666862,
0.10067287087440491,
-0.07750094681978226,
-0.04655391722917557,
0.010311707854270935,
-0.5420810580253601,
-0.26967689394950867,
0.14991000294685364,
-0.0966624766588211,
0.07544510066509247,
0.3981233239173889,
0.09652493894100189,
0.04153711348772049,
0.13556744158267975,
-0.20735105872154236,
0.08010713011026382,
0.5916277766227722,
0.17521585524082184,
0.10622365027666092,
0.09708917140960693,
0.019881684333086014,
0.02555643394589424,
-0.024785522371530533,
0.1171044334769249,
0.11115194857120514,
-0.13142049312591553,
-0.015419403091073036,
0.20284497737884521,
-0.06086132675409317,
-0.2965807318687439,
-0.30982348322868347,
-0.45137453079223633,
-0.2555306553840637,
-0.19112567603588104,
-0.14729651808738708,
-0.15576708316802979,
-0.13286037743091583,
0.13090789318084717,
0.07797189801931381,
0.014390937983989716,
-0.4827423691749573,
0.22568193078041077,
-0.21510633826255798,
0.25157713890075684,
-0.09725858271121979,
0.1495199054479599,
-0.0002763529773801565,
-0.05023433268070221,
0.04456475004553795,
0.12908262014389038,
0.24697478115558624,
0.18958786129951477,
0.5016099214553833,
-0.11936318874359131,
-0.04702064394950867,
-0.3728875517845154,
0.20446962118148804,
0.2573812007904053,
0.09038460999727249,
0.06380896270275116,
0.2950482666492462,
0.09182357043027878,
-0.2226516455411911,
0.2888721823692322,
-0.23050370812416077,
-0.20139402151107788,
-0.18630316853523254,
0.12676364183425903,
-0.021069806069135666,
-0.19755569100379944,
-0.31091368198394775,
-0.16034024953842163,
0.18026570975780487,
-0.015163816511631012,
-0.3553696870803833,
0.19000335037708282,
0.22559238970279694,
-0.04182204231619835,
-0.1311609297990799,
0.22774817049503326,
0.2554951012134552,
-0.06322768330574036,
-0.05395831912755966,
0.1503247320652008,
0.7298564314842224,
0.2667449414730072,
0.1422620713710785,
-0.16784663498401642,
0.041503921151161194,
0.4384757876396179,
0.2494744211435318,
0.014322001487016678,
0.23090054094791412,
0.5041629076004028,
0.6058549880981445,
0.10812121629714966,
-0.04871394485235214,
0.29230350255966187,
0.12374924123287201,
0.03654119372367859,
-0.4599583148956299,
-0.06597040593624115,
-0.04848200082778931,
-0.2736518681049347,
-0.19247521460056305,
-0.0760037899017334,
-0.14734040200710297,
0.37071287631988525,
0.15805155038833618,
-0.05577407032251358,
0.16497400403022766,
0.07142594456672668,
0.324858158826828,
-0.2492869645357132,
0.08210805058479309,
-0.12004059553146362,
0.01536385715007782,
0.03747386485338211,
0.43583157658576965,
0.3315373957157135,
0.17218945920467377,
-0.13928698003292084,
0.14918887615203857,
-0.0002274494618177414,
-0.10717981308698654,
0.1763480007648468,
0.19603392481803894,
0.4006015956401825,
0.03843868523836136,
0.07309971749782562,
0.045242540538311005,
0.02798810601234436,
-0.12604179978370667,
0.31556347012519836,
-0.21342405676841736,
0.09988749027252197,
-0.15060198307037354,
0.07479558885097504,
-0.3740050792694092,
-0.16975471377372742,
0.09984663873910904,
-0.16131079196929932,
0.3633503019809723,
0.6061455011367798,
-0.23281389474868774,
-0.04642936587333679,
-0.11821354180574417,
0.011206597089767456,
-0.10335047543048859,
0.41821733117103577,
0.3434796929359436,
0.12700296938419342,
-0.29066649079322815,
-0.2813267707824707,
-0.047038279473781586,
0.10857333987951279,
-0.03955468162894249,
-0.23724059760570526,
-0.05329872667789459,
0.03458254039287567,
0.2613576650619507,
0.41253042221069336,
0.04884767532348633,
0.13425299525260925,
-0.11785807460546494,
0.47180449962615967,
-0.28801384568214417,
-0.04197234287858009,
0.27318787574768066,
0.5164781808853149,
-0.1628139615058899,
-0.10243487358093262,
0.15229006111621857,
0.3586495816707611,
-0.06448974460363388,
-0.23673920333385468,
-0.08922378718852997,
0.32758402824401855,
-0.17799578607082367,
0.22377021610736847,
-0.09077423065900803,
0.15293294191360474,
-0.05167493224143982,
-0.12333330512046814,
0.004621267318725586,
-0.08744807541370392,
0.10571654886007309,
0.4439932107925415,
0.3223770558834076,
-0.1910894215106964,
-0.26522544026374817,
-0.0015395544469356537,
0.04711391031742096,
0.27495089173316956,
-0.28760039806365967,
-0.050848063081502914,
-0.27267876267433167,
-0.023377373814582825,
-0.26177310943603516,
0.14743778109550476,
-0.03487565740942955,
0.28765204548835754,
-0.21054619550704956,
0.11583209037780762,
-0.12690198421478271,
-0.13028763234615326,
0.09160180389881134,
-0.25090840458869934,
0.03996610268950462,
0.26852038502693176,
0.21695390343666077,
0.5681498050689697,
0.3674054443836212,
-0.5660695433616638,
0.21065393090248108,
0.23423747718334198,
0.07025489211082458,
0.1036049872636795,
0.06293847411870956,
0.00258641317486763,
0.10403327643871307,
-0.016969434916973114,
0.3965064287185669,
-0.05848296731710434,
-0.0382046215236187,
-0.46145692467689514,
-0.49836641550064087
] |
https://github.com/huggingface/datasets/issues/192 | [Question] Create Apache Arrow dataset from raw text file | Hello @mrm8488 and @lhoestq
Is there a way to convert a dataset to Apache arrow format (locally/personal use) & use it before sending it to hugging face?
Thanks :) | Hi guys, I have gathered and preprocessed about 2GB of COVID papers from CORD dataset @ Kggle. I have seen you have a text dataset as "Crime and punishment" in Apache arrow format. Do you have any script to do it from a raw txt file (preprocessed as for BERT like) or any guide?
Is the worth of send it to you and add it to the NLP library?
Thanks, Manu
| 29 | [Question] Create Apache Arrow dataset from raw text file
Hi guys, I have gathered and preprocessed about 2GB of COVID papers from CORD dataset @ Kggle. I have seen you have a text dataset as "Crime and punishment" in Apache arrow format. Do you have any script to do it from a raw txt file (preprocessed as for BERT like) or any guide?
Is the worth of send it to you and add it to the NLP library?
Thanks, Manu
Hello @mrm8488 and @lhoestq
Is there a way to convert a dataset to Apache arrow format (locally/personal use) & use it before sending it to hugging face?
Thanks :) | [
-0.10410341620445251,
-0.0871485024690628,
-0.09965090453624725,
0.15440313518047333,
-0.3756243586540222,
0.15951833128929138,
0.11732514202594757,
0.42783257365226746,
-0.043595489114522934,
-0.29375743865966797,
0.07305074483156204,
0.11510443687438965,
-0.08337914943695068,
0.1475035399198532,
0.25153082609176636,
-0.15385308861732483,
-0.0880170688033104,
0.21654415130615234,
-0.2933834493160248,
0.015711992979049683,
0.27406173944473267,
-0.024749254807829857,
-0.08778530359268188,
0.012240864336490631,
-0.17144320905208588,
-0.23625531792640686,
-0.12816700339317322,
-0.0033138543367385864,
-0.14507731795310974,
-0.3376830518245697,
-0.02538456954061985,
-0.02935335412621498,
0.5116754770278931,
0.20511534810066223,
-0.00012170407717349008,
-0.34656012058258057,
0.12741808593273163,
-0.004115752875804901,
-0.2411179542541504,
-0.20824997127056122,
-0.151987686753273,
-0.009040888398885727,
0.19447427988052368,
-0.3356022834777832,
-0.06002156808972359,
-0.3797878324985504,
0.030287371948361397,
-0.46885737776756287,
0.8392431735992432,
0.3928324580192566,
0.07577163726091385,
-0.16022609174251556,
0.1887146681547165,
0.2179344743490219,
0.34135088324546814,
0.5511065721511841,
-0.34023723006248474,
-0.07742129266262054,
0.14995825290679932,
0.03337541222572327,
-0.16508617997169495,
0.19850076735019684,
0.04398871213197708,
-0.153246209025383,
0.3540644347667694,
-0.03162287548184395,
-0.2806325852870941,
-0.22104308009147644,
0.12315778434276581,
0.32636189460754395,
0.49540793895721436,
-0.47507354617118835,
-0.045036979019641876,
-0.011971943080425262,
0.2050464153289795,
-0.42492926120758057,
-0.22572112083435059,
0.5759365558624268,
-0.4589052200317383,
0.4854774475097656,
0.1496037244796753,
-0.40089502930641174,
-0.4561852514743805,
-0.07455518841743469,
0.3925391137599945,
-0.11834357678890228,
-0.10440413653850555,
-0.06381229311227798,
-0.14212647080421448,
0.16296061873435974,
0.22700129449367523,
-0.33754250407218933,
-0.12779399752616882,
0.2690401077270508,
-0.04277494177222252,
-0.21517270803451538,
-0.5973444581031799,
-0.19733577966690063,
0.18537640571594238,
0.07732850313186646,
0.3857082426548004,
-0.112907774746418,
-0.04760902002453804,
-0.2783753573894501,
0.07719891518354416,
-0.07277937233448029,
0.43398335576057434,
0.13293291628360748,
-0.007070891559123993,
-0.2632562220096588,
0.17075678706169128,
-0.11871539801359177,
-0.09468083083629608,
0.017398886382579803,
-0.1367938220500946,
0.20157131552696228,
-0.010499807074666023,
-0.2780986428260803,
-0.03335587680339813,
-0.019908487796783447,
-0.3864952623844147,
-0.07700014114379883,
-0.2138030230998993,
0.026128772646188736,
0.20136471092700958,
-0.14675667881965637,
0.22471027076244354,
0.37763166427612305,
0.05205434560775757,
-0.28021350502967834,
0.17620937526226044,
-0.01802181825041771,
-0.23208202421665192,
0.2816554605960846,
0.08700843155384064,
0.1653803437948227,
-0.13530714809894562,
-0.06850451976060867,
-0.058296531438827515,
-0.14523959159851074,
0.25249144434928894,
-0.036170680075883865,
0.21758876740932465,
-0.06669114530086517,
0.20696479082107544,
0.016298608854413033,
-0.12016589939594269,
-0.007247496396303177,
-0.07581132650375366,
0.35496294498443604,
-0.18190181255340576,
0.035340290516614914,
-0.04450523108243942,
0.015734387561678886,
0.07062423974275589,
-0.08456777036190033,
-0.2357397973537445,
0.16044221818447113,
-0.0032508820295333862,
0.33366259932518005,
0.07029986381530762,
0.28684478998184204,
0.06052299961447716,
-0.14232565462589264,
-0.06134990602731705,
0.44516944885253906,
-0.33855628967285156,
0.14817200601100922,
-0.09775698930025101,
0.2030450850725174,
-0.11506327241659164,
0.3096967041492462,
-0.2214798778295517,
0.28552699089050293,
-0.021732572466135025,
0.2480594962835312,
0.7609075903892517,
-0.0031955912709236145,
0.1953616440296173,
0.49882906675338745,
0.032613471150398254,
-0.3793385624885559,
0.09234792739152908,
-0.08416327834129333,
-0.08584770560264587,
-0.029711073264479637,
-0.2868659794330597,
0.5281493067741394,
0.11185752600431442,
-0.0169500932097435,
-0.11940550804138184,
-0.17205464839935303,
-0.11659656465053558,
-0.053938183933496475,
-0.23231525719165802,
-0.05483003705739975,
0.09218277782201767,
-0.4823828935623169,
0.48952716588974,
-0.335669606924057,
0.45325058698654175,
0.23785249888896942,
0.025121541693806648,
-0.03932981193065643,
0.17496195435523987,
-0.03196074441075325,
-0.0986606702208519,
-0.3560510277748108,
-0.3879697024822235,
0.2141292244195938,
-0.32696717977523804,
-0.23821283876895905,
-0.2696836590766907,
-0.12529027462005615,
-0.06862235069274902,
0.08229755610227585,
-0.01979624107480049,
-0.23528045415878296,
-0.15579433739185333,
0.014363888651132584,
-0.21273356676101685,
0.3180287480354309,
-0.11018781363964081,
0.14913520216941833,
-0.22364474833011627,
0.11636769771575928,
0.1057070791721344,
-0.004393856041133404,
0.2375989556312561,
0.13671763241291046,
-0.23089119791984558,
0.052421558648347855,
-0.054583676159381866,
0.0032957755029201508,
-0.07111269235610962,
0.17900681495666504,
0.5197829604148865,
-0.2920801639556885,
0.07352743297815323,
-0.6826451420783997,
0.3104526400566101,
0.01753075420856476,
0.2184138298034668,
-0.10102784633636475,
-0.4654025137424469,
0.4807800054550171,
-0.08094540238380432,
0.19033676385879517,
-0.1441078782081604,
0.043296992778778076,
-0.13720957934856415,
-0.11262868344783783,
-0.16778352856636047,
0.14391864836215973,
-0.06783577799797058,
0.3569745719432831,
0.2148139476776123,
-0.09206975251436234,
0.09972019493579865,
0.03115183860063553,
-0.1916438192129135,
-0.1972682625055313,
0.2329721748828888,
0.21440386772155762,
-0.2332383096218109,
-0.07656899094581604,
-0.061181455850601196,
0.040917832404375076,
0.11759556829929352,
0.14910176396369934,
0.021691661328077316,
0.07660005986690521,
0.22029925882816315,
-0.1371527761220932,
0.33411848545074463,
-0.1321944296360016,
0.3828599154949188,
-0.15953022241592407,
-0.16526348888874054,
0.021199064329266548,
-0.09979048371315002,
-0.193245530128479,
-0.1010817438364029,
0.14014826714992523,
-0.08165815472602844,
-0.038220860064029694,
-0.13772624731063843,
-0.40400800108909607,
-0.3725435733795166,
0.26179951429367065,
-0.03137803450226784,
0.2539513111114502,
-0.0742642879486084,
-0.424617737531662,
0.14733347296714783,
-0.1559280902147293,
-0.07536538690328598,
0.5126533508300781,
0.07902292907238007,
0.06046071648597717,
-0.28361693024635315,
-0.3982830345630646,
-0.16304075717926025,
0.07741984724998474,
0.30698493123054504,
0.40575915575027466,
0.34915289282798767,
-0.08209364116191864,
0.19486449658870697,
-0.1915404498577118,
0.09424611181020737,
0.027147049084305763,
-0.03498043864965439,
-0.30891913175582886,
-0.15635044872760773,
0.16644491255283356,
-0.5549853444099426,
0.11955296993255615,
-0.18406939506530762,
0.1168874204158783,
-0.23893514275550842,
-0.2792016863822937,
-0.07527559995651245,
-0.021391257643699646,
0.22103792428970337,
-0.4112202525138855,
-0.13717827200889587,
-0.08414331823587418,
0.42231398820877075,
0.23396296799182892,
0.2500331997871399,
-0.04165847972035408,
0.1320330649614334,
0.1708654910326004,
-0.23383069038391113,
-0.0723307654261589,
0.19056569039821625,
-0.15384632349014282,
0.2510853707790375,
-0.36824554204940796,
-0.5960063338279724,
-0.0636395588517189,
-0.015842750668525696,
0.021004999056458473,
0.3126481771469116,
-0.4215537905693054,
0.5755350589752197,
-0.035364747047424316,
0.053930897265672684,
-0.14537562429904938,
-0.005995715036988258,
0.20333749055862427,
-0.033618539571762085,
0.044098325073719025,
-0.030090264976024628,
0.08547812700271606,
0.3154035210609436,
-0.16932356357574463,
0.3524860143661499,
0.41920360922813416,
0.13491728901863098,
0.08188965916633606,
0.6222638487815857,
0.24559468030929565,
0.10145352780818939,
0.23656949400901794,
-0.0248213279992342,
0.006416585296392441,
0.026079073548316956,
0.051901571452617645,
-0.14044982194900513,
0.19511981308460236,
0.1238490492105484,
0.07361648231744766,
0.2893804609775543,
-0.0958741158246994,
-0.29619133472442627,
-0.26517927646636963,
-0.3516789674758911,
-0.2011638581752777,
0.29699963331222534,
-0.3599572479724884,
0.2795429825782776,
-0.15597039461135864,
-0.21718445420265198,
-0.06307139992713928,
-0.31133943796157837,
0.05996665731072426,
0.12868838012218475,
0.3190666437149048,
0.14906051754951477,
-0.2706942558288574,
0.34821566939353943,
-0.6118109822273254,
0.34974855184555054,
0.051624152809381485,
-0.10029660165309906,
0.05672121420502663,
0.030564218759536743,
0.1468581110239029,
0.08642438799142838,
-0.17882390320301056,
0.11098543554544449,
-0.02531621605157852,
0.009351830929517746,
0.2899273633956909,
-0.4226803779602051,
0.3903345763683319,
-0.228807270526886,
0.11045856028795242,
0.012456780299544334,
0.1247149258852005,
-0.3796062767505646,
-0.2781963348388672,
0.13440150022506714,
0.24216262996196747,
-0.14169588685035706,
-0.36481356620788574,
0.2568521499633789,
0.008763179183006287,
-0.18793970346450806,
-0.11055953055620193,
0.37304532527923584,
0.020873036235570908,
-0.07553976774215698,
-0.19689372181892395,
-0.05982205271720886,
0.15742221474647522,
0.12727102637290955,
-0.3288094103336334,
0.10629283636808395,
-0.27296242117881775,
0.026045743376016617,
0.05754533410072327,
0.38840243220329285,
0.008848275989294052,
0.08767350763082504,
0.17699673771858215,
-0.21610409021377563,
-0.06899258494377136,
-0.30543607473373413,
0.6498403549194336,
0.22233113646507263,
0.12618371844291687,
0.1377880573272705,
0.21072715520858765,
-0.2504120469093323,
-0.07103036344051361,
-0.1461544930934906,
0.04115205258131027,
-0.06889695674180984,
-0.4261358380317688,
-0.34913817048072815,
0.5717188119888306,
0.053953658789396286,
0.0027203261852264404,
0.19814103841781616,
0.08373086154460907,
-0.2717004716396332,
0.5873885154724121,
0.27925077080726624,
1.185522437095642,
-0.27428150177001953,
0.27304890751838684,
-0.1355077624320984,
-0.316017746925354,
0.4253915250301361,
-0.27867889404296875,
-0.2547183632850647,
-0.5003959536552429,
0.44879671931266785,
-0.07695700973272324,
-0.15314775705337524,
0.429432213306427,
0.41808271408081055,
-0.04471581056714058,
0.023450668901205063,
0.21344710886478424,
-0.19627436995506287,
0.11166626214981079,
0.44475460052490234,
-0.3399270176887512,
-0.30095478892326355,
-0.09718866646289825,
-0.05439300835132599,
-0.12668243050575256,
0.1494974046945572,
0.12932434678077698,
-0.4405778646469116,
-0.37254294753074646,
0.08562347292900085,
-0.2790433466434479,
0.06759664416313171,
-0.16045573353767395,
-0.2300846427679062,
-0.30945369601249695,
-0.6526288986206055,
0.38459211587905884,
0.30310294032096863,
0.16113793849945068,
0.0180328581482172,
-0.1456814706325531,
0.06527063995599747,
-0.3059377670288086,
-0.21463371813297272,
0.14000774919986725,
-0.09702987968921661,
0.014985751360654831,
-0.17341473698616028,
-0.14731064438819885,
0.1327158510684967,
0.07229085266590118,
-0.22374700009822845,
0.036948010325431824,
-0.2066386193037033,
0.5542380809783936,
-0.22024859488010406,
-0.057372454553842545,
0.20829910039901733,
-0.3871699273586273,
0.0955580472946167,
0.07478738576173782,
0.34375059604644775,
0.010053078643977642,
-0.019843056797981262,
0.2923174500465393,
-0.19841399788856506,
0.06222645193338394,
0.19615569710731506,
0.20381462574005127,
-0.19679836928844452,
0.43999484181404114,
0.38451290130615234,
-0.09716885536909103,
-0.32262328267097473,
0.5589426755905151,
0.48946595191955566,
-0.7103240489959717,
-0.05827130004763603,
-0.08733179420232773,
0.17481128871440887,
0.0075123547576367855,
0.07378527522087097,
-0.04773649573326111,
-0.024275466799736023,
-0.041590385138988495,
-0.45077306032180786,
-0.3029094338417053,
0.02130497619509697,
-0.0532931424677372,
0.0931830033659935,
0.31392353773117065,
0.018152650445699692,
0.0753161758184433,
0.04191654548048973,
-0.20519816875457764,
0.15909433364868164,
0.6357861757278442,
0.17778651416301727,
0.027765974402427673,
0.04229686036705971,
-0.056716982275247574,
-0.0001512644812464714,
-0.004828028380870819,
0.13855107128620148,
0.0704178512096405,
-0.174381822347641,
-0.03296966105699539,
0.2171880006790161,
-0.09015798568725586,
-0.3297184407711029,
-0.33929261565208435,
-0.44494307041168213,
-0.15494011342525482,
-0.03558608517050743,
-0.13536983728408813,
-0.08628912270069122,
-0.06770709156990051,
0.16228163242340088,
0.17669163644313812,
-0.09132010489702225,
-0.5623161196708679,
0.1294589340686798,
-0.10235713422298431,
0.21732443571090698,
-0.13209490478038788,
0.16996757686138153,
0.09857195615768433,
-0.05798983946442604,
0.04792109131813049,
0.009129434823989868,
0.3277367353439331,
0.16313984990119934,
0.35374221205711365,
-0.17176230251789093,
0.04795057699084282,
-0.2062690705060959,
0.3029593527317047,
0.14168061316013336,
-0.008553537540137768,
0.07447546720504761,
0.2950400114059448,
0.07731816917657852,
-0.20862732827663422,
0.2393229603767395,
-0.21360789239406586,
-0.22185061872005463,
-0.2649485170841217,
0.059707723557949066,
0.004555646330118179,
0.026559151709079742,
-0.4137255549430847,
-0.2439277172088623,
0.04004896059632301,
0.009618261829018593,
-0.2730497121810913,
0.3426245152950287,
0.1418381780385971,
-0.0367220900952816,
-0.012312350794672966,
0.22880738973617554,
0.16126631200313568,
-0.057614587247371674,
-0.10032588988542557,
0.1408086121082306,
0.7164052724838257,
0.25883302092552185,
0.22971674799919128,
-0.14957675337791443,
0.10609418153762817,
0.3407496213912964,
0.17358361184597015,
0.06045181676745415,
0.30843037366867065,
0.501695990562439,
0.49053341150283813,
-0.06533706933259964,
0.10396670550107956,
0.2332955002784729,
0.02620002068579197,
0.09245093166828156,
-0.2975195050239563,
-0.09762099385261536,
-0.07974141836166382,
-0.2705274224281311,
-0.26703470945358276,
-0.0659562349319458,
-0.12805064022541046,
0.37830907106399536,
0.22421573102474213,
0.006519787944853306,
0.09486521780490875,
0.0762881189584732,
0.30902552604675293,
-0.19678980112075806,
-0.08400505036115646,
-0.047924816608428955,
0.06425436586141586,
0.014819752424955368,
0.44661566615104675,
0.14851871132850647,
0.1166367381811142,
-0.18219128251075745,
0.21957474946975708,
-0.032384149730205536,
-0.13474971055984497,
0.25331494212150574,
0.24931135773658752,
0.43743470311164856,
0.024659302085638046,
0.16236242651939392,
0.0377783477306366,
0.06002858281135559,
0.010893892496824265,
0.19675016403198242,
-0.1606857180595398,
-0.10829699039459229,
-0.048386819660663605,
-0.07437437772750854,
-0.45578721165657043,
-0.21377207338809967,
0.07236243784427643,
-0.1384688913822174,
0.20172850787639618,
0.6342796087265015,
-0.3023315668106079,
-0.0542244054377079,
-0.2243732064962387,
0.012459781020879745,
-0.11517803370952606,
0.42381569743156433,
0.3466522991657257,
0.143425852060318,
-0.2957482635974884,
-0.2863423228263855,
-0.06824139505624771,
0.11662796139717102,
-0.023076195269823074,
-0.04253184050321579,
-0.09624232351779938,
-0.031166289001703262,
0.2795169949531555,
0.5127824544906616,
0.13443022966384888,
0.12040817737579346,
-0.17573872208595276,
0.48935070633888245,
-0.23794102668762207,
-0.019993234425783157,
0.4501163959503174,
0.5878046154975891,
-0.15019407868385315,
-0.1882663369178772,
0.3224354684352875,
0.615074634552002,
-0.06042851135134697,
-0.1997968554496765,
0.00783056765794754,
0.33421847224235535,
-0.17057214677333832,
0.20960336923599243,
-0.01346089132130146,
0.09708046913146973,
0.02499491721391678,
-0.09996960312128067,
0.14133583009243011,
0.032871756702661514,
0.12586301565170288,
0.5581203699111938,
0.25094497203826904,
-0.17178665101528168,
-0.20902101695537567,
-0.06832177937030792,
0.015021784231066704,
0.2349604070186615,
-0.33540862798690796,
-0.0859619528055191,
-0.31260308623313904,
-0.09726447612047195,
-0.2712610065937042,
0.04189324751496315,
0.01688387617468834,
0.3037467896938324,
-0.17290370166301727,
0.012211451306939125,
-0.20690622925758362,
0.023852596059441566,
0.11828340590000153,
-0.2757697105407715,
0.030768264085054398,
0.364524245262146,
0.10293464362621307,
0.6225420236587524,
0.15047995746135712,
-0.4848259389400482,
0.14814814925193787,
0.3166601061820984,
-0.022683419287204742,
0.26371610164642334,
0.09053975343704224,
0.05713647976517677,
0.13081464171409607,
0.010113336145877838,
0.5547727942466736,
-0.056815773248672485,
0.00499417819082737,
-0.5158873200416565,
-0.4087069034576416
] |
https://github.com/huggingface/datasets/issues/192 | [Question] Create Apache Arrow dataset from raw text file | > Is there a way to convert a dataset to Apache arrow format (locally/personal use) & use it before sending it to hugging face?
Sure, to get a dataset in arrow format you can either:
- [load from local files (txt, json, csv)](https://huggingface.co/nlp/loading_datasets.html?highlight=csv#from-local-files)
- OR [load from python data (dict, pandas)](https://huggingface.co/nlp/loading_datasets.html?highlight=csv#from-in-memory-data)
- OR [create your own dataset script](https://huggingface.co/nlp/loading_datasets.html?highlight=csv#using-a-custom-dataset-loading-script)
| Hi guys, I have gathered and preprocessed about 2GB of COVID papers from CORD dataset @ Kggle. I have seen you have a text dataset as "Crime and punishment" in Apache arrow format. Do you have any script to do it from a raw txt file (preprocessed as for BERT like) or any guide?
Is the worth of send it to you and add it to the NLP library?
Thanks, Manu
| 58 | [Question] Create Apache Arrow dataset from raw text file
Hi guys, I have gathered and preprocessed about 2GB of COVID papers from CORD dataset @ Kggle. I have seen you have a text dataset as "Crime and punishment" in Apache arrow format. Do you have any script to do it from a raw txt file (preprocessed as for BERT like) or any guide?
Is the worth of send it to you and add it to the NLP library?
Thanks, Manu
> Is there a way to convert a dataset to Apache arrow format (locally/personal use) & use it before sending it to hugging face?
Sure, to get a dataset in arrow format you can either:
- [load from local files (txt, json, csv)](https://huggingface.co/nlp/loading_datasets.html?highlight=csv#from-local-files)
- OR [load from python data (dict, pandas)](https://huggingface.co/nlp/loading_datasets.html?highlight=csv#from-in-memory-data)
- OR [create your own dataset script](https://huggingface.co/nlp/loading_datasets.html?highlight=csv#using-a-custom-dataset-loading-script)
| [
-0.11623531579971313,
-0.18411743640899658,
-0.07161258906126022,
0.17512014508247375,
-0.3280264139175415,
0.13923606276512146,
0.11795933544635773,
0.38174307346343994,
0.0022522900253534317,
-0.27272242307662964,
0.056914299726486206,
0.09839931130409241,
-0.07723778486251831,
0.2192150205373764,
0.3109802007675171,
-0.05802804231643677,
-0.10293128341436386,
0.18729205429553986,
-0.2899806499481201,
0.03419706970453262,
0.24861109256744385,
0.02355029247701168,
-0.06273826211690903,
0.014808647334575653,
-0.18604975938796997,
-0.21685835719108582,
-0.12376022338867188,
0.10292959213256836,
-0.11955898255109787,
-0.40562549233436584,
0.04538264870643616,
-0.02501906082034111,
0.5199143886566162,
0.17655107378959656,
-0.00012255784531589597,
-0.3012934923171997,
0.14918234944343567,
-0.008922338485717773,
-0.2559577226638794,
-0.3521430492401123,
-0.09115904569625854,
-0.05141822248697281,
0.3022270202636719,
-0.27631571888923645,
-0.13665299117565155,
-0.36661404371261597,
0.044753964990377426,
-0.4632765054702759,
0.894417405128479,
0.38236698508262634,
0.06688161194324493,
-0.06973031163215637,
0.12017402052879333,
0.17469841241836548,
0.29358938336372375,
0.6498956084251404,
-0.29851973056793213,
0.01733425073325634,
0.22698600590229034,
-0.0276035163551569,
-0.18706870079040527,
0.21038703620433807,
0.03350234031677246,
-0.16015806794166565,
0.41826844215393066,
0.03294292464852333,
-0.3197293281555176,
-0.26673150062561035,
0.10459907352924347,
0.29186373949050903,
0.44357216358184814,
-0.5081267356872559,
-0.06863570958375931,
-0.1588287353515625,
0.19593681395053864,
-0.40478408336639404,
-0.20237398147583008,
0.5912532806396484,
-0.45607396960258484,
0.4850004315376282,
0.11115680634975433,
-0.3301267623901367,
-0.4546760320663452,
-0.023367010056972504,
0.41302016377449036,
-0.11923055350780487,
-0.1424250602722168,
-0.03422095626592636,
-0.08781935274600983,
0.11395935714244843,
0.14466159045696259,
-0.34028249979019165,
-0.08196960389614105,
0.2702951431274414,
-0.030417662113904953,
-0.14818450808525085,
-0.5688720941543579,
-0.11655572801828384,
0.2962394058704376,
0.19481061398983002,
0.3581240773200989,
-0.14922824501991272,
-0.08302667737007141,
-0.24126338958740234,
0.11707843840122223,
-0.035984721034765244,
0.4621579349040985,
0.12294962257146835,
-0.022878237068653107,
-0.10338762402534485,
0.21610522270202637,
-0.11804764717817307,
-0.07146736234426498,
-0.007160442881286144,
-0.19580762088298798,
0.1252121478319168,
0.06821299344301224,
-0.35838767886161804,
-0.06369633227586746,
-0.06358198821544647,
-0.3160603940486908,
-0.06485778838396072,
-0.16414423286914825,
0.12130085378885269,
0.15002983808517456,
-0.1485426127910614,
0.20260143280029297,
0.4209895133972168,
0.002455327659845352,
-0.23466061055660248,
0.1313377469778061,
-0.01091739907860756,
-0.2892898917198181,
0.3412545621395111,
0.15145495533943176,
0.04102557897567749,
-0.033676959574222565,
-0.06513373553752899,
0.041875869035720825,
-0.18664006888866425,
0.2114461213350296,
0.0035024136304855347,
0.25545647740364075,
-0.027918193489313126,
0.22552108764648438,
0.05125468969345093,
-0.08152379095554352,
-0.015555758029222488,
-0.1415528506040573,
0.3194226622581482,
-0.19716235995292664,
-0.0013497546315193176,
-0.01955215446650982,
-0.012566233985126019,
-0.07126863300800323,
-0.1170920580625534,
-0.29664430022239685,
0.16671687364578247,
-0.05532965809106827,
0.3410831391811371,
0.05154557526111603,
0.30411356687545776,
-0.004431478679180145,
-0.15689964592456818,
0.06064585596323013,
0.5751582980155945,
-0.27983880043029785,
0.0774809867143631,
-0.06367764621973038,
0.1921238899230957,
-0.13203993439674377,
0.32104748487472534,
-0.2403281182050705,
0.20451784133911133,
-0.10772127658128738,
0.21508730947971344,
0.6738172769546509,
-0.111568883061409,
0.16387313604354858,
0.5188359022140503,
0.056450217962265015,
-0.2370753288269043,
0.11921419203281403,
-0.11641399562358856,
-0.07434406876564026,
-0.0028064223006367683,
-0.3140353560447693,
0.5571510791778564,
0.08260932564735413,
0.01825597696006298,
-0.12995746731758118,
-0.21523694694042206,
-0.09700989723205566,
0.00468393974006176,
-0.23405607044696808,
-0.014258526265621185,
0.060363639146089554,
-0.5500681400299072,
0.4852308928966522,
-0.32607460021972656,
0.400387167930603,
0.23203349113464355,
0.0025297626852989197,
0.02298756316304207,
0.1399737000465393,
-0.031166348606348038,
-0.26830238103866577,
-0.25660666823387146,
-0.31450095772743225,
0.2239762395620346,
-0.45106619596481323,
-0.24881407618522644,
-0.3250754177570343,
-0.13213957846164703,
-0.10724616050720215,
-0.021121937781572342,
-0.06251736730337143,
-0.2079959213733673,
-0.10984879732131958,
0.053021226078271866,
-0.21073785424232483,
0.36422213912010193,
-0.05453042685985565,
0.24731077253818512,
-0.369183212518692,
0.1250729113817215,
0.131422221660614,
-0.010291158221662045,
0.23380392789840698,
0.17634448409080505,
-0.1896401047706604,
0.03401071950793266,
0.007023070938885212,
0.08414427936077118,
0.010062401182949543,
0.2041340172290802,
0.4599419832229614,
-0.2706068158149719,
0.12420658022165298,
-0.7130149602890015,
0.2794916331768036,
0.007425929419696331,
0.1846461296081543,
-0.09204725921154022,
-0.4825463593006134,
0.5747973918914795,
-0.14493034780025482,
0.23111018538475037,
-0.1459645926952362,
0.027441812679171562,
-0.13340207934379578,
-0.07772533595561981,
-0.22561107575893402,
0.06281210482120514,
-0.032138075679540634,
0.32594117522239685,
0.3570249378681183,
-0.12372724711894989,
0.017253518104553223,
0.03389055281877518,
-0.22877836227416992,
-0.2201501429080963,
0.15034902095794678,
0.26336804032325745,
-0.24480053782463074,
-0.07236368954181671,
-0.03271276503801346,
-0.008668195456266403,
0.114156574010849,
0.1704612672328949,
-0.025074291974306107,
0.12046820670366287,
0.2024989277124405,
-0.14061719179153442,
0.3045223653316498,
-0.10037079453468323,
0.4107745289802551,
-0.17753532528877258,
-0.13777637481689453,
-0.01287070196121931,
-0.12090450525283813,
-0.23075637221336365,
-0.16143406927585602,
0.10699710994958878,
-0.17705467343330383,
-0.008562078699469566,
-0.16584168374538422,
-0.49550169706344604,
-0.41691046953201294,
0.23199589550495148,
-0.06793010234832764,
0.2515646815299988,
-0.16291965544223785,
-0.33356720209121704,
0.12842419743537903,
-0.1341254860162735,
-0.10172967612743378,
0.473461389541626,
-0.0070494599640369415,
0.01629512384533882,
-0.2771504819393158,
-0.38154298067092896,
-0.16488194465637207,
0.06597517430782318,
0.3686506152153015,
0.41833606362342834,
0.3976905047893524,
-0.12005145847797394,
0.13771796226501465,
-0.19119052588939667,
0.014920510351657867,
0.048584356904029846,
-0.0908251702785492,
-0.21377716958522797,
-0.1240314245223999,
0.13249337673187256,
-0.5243587493896484,
0.0738309845328331,
-0.11730518937110901,
0.08368150889873505,
-0.23695914447307587,
-0.287192702293396,
-0.09819870442152023,
0.013112182728946209,
0.1493162214756012,
-0.3908492922782898,
-0.1651652455329895,
-0.10185348987579346,
0.5026170015335083,
0.25109153985977173,
0.19040639698505402,
0.04375794902443886,
0.10605809837579727,
0.1319570392370224,
-0.2570900022983551,
-0.10649888217449188,
0.18408675491809845,
-0.20155015587806702,
0.2977464199066162,
-0.39212673902511597,
-0.5845625400543213,
-0.11088474094867706,
-0.006884768605232239,
0.03418830409646034,
0.28568094968795776,
-0.4618057608604431,
0.41268226504325867,
-0.07110361754894257,
0.07117271423339844,
-0.11788609623908997,
-0.01039588637650013,
0.20418310165405273,
-0.025251850485801697,
0.0849703848361969,
-0.020421545952558517,
-0.017280973494052887,
0.298691987991333,
-0.20029914379119873,
0.2878692150115967,
0.4254693388938904,
0.1723223626613617,
0.058060433715581894,
0.5829074382781982,
0.3013733923435211,
0.1089276522397995,
0.2840297222137451,
-0.08005814254283905,
0.05360933393239975,
-0.02631373703479767,
0.013504425063729286,
-0.2094152867794037,
0.12492375075817108,
0.14099834859371185,
0.10728881508111954,
0.30725088715553284,
-0.03692931681871414,
-0.3321259319782257,
-0.28665441274642944,
-0.41476643085479736,
-0.21308201551437378,
0.30389174818992615,
-0.38708120584487915,
0.23486050963401794,
-0.18260973691940308,
-0.18359503149986267,
-0.07116365432739258,
-0.31488892436027527,
0.05090334266424179,
0.22340431809425354,
0.3517563045024872,
0.2050117701292038,
-0.2665773034095764,
0.42818528413772583,
-0.6509031653404236,
0.36899155378341675,
0.05844457447528839,
-0.1497977375984192,
0.050097446888685226,
-0.004401609301567078,
0.17925038933753967,
0.07588078081607819,
-0.10500721633434296,
0.169464573264122,
-0.018786177039146423,
-0.022987715899944305,
0.1463407278060913,
-0.5188398957252502,
0.39623939990997314,
-0.1713441163301468,
0.02779264748096466,
0.012690221890807152,
0.19453568756580353,
-0.43167951703071594,
-0.3492641746997833,
0.11258301883935928,
0.2232145220041275,
-0.12154300510883331,
-0.3311595916748047,
0.21770144999027252,
-0.06027301028370857,
-0.24204589426517487,
-0.0690440908074379,
0.3726750910282135,
0.03390030562877655,
-0.047613754868507385,
-0.13076594471931458,
-0.04701988399028778,
0.12143319100141525,
0.11338669061660767,
-0.26113712787628174,
0.13783738017082214,
-0.2840893566608429,
0.09319926798343658,
0.14680469036102295,
0.42589765787124634,
0.07082612812519073,
0.21173246204853058,
0.13413259387016296,
-0.340861976146698,
-0.12266609817743301,
-0.22335781157016754,
0.6217302083969116,
0.2724975347518921,
0.15294653177261353,
0.09791561961174011,
0.2817009389400482,
-0.2173740416765213,
-0.17630131542682648,
-0.09220097959041595,
0.029144084081053734,
-0.06997953355312347,
-0.421385794878006,
-0.37580588459968567,
0.5728219747543335,
0.03647741302847862,
-0.021538957953453064,
0.15765061974525452,
0.14217323064804077,
-0.2886929512023926,
0.5798212289810181,
0.24263042211532593,
1.1859325170516968,
-0.2814680337905884,
0.31370726227760315,
-0.03596274554729462,
-0.360617458820343,
0.5188565254211426,
-0.201727956533432,
-0.27785593271255493,
-0.4951661229133606,
0.3837963938713074,
-0.04490648955106735,
-0.18553081154823303,
0.3748287558555603,
0.3764258027076721,
-0.030155284330248833,
0.1241893395781517,
0.16666489839553833,
-0.12160615622997284,
0.05953522026538849,
0.47545504570007324,
-0.312310129404068,
-0.34697553515434265,
-0.15084673464298248,
-0.07249189913272858,
-0.1424747258424759,
0.2328319400548935,
0.12784799933433533,
-0.45531749725341797,
-0.36892133951187134,
0.06390170753002167,
-0.25991761684417725,
0.1060086116194725,
-0.21665330231189728,
-0.24640588462352753,
-0.2637867033481598,
-0.6389373540878296,
0.41278719902038574,
0.36399346590042114,
0.220606729388237,
-0.04784080758690834,
-0.2109031081199646,
0.08878776431083679,
-0.3631051182746887,
-0.18496039509773254,
0.12916597723960876,
-0.14812685549259186,
0.03022698499262333,
-0.1457628458738327,
-0.11702010035514832,
0.0354306623339653,
0.11575955152511597,
-0.17766138911247253,
-0.019819527864456177,
-0.1916959434747696,
0.45271193981170654,
-0.26642051339149475,
-0.10804013907909393,
0.19887083768844604,
-0.2783833146095276,
0.08723224699497223,
0.03405511751770973,
0.31136322021484375,
0.049848657101392746,
-0.0752512738108635,
0.2784467041492462,
-0.22621800005435944,
0.027817463502287865,
0.228594571352005,
0.16525056958198547,
-0.264872282743454,
0.4430118799209595,
0.425874799489975,
-0.09706966578960419,
-0.254608690738678,
0.4642239212989807,
0.581470251083374,
-0.8045464754104614,
-0.02388336881995201,
-0.05021890625357628,
0.1676592379808426,
0.02494833618402481,
0.11201559752225876,
-0.013125497847795486,
-0.09906893223524094,
0.03518950566649437,
-0.4654947817325592,
-0.3229876458644867,
0.0847470685839653,
-0.05763581767678261,
0.10016071796417236,
0.33518677949905396,
0.10849267244338989,
0.05705278366804123,
0.0697697326540947,
-0.19205892086029053,
0.1754726767539978,
0.6514856219291687,
0.16727936267852783,
0.12899954617023468,
0.044357120990753174,
0.05866865813732147,
-0.010351757518947124,
-0.029424188658595085,
0.15425318479537964,
0.033484265208244324,
-0.14044460654258728,
-0.05531327426433563,
0.22434090077877045,
-0.11151164025068283,
-0.3583466410636902,
-0.30706509947776794,
-0.3529408574104309,
-0.0504787378013134,
-0.14498578011989594,
-0.0487508662045002,
-0.06242793798446655,
-0.048514626920223236,
0.11967781186103821,
0.09116675704717636,
-0.06606367975473404,
-0.5188183188438416,
0.16587643325328827,
-0.12332658469676971,
0.21302790939807892,
-0.027788789942860603,
0.16786661744117737,
-0.014582027681171894,
-0.0924047976732254,
0.06336070597171783,
0.019591279327869415,
0.347075879573822,
0.2004651129245758,
0.3311263918876648,
-0.11110356450080872,
-0.019029829651117325,
-0.20461252331733704,
0.34920892119407654,
0.1420440375804901,
0.04396386072039604,
0.04862738400697708,
0.3234454393386841,
0.06121771037578583,
-0.1930483877658844,
0.2455327957868576,
-0.1727200746536255,
-0.18861542642116547,
-0.2519422173500061,
0.0988527461886406,
0.03157603368163109,
0.10778237879276276,
-0.4496346116065979,
-0.23619261384010315,
0.17203710973262787,
0.06814950704574585,
-0.258975625038147,
0.2703651189804077,
0.14384567737579346,
-0.03995649889111519,
-0.007922982797026634,
0.27942895889282227,
0.22925084829330444,
-0.08278056979179382,
-0.1410936713218689,
0.1737515926361084,
0.6221064329147339,
0.35927021503448486,
0.29032212495803833,
-0.23674072325229645,
0.06427210569381714,
0.33668479323387146,
0.18424676358699799,
0.03932691365480423,
0.2048325389623642,
0.6484082937240601,
0.5068117380142212,
-0.07449229806661606,
0.11960945278406143,
0.29356828331947327,
0.04900941997766495,
0.03089677169919014,
-0.2590872049331665,
-0.08743606507778168,
-0.12445281445980072,
-0.19977828860282898,
-0.26839759945869446,
-0.1559889018535614,
-0.07701228559017181,
0.32390719652175903,
0.19428834319114685,
-0.028334075585007668,
0.028100455179810524,
0.09170132130384445,
0.30897948145866394,
-0.1727255880832672,
0.022006860002875328,
0.0015087723731994629,
0.01093374565243721,
0.040897201746702194,
0.43185803294181824,
0.2473566234111786,
0.09488613903522491,
-0.12778662145137787,
0.2288220226764679,
0.026229051873087883,
-0.09294761717319489,
0.2152305394411087,
0.19966132938861847,
0.3968440890312195,
0.03586225211620331,
0.18723459541797638,
0.03754754364490509,
0.06753221154212952,
-0.055728521198034286,
0.18198063969612122,
-0.15538348257541656,
-0.07866621017456055,
-0.150333434343338,
-0.051529377698898315,
-0.3914935290813446,
-0.19860784709453583,
0.06892629712820053,
-0.17805668711662292,
0.2038511484861374,
0.5880892276763916,
-0.2470196932554245,
-0.04993647709488869,
-0.16663672029972076,
0.00043440423905849457,
-0.03191450983285904,
0.45689618587493896,
0.3662309944629669,
0.14163066446781158,
-0.30244672298431396,
-0.32491812109947205,
-0.13995331525802612,
0.09046223759651184,
-0.014410216361284256,
-0.09643401205539703,
-0.05399131029844284,
-0.05557709187269211,
0.22304940223693848,
0.45404696464538574,
0.02330099046230316,
0.1714804321527481,
-0.1257140189409256,
0.4537195563316345,
-0.22176793217658997,
-0.010113108903169632,
0.37255823612213135,
0.5218807458877563,
-0.10128220170736313,
-0.13284358382225037,
0.25423502922058105,
0.5032428503036499,
-0.09317536652088165,
-0.1573285311460495,
0.05690664052963257,
0.23135694861412048,
-0.25062325596809387,
0.20016826689243317,
0.035372328013181686,
0.13309989869594574,
-0.007061762735247612,
-0.15031678974628448,
0.09966996312141418,
-0.02799461968243122,
0.05913616344332695,
0.6108744144439697,
0.24947255849838257,
-0.10200604051351547,
-0.21705719828605652,
-0.11341233551502228,
-0.05578731745481491,
0.2859748899936676,
-0.2583238482475281,
-0.12872783839702606,
-0.3091915249824524,
-0.062091320753097534,
-0.24192306399345398,
0.025370411574840546,
0.0015793079510331154,
0.40263399481773376,
-0.155255526304245,
0.06434876471757889,
-0.16876152157783508,
-0.04738273471593857,
0.2202804833650589,
-0.31012842059135437,
0.08213500678539276,
0.32826653122901917,
0.12444241344928741,
0.6768010258674622,
0.10875971615314484,
-0.5213270783424377,
0.1987709403038025,
0.2741400897502899,
0.004109051078557968,
0.219305157661438,
0.09368613362312317,
0.053228069096803665,
0.07330302894115448,
-0.03502937778830528,
0.4586232900619507,
-0.029533907771110535,
-0.029490791261196136,
-0.42908352613449097,
-0.4309493899345398
] |
https://github.com/huggingface/datasets/issues/189 | [Question] BERT-style multiple choice formatting | Hi @sarahwie, can you details this a little more?
I'm not sure I understand what you refer to and what you mean when you say "Previously, this was done by passing a list of InputFeatures to the dataloader instead of a list of InputFeature" | Hello, I am wondering what the equivalent formatting of a dataset should be to allow for multiple-choice answering prediction, BERT-style. Previously, this was done by passing a list of `InputFeatures` to the dataloader instead of a list of `InputFeature`, where `InputFeatures` contained lists of length equal to the number of answer choices in the MCQ instead of single items. I'm a bit confused on what the output of my feature conversion function should be when using `dataset.map()` to ensure similar behavior.
Thanks! | 44 | [Question] BERT-style multiple choice formatting
Hello, I am wondering what the equivalent formatting of a dataset should be to allow for multiple-choice answering prediction, BERT-style. Previously, this was done by passing a list of `InputFeatures` to the dataloader instead of a list of `InputFeature`, where `InputFeatures` contained lists of length equal to the number of answer choices in the MCQ instead of single items. I'm a bit confused on what the output of my feature conversion function should be when using `dataset.map()` to ensure similar behavior.
Thanks!
Hi @sarahwie, can you details this a little more?
I'm not sure I understand what you refer to and what you mean when you say "Previously, this was done by passing a list of InputFeatures to the dataloader instead of a list of InputFeature" | [
0.189832866191864,
-0.4081777036190033,
-0.02667148783802986,
-0.07893197238445282,
0.17554613947868347,
-0.11440110206604004,
0.2933264672756195,
0.23464734852313995,
-0.11313799023628235,
-0.006701231002807617,
-0.07507719844579697,
0.5407452583312988,
-0.25638607144355774,
0.21988382935523987,
0.0012711333110928535,
-0.44989344477653503,
0.16272661089897156,
0.13243573904037476,
-0.12136062979698181,
-0.11142566800117493,
-0.2248261719942093,
-0.18424540758132935,
-0.2530255913734436,
-0.1031172126531601,
-0.15764784812927246,
0.06863262504339218,
-0.3666492998600006,
-0.21603578329086304,
-0.37540403008461,
-0.333639919757843,
-0.1936650276184082,
0.2823522686958313,
-0.21831154823303223,
-0.03667692095041275,
-0.00012514082482084632,
-0.4015752077102661,
-0.1773592233657837,
-0.17478589713573456,
-0.11023940145969391,
-0.11791358888149261,
-0.8842170238494873,
-0.007036093156784773,
0.38440045714378357,
0.018586695194244385,
0.007791262120008469,
0.026044782251119614,
0.026937825605273247,
-0.3077804744243622,
0.4810143709182739,
-0.008772121742367744,
0.07200632989406586,
-0.037221767008304596,
0.03685818985104561,
0.0641988143324852,
0.1308983862400055,
0.5086036324501038,
0.01867283694446087,
-0.04318332299590111,
0.6300451755523682,
0.003555065020918846,
-0.20570045709609985,
0.3613415062427521,
0.09690244495868683,
0.10612984001636505,
0.34404945373535156,
-0.02620140090584755,
-0.05275914818048477,
-0.08939734101295471,
-0.2308887541294098,
0.3512212038040161,
0.7839898467063904,
-0.0999956950545311,
-0.26931700110435486,
-0.037071987986564636,
0.02138654515147209,
0.06871125102043152,
-0.1864115297794342,
0.01460917480289936,
-0.1401163786649704,
-0.06115397438406944,
-0.48590776324272156,
-0.3253767192363739,
-0.3561829626560211,
0.06938893347978592,
-0.2764469087123871,
0.4265614151954651,
0.008110159076750278,
-0.035178884863853455,
-0.05221099033951759,
-0.2725643515586853,
-0.021641220897436142,
-0.4392715394496918,
0.39041703939437866,
0.1420876681804657,
0.1063588410615921,
-0.37915337085723877,
-0.1874583661556244,
0.07733557373285294,
0.37103471159935,
-0.2946627140045166,
-0.0931793674826622,
-0.0026956871151924133,
-0.5204649567604065,
-0.0124722421169281,
0.5711627006530762,
0.0022489195689558983,
-0.04572527855634689,
0.07216678559780121,
-0.3457534909248352,
-0.29139602184295654,
-0.2567962408065796,
0.04164757579565048,
0.12521547079086304,
0.2284185141324997,
0.07164223492145538,
0.1218288317322731,
0.05681435763835907,
-0.321562260389328,
0.06382282078266144,
0.07790405303239822,
-0.3623915910720825,
-0.20421423017978668,
0.03367452695965767,
0.154516339302063,
-0.08497203886508942,
0.5170227289199829,
-0.1964961290359497,
0.20776639878749847,
0.08788135647773743,
-0.35689577460289,
0.1389586180448532,
-0.10198041796684265,
-0.5272906422615051,
-0.2540569603443146,
0.19491790235042572,
0.2871021330356598,
-0.010821458883583546,
0.36924538016319275,
0.37839585542678833,
-0.2300274521112442,
0.07069475948810577,
0.0249626524746418,
0.5642063617706299,
-0.18388137221336365,
-0.35279953479766846,
0.3267550468444824,
0.29061374068260193,
0.3297920227050781,
-0.08868296444416046,
0.5011613368988037,
-0.21087926626205444,
-0.014086801558732986,
-0.153348907828331,
0.017584221437573433,
0.21666352450847626,
-0.21159717440605164,
0.04111845791339874,
0.3512011468410492,
0.045034557580947876,
-0.3355676531791687,
0.13014280796051025,
-0.5346509218215942,
0.04989193007349968,
-0.2956683039665222,
0.002575365826487541,
0.4049500823020935,
-0.46270552277565,
0.09012217819690704,
-0.19625224173069,
0.23597614467144012,
0.2237938642501831,
0.26253271102905273,
-0.07536926865577698,
-0.059609390795230865,
-0.011268031783401966,
0.356981098651886,
0.31552308797836304,
-0.16380952298641205,
-0.31837132573127747,
0.22978602349758148,
0.16081301867961884,
0.11740314215421677,
-0.036376602947711945,
0.23446999490261078,
0.1547362357378006,
0.2690247595310211,
0.05115576088428497,
-0.1387476921081543,
-0.30224430561065674,
0.36625227332115173,
-0.018001213669776917,
-0.04290368780493736,
0.12097165733575821,
-0.04484010487794876,
-0.07994233071804047,
-0.14226484298706055,
-0.08018431812524796,
0.11475404351949692,
0.21867242455482483,
-0.20548701286315918,
-0.05747019499540329,
-0.42732083797454834,
0.15273521840572357,
0.029008686542510986,
-0.12003201246261597,
-0.17264282703399658,
-0.6358430981636047,
-0.07989707589149475,
-0.028847303241491318,
-0.1870037466287613,
0.22696946561336517,
-0.2735062837600708,
-0.2580797076225281,
0.058287858963012695,
-0.33636143803596497,
0.10470384359359741,
-0.013620542362332344,
0.020014546811580658,
-0.2457858920097351,
-0.29985085129737854,
-0.27718693017959595,
-0.06258738040924072,
0.5232810378074646,
0.018669795244932175,
0.05305280163884163,
0.11633943021297455,
0.09669698029756546,
0.0029886425472795963,
0.13223706185817719,
0.3557763993740082,
0.19228729605674744,
0.2523917853832245,
-0.03136170655488968,
0.2370242476463318,
0.45958828926086426,
-0.048325315117836,
-0.03865766525268555,
0.11578787118196487,
0.4056984782218933,
-0.23331999778747559,
0.32311785221099854,
0.17757375538349152,
0.09546326100826263,
-0.013860311359167099,
-0.8099335432052612,
0.189357727766037,
-0.07852838933467865,
0.11697982251644135,
-0.14940418303012848,
0.2087828814983368,
-0.1929720640182495,
0.2378268837928772,
-0.06035556644201279,
-0.4787614345550537,
-0.12163159251213074,
0.26565828919410706,
0.1503821611404419,
0.07501419633626938,
-0.4771554172039032,
0.2781411111354828,
0.37942156195640564,
-0.017873769626021385,
0.2281641960144043,
-0.06022486835718155,
-0.01726694405078888,
-0.09874344617128372,
0.41970616579055786,
-0.21944649517536163,
0.23195873200893402,
0.1562119424343109,
-0.06431920826435089,
-0.14587201178073883,
0.008576968684792519,
-0.12822508811950684,
-0.002887815237045288,
-0.03820955008268356,
-0.10356047749519348,
0.10288208723068237,
0.1906561404466629,
-0.10545209050178528,
0.0022766776382923126,
0.07329021394252777,
-0.05676286667585373,
-0.09499042481184006,
-0.12194760143756866,
0.005622925236821175,
-0.5228880047798157,
-0.01635923981666565,
-0.15502753853797913,
-0.5842819213867188,
-0.19491051137447357,
-0.18189498782157898,
0.20081683993339539,
-0.1969064623117447,
-0.08773282170295715,
0.006360802333801985,
0.0872836709022522,
0.3509705066680908,
0.13916301727294922,
0.0905078649520874,
0.07922898232936859,
-0.0174418892711401,
0.06981420516967773,
0.04823223873972893,
0.004030964337289333,
0.03277851268649101,
0.19473370909690857,
0.10559012740850449,
0.011595755815505981,
-0.35372409224510193,
0.015375129878520966,
0.19428357481956482,
-0.04946019500494003,
0.010338237509131432,
0.33580487966537476,
0.08736909180879593,
-0.495445191860199,
0.13991816341876984,
0.14058928191661835,
0.3530597984790802,
-0.05232655256986618,
0.030834835022687912,
0.3473846912384033,
0.017780210822820663,
0.09395411610603333,
-0.3488008379936218,
-0.1854475885629654,
0.04607253149151802,
0.09167945384979248,
-0.024083953350782394,
0.10844962298870087,
-0.23966284096240997,
0.17827773094177246,
-0.1272117793560028,
-0.34878531098365784,
-0.247926265001297,
-0.20571362972259521,
0.11752523481845856,
0.048901788890361786,
-0.14117513597011566,
-0.01738835498690605,
-0.2172677367925644,
0.14096347987651825,
-0.13892053067684174,
0.18003641068935394,
0.27049028873443604,
-0.27786785364151,
-0.04547499865293503,
0.12244537472724915,
0.0982365608215332,
0.4216066300868988,
0.3028852343559265,
0.3918447494506836,
0.08133647590875626,
-0.07759658992290497,
0.10318781435489655,
0.11008711159229279,
0.3211497962474823,
0.009788133203983307,
0.14529214799404144,
0.04953548312187195,
-0.1308119148015976,
0.7850809693336487,
0.47630518674850464,
0.14479035139083862,
0.1125241294503212,
0.002753874287009239,
-0.16256743669509888,
-0.13791394233703613,
-0.10453397035598755,
0.2698311507701874,
-0.07678432762622833,
0.19053786993026733,
0.45777904987335205,
0.08809159696102142,
-0.06342166662216187,
0.03595363348722458,
0.2923191487789154,
-0.23634710907936096,
-0.2863630950450897,
0.42527344822883606,
-0.17180877923965454,
0.25057095289230347,
0.014177825301885605,
-0.11715613305568695,
-0.2502304017543793,
-0.12013731896877289,
-0.06141114979982376,
-0.11164245009422302,
0.34356555342674255,
-0.39867067337036133,
-0.09759130328893661,
-0.256198525428772,
-0.15704861283302307,
0.29891878366470337,
0.47733354568481445,
0.10383498668670654,
-0.01350841298699379,
-0.07692837715148926,
0.16502931714057922,
0.3424927592277527,
0.517250120639801,
-0.03934948891401291,
-0.11622586846351624,
-0.09208141267299652,
0.05629953742027283,
0.17325051128864288,
-0.03681115061044693,
-0.6540710926055908,
0.32207465171813965,
-0.2926149070262909,
0.1334902048110962,
-0.22548875212669373,
-0.35192811489105225,
0.17181181907653809,
0.14538055658340454,
-0.10473287105560303,
-0.22611120343208313,
0.13815724849700928,
0.5807726979255676,
0.0008972045034170151,
0.2521328330039978,
0.2287890464067459,
-0.15927039086818695,
0.19195635616779327,
-0.09325660765171051,
0.18506526947021484,
-0.006664203479886055,
0.3489795923233032,
0.21433041989803314,
0.06443063169717789,
0.16485711932182312,
-0.3918599486351013,
0.2294236570596695,
0.1500619798898697,
0.19573739171028137,
0.20301252603530884,
-0.6772517561912537,
-0.060861051082611084,
0.08496478945016861,
-0.11696672439575195,
0.6384943127632141,
0.3110847771167755,
0.2727363705635071,
-0.08074901252985,
0.09046341478824615,
-0.014859922230243683,
-0.18671002984046936,
-0.07817530632019043,
0.3036341369152069,
0.08140749484300613,
-0.2078104019165039,
-0.416168749332428,
0.38397493958473206,
-0.11780276894569397,
-0.26804718375205994,
-0.13686548173427582,
0.5329189300537109,
0.006374480202794075,
0.03252534568309784,
0.41089504957199097,
0.8881409764289856,
-0.18266119062900543,
0.3090890645980835,
0.13335850834846497,
0.07515868544578552,
0.3711303472518921,
-0.13379468023777008,
0.22359661757946014,
-0.22098954021930695,
0.105465367436409,
-0.18438202142715454,
-0.19609878957271576,
-0.000308893620967865,
0.5590388774871826,
-0.693390965461731,
0.2738444209098816,
-0.154904305934906,
0.15904928743839264,
0.14156168699264526,
-0.0622471459209919,
0.3114883601665497,
-0.1365651935338974,
-0.1344507783651352,
-0.012796031311154366,
-0.2086646407842636,
-0.13177862763404846,
-0.15400856733322144,
-0.04845869541168213,
0.03196627274155617,
0.005609109997749329,
-0.3148159086704254,
-0.06546637415885925,
-0.5026320815086365,
-0.22931347787380219,
0.0704682394862175,
-0.13271108269691467,
0.49281880259513855,
0.4730241298675537,
0.11013013124465942,
0.12637798488140106,
-0.08461261540651321,
-0.18574948608875275,
0.1338845044374466,
0.28642597794532776,
-0.23144900798797607,
0.10738244652748108,
0.5054354071617126,
-0.028761200606822968,
-0.30972820520401,
0.23615384101867676,
-0.12689198553562164,
-0.08921197056770325,
-0.48502466082572937,
0.11372119188308716,
0.7107093930244446,
-0.5381376147270203,
-0.4216567277908325,
-0.03158755600452423,
0.1221124529838562,
0.02823345735669136,
-0.08895732462406158,
0.2638345956802368,
0.11011446267366409,
0.5779937505722046,
0.23609013855457306,
0.1575019657611847,
0.24454277753829956,
-0.13318315148353577,
0.14268717169761658,
-0.1016162782907486,
0.31638839840888977,
0.20700936019420624,
-0.1430155485868454,
-0.13768139481544495,
0.08183915168046951,
0.22919079661369324,
-0.10338245332241058,
0.1376062035560608,
-0.25277161598205566,
-0.08193708956241608,
-0.03888702765107155,
0.3396036922931671,
0.3437861204147339,
0.30378568172454834,
-0.009304389357566833,
0.04974660277366638,
-0.11958939582109451,
0.2682490944862366,
-0.22673340141773224,
0.1715279519557953,
0.19719451665878296,
-0.1525161862373352,
0.06678889691829681,
0.260731965303421,
-0.17686200141906738,
-0.09415048360824585,
0.11468591541051865,
0.3973570764064789,
-0.0025256630033254623,
-0.2013346254825592,
-0.2250729501247406,
-0.05165468156337738,
-0.04072563350200653,
-0.22952820360660553,
-0.22013938426971436,
-0.12144707143306732,
-0.1096401959657669,
0.13896621763706207,
0.09552144259214401,
-0.07645708322525024,
-0.12439693510532379,
-0.12791964411735535,
-0.008751053363084793,
-0.12493596971035004,
-0.002041764557361603,
-0.06993503123521805,
-0.16730575263500214,
0.3306974470615387,
0.1385970115661621,
-0.3417626917362213,
-0.19411854445934296,
0.12415020167827606,
0.32734930515289307,
-0.046312421560287476,
0.1761833131313324,
0.1268651783466339,
0.06882397085428238,
-0.21992753446102142,
-0.07351990044116974,
0.43982794880867004,
0.2794691324234009,
0.0344989113509655,
0.028155870735645294,
0.09866347163915634,
0.16357484459877014,
0.0910554826259613,
0.29285088181495667,
0.05899415537714958,
0.04810664430260658,
0.09166944772005081,
0.04486217349767685,
0.08739277720451355,
-0.10868410021066666,
-0.21807761490345,
0.5362933874130249,
0.10885204374790192,
0.16727371513843536,
0.35398173332214355,
0.058678146451711655,
0.017523393034934998,
0.37596338987350464,
-0.028894171118736267,
-0.35815781354904175,
0.0637386292219162,
0.01486562192440033,
0.6164768934249878,
-0.09675905853509903,
0.06004120409488678,
0.1579797863960266,
0.21127848327159882,
0.06314335763454437,
-0.00310448557138443,
0.07378453016281128,
0.21520675718784332,
0.119562529027462,
-0.13529027998447418,
0.49863874912261963,
-0.016309211030602455,
0.21602973341941833,
0.22185903787612915,
0.1069485992193222,
0.44822293519973755,
0.35138222575187683,
0.1383226215839386,
-0.26116451621055603,
-0.5070874691009521,
-0.005821077153086662,
0.08295352756977081,
-0.14927971363067627,
-0.18763838708400726,
-0.023021284490823746,
-0.2203642725944519,
-0.34096357226371765,
-0.03082037903368473,
-0.6939731240272522,
-0.13618916273117065,
0.4685724377632141,
0.323300838470459,
0.503394603729248,
-0.12030547857284546,
-0.049626708030700684,
0.10586360841989517,
0.2920260429382324,
-0.12352420389652252,
0.18553775548934937,
0.03374519944190979,
0.02798856794834137,
0.10734626650810242,
0.3419782519340515,
-0.0009043291211128235,
0.21667702496051788,
-0.18185119330883026,
-0.0319611132144928,
-0.3361881673336029,
-0.08698029071092606,
0.2088313102722168,
-0.23594453930854797,
0.22233769297599792,
-0.0785495787858963,
0.1523190289735794,
0.011357923969626427,
0.051598161458969116,
0.15603037178516388,
0.06995577365159988,
0.006510185077786446,
-0.2356921285390854,
-0.5836465358734131,
0.2164982706308365,
-0.25015977025032043,
0.08592202514410019,
-0.031399063766002655,
-0.6951836943626404,
-0.0269295834004879,
0.056830644607543945,
-0.1017041802406311,
-0.08000939339399338,
0.14819777011871338,
-0.012619556859135628,
0.26396527886390686,
-0.02980627492070198,
0.36169663071632385,
0.014449577778577805,
-0.3209570646286011,
-0.17841556668281555,
-0.2791803777217865,
-0.11175758391618729,
0.2492118626832962,
-0.12218450754880905,
0.07240916043519974,
-0.02137771062552929,
0.05432358384132385,
0.3683212995529175,
0.05567166954278946,
-0.5797141790390015,
-0.25978291034698486,
0.473615437746048,
-0.1560894399881363,
0.1644119769334793,
0.28888195753097534,
0.2590021789073944,
-0.028212402015924454,
-0.06761834025382996,
0.27827516198158264,
0.310769647359848,
-0.151582270860672,
-0.23049874603748322,
0.010738961398601532,
-0.24945521354675293,
-0.05991800129413605,
-0.227616548538208,
0.36596599221229553,
0.2763817608356476,
0.10707373172044754,
-0.20322701334953308,
0.28647246956825256,
0.40573084354400635,
0.11927688121795654,
0.09432676434516907,
0.11116792261600494,
0.6024980545043945,
-0.1494073122739792,
0.2883363664150238,
-0.05454804003238678,
0.023511825129389763,
0.09809628129005432,
-0.1638512909412384,
-0.6133045554161072,
-0.02244396135210991,
-0.023944184184074402,
-0.3201178014278412,
0.138483926653862,
0.41740283370018005,
-0.1201280951499939,
0.1861407607793808,
-0.24419832229614258,
0.2617798149585724,
0.13630354404449463,
-0.22383365035057068,
-0.34966403245925903,
-0.30819401144981384,
-0.04592210054397583,
-0.2481653094291687,
-0.014777405187487602,
-0.7189196348190308,
-0.241082102060318,
0.2345632165670395,
-0.11553273350000381,
-0.14388951659202576,
0.04211653769016266,
-0.039306651800870895,
-0.16625675559043884,
-0.3629511594772339,
0.6250200271606445,
0.036941591650247574,
0.10133044421672821,
-0.3119325041770935,
-0.45195573568344116
] |
https://github.com/huggingface/datasets/issues/189 | [Question] BERT-style multiple choice formatting | I think I've resolved it. For others' reference: to convert from using the [`MultipleChoiceDataset` class](https://github.com/huggingface/transformers/blob/a34a9896ac2a4a33ff9cd805c76eed914c8d8965/examples/multiple-choice/utils_multiple_choice.py#L82)/[`run_multiple_choice.py`](https://github.com/huggingface/transformers/blob/a34a9896ac2a4a33ff9cd805c76eed914c8d8965/examples/multiple-choice/run_multiple_choice.py) script in Huggingface Transformers, I've done the following for hellaswag:
1. converted the `convert_examples_to_features()` function to only take one input and return a dictionary rather than a list:
```
def convert_examples_to_features(example, tokenizer, max_length):
choices_inputs = defaultdict(list)
for ending_idx, ending in enumerate(example['endings']['ending']):
text_a = example['ctx']
text_b = ending
inputs = tokenizer.encode_plus(
text_a,
text_b,
add_special_tokens=True,
max_length=max_length,
pad_to_max_length=True,
return_overflowing_tokens=True,
)
if "num_truncated_tokens" in inputs and inputs["num_truncated_tokens"] > 0:
logger.info(
"Attention! you are cropping tokens (swag task is ok). "
"If you are training ARC and RACE and you are poping question + options,"
"you need to try to use a bigger max seq length!"
)
for key in inputs:
choices_inputs[key].append(inputs[key])
choices_inputs['label'] = int(example['label'])
return choices_inputs
```
2. apply this directly (instance-wise) to dataset, convert dataset to torch tensors. Dataset is then ready to be passed to `Trainer` instance.
```
dataset['train'] = dataset['train'].map(lambda x: convert_examples_to_features(x, tokenizer, max_length), batched=False)
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'label']
dataset['train'].set_format(type='torch', columns=columns)
``` | Hello, I am wondering what the equivalent formatting of a dataset should be to allow for multiple-choice answering prediction, BERT-style. Previously, this was done by passing a list of `InputFeatures` to the dataloader instead of a list of `InputFeature`, where `InputFeatures` contained lists of length equal to the number of answer choices in the MCQ instead of single items. I'm a bit confused on what the output of my feature conversion function should be when using `dataset.map()` to ensure similar behavior.
Thanks! | 168 | [Question] BERT-style multiple choice formatting
Hello, I am wondering what the equivalent formatting of a dataset should be to allow for multiple-choice answering prediction, BERT-style. Previously, this was done by passing a list of `InputFeatures` to the dataloader instead of a list of `InputFeature`, where `InputFeatures` contained lists of length equal to the number of answer choices in the MCQ instead of single items. I'm a bit confused on what the output of my feature conversion function should be when using `dataset.map()` to ensure similar behavior.
Thanks!
I think I've resolved it. For others' reference: to convert from using the [`MultipleChoiceDataset` class](https://github.com/huggingface/transformers/blob/a34a9896ac2a4a33ff9cd805c76eed914c8d8965/examples/multiple-choice/utils_multiple_choice.py#L82)/[`run_multiple_choice.py`](https://github.com/huggingface/transformers/blob/a34a9896ac2a4a33ff9cd805c76eed914c8d8965/examples/multiple-choice/run_multiple_choice.py) script in Huggingface Transformers, I've done the following for hellaswag:
1. converted the `convert_examples_to_features()` function to only take one input and return a dictionary rather than a list:
```
def convert_examples_to_features(example, tokenizer, max_length):
choices_inputs = defaultdict(list)
for ending_idx, ending in enumerate(example['endings']['ending']):
text_a = example['ctx']
text_b = ending
inputs = tokenizer.encode_plus(
text_a,
text_b,
add_special_tokens=True,
max_length=max_length,
pad_to_max_length=True,
return_overflowing_tokens=True,
)
if "num_truncated_tokens" in inputs and inputs["num_truncated_tokens"] > 0:
logger.info(
"Attention! you are cropping tokens (swag task is ok). "
"If you are training ARC and RACE and you are poping question + options,"
"you need to try to use a bigger max seq length!"
)
for key in inputs:
choices_inputs[key].append(inputs[key])
choices_inputs['label'] = int(example['label'])
return choices_inputs
```
2. apply this directly (instance-wise) to dataset, convert dataset to torch tensors. Dataset is then ready to be passed to `Trainer` instance.
```
dataset['train'] = dataset['train'].map(lambda x: convert_examples_to_features(x, tokenizer, max_length), batched=False)
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'label']
dataset['train'].set_format(type='torch', columns=columns)
``` | [
0.1992310732603073,
-0.575800895690918,
0.010819882154464722,
-0.0699361115694046,
0.2859188914299011,
-0.15366774797439575,
0.24460144340991974,
0.24167530238628387,
-0.009871283546090126,
0.018018953502178192,
-0.15490840375423431,
0.455800861120224,
-0.2713589370250702,
0.0753546729683876,
0.12558721005916595,
-0.37995249032974243,
0.15262764692306519,
0.06899324059486389,
-0.20162361860275269,
-0.06752023845911026,
-0.11300843954086304,
0.02811495028436184,
-0.16656044125556946,
-0.02064725011587143,
-0.3513280153274536,
0.04645802080631256,
-0.36015385389328003,
-0.0656294897198677,
-0.30250850319862366,
-0.3981378674507141,
-0.1327248066663742,
0.19807399809360504,
-0.25676780939102173,
0.11358477175235748,
-0.00013058973127044737,
-0.31119462847709656,
-0.21208496391773224,
-0.21448419988155365,
-0.09534168243408203,
-0.031543880701065063,
-0.7208173274993896,
-0.0117108765989542,
0.39389553666114807,
0.10779359191656113,
-0.025061124935746193,
-0.024407606571912766,
0.0035536643117666245,
-0.1321898251771927,
0.6255216598510742,
-0.02035348489880562,
0.009229175746440887,
0.04004726558923721,
0.08175075054168701,
0.09900170564651489,
0.1613849401473999,
0.5654871463775635,
-0.07321750372648239,
0.08077193796634674,
0.569547712802887,
-0.0895318016409874,
-0.2318439483642578,
0.5064967274665833,
0.03164707124233246,
0.07505442947149277,
0.2941820025444031,
0.11394406110048294,
-0.015605650842189789,
-0.08051556348800659,
-0.22278180718421936,
0.41991183161735535,
0.5713568329811096,
-0.30700618028640747,
-0.44495052099227905,
-0.2811705470085144,
0.07755261659622192,
-0.05330924317240715,
-0.1852957308292389,
0.044255949556827545,
-0.2463555932044983,
0.0007777474820613861,
-0.3870481550693512,
-0.14347663521766663,
-0.24800752103328705,
0.03583591803908348,
-0.2692349851131439,
0.511880099773407,
-0.05074486881494522,
0.021876029670238495,
-0.006453309208154678,
-0.23134665191173553,
-0.15191029012203217,
-0.3797209858894348,
0.30629488825798035,
0.20800743997097015,
-0.04424024000763893,
-0.39680713415145874,
-0.13806238770484924,
-0.07668542116880417,
0.4508575201034546,
-0.24334202706813812,
-0.00857329647988081,
0.023109758272767067,
-0.4934563934803009,
-0.022741883993148804,
0.648693859577179,
0.04183975234627724,
-0.011994697153568268,
-0.0025547584518790245,
-0.23035399615764618,
-0.08692910522222519,
-0.10430460423231125,
0.06293801963329315,
0.14950506389141083,
0.1489628553390503,
0.12328298389911652,
0.10730724781751633,
0.024612929672002792,
-0.2623036205768585,
-0.03937054052948952,
0.012350460514426231,
-0.32854601740837097,
-0.13844557106494904,
0.13970710337162018,
0.24745827913284302,
-0.127646803855896,
0.503680944442749,
-0.1274145245552063,
0.3086261749267578,
-0.009251781739294529,
-0.09967132657766342,
0.09143596142530441,
-0.1582871973514557,
-0.4034566283226013,
-0.10639635473489761,
0.21177919209003448,
0.33019858598709106,
0.09043743461370468,
0.4027234613895416,
0.5290735960006714,
-0.2610943913459778,
0.02161410264670849,
0.01453854888677597,
0.4841368496417999,
0.02228257805109024,
-0.33286750316619873,
0.40923282504081726,
0.35748252272605896,
0.270408034324646,
-0.1167823001742363,
0.37184426188468933,
-0.17706051468849182,
-0.03748030960559845,
-0.016465483233332634,
-0.05915633961558342,
0.1264021247625351,
-0.16889415681362152,
-0.15660089254379272,
0.36347857117652893,
0.12413916736841202,
-0.1976221203804016,
0.08903414756059647,
-0.5058838129043579,
-0.01267833262681961,
-0.18312636017799377,
0.15960529446601868,
0.5324588418006897,
-0.2871987521648407,
-0.14317461848258972,
-0.023123497143387794,
0.14544807374477386,
0.0770607516169548,
0.36676448583602905,
-0.08329935371875763,
-0.09566760808229446,
-0.028542842715978622,
0.4020654559135437,
0.20190644264221191,
-0.2790754437446594,
-0.2886229157447815,
0.18329249322414398,
0.32033413648605347,
0.30419206619262695,
-0.12321639806032181,
0.13023139536380768,
0.020967885851860046,
0.22887706756591797,
0.10841445624828339,
-0.16214489936828613,
-0.17627912759780884,
0.4218747615814209,
-0.05920543894171715,
-0.13189488649368286,
0.07925218343734741,
-0.036505427211523056,
-0.10871562361717224,
-0.2211264967918396,
-0.21198472380638123,
0.1571851372718811,
0.3730960488319397,
-0.13576793670654297,
-0.15732991695404053,
-0.19157469272613525,
0.14541824162006378,
-0.08411453664302826,
-0.03216903656721115,
-0.18415400385856628,
-0.6730773448944092,
0.03187338262796402,
-0.058820322155952454,
-0.013976752758026123,
-0.023560382425785065,
-0.23712123930454254,
-0.3311190903186798,
0.15139460563659668,
-0.35942086577415466,
-0.06123196706175804,
-0.06678400933742523,
-0.011039458215236664,
-0.09729538857936859,
-0.21554264426231384,
-0.23209570348262787,
0.05262405425310135,
0.48802900314331055,
0.11189083009958267,
-0.011933045461773872,
0.19364546239376068,
0.19373174011707306,
-0.12392780184745789,
0.06306765973567963,
0.3638549745082855,
0.2385554313659668,
0.18986479938030243,
0.015624390915036201,
0.21068793535232544,
0.533371090888977,
-0.07160782814025879,
-0.12715297937393188,
0.23659689724445343,
0.4539567232131958,
-0.19625253975391388,
0.1511325240135193,
0.20681197941303253,
0.19266006350517273,
-0.04783997684717178,
-0.7790422439575195,
0.2532617449760437,
0.013713613152503967,
0.25994306802749634,
-0.09325248003005981,
0.192877396941185,
-0.07523898035287857,
0.3315355181694031,
-0.059525735676288605,
-0.39366692304611206,
-0.20147694647312164,
0.12461215257644653,
0.14805004000663757,
-0.029560385271906853,
-0.4988958537578583,
0.3210471272468567,
0.37384963035583496,
-0.052154675126075745,
0.25738486647605896,
-0.057632751762866974,
-0.10829807072877884,
-0.15855783224105835,
0.3733244240283966,
-0.35355350375175476,
0.28380057215690613,
0.06916701793670654,
-0.08368012309074402,
-0.12158340960741043,
-0.04242310672998428,
-0.03475860506296158,
0.027157500386238098,
0.06743291020393372,
-0.07191870361566544,
0.1330578774213791,
0.1848296970129013,
-0.22043871879577637,
-0.08031675219535828,
-0.005193222314119339,
-0.08777441084384918,
-0.0895499438047409,
-0.20640704035758972,
0.09672456979751587,
-0.5124544501304626,
0.1038118526339531,
-0.2801769971847534,
-0.554701030254364,
-0.36573559045791626,
-0.2290543168783188,
0.26497071981430054,
-0.08991865813732147,
-0.16554860770702362,
0.05860508233308792,
0.11672475934028625,
0.09931112080812454,
0.19559450447559357,
-0.0060081202536821365,
-0.08945012092590332,
0.04601384326815605,
0.10184025764465332,
-0.05130700021982193,
-0.04768429696559906,
-0.04785206541419029,
0.037647977471351624,
0.12882810831069946,
-0.11320019513368607,
-0.4533537030220032,
-0.008424080908298492,
0.3111928105354309,
-0.11082722246646881,
0.1549980491399765,
0.3773556053638458,
0.1029159426689148,
-0.48735517263412476,
0.048792775720357895,
0.212270125746727,
0.2985989451408386,
-0.0036084335297346115,
0.11281442642211914,
0.30032792687416077,
-0.022947629913687706,
-0.012343760579824448,
-0.19157731533050537,
-0.13206130266189575,
-0.003897925838828087,
0.10018597543239594,
0.026955600827932358,
0.15248650312423706,
-0.16705459356307983,
0.26794713735580444,
-0.03599873557686806,
-0.33557772636413574,
-0.2415345013141632,
-0.14004871249198914,
0.08695998787879944,
0.14672958850860596,
-0.08437187224626541,
-0.05225079879164696,
-0.2838633954524994,
0.04827546328306198,
-0.018866952508687973,
0.11450206488370895,
0.18315814435482025,
-0.35383525490760803,
-0.0870286300778389,
-0.06288972496986389,
0.1746329367160797,
0.48489096760749817,
0.28579121828079224,
0.2647237479686737,
0.11941230297088623,
-0.056173358112573624,
-0.00612759031355381,
0.1639111042022705,
0.34851157665252686,
0.04665456712245941,
0.004913097247481346,
-0.09494320303201675,
0.0010067038238048553,
1.0838128328323364,
0.48438388109207153,
0.24819226562976837,
-0.003678448498249054,
-0.11817046254873276,
-0.1263032853603363,
-0.15671616792678833,
-0.09003377705812454,
0.11810848861932755,
-0.07367570698261261,
0.30270129442214966,
0.46514344215393066,
0.2442467212677002,
0.01206075306981802,
0.053465522825717926,
0.38583505153656006,
-0.16218233108520508,
-0.4523179829120636,
0.3965875506401062,
-0.0745377242565155,
0.14584703743457794,
0.01808437705039978,
0.06413006037473679,
-0.18320032954216003,
-0.1223573312163353,
-0.0762113481760025,
0.04760737344622612,
0.31014183163642883,
-0.19234776496887207,
-0.04028281196951866,
-0.2107447385787964,
-0.25974369049072266,
0.2814566195011139,
0.522388219833374,
0.1269291490316391,
-0.0026252418756484985,
-0.1497012972831726,
0.2083989381790161,
0.23716433346271515,
0.635626494884491,
0.178530752658844,
-0.20981650054454803,
-0.00905932392925024,
-0.12181360274553299,
-0.010507297702133656,
-0.12758637964725494,
-0.6342929005622864,
0.18389475345611572,
-0.2725788950920105,
0.22634418308734894,
-0.39750564098358154,
-0.46626895666122437,
-0.0781315416097641,
0.11758805066347122,
-0.1353408247232437,
-0.10770022124052048,
-0.05650631710886955,
0.4158494174480438,
-0.15804964303970337,
0.32521000504493713,
0.3609256148338318,
-0.14264832437038422,
0.17127522826194763,
-0.06450578570365906,
0.2282078117132187,
-0.05428936332464218,
0.34357163310050964,
0.33272436261177063,
0.13303759694099426,
0.09885770082473755,
-0.36606472730636597,
0.22141101956367493,
0.08414459228515625,
-0.009226266294717789,
0.3217577636241913,
-0.5721666812896729,
-0.29042747616767883,
0.14899960160255432,
-0.04958136007189751,
0.4967501759529114,
0.44231799244880676,
0.21683450043201447,
-0.05097954720258713,
0.2642033100128174,
0.07970675826072693,
-0.13998578488826752,
0.1115492433309555,
0.2770272195339203,
0.08728804439306259,
-0.1706182211637497,
-0.3983020782470703,
0.4744041860103607,
-0.06491909176111221,
-0.28020185232162476,
0.013689447194337845,
0.5781557559967041,
-0.08784236013889313,
-0.0790267363190651,
0.2935151755809784,
0.9808769822120667,
-0.23133574426174164,
0.39982396364212036,
0.40193745493888855,
0.026256516575813293,
0.31943967938423157,
-0.282145231962204,
0.2668992877006531,
-0.22960402071475983,
0.11477533727884293,
-0.12683071196079254,
-0.18965332210063934,
0.09107086062431335,
0.48549652099609375,
-0.6954213380813599,
0.40398919582366943,
-0.06320933252573013,
0.07957585901021957,
0.06719355285167694,
-0.02080794982612133,
0.16373121738433838,
-0.2564390003681183,
-0.26492947340011597,
-0.06672534346580505,
-0.2586745023727417,
0.00040293484926223755,
-0.10235649347305298,
-0.06116139143705368,
-0.00667085126042366,
-0.12094180285930634,
-0.3932931423187256,
-0.014796941541135311,
-0.45530563592910767,
-0.17547589540481567,
0.29111674427986145,
-0.15258720517158508,
0.3953568637371063,
0.43452224135398865,
0.0012733116745948792,
0.14556869864463806,
-0.12557163834571838,
-0.028710704296827316,
-0.08400887995958328,
0.4058331251144409,
-0.26161664724349976,
0.09170582890510559,
0.5665050745010376,
-0.006685782223939896,
-0.3421810269355774,
0.15743711590766907,
-0.08092371374368668,
-0.10101303458213806,
-0.43462657928466797,
0.18062655627727509,
0.6312641501426697,
-0.5566819310188293,
-0.27094703912734985,
0.1057053655385971,
0.11234088242053986,
-0.04159419611096382,
-0.1443416178226471,
0.3904123902320862,
-0.03776446357369423,
0.5050055384635925,
0.15269379317760468,
0.07537214457988739,
0.15192118287086487,
-0.024606160819530487,
0.04468595236539841,
-0.2201678305864334,
0.35747721791267395,
0.2970626950263977,
-0.1157662644982338,
-0.10506823658943176,
-0.057065773755311966,
0.20738916099071503,
-0.19489699602127075,
0.3421352207660675,
-0.21411162614822388,
-0.22223147749900818,
-0.09522446990013123,
0.30014461278915405,
0.18653343617916107,
0.1520581692457199,
0.04173438623547554,
-0.03233838826417923,
-0.11665630340576172,
0.328619122505188,
-0.14338849484920502,
0.2544211447238922,
0.19086512923240662,
-0.03195108100771904,
0.028394566848874092,
0.1957789808511734,
-0.1289578676223755,
-0.08749967813491821,
0.008275063708424568,
0.34924253821372986,
-0.11322985589504242,
-0.26551559567451477,
-0.029820891097187996,
0.003573790192604065,
-0.03897588327527046,
-0.09551601111888885,
-0.2530175447463989,
-0.06898951530456543,
-0.2502748966217041,
0.16109591722488403,
0.04794320464134216,
-0.12595948576927185,
-0.02653845027089119,
0.03126091882586479,
-0.023183010518550873,
-0.23883140087127686,
0.19180499017238617,
-0.08689837157726288,
-0.14084836840629578,
0.3501245677471161,
0.007580507546663284,
-0.2158450484275818,
-0.13044050335884094,
0.02710792049765587,
0.18230727314949036,
-0.03597831726074219,
0.33490630984306335,
0.15295855700969696,
-0.03547601401805878,
-0.23685064911842346,
0.0391065776348114,
0.4817042350769043,
0.15812793374061584,
-0.013921603560447693,
0.07354781031608582,
0.08150287717580795,
0.07890522480010986,
0.017839156091213226,
0.2860039174556732,
0.00811094418168068,
0.07826099544763565,
0.0466495081782341,
0.14516785740852356,
-0.006222911179065704,
-0.10724980384111404,
-0.29134562611579895,
0.4584799110889435,
0.10486221313476562,
0.2002466320991516,
0.4067821204662323,
0.017292674630880356,
-0.003218837082386017,
0.3959064483642578,
-0.0531291626393795,
-0.2769777476787567,
0.06952840089797974,
0.011238678358495235,
0.6116731762886047,
-0.16785180568695068,
0.12471422553062439,
0.07526944577693939,
0.21174637973308563,
0.1798262596130371,
0.03575913980603218,
-0.18006432056427002,
0.20812660455703735,
-0.13592606782913208,
-0.15321236848831177,
0.541154146194458,
-0.1362389177083969,
0.014910653233528137,
-0.006787106394767761,
0.021940521895885468,
0.4590047299861908,
0.2312006950378418,
0.25780022144317627,
-0.3163483440876007,
-0.3504883646965027,
0.0007417444139719009,
0.10561448335647583,
-0.11325456947088242,
-0.19692258536815643,
0.20105041563510895,
-0.11095333099365234,
-0.30959609150886536,
-0.06364308297634125,
-0.5783081650733948,
-0.3299182057380676,
0.48669734597206116,
0.22485026717185974,
0.5121278762817383,
-0.1676066368818283,
-0.11800263077020645,
0.14495772123336792,
0.36797523498535156,
-0.15258798003196716,
0.15408723056316376,
0.30220744013786316,
-0.0390835702419281,
0.018621642142534256,
0.20260384678840637,
0.0895346850156784,
0.13583555817604065,
-0.20486100018024445,
-0.01434855256229639,
-0.3012128472328186,
-0.027429647743701935,
0.18805748224258423,
-0.1548427939414978,
0.18413934111595154,
0.026713328436017036,
0.22319234907627106,
-0.06094777584075928,
0.06802726536989212,
-0.11772581934928894,
0.031707536429166794,
0.1584734469652176,
-0.18284845352172852,
-0.3853932023048401,
-0.013146482408046722,
-0.17111173272132874,
0.04769604653120041,
-0.000627957284450531,
-0.7032938599586487,
-0.06327411532402039,
0.07264988124370575,
-0.06937970966100693,
-0.03406525403261185,
0.09923778474330902,
-0.043120697140693665,
0.20425191521644592,
0.15444724261760712,
0.24497471749782562,
0.1417865753173828,
-0.2718694806098938,
0.12096333503723145,
-0.2757836580276489,
-0.18676051497459412,
0.28453966975212097,
-0.23186273872852325,
0.03978751599788666,
0.020781049504876137,
0.10187821835279465,
0.34108859300613403,
0.06822305917739868,
-0.5816965103149414,
-0.113857202231884,
0.4657232463359833,
-0.20126885175704956,
0.1362157016992569,
0.18447740375995636,
0.26688218116760254,
0.10629057884216309,
-0.12843114137649536,
0.212474524974823,
0.35382887721061707,
-0.21196269989013672,
-0.170796200633049,
-0.07130181044340134,
-0.33269795775413513,
-0.05884702503681183,
-0.2403455674648285,
0.5293843150138855,
0.20186175405979156,
0.1224137619137764,
-0.2680337727069855,
0.1406514048576355,
0.2860543131828308,
0.05670357123017311,
-0.028978899121284485,
0.027318062260746956,
0.7622185945510864,
-0.09328220784664154,
0.10506893694400787,
-0.11119595170021057,
0.215980663895607,
0.12799906730651855,
-0.3299756944179535,
-0.49485650658607483,
0.08940304815769196,
-0.02528863400220871,
-0.2356468141078949,
0.10793600976467133,
0.4834584593772888,
-0.12256108224391937,
0.13673877716064453,
-0.26708289980888367,
0.1285669058561325,
0.31999218463897705,
-0.2631489634513855,
-0.3871843218803406,
-0.39997532963752747,
-0.07116074860095978,
-0.03558336943387985,
-0.03292090445756912,
-0.8910266160964966,
-0.17213231325149536,
0.11249079555273056,
-0.03815922886133194,
-0.2536053955554962,
0.08522751927375793,
-0.022356484085321426,
-0.2716106176376343,
-0.37771695852279663,
0.6619982719421387,
0.05689779669046402,
0.03396216034889221,
-0.22671574354171753,
-0.5398955345153809
] |
https://github.com/huggingface/datasets/issues/188 | When will the remaining math_dataset modules be added as dataset objects | Hi @tylerroost, we don't have a timeline for this at the moment.
If you want to give it a look we would be happy to review a PR on it.
Also, the library is one week old so everything is quite barebones, in particular the doc.
You should expect some bumps on the road.
To get you started, you can check the datasets scripts in the `./datasets` folder on the repo and find the one on math_datasets that will need to be modified. Then you should check the original repository on the math_dataset to see where the other files to download are located and what is the expected format for the various parts of the dataset.
To get a general overview on how datasets scripts are written and used, you can read the nice tutorial on how to add a new dataset for TensorFlow Dataset [here](https://www.tensorflow.org/datasets/add_dataset), our API is not exactly identical but it can give you a high-level overview. | Currently only the algebra_linear_1d is supported. Is there a timeline for making the other modules supported. If no timeline is established, how can I help? | 160 | When will the remaining math_dataset modules be added as dataset objects
Currently only the algebra_linear_1d is supported. Is there a timeline for making the other modules supported. If no timeline is established, how can I help?
Hi @tylerroost, we don't have a timeline for this at the moment.
If you want to give it a look we would be happy to review a PR on it.
Also, the library is one week old so everything is quite barebones, in particular the doc.
You should expect some bumps on the road.
To get you started, you can check the datasets scripts in the `./datasets` folder on the repo and find the one on math_datasets that will need to be modified. Then you should check the original repository on the math_dataset to see where the other files to download are located and what is the expected format for the various parts of the dataset.
To get a general overview on how datasets scripts are written and used, you can read the nice tutorial on how to add a new dataset for TensorFlow Dataset [here](https://www.tensorflow.org/datasets/add_dataset), our API is not exactly identical but it can give you a high-level overview. | [
-0.2745407223701477,
-0.07471400499343872,
-0.2828441560268402,
0.08163279294967651,
0.10131534188985825,
0.08511572331190109,
0.16226986050605774,
0.18157170712947845,
0.15496572852134705,
0.028999298810958862,
0.0906955748796463,
0.2542612552642822,
-0.24301375448703766,
0.09133551269769669,
0.2556442618370056,
-0.34201547503471375,
0.2013435810804367,
-0.07195033133029938,
-0.24810531735420227,
-0.35922640562057495,
-0.10869914293289185,
0.0939246341586113,
-0.26665621995925903,
-0.21100129187107086,
-0.13362134993076324,
-0.060056932270526886,
-0.2486087530851364,
-0.04428119212388992,
-0.42535167932510376,
-0.23080095648765564,
0.06616612523794174,
0.2980559170246124,
0.23175828158855438,
0.3571215569972992,
-0.00010253637447021902,
-0.1791471242904663,
0.1952541172504425,
0.06595970690250397,
-0.09675733745098114,
-0.3587573766708374,
-0.36296626925468445,
-0.2668955326080322,
0.17846550047397614,
0.10846651345491409,
0.09927225857973099,
0.0903831422328949,
-0.03913361579179764,
-0.40964069962501526,
0.027926310896873474,
0.35471290349960327,
0.23870010673999786,
0.356764554977417,
0.4147942364215851,
-0.1960522085428238,
0.23967823386192322,
0.0669640302658081,
-0.18212391436100006,
0.08796869218349457,
0.4211682081222534,
0.1152283251285553,
0.30466559529304504,
0.14688749611377716,
0.1961059272289276,
0.10997584462165833,
0.3800206184387207,
0.01832268200814724,
0.013787861913442612,
-0.5149791240692139,
-0.326249897480011,
0.28526046872138977,
0.7866032719612122,
-0.23449641466140747,
-0.23747442662715912,
-0.1045805960893631,
-0.03371289744973183,
-0.28094711899757385,
0.03654807060956955,
0.03145764395594597,
0.21467262506484985,
-0.16369502246379852,
0.06738597899675369,
-0.4039888083934784,
-0.33536893129348755,
0.4025501608848572,
0.1397748440504074,
0.48646020889282227,
0.123641736805439,
0.12610046565532684,
0.09881323575973511,
-0.14917506277561188,
0.395193874835968,
-0.0036636944860219955,
0.21630744636058807,
0.26635605096817017,
-0.21953915059566498,
-0.21650680899620056,
-0.09907501190900803,
-0.08511698991060257,
0.01853322610259056,
-0.1848432719707489,
-0.14839716255664825,
0.35971978306770325,
-0.30942848324775696,
0.25821059942245483,
0.21343915164470673,
-0.15015840530395508,
-0.1043485626578331,
-0.0047554695047438145,
0.4263310432434082,
-0.033694855868816376,
0.0713232159614563,
0.19717857241630554,
-0.1961682140827179,
0.0076111555099487305,
-0.27579036355018616,
0.027275169268250465,
0.02952425181865692,
-0.012821812182664871,
0.12252480536699295,
-0.3832065761089325,
0.09562390297651291,
-0.36199119687080383,
-0.04778095707297325,
-0.08453317731618881,
-0.3333871066570282,
0.1714133322238922,
-0.009538624435663223,
0.027227267622947693,
-0.14987407624721527,
-0.023156672716140747,
-0.0725000873208046,
0.15157699584960938,
-0.2152206152677536,
0.01989271305501461,
0.23342444002628326,
-0.10189911723136902,
0.0881504938006401,
0.012576811946928501,
0.20164771378040314,
0.15531834959983826,
0.18760861456394196,
0.1086168885231018,
-0.1332702934741974,
0.22911305725574493,
-0.16917988657951355,
0.03806190937757492,
-0.26937001943588257,
0.18624171614646912,
-0.0961536169052124,
-0.050221510231494904,
-0.14967170357704163,
-0.21687638759613037,
-0.16860432922840118,
0.2626044452190399,
-0.14511266350746155,
-0.3540809154510498,
-0.22397267818450928,
0.37762829661369324,
-0.28075385093688965,
0.2039029896259308,
-0.1772482991218567,
-0.12753510475158691,
-0.09540987014770508,
-0.33919641375541687,
0.005437646061182022,
0.0747956857085228,
-0.4191731810569763,
0.15557458996772766,
-0.13233238458633423,
-0.058336492627859116,
-0.23669740557670593,
-0.05418844893574715,
-0.19494976103305817,
0.015208423137664795,
-0.09529176354408264,
-0.12077134847640991,
0.45636481046676636,
-0.552367091178894,
-0.06465820223093033,
-0.16999679803848267,
0.22772087156772614,
-0.2298593372106552,
-0.16411623358726501,
0.19302158057689667,
0.039700623601675034,
-0.1482827514410019,
-0.2039141058921814,
0.32110273838043213,
-0.14256274700164795,
-0.2917487621307373,
-0.20709387958049774,
-0.11056298762559891,
0.05193526670336723,
0.11169503629207611,
0.3645804524421692,
0.01750713586807251,
0.16154718399047852,
0.2132958471775055,
0.014443308115005493,
0.10343044996261597,
0.03156667202711105,
0.20741131901741028,
0.414486825466156,
0.21465058624744415,
0.46539101004600525,
-0.4261690080165863,
-0.43927866220474243,
0.1380772590637207,
0.19536946713924408,
0.18815842270851135,
0.10498815029859543,
0.08624672889709473,
-0.004376244731247425,
0.10294608771800995,
-0.12055496871471405,
0.3178800642490387,
0.14472611248493195,
-0.04055717587471008,
0.21057137846946716,
-0.14622390270233154,
-0.5968180298805237,
0.09261275082826614,
-0.10412328690290451,
0.41401198506355286,
-0.4701024889945984,
0.30474185943603516,
0.015341789461672306,
-0.15350066125392914,
0.16933949291706085,
0.2441728115081787,
0.005732301622629166,
-0.4595033824443817,
0.0803297832608223,
0.296469122171402,
0.1613711416721344,
0.2357262521982193,
-0.03380635380744934,
0.44494009017944336,
0.4259870946407318,
-0.06091940402984619,
0.3119790256023407,
-0.31688180565834045,
-0.026507500559091568,
-0.056937284767627716,
0.010205831378698349,
0.2147311419248581,
-0.0372154675424099,
-0.09473753720521927,
0.268436074256897,
0.016563652083277702,
0.16712196171283722,
0.26641350984573364,
-0.04216377064585686,
-0.21579426527023315,
0.030043838545680046,
-0.008427707478404045,
-0.021350311115384102,
-0.13367782533168793,
-0.2969609498977661,
0.22897610068321228,
0.6034261584281921,
-0.12870319187641144,
0.03560430929064751,
0.06194142997264862,
-0.24993255734443665,
-0.008935527876019478,
0.09163682162761688,
0.27020007371902466,
0.19163954257965088,
0.14972513914108276,
0.2187141478061676,
-0.018969638273119926,
-0.29128900170326233,
-0.12581434845924377,
0.03649461269378662,
0.19965317845344543,
0.14305704832077026,
-0.06021957844495773,
-0.013700097799301147,
0.005899482406675816,
-0.09948026388883591,
-0.019224274903535843,
-0.04581395536661148,
0.4715065062046051,
0.07942873239517212,
-0.18269290030002594,
-0.4099806249141693,
-0.18739193677902222,
-0.07155609130859375,
-0.17729948461055756,
-0.15517424046993256,
-0.30651596188545227,
0.03282032534480095,
-0.01460038498044014,
0.19896554946899414,
0.016423966735601425,
0.19826912879943848,
0.09923149645328522,
-0.2671225666999817,
0.36756622791290283,
-0.27087801694869995,
0.002239215886220336,
-0.21750178933143616,
0.19029970467090607,
0.2565094530582428,
-0.08611162006855011,
0.41823428869247437,
-0.03400958701968193,
0.23329398036003113,
-0.13853555917739868,
-0.64036625623703,
0.17638804018497467,
-0.1495903730392456,
-0.02689194120466709,
-0.02024998515844345,
-0.08343067765235901,
0.1799279749393463,
0.11929908394813538,
0.07279106974601746,
-0.2918451130390167,
-0.05149553716182709,
-0.044087156653404236,
-0.1970873326063156,
-0.11120231449604034,
-0.13188080489635468,
-0.5581414103507996,
-0.45936694741249084,
-0.2616689205169678,
0.1764208823442459,
0.3262961208820343,
0.08081508427858353,
0.1624584197998047,
0.08413614332675934,
0.1643996685743332,
-0.06314384937286377,
0.03947480395436287,
0.11278688907623291,
-0.25843706727027893,
0.40675827860832214,
-0.30711066722869873,
-0.3843969404697418,
0.4961083233356476,
-0.10421452671289444,
0.3492160439491272,
0.2127215713262558,
-0.3054114878177643,
-0.19868513941764832,
-0.02530968002974987,
-0.01599104329943657,
0.16639338433742523,
-0.019606439396739006,
0.23422180116176605,
-0.009280534461140633,
0.05265606939792633,
-0.25241121649742126,
-0.1440179944038391,
-0.08615788072347641,
0.3769686222076416,
0.029445581138134003,
0.14342643320560455,
0.334758460521698,
-0.03322427347302437,
0.430533230304718,
0.03644873574376106,
-0.2452239841222763,
0.050405580550432205,
0.16883547604084015,
0.10867685079574585,
0.011381909251213074,
-0.050217658281326294,
0.07712594419717789,
0.03132672607898712,
0.29908913373947144,
0.04891547933220863,
0.12088093906641006,
-0.10746306926012039,
-0.31403422355651855,
0.3371352255344391,
-0.17844313383102417,
-0.0018074177205562592,
-0.0018808655440807343,
-0.25169336795806885,
0.3295738101005554,
0.08878345787525177,
-0.19609886407852173,
-0.28800487518310547,
-0.14876821637153625,
0.1574668139219284,
0.3545747995376587,
0.24198195338249207,
-0.12902605533599854,
-0.5378569960594177,
-0.1852819323539734,
-0.1731891632080078,
0.41747599840164185,
-0.10197825729846954,
0.17927797138690948,
-0.19229258596897125,
0.11066804081201553,
0.11774341017007828,
0.0859801396727562,
0.18783017992973328,
-0.4766133427619934,
-0.527123212814331,
0.279164582490921,
-0.13627249002456665,
-0.23418812453746796,
-0.024256978183984756,
-0.3106381893157959,
0.11367247253656387,
-0.02908310294151306,
0.44889017939567566,
0.015480495989322662,
-0.3676788806915283,
0.24308724701404572,
0.1308567374944687,
0.08591009676456451,
-0.1405642330646515,
0.26299381256103516,
-0.010136343538761139,
-0.11732552200555801,
-0.2620445787906647,
-0.10521437972784042,
-0.11233888566493988,
-0.11672763526439667,
-0.5168623328208923,
0.07123604416847229,
-0.33272644877433777,
0.1847611665725708,
-0.047048330307006836,
-0.05658993870019913,
0.27492934465408325,
0.03683147206902504,
0.3168187141418457,
-0.14537106454372406,
0.46666744351387024,
-0.011513415724039078,
-0.38040339946746826,
-0.16965311765670776,
0.17406600713729858,
-0.09162214398384094,
0.19564741849899292,
0.15047915279865265,
-0.05298173800110817,
0.18283626437187195,
-0.06081804633140564,
-0.031034313142299652,
-0.1255171000957489,
0.16413477063179016,
0.41934022307395935,
0.2279086709022522,
-0.28524813055992126,
-0.607187807559967,
0.1147230863571167,
0.016152273863554,
-0.0485958456993103,
0.4207155108451843,
-0.13392092287540436,
-0.17450818419456482,
0.11098363250494003,
0.04105674847960472,
0.5863262414932251,
-0.2631884217262268,
-0.29278111457824707,
0.034749798476696014,
-0.0863000750541687,
0.4732598662376404,
-0.6111388802528381,
0.1742394119501114,
-0.03426749259233475,
0.10870567709207535,
-0.08511227369308472,
-0.2548709809780121,
0.2109452486038208,
0.0722760558128357,
-0.20136064291000366,
0.09954236447811127,
0.17709039151668549,
0.13807952404022217,
-0.1942109316587448,
0.659774661064148,
-0.06312782317399979,
-0.14037330448627472,
-0.09899745136499405,
0.2516936659812927,
-0.028308488428592682,
0.052181921899318695,
-0.060260724276304245,
-0.19137771427631378,
-0.03187745064496994,
0.18113330006599426,
-0.28495216369628906,
-0.16876009106636047,
-0.22131681442260742,
0.008319931104779243,
0.09131792932748795,
-0.04329487308859825,
0.3468938171863556,
0.09623097628355026,
0.5915396809577942,
-0.03202419355511665,
-0.2376018762588501,
0.27973926067352295,
-0.2682269215583801,
-0.11788816750049591,
-0.1228887066245079,
0.017207536846399307,
0.37216290831565857,
-0.29674217104911804,
-0.012082837522029877,
-0.07735525816679001,
-0.0002788277342915535,
-0.24259760975837708,
-0.36513471603393555,
-0.07142254710197449,
0.3298625946044922,
0.09708575904369354,
0.19230224192142487,
0.30334579944610596,
-0.09278278797864914,
0.00755995512008667,
0.24786651134490967,
0.45117902755737305,
0.014724215492606163,
0.4076642096042633,
0.04798474907875061,
0.000529654324054718,
-0.1513432413339615,
-0.15054932236671448,
0.27086058259010315,
-0.2877451181411743,
0.07257498800754547,
0.43703028559684753,
-0.19491265714168549,
-0.2097458839416504,
-0.19884449243545532,
0.1838003695011139,
0.05712958425283432,
0.07818350195884705,
0.1559590846300125,
0.09627260267734528,
0.19285620748996735,
0.09991782903671265,
-0.023509129881858826,
-0.4111431837081909,
-0.4108959436416626,
-0.29322004318237305,
-0.22436915338039398,
0.2566511332988739,
0.04946180060505867,
0.27945002913475037,
-0.1963750422000885,
-0.07223781943321228,
0.17411194741725922,
0.14937160909175873,
-0.37918296456336975,
0.0570145845413208,
0.15133535861968994,
0.03618868067860603,
0.22612495720386505,
-0.0725005641579628,
-0.03612145036458969,
-0.07173995673656464,
0.09386391192674637,
-0.027947835624217987,
-0.46794483065605164,
-0.18472224473953247,
0.04202614352107048,
0.1002144068479538,
-0.042637549340724945,
-0.2287178486585617,
0.1266716569662094,
-0.31415069103240967,
-0.28279295563697815,
-0.024908896535634995,
-0.0397677943110466,
-0.3050770163536072,
-0.1421203762292862,
0.3311747610569,
0.18199796974658966,
0.1702476441860199,
0.5582084059715271,
0.09513989090919495,
0.21245083212852478,
0.20485800504684448,
0.402187317609787,
0.18952004611492157,
0.2601071000099182,
-0.08211477845907211,
-0.14819790422916412,
0.07816367596387863,
-0.13820554316043854,
-0.17945772409439087,
0.3982885479927063,
-0.16925735771656036,
0.15359097719192505,
0.03235531225800514,
0.10143978893756866,
0.2642422914505005,
0.021073685958981514,
0.03696414828300476,
0.14142945408821106,
0.21311019361019135,
-0.13443012535572052,
-0.055899783968925476,
0.40270641446113586,
0.49797600507736206,
0.10187976062297821,
0.076864093542099,
0.5620503425598145,
0.1583326905965805,
0.28498029708862305,
0.17854461073875427,
0.23345711827278137,
-0.14217440783977509,
0.40867558121681213,
-0.1030537486076355,
-0.053733132779598236,
0.07344022393226624,
0.08991994708776474,
0.38149261474609375,
0.09467067569494247,
0.3289194703102112,
0.18405809998512268,
0.4397299289703369,
0.14604389667510986,
-0.08007971942424774,
0.5982280969619751,
-0.3191629648208618,
0.06604903936386108,
0.16271120309829712,
0.06078612431883812,
0.09383036196231842,
0.07741852104663849,
0.4690662920475006,
-0.009389805607497692,
-0.13898442685604095,
-0.05403551459312439,
-0.1166994571685791,
-0.10878206044435501,
-0.005931571591645479,
-0.04140736907720566,
-0.17655441164970398,
-0.20635242760181427,
-0.09554574638605118,
0.042455997318029404,
-0.24463890492916107,
0.10841155052185059,
-0.0067840442061424255,
0.02507495880126953,
-0.1830291897058487,
0.3499510884284973,
-0.0880805179476738,
-0.06958433240652084,
0.20820173621177673,
0.4416111409664154,
-0.2254699021577835,
-0.20558935403823853,
-0.09230738878250122,
-0.07757948338985443,
-0.06999090313911438,
0.02039320021867752,
-0.3597542941570282,
0.3094954788684845,
0.051701620221138,
-0.19295810163021088,
0.20771804451942444,
0.40192317962646484,
0.07114528864622116,
0.36640802025794983,
-0.1109786331653595,
0.15951362252235413,
-0.05355575680732727,
-0.022820819169282913,
-0.2833409607410431,
-0.021147258579730988,
-0.41630253195762634,
-0.08433752506971359,
0.11024495214223862,
-0.15187138319015503,
-0.045349545776844025,
-0.04589655250310898,
-0.47221639752388,
-0.5669896006584167,
0.5651452541351318,
-0.18957000970840454,
-0.15351352095603943,
-0.25356125831604004,
0.10814587771892548,
-0.09533166885375977,
0.2511746883392334,
0.12147380411624908,
0.45501282811164856,
0.05822417885065079,
-0.37744593620300293,
-0.2873685956001282,
0.0056760311126708984,
0.149158775806427,
0.2815351188182831,
-0.11302030831575394,
0.19985252618789673,
0.2401162087917328,
-0.03342721611261368,
0.4303882122039795,
-0.2973402440547943,
0.09230461716651917,
-0.004097919911146164,
-0.32758745551109314,
0.00985543429851532,
-0.20289473235607147,
0.04155024141073227,
0.1104595810174942,
0.25907841324806213,
0.07082263380289078,
-0.2688300609588623,
-0.025742657482624054,
-0.41214805841445923,
-0.02335938811302185,
0.33951470255851746,
0.0814245343208313,
0.4212687015533447,
0.14328189194202423,
0.29541245102882385,
0.18000543117523193,
-0.045552950352430344,
-0.41668328642845154,
-0.1639951467514038,
-0.01975807175040245,
0.23975995182991028,
-0.12995515763759613,
0.0806007981300354,
-0.19504308700561523,
0.01444610022008419,
-0.16572193801403046,
0.14214080572128296,
-0.16518990695476532,
-0.35498902201652527,
0.03663385659456253,
0.06656566262245178,
-0.08965340256690979,
0.03277633339166641,
0.4078938066959381,
0.13496807217597961,
0.233576238155365,
-0.24015268683433533,
-0.21379780769348145,
0.1258505880832672,
0.05555248260498047,
-0.07777585834264755,
-0.24822504818439484,
-0.1938065141439438,
-0.18507090210914612,
0.26290974020957947,
0.1135978028178215,
-0.875744104385376,
-0.21726350486278534,
0.2978818118572235,
-0.09050773829221725,
0.06773225963115692,
0.26117268204689026,
0.4608120918273926,
-0.01169823482632637,
-0.1992034763097763,
0.08760400116443634,
0.004510505124926567,
-0.05850180238485336,
-0.1302710324525833,
-0.15369963645935059
] |
https://github.com/huggingface/datasets/issues/187 | [Question] How to load wikipedia ? Beam runner ? | I have seen that somebody is hard working on easierly loadable wikipedia. #129
Maybe I should wait a few days for that version ? | When `nlp.load_dataset('wikipedia')`, I got
* `WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be used.`
* `AttributeError: 'NoneType' object has no attribute 'size'`
Could somebody tell me what should I do ?
# Env
On Colab,
```
git clone https://github.com/huggingface/nlp
cd nlp
pip install -q .
```
```
%pip install -q apache_beam mwparserfromhell
-> ERROR: pydrive 1.3.1 has requirement oauth2client>=4.0.0, but you'll have oauth2client 3.0.0 which is incompatible.
ERROR: google-api-python-client 1.7.12 has requirement httplib2<1dev,>=0.17.0, but you'll have httplib2 0.12.0 which is incompatible.
ERROR: chainer 6.5.0 has requirement typing-extensions<=3.6.6, but you'll have typing-extensions 3.7.4.2 which is incompatible.
```
```
pip install -q apache-beam[interactive]
ERROR: google-colab 1.0.0 has requirement ipython~=5.5.0, but you'll have ipython 5.10.0 which is incompatible.
```
# The whole message
```
WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be used.
Downloading and preparing dataset wikipedia/20200501.aa (download: Unknown size, generated: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/wikipedia/20200501.aa/1.0.0...
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()
44 frames
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker.invoke_process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window()
/usr/local/lib/python3.6/dist-packages/apache_beam/io/iobase.py in process(self, element, init_result)
1081 writer.write(e)
-> 1082 return [window.TimestampedValue(writer.close(), timestamp.MAX_TIMESTAMP)]
1083
/usr/local/lib/python3.6/dist-packages/apache_beam/io/filebasedsink.py in close(self)
422 def close(self):
--> 423 self.sink.close(self.temp_handle)
424 return self.temp_shard_path
/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in close(self, writer)
537 if len(self._buffer[0]) > 0:
--> 538 self._flush_buffer()
539 if self._record_batches_byte_size > 0:
/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in _flush_buffer(self)
569 for b in x.buffers():
--> 570 size = size + b.size
571 self._record_batches_byte_size = self._record_batches_byte_size + size
AttributeError: 'NoneType' object has no attribute 'size'
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
<ipython-input-9-340aabccefff> in <module>()
----> 1 dset = nlp.load_dataset('wikipedia')
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=download_mode,
519 ignore_verifications=ignore_verifications,
--> 520 save_infos=save_infos,
521 )
522
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
370 verify_infos = not save_infos and not ignore_verifications
371 self._download_and_prepare(
--> 372 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
373 )
374 # Sync info
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos)
770 with beam.Pipeline(runner=beam_runner, options=beam_options,) as pipeline:
771 super(BeamBasedBuilder, self)._download_and_prepare(
--> 772 dl_manager, pipeline=pipeline, verify_infos=False
773 ) # TODO{beam} verify infos
774
/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in __exit__(self, exc_type, exc_val, exc_tb)
501 def __exit__(self, exc_type, exc_val, exc_tb):
502 if not exc_type:
--> 503 self.run().wait_until_finish()
504
505 def visit(self, visitor):
/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in run(self, test_runner_api)
481 return Pipeline.from_runner_api(
482 self.to_runner_api(use_fake_coders=True), self.runner,
--> 483 self._options).run(False)
484
485 if self._options.view_as(TypeOptions).runtime_type_check:
/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in run(self, test_runner_api)
494 finally:
495 shutil.rmtree(tmpdir)
--> 496 return self.runner.run_pipeline(self, self._options)
497
498 def __enter__(self):
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/direct/direct_runner.py in run_pipeline(self, pipeline, options)
128 runner = BundleBasedDirectRunner()
129
--> 130 return runner.run_pipeline(pipeline, options)
131
132
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_pipeline(self, pipeline, options)
553
554 self._latest_run_result = self.run_via_runner_api(
--> 555 pipeline.to_runner_api(default_environment=self._default_environment))
556 return self._latest_run_result
557
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_via_runner_api(self, pipeline_proto)
563 # TODO(pabloem, BEAM-7514): Create a watermark manager (that has access to
564 # the teststream (if any), and all the stages).
--> 565 return self.run_stages(stage_context, stages)
566
567 @contextlib.contextmanager
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_stages(self, stage_context, stages)
704 stage,
705 pcoll_buffers,
--> 706 stage_context.safe_coders)
707 metrics_by_stage[stage.name] = stage_results.process_bundle.metrics
708 monitoring_infos_by_stage[stage.name] = (
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in _run_stage(self, worker_handler_factory, pipeline_components, stage, pcoll_buffers, safe_coders)
1071 cache_token_generator=cache_token_generator)
1072
-> 1073 result, splits = bundle_manager.process_bundle(data_input, data_output)
1074
1075 def input_for(transform_id, input_id):
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in process_bundle(self, inputs, expected_outputs)
2332
2333 with UnboundedThreadPoolExecutor() as executor:
-> 2334 for result, split_result in executor.map(execute, part_inputs):
2335
2336 split_result_list += split_result
/usr/lib/python3.6/concurrent/futures/_base.py in result_iterator()
584 # Careful not to keep a reference to the popped future
585 if timeout is None:
--> 586 yield fs.pop().result()
587 else:
588 yield fs.pop().result(end_time - time.monotonic())
/usr/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
430 raise CancelledError()
431 elif self._state == FINISHED:
--> 432 return self.__get_result()
433 else:
434 raise TimeoutError()
/usr/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
382 def __get_result(self):
383 if self._exception:
--> 384 raise self._exception
385 else:
386 return self._result
/usr/local/lib/python3.6/dist-packages/apache_beam/utils/thread_pool_executor.py in run(self)
42 # If the future wasn't cancelled, then attempt to execute it.
43 try:
---> 44 self._future.set_result(self._fn(*self._fn_args, **self._fn_kwargs))
45 except BaseException as exc:
46 # Even though Python 2 futures library has #set_exection(),
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in execute(part_map)
2329 self._registered,
2330 cache_token_generator=self._cache_token_generator)
-> 2331 return bundle_manager.process_bundle(part_map, expected_outputs)
2332
2333 with UnboundedThreadPoolExecutor() as executor:
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in process_bundle(self, inputs, expected_outputs)
2243 process_bundle_descriptor_id=self._bundle_descriptor.id,
2244 cache_tokens=[next(self._cache_token_generator)]))
-> 2245 result_future = self._worker_handler.control_conn.push(process_bundle_req)
2246
2247 split_results = [] # type: List[beam_fn_api_pb2.ProcessBundleSplitResponse]
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in push(self, request)
1557 self._uid_counter += 1
1558 request.instruction_id = 'control_%s' % self._uid_counter
-> 1559 response = self.worker.do_instruction(request)
1560 return ControlFuture(request.instruction_id, response)
1561
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/sdk_worker.py in do_instruction(self, request)
413 # E.g. if register is set, this will call self.register(request.register))
414 return getattr(self, request_type)(
--> 415 getattr(request, request_type), request.instruction_id)
416 else:
417 raise NotImplementedError
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/sdk_worker.py in process_bundle(self, request, instruction_id)
448 with self.maybe_profile(instruction_id):
449 delayed_applications, requests_finalization = (
--> 450 bundle_processor.process_bundle(instruction_id))
451 monitoring_infos = bundle_processor.monitoring_infos()
452 monitoring_infos.extend(self.state_cache_metrics_fn())
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/bundle_processor.py in process_bundle(self, instruction_id)
837 for data in data_channel.input_elements(instruction_id,
838 expected_transforms):
--> 839 input_op_by_transform_id[data.transform_id].process_encoded(data.data)
840
841 # Finish all operations.
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/bundle_processor.py in process_encoded(self, encoded_windowed_values)
214 decoded_value = self.windowed_coder_impl.decode_from_stream(
215 input_stream, True)
--> 216 self.output(decoded_value)
217
218 def try_split(self, fraction_of_remainder, total_buffer_size):
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.Operation.output()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.Operation.output()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.SingletonConsumerSet.receive()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.DoOperation.process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.DoOperation.process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner._reraise_augmented()
/usr/local/lib/python3.6/dist-packages/future/utils/__init__.py in raise_with_traceback(exc, traceback)
417 if traceback == Ellipsis:
418 _, _, traceback = sys.exc_info()
--> 419 raise exc.with_traceback(traceback)
420
421 else:
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker.invoke_process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window()
/usr/local/lib/python3.6/dist-packages/apache_beam/io/iobase.py in process(self, element, init_result)
1080 for e in bundle[1]: # values
1081 writer.write(e)
-> 1082 return [window.TimestampedValue(writer.close(), timestamp.MAX_TIMESTAMP)]
1083
1084
/usr/local/lib/python3.6/dist-packages/apache_beam/io/filebasedsink.py in close(self)
421
422 def close(self):
--> 423 self.sink.close(self.temp_handle)
424 return self.temp_shard_path
/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in close(self, writer)
536 def close(self, writer):
537 if len(self._buffer[0]) > 0:
--> 538 self._flush_buffer()
539 if self._record_batches_byte_size > 0:
540 self._write_batches(writer)
/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in _flush_buffer(self)
568 for x in arrays:
569 for b in x.buffers():
--> 570 size = size + b.size
571 self._record_batches_byte_size = self._record_batches_byte_size + size
AttributeError: 'NoneType' object has no attribute 'size' [while running 'train/Save to parquet/Write/WriteImpl/WriteBundles']
``` | 24 | [Question] How to load wikipedia ? Beam runner ?
When `nlp.load_dataset('wikipedia')`, I got
* `WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be used.`
* `AttributeError: 'NoneType' object has no attribute 'size'`
Could somebody tell me what should I do ?
# Env
On Colab,
```
git clone https://github.com/huggingface/nlp
cd nlp
pip install -q .
```
```
%pip install -q apache_beam mwparserfromhell
-> ERROR: pydrive 1.3.1 has requirement oauth2client>=4.0.0, but you'll have oauth2client 3.0.0 which is incompatible.
ERROR: google-api-python-client 1.7.12 has requirement httplib2<1dev,>=0.17.0, but you'll have httplib2 0.12.0 which is incompatible.
ERROR: chainer 6.5.0 has requirement typing-extensions<=3.6.6, but you'll have typing-extensions 3.7.4.2 which is incompatible.
```
```
pip install -q apache-beam[interactive]
ERROR: google-colab 1.0.0 has requirement ipython~=5.5.0, but you'll have ipython 5.10.0 which is incompatible.
```
# The whole message
```
WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be used.
Downloading and preparing dataset wikipedia/20200501.aa (download: Unknown size, generated: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/wikipedia/20200501.aa/1.0.0...
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()
44 frames
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker.invoke_process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window()
/usr/local/lib/python3.6/dist-packages/apache_beam/io/iobase.py in process(self, element, init_result)
1081 writer.write(e)
-> 1082 return [window.TimestampedValue(writer.close(), timestamp.MAX_TIMESTAMP)]
1083
/usr/local/lib/python3.6/dist-packages/apache_beam/io/filebasedsink.py in close(self)
422 def close(self):
--> 423 self.sink.close(self.temp_handle)
424 return self.temp_shard_path
/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in close(self, writer)
537 if len(self._buffer[0]) > 0:
--> 538 self._flush_buffer()
539 if self._record_batches_byte_size > 0:
/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in _flush_buffer(self)
569 for b in x.buffers():
--> 570 size = size + b.size
571 self._record_batches_byte_size = self._record_batches_byte_size + size
AttributeError: 'NoneType' object has no attribute 'size'
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
<ipython-input-9-340aabccefff> in <module>()
----> 1 dset = nlp.load_dataset('wikipedia')
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=download_mode,
519 ignore_verifications=ignore_verifications,
--> 520 save_infos=save_infos,
521 )
522
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
370 verify_infos = not save_infos and not ignore_verifications
371 self._download_and_prepare(
--> 372 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
373 )
374 # Sync info
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos)
770 with beam.Pipeline(runner=beam_runner, options=beam_options,) as pipeline:
771 super(BeamBasedBuilder, self)._download_and_prepare(
--> 772 dl_manager, pipeline=pipeline, verify_infos=False
773 ) # TODO{beam} verify infos
774
/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in __exit__(self, exc_type, exc_val, exc_tb)
501 def __exit__(self, exc_type, exc_val, exc_tb):
502 if not exc_type:
--> 503 self.run().wait_until_finish()
504
505 def visit(self, visitor):
/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in run(self, test_runner_api)
481 return Pipeline.from_runner_api(
482 self.to_runner_api(use_fake_coders=True), self.runner,
--> 483 self._options).run(False)
484
485 if self._options.view_as(TypeOptions).runtime_type_check:
/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in run(self, test_runner_api)
494 finally:
495 shutil.rmtree(tmpdir)
--> 496 return self.runner.run_pipeline(self, self._options)
497
498 def __enter__(self):
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/direct/direct_runner.py in run_pipeline(self, pipeline, options)
128 runner = BundleBasedDirectRunner()
129
--> 130 return runner.run_pipeline(pipeline, options)
131
132
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_pipeline(self, pipeline, options)
553
554 self._latest_run_result = self.run_via_runner_api(
--> 555 pipeline.to_runner_api(default_environment=self._default_environment))
556 return self._latest_run_result
557
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_via_runner_api(self, pipeline_proto)
563 # TODO(pabloem, BEAM-7514): Create a watermark manager (that has access to
564 # the teststream (if any), and all the stages).
--> 565 return self.run_stages(stage_context, stages)
566
567 @contextlib.contextmanager
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_stages(self, stage_context, stages)
704 stage,
705 pcoll_buffers,
--> 706 stage_context.safe_coders)
707 metrics_by_stage[stage.name] = stage_results.process_bundle.metrics
708 monitoring_infos_by_stage[stage.name] = (
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in _run_stage(self, worker_handler_factory, pipeline_components, stage, pcoll_buffers, safe_coders)
1071 cache_token_generator=cache_token_generator)
1072
-> 1073 result, splits = bundle_manager.process_bundle(data_input, data_output)
1074
1075 def input_for(transform_id, input_id):
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in process_bundle(self, inputs, expected_outputs)
2332
2333 with UnboundedThreadPoolExecutor() as executor:
-> 2334 for result, split_result in executor.map(execute, part_inputs):
2335
2336 split_result_list += split_result
/usr/lib/python3.6/concurrent/futures/_base.py in result_iterator()
584 # Careful not to keep a reference to the popped future
585 if timeout is None:
--> 586 yield fs.pop().result()
587 else:
588 yield fs.pop().result(end_time - time.monotonic())
/usr/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
430 raise CancelledError()
431 elif self._state == FINISHED:
--> 432 return self.__get_result()
433 else:
434 raise TimeoutError()
/usr/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
382 def __get_result(self):
383 if self._exception:
--> 384 raise self._exception
385 else:
386 return self._result
/usr/local/lib/python3.6/dist-packages/apache_beam/utils/thread_pool_executor.py in run(self)
42 # If the future wasn't cancelled, then attempt to execute it.
43 try:
---> 44 self._future.set_result(self._fn(*self._fn_args, **self._fn_kwargs))
45 except BaseException as exc:
46 # Even though Python 2 futures library has #set_exection(),
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in execute(part_map)
2329 self._registered,
2330 cache_token_generator=self._cache_token_generator)
-> 2331 return bundle_manager.process_bundle(part_map, expected_outputs)
2332
2333 with UnboundedThreadPoolExecutor() as executor:
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in process_bundle(self, inputs, expected_outputs)
2243 process_bundle_descriptor_id=self._bundle_descriptor.id,
2244 cache_tokens=[next(self._cache_token_generator)]))
-> 2245 result_future = self._worker_handler.control_conn.push(process_bundle_req)
2246
2247 split_results = [] # type: List[beam_fn_api_pb2.ProcessBundleSplitResponse]
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in push(self, request)
1557 self._uid_counter += 1
1558 request.instruction_id = 'control_%s' % self._uid_counter
-> 1559 response = self.worker.do_instruction(request)
1560 return ControlFuture(request.instruction_id, response)
1561
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/sdk_worker.py in do_instruction(self, request)
413 # E.g. if register is set, this will call self.register(request.register))
414 return getattr(self, request_type)(
--> 415 getattr(request, request_type), request.instruction_id)
416 else:
417 raise NotImplementedError
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/sdk_worker.py in process_bundle(self, request, instruction_id)
448 with self.maybe_profile(instruction_id):
449 delayed_applications, requests_finalization = (
--> 450 bundle_processor.process_bundle(instruction_id))
451 monitoring_infos = bundle_processor.monitoring_infos()
452 monitoring_infos.extend(self.state_cache_metrics_fn())
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/bundle_processor.py in process_bundle(self, instruction_id)
837 for data in data_channel.input_elements(instruction_id,
838 expected_transforms):
--> 839 input_op_by_transform_id[data.transform_id].process_encoded(data.data)
840
841 # Finish all operations.
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/bundle_processor.py in process_encoded(self, encoded_windowed_values)
214 decoded_value = self.windowed_coder_impl.decode_from_stream(
215 input_stream, True)
--> 216 self.output(decoded_value)
217
218 def try_split(self, fraction_of_remainder, total_buffer_size):
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.Operation.output()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.Operation.output()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.SingletonConsumerSet.receive()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.DoOperation.process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.DoOperation.process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner._reraise_augmented()
/usr/local/lib/python3.6/dist-packages/future/utils/__init__.py in raise_with_traceback(exc, traceback)
417 if traceback == Ellipsis:
418 _, _, traceback = sys.exc_info()
--> 419 raise exc.with_traceback(traceback)
420
421 else:
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker.invoke_process()
/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window()
/usr/local/lib/python3.6/dist-packages/apache_beam/io/iobase.py in process(self, element, init_result)
1080 for e in bundle[1]: # values
1081 writer.write(e)
-> 1082 return [window.TimestampedValue(writer.close(), timestamp.MAX_TIMESTAMP)]
1083
1084
/usr/local/lib/python3.6/dist-packages/apache_beam/io/filebasedsink.py in close(self)
421
422 def close(self):
--> 423 self.sink.close(self.temp_handle)
424 return self.temp_shard_path
/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in close(self, writer)
536 def close(self, writer):
537 if len(self._buffer[0]) > 0:
--> 538 self._flush_buffer()
539 if self._record_batches_byte_size > 0:
540 self._write_batches(writer)
/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in _flush_buffer(self)
568 for x in arrays:
569 for b in x.buffers():
--> 570 size = size + b.size
571 self._record_batches_byte_size = self._record_batches_byte_size + size
AttributeError: 'NoneType' object has no attribute 'size' [while running 'train/Save to parquet/Write/WriteImpl/WriteBundles']
```
I have seen that somebody is hard working on easierly loadable wikipedia. #129
Maybe I should wait a few days for that version ? | [
-0.15169493854045868,
0.00311848521232605,
-0.01721992902457714,
0.3954119086265564,
-0.06618136167526245,
0.05573359876871109,
0.04334799572825432,
0.33450645208358765,
0.34885430335998535,
0.1168280839920044,
0.319930762052536,
0.17322245240211487,
-0.1478523463010788,
-0.08189839869737625,
-0.01621365174651146,
-0.45966222882270813,
-0.051987938582897186,
0.24634328484535217,
0.036583516746759415,
-0.055987875908613205,
-0.2965039908885956,
0.26790350675582886,
-0.29956990480422974,
0.1040332168340683,
-0.06252715736627579,
-0.14766909182071686,
0.150971457362175,
0.02395021542906761,
-0.2917691171169281,
-0.37569132447242737,
0.04113136976957321,
-0.22728359699249268,
0.27645933628082275,
0.149385467171669,
-0.00011269281822023913,
-0.03307892754673958,
0.666763961315155,
0.013357171788811684,
-0.44841063022613525,
-0.39789509773254395,
-0.1365269124507904,
-0.40732404589653015,
0.45148611068725586,
-0.2783578336238861,
0.010811049491167068,
-0.1832435578107834,
0.3193396329879761,
0.17982672154903412,
0.41272199153900146,
0.29741448163986206,
0.2151002287864685,
0.013293188065290451,
0.31618157029151917,
0.02897235006093979,
0.43313151597976685,
0.023455746471881866,
0.037681788206100464,
-0.08287952840328217,
-0.13199631869792938,
0.034157395362854004,
-0.12720948457717896,
0.15120500326156616,
-0.2554621398448944,
0.08563673496246338,
0.34953808784484863,
-0.19634762406349182,
-0.0711800679564476,
-0.5439115762710571,
0.13230383396148682,
0.14068442583084106,
0.6836259961128235,
-0.046239934861660004,
0.16607248783111572,
0.09736485034227371,
0.11649180203676224,
0.05789187550544739,
0.23870918154716492,
0.3242081105709076,
-0.4263734519481659,
-0.30791041254997253,
-0.21799717843532562,
-0.24967512488365173,
-0.2927876114845276,
0.46477794647216797,
0.04294971376657486,
0.5524114370346069,
-0.06267865002155304,
0.22764942049980164,
-0.04183034226298332,
-0.023902785032987595,
-0.06886428594589233,
-0.1292952299118042,
0.028790326789021492,
0.30135416984558105,
0.060495082288980484,
0.09357406198978424,
0.021500572562217712,
0.22951245307922363,
0.19686871767044067,
-0.043417222797870636,
-0.17343655228614807,
-0.1454145312309265,
0.14635173976421356,
0.14654338359832764,
0.03337777405977249,
0.25672271847724915,
0.1367921382188797,
-0.16623704135417938,
0.1898491382598877,
0.21545089781284332,
-0.06594294309616089,
0.08795030415058136,
-0.03179530054330826,
-0.17879846692085266,
-0.46619170904159546,
0.02353104203939438,
0.2609488368034363,
-0.17632582783699036,
-0.036259714514017105,
0.04170362651348114,
-0.42591845989227295,
-0.24169892072677612,
-0.02936335653066635,
0.32280653715133667,
-0.21127139031887054,
0.3524998724460602,
0.374053955078125,
0.07673802971839905,
-0.3170037269592285,
-0.3271934688091278,
0.020153403282165527,
0.2933025062084198,
-0.2867259681224823,
0.08495920896530151,
0.23058660328388214,
0.30473241209983826,
0.35114482045173645,
-0.017778804525732994,
-0.07731509208679199,
0.008208584040403366,
0.16384051740169525,
-0.08172617852687836,
-0.21706679463386536,
0.2386733442544937,
0.31429746747016907,
0.27012401819229126,
0.058486949652433395,
-0.33255624771118164,
-0.07982198894023895,
0.25485438108444214,
-0.3396589457988739,
-0.07505985349416733,
-0.03394258767366409,
0.16418899595737457,
-0.10578513890504837,
0.013759659603238106,
-0.34825336933135986,
0.24756541848182678,
0.03083135187625885,
-0.2846430242061615,
-0.17346858978271484,
-0.1604103446006775,
-0.08583105355501175,
-0.35577037930488586,
0.2626807987689972,
0.33504220843315125,
0.13158604502677917,
-0.10666563361883163,
-0.08848176151514053,
0.1678844690322876,
0.22503505647182465,
0.056384846568107605,
-0.12499351054430008,
0.4726501703262329,
-0.04442140460014343,
-0.07877199351787567,
0.7422001957893372,
-0.13415753841400146,
-0.17248471081256866,
0.23400962352752686,
0.13185544312000275,
0.019067810848355293,
0.0614241324365139,
-0.06255611777305603,
0.12045732885599136,
0.08603453636169434,
-0.051530465483665466,
0.566815197467804,
-0.011338306590914726,
0.0343194380402565,
-0.40983110666275024,
-0.2514777183532715,
0.17665739357471466,
0.06843884289264679,
0.3860551118850708,
0.15072938799858093,
0.010939329862594604,
0.5279035568237305,
0.08195846527814865,
-0.03969378396868706,
0.026423433795571327,
0.3199971318244934,
-0.297061026096344,
-0.09037400782108307,
-0.021785132586956024,
0.06996960937976837,
-0.1751367151737213,
-0.0254768468439579,
-0.3948405385017395,
0.15085041522979736,
0.15849989652633667,
0.10617592930793762,
-0.3540581166744232,
-0.1429709494113922,
-0.052457261830568314,
-0.1548895239830017,
0.1619727909564972,
0.1855083703994751,
0.09486676752567291,
0.15069285035133362,
0.054137613624334335,
0.06682412326335907,
-0.1275254189968109,
-0.04091872274875641,
-0.6120949387550354,
0.1855083703994751,
-0.27361801266670227,
-0.07680457085371017,
0.11377494037151337,
0.2102164924144745,
0.24915528297424316,
0.011264992877840996,
-0.1234433725476265,
0.006876267492771149,
-0.20115044713020325,
-0.06263680756092072,
-0.027232900261878967,
-0.07050861418247223,
0.20225463807582855,
-0.3002311587333679,
0.31451135873794556,
0.2933093011379242,
0.1526009440422058,
-0.1323699653148651,
0.08773380517959595,
-0.07689173519611359,
0.11841444671154022,
0.3404713273048401,
0.07403960824012756,
0.10327670723199844,
0.004244735464453697,
-0.06270985305309296,
-0.0017370712012052536,
0.2277480959892273,
0.3068396747112274,
0.42919909954071045,
0.0985184907913208,
-0.10778805613517761,
0.0011934638023376465,
-0.20937365293502808,
0.36993667483329773,
0.04473312571644783,
0.04405396431684494,
0.26717716455459595,
-0.4356001019477844,
-0.015432308427989483,
0.1121867448091507,
-0.16287536919116974,
0.16692376136779785,
0.2249116748571396,
-0.1555088311433792,
-0.03987376391887665,
-0.0813923254609108,
-0.12739378213882446,
0.20037701725959778,
0.1784820258617401,
0.36961862444877625,
0.11934078484773636,
0.08972068876028061,
0.07794459909200668,
-0.07833760231733322,
-0.1367141604423523,
-0.14669492840766907,
0.317047655582428,
-0.3040972650051117,
0.07823999971151352,
-0.023409854620695114,
-0.47671717405319214,
-0.24302992224693298,
0.04412386193871498,
-0.45233333110809326,
-0.3893639147281647,
-0.04385986179113388,
0.26631495356559753,
0.10461795330047607,
0.09521710127592087,
0.34473323822021484,
0.14382530748844147,
-0.01657220348715782,
-0.09474824368953705,
-0.16188697516918182,
-0.2388000786304474,
-0.46269989013671875,
0.06032678112387657,
0.3643651306629181,
0.2716529369354248,
0.26252681016921997,
-0.03581193834543228,
0.0011127106845378876,
-0.016719801351428032,
-0.26169857382774353,
0.035663191229104996,
-0.08692272007465363,
0.19745075702667236,
-0.1058526337146759,
0.4281997084617615,
-0.06742101907730103,
-0.19357021152973175,
0.26940399408340454,
-0.03542928025126457,
-0.09465430676937103,
0.0787811279296875,
-0.13136334717273712,
0.01989472657442093,
-0.018719865009188652,
-0.3938398063182831,
-0.19605626165866852,
-0.5722573399543762,
0.03628219664096832,
0.5017025470733643,
0.15746326744556427,
0.1577184647321701,
0.22311870753765106,
0.07921328395605087,
0.37221410870552063,
0.3003673851490021,
-0.07484946399927139,
0.08280737698078156,
0.3569962978363037,
-0.24258480966091156,
-0.45372629165649414,
0.006873439997434616,
-0.25352829694747925,
0.20978479087352753,
0.1102360263466835,
-0.5407999753952026,
-0.06307719647884369,
-0.03617759048938751,
-0.09409025311470032,
-0.07280644029378891,
0.09220913052558899,
0.4026174247264862,
-0.02519320696592331,
0.0642644464969635,
0.03355094790458679,
-0.004459993913769722,
-0.15063700079917908,
-0.2979053556919098,
0.539756178855896,
0.3464975655078888,
0.3857057988643646,
-0.12387114763259888,
0.9763141870498657,
0.11937181651592255,
-0.010839805006980896,
0.21248789131641388,
0.1578991711139679,
0.04472491145133972,
-0.20025968551635742,
-0.21275107562541962,
0.1421237289905548,
-0.015238747000694275,
-0.051308535039424896,
0.37091290950775146,
-0.09053631126880646,
-0.25643083453178406,
-0.28977763652801514,
-0.05816591531038284,
-0.2621939778327942,
-0.12282593548297882,
0.2391219139099121,
0.04297163337469101,
0.1968320608139038,
-0.11754602193832397,
0.04727274924516678,
-0.060972217470407486,
-0.3704538345336914,
0.08413924276828766,
0.2635555863380432,
-0.059675805270671844,
0.08931107074022293,
0.2353031486272812,
-0.1747625172138214,
-0.500149667263031,
0.40322381258010864,
0.02955075167119503,
0.09460225701332092,
-0.2325175553560257,
-0.02591796964406967,
0.172696053981781,
-0.04392104223370552,
0.22944006323814392,
-0.17277568578720093,
-0.18007849156856537,
0.3131050765514374,
0.27893176674842834,
-0.4931185841560364,
-0.0071612149477005005,
-0.22605517506599426,
0.21649278700351715,
0.31887030601501465,
-0.06501565873622894,
-0.4468342065811157,
0.011840201914310455,
0.35860732197761536,
0.2625586986541748,
-0.16119277477264404,
-0.06786547601222992,
-0.4241856336593628,
-0.10542401671409607,
-0.35802534222602844,
-0.16013994812965393,
-0.1432648003101349,
0.3781591057777405,
0.014349144883453846,
0.08232946693897247,
-0.051163285970687866,
-0.07533728331327438,
0.03009631484746933,
0.056553084403276443,
0.1316145658493042,
0.15762071311473846,
-0.3129262924194336,
-0.17733995616436005,
0.2570785880088806,
-0.3667410910129547,
0.207405686378479,
0.33988094329833984,
0.022439733147621155,
0.009034428745508194,
0.1605154275894165,
0.10108733922243118,
0.1211695596575737,
0.038661349564790726,
-0.09372284263372421,
-0.09350200742483139,
-0.02033752202987671,
-0.10446882992982864,
0.04888502135872841,
0.20298326015472412,
-0.1898670792579651,
-0.19062067568302155,
-0.1861119568347931,
0.9091108441352844,
0.11542610824108124,
-0.08426406234502792,
0.39913371205329895,
-0.10438928008079529,
-0.30044353008270264,
0.4643959403038025,
0.2923504114151001,
1.033750057220459,
-0.05213094502687454,
0.07410755753517151,
0.35504287481307983,
0.14539143443107605,
0.5975180864334106,
-0.5634698271751404,
0.24681450426578522,
-0.46771374344825745,
0.19664128124713898,
-0.042075254023075104,
-0.0888727456331253,
0.18185505270957947,
-0.025462642312049866,
-0.42296040058135986,
0.30799660086631775,
0.21473200619220734,
0.05316548049449921,
-0.004552369937300682,
0.4972430467605591,
-0.007547469809651375,
-0.2034151405096054,
-0.2026687115430832,
0.11879855394363403,
-0.45273542404174805,
0.4196888506412506,
-0.31372305750846863,
-0.07739031314849854,
-0.03726926073431969,
-0.26645174622535706,
-0.32122600078582764,
0.23819094896316528,
-0.28426429629325867,
0.2605060935020447,
-0.0788804292678833,
-0.4040435552597046,
0.13645246624946594,
0.20011821389198303,
-0.07382701337337494,
0.22187985479831696,
-0.36752042174339294,
0.30768585205078125,
-0.3412056267261505,
-0.3970913589000702,
-0.16703787446022034,
0.30388855934143066,
0.31267955899238586,
-0.20412343740463257,
-0.09111820161342621,
0.26975297927856445,
-0.1574624627828598,
-0.19343270361423492,
-0.11627297103404999,
-0.04585834592580795,
0.4036433696746826,
-0.08228058367967606,
-0.28408175706863403,
0.08862954378128052,
-0.11740091443061829,
0.10527443885803223,
0.12881626188755035,
-0.15789106488227844,
-0.023842837661504745,
-0.1117863580584526,
0.4168771505355835,
-0.12245699763298035,
0.15307927131652832,
0.21601274609565735,
0.351275771856308,
-0.0435095876455307,
0.6242598295211792,
0.2489510029554367,
-0.12671306729316711,
-0.19333383440971375,
-0.08216258138418198,
-0.36340129375457764,
-0.22032541036605835,
-0.13269227743148804,
0.06104392185807228,
0.026035770773887634,
-0.16175705194473267,
0.31193411350250244,
0.045710865408182144,
0.14814773201942444,
0.08542022109031677,
-0.47049370408058167,
-0.08573375642299652,
0.3661576509475708,
-0.21597419679164886,
-0.02671365812420845,
0.1270245611667633,
-0.11447963118553162,
0.46333280205726624,
0.13523633778095245,
-0.2516554594039917,
-0.19684122502803802,
-0.2700388729572296,
0.20194363594055176,
0.33353686332702637,
-0.0315210297703743,
-0.09638059884309769,
0.18977464735507965,
0.038723282516002655,
-0.18776559829711914,
-0.1967306137084961,
-0.19243746995925903,
0.07814830541610718,
0.16214875876903534,
0.20964843034744263,
-0.0580848827958107,
-0.10040753334760666,
-0.2537480890750885,
0.040457434952259064,
-0.17626824975013733,
-0.17049220204353333,
-0.2846740782260895,
-0.16244207322597504,
0.07903767377138138,
-0.0626453310251236,
0.28314512968063354,
-0.39182209968566895,
0.21595892310142517,
-0.15372951328754425,
0.45376354455947876,
0.1176493689417839,
0.04202556237578392,
0.5127455592155457,
-0.055491093546152115,
-0.742988646030426,
0.03110482543706894,
0.013880766928195953,
0.11196262389421463,
0.25134673714637756,
-0.10180933773517609,
0.07591325044631958,
-0.050089895725250244,
-0.18661344051361084,
0.017425913363695145,
-0.12645600736141205,
0.07031650841236115,
0.11335647851228714,
0.15643487870693207,
-0.16165699064731598,
0.36316293478012085,
0.39460474252700806,
0.1727810800075531,
-0.17091768980026245,
0.0786660835146904,
0.03425268456339836,
-0.0917048379778862,
-0.0037516653537750244,
0.2260856032371521,
-0.005977984517812729,
-0.055716536939144135,
0.023208700120449066,
-0.12723307311534882,
-0.02531924471259117,
-0.013456884771585464,
0.011188994161784649,
-0.020251654088497162,
0.12814384698867798,
0.11533625423908234,
-0.1465819776058197,
0.184061661362648,
0.054378442466259,
0.006913401186466217,
0.01574249565601349,
-0.18640601634979248,
0.23530103266239166,
0.15203259885311127,
0.37113508582115173,
0.04706276208162308,
0.0498722605407238,
0.04481049254536629,
0.11762683093547821,
-0.14441266655921936,
-0.4065524935722351,
0.1806311309337616,
-0.12935304641723633,
0.12624359130859375,
-0.4547829329967499,
-0.07528595626354218,
-0.28914397954940796,
0.14150762557983398,
0.107052743434906,
-0.2766270637512207,
0.057172488421201706,
0.28942739963531494,
-0.34862011671066284,
-0.408365935087204,
0.43975356221199036,
0.14451634883880615,
0.02715018391609192,
-0.15341520309448242,
0.36439910531044006,
-0.1512814313173294,
0.0181087926030159,
-0.08264751732349396,
0.383638471364975,
0.3436254858970642,
0.5497421622276306,
-0.47595930099487305,
-0.05491851642727852,
0.05561330169439316,
-0.15051956474781036,
-0.07915543764829636,
0.11907316744327545,
0.4115956425666809,
0.23406927287578583,
0.18227368593215942,
0.13737617433071136,
-0.23148688673973083,
-0.03167343512177467,
0.18226854503154755,
-0.10571850836277008,
-0.08261997997760773,
0.1635473072528839,
0.002595210447907448,
-0.1768183410167694,
-0.24999567866325378,
-0.02985338866710663,
-0.678904116153717,
0.08470211923122406,
-0.017861846834421158,
0.19374920427799225,
-0.09923888742923737,
-0.31724512577056885,
0.028229273855686188,
-0.19291368126869202,
0.453159362077713,
0.33714932203292847,
0.3244171142578125,
-0.3690621852874756,
-0.31667032837867737,
-0.3890501856803894,
0.1598982959985733,
-0.3162230849266052,
-0.3201473355293274,
-0.09974776208400726,
0.23386363685131073,
-0.15514898300170898,
0.3409181237220764,
-0.23970501124858856,
-0.0007637313101440668,
0.07648145407438278,
0.029246600344777107,
-0.2659042179584503,
-0.16083340346813202,
0.0497715026140213,
-0.11939367651939392,
-0.3061857521533966,
-0.12973952293395996,
-0.004993867129087448,
-0.2757503390312195,
0.06248512119054794,
-0.026224423199892044,
-0.25990456342697144,
0.2788187861442566,
0.053317029029130936,
0.2739656865596771,
0.07670781761407852,
0.626677393913269,
-0.10283482819795609,
-0.06840270757675171,
-0.0048550330102443695,
-0.06971421837806702,
-0.06355053931474686,
0.3697381615638733,
0.03681907430291176,
0.5085330009460449,
-0.08119191974401474,
0.17832893133163452,
-0.3596469461917877,
0.49303311109542847,
-0.26348695158958435,
0.14966356754302979,
-0.1138262078166008,
-0.1301417201757431,
-0.2357620894908905,
0.315569132566452,
-0.03986366465687752,
0.08727344125509262,
-0.11603307723999023,
0.07417353987693787,
-0.4722554087638855,
-0.21190263330936432,
0.31642910838127136,
-0.7915248274803162,
-0.3263425827026367,
0.11869138479232788,
0.09361734986305237,
-0.08433306962251663,
0.023439951241016388,
-0.5125057101249695,
-0.06366849690675735,
0.2648855447769165,
-0.07161727547645569,
-0.10451541841030121,
0.03642389550805092,
-0.11945199966430664,
-0.058210816234350204,
-0.11786192655563354,
-0.22919020056724548,
-0.12916311621665955,
-0.22626130282878876,
-0.18604321777820587,
-0.30095940828323364
] |
https://github.com/huggingface/datasets/issues/186 | Weird-ish: Not creating unique caches for different phases | Looks like a duplicate of #120.
This is already fixed on master. We'll do a new release on pypi soon | Sample code:
```python
import nlp
dataset = nlp.load_dataset('boolq')
def func1(x):
return x
def func2(x):
return None
train_output = dataset["train"].map(func1)
valid_output = dataset["validation"].map(func1)
print()
print(len(train_output), len(valid_output))
# Output: 9427 9427
```
The map method in both cases seem to be pointing to the same cache, so the latter call based on the validation data will return the processed train data cache.
What's weird is that the following doesn't seem to be an issue:
```python
train_output = dataset["train"].map(func2)
valid_output = dataset["validation"].map(func2)
print()
print(len(train_output), len(valid_output))
# 9427 3270
``` | 20 | Weird-ish: Not creating unique caches for different phases
Sample code:
```python
import nlp
dataset = nlp.load_dataset('boolq')
def func1(x):
return x
def func2(x):
return None
train_output = dataset["train"].map(func1)
valid_output = dataset["validation"].map(func1)
print()
print(len(train_output), len(valid_output))
# Output: 9427 9427
```
The map method in both cases seem to be pointing to the same cache, so the latter call based on the validation data will return the processed train data cache.
What's weird is that the following doesn't seem to be an issue:
```python
train_output = dataset["train"].map(func2)
valid_output = dataset["validation"].map(func2)
print()
print(len(train_output), len(valid_output))
# 9427 3270
```
Looks like a duplicate of #120.
This is already fixed on master. We'll do a new release on pypi soon | [
0.3151267468929291,
-0.1353006213903427,
-0.005951644852757454,
0.20902259647846222,
0.09835072606801987,
-0.18703681230545044,
0.2608935534954071,
0.3269939124584198,
-0.1120341569185257,
-0.1279546171426773,
-0.10739805549383163,
0.4277702271938324,
0.081903837621212,
-0.20389296114444733,
0.09390927851200104,
0.06840936839580536,
0.16564157605171204,
0.11475609987974167,
-0.11452038586139679,
-0.04316331818699837,
-0.17623743414878845,
0.10245218127965927,
-0.08972574025392532,
-0.11245466768741608,
-0.4616798460483551,
0.14604823291301727,
-0.2929147779941559,
-0.15815600752830505,
0.21726326644420624,
-0.39209818840026855,
0.3604980707168579,
0.07840589433908463,
-0.25562795996665955,
0.2644164264202118,
-0.00011643479956546798,
-0.03943786397576332,
0.1898857206106186,
-0.06046994775533676,
-0.09947286546230316,
0.1508258432149887,
0.02018778771162033,
-0.14972227811813354,
0.16033540666103363,
-0.3118852376937866,
-0.01663912460207939,
0.11477603018283844,
0.05911436304450035,
0.13279888033866882,
0.5603553056716919,
0.0672883465886116,
0.19152891635894775,
0.2768821120262146,
-0.3045634329319,
0.1994514763355255,
0.15829500555992126,
-0.0923035740852356,
-0.19662734866142273,
-0.07651291787624359,
0.018527425825595856,
-0.2760593891143799,
-0.03462202101945877,
0.3285541534423828,
-0.0990368127822876,
0.09711770713329315,
-0.01888156682252884,
0.09337882697582245,
0.16540852189064026,
-0.19152851402759552,
0.08571898192167282,
0.06397505104541779,
-0.12460622936487198,
-0.3299974203109741,
-0.2282962203025818,
-0.36594727635383606,
-0.22737908363342285,
-0.3725855350494385,
0.13380682468414307,
0.1214892566204071,
-0.151002898812294,
-0.11508496105670929,
-0.28873348236083984,
0.2583758533000946,
0.18000319600105286,
0.06546595692634583,
0.14850790798664093,
0.34907928109169006,
0.17052243649959564,
0.003995656967163086,
0.2054346650838852,
0.1646483838558197,
-0.022904343903064728,
-0.167671337723732,
0.039331141859292984,
0.38251471519470215,
-0.32864588499069214,
-0.1350691169500351,
0.25804200768470764,
-0.037615031003952026,
-0.02088424563407898,
-0.035171620547771454,
0.2935587465763092,
-0.05806347727775574,
0.030032485723495483,
0.03780946135520935,
0.14594821631908417,
0.44085782766342163,
-0.05845873802900314,
0.26226210594177246,
0.03631453216075897,
-0.1119014173746109,
-0.47820383310317993,
0.07153686881065369,
0.3043478727340698,
0.08766844123601913,
0.30457645654678345,
0.055590637028217316,
-0.07608941942453384,
-0.09867473691701889,
0.04273633658885956,
0.09191568940877914,
-0.3604728877544403,
-0.16655229032039642,
0.04151648283004761,
0.12388285994529724,
0.010513169690966606,
0.18547239899635315,
-0.2612515091896057,
0.041237086057662964,
-0.5030217170715332,
0.16908606886863708,
-0.31585007905960083,
0.011568843387067318,
-0.47468942403793335,
0.30212485790252686,
0.2482239156961441,
-0.20883436501026154,
0.27461838722229004,
0.3141807019710541,
-0.2436191588640213,
-0.2717688977718353,
0.29848527908325195,
-0.20965208113193512,
0.355764776468277,
0.09198476374149323,
-0.11236394941806793,
0.2093500941991806,
-0.05222238227725029,
0.1795106679201126,
-0.20357465744018555,
0.10834099352359772,
-0.10235651582479477,
-0.1805284470319748,
0.34438660740852356,
0.16676528751850128,
-0.2625376582145691,
0.15600115060806274,
0.325206995010376,
0.21365125477313995,
0.7869170308113098,
-0.38525667786598206,
0.1696178913116455,
-0.07720290124416351,
-0.2634733319282532,
-0.3530149459838867,
-0.03340950608253479,
0.2723201513290405,
0.12401340901851654,
-0.3135712146759033,
0.16955462098121643,
0.23233549296855927,
0.0021243467926979065,
0.5360867381095886,
-0.16725273430347443,
0.15477803349494934,
-0.32080078125,
0.03022192418575287,
0.4241330027580261,
-0.29382696747779846,
-0.46321871876716614,
0.1235976591706276,
-0.010485541075468063,
0.175144225358963,
0.11865317821502686,
0.19418875873088837,
0.11643929779529572,
-0.28288182616233826,
0.20412296056747437,
0.04053041338920593,
-0.10490642488002777,
0.09167332202196121,
-0.37813282012939453,
0.01463225670158863,
0.3601006269454956,
-0.24554426968097687,
0.000285957008600235,
0.06188816577196121,
-0.17130637168884277,
-0.0000895848497748375,
0.2635815441608429,
0.0021530501544475555,
0.13179726898670197,
0.021445900201797485,
-0.0550762377679348,
-0.1804734319448471,
0.07052115350961685,
-0.18271583318710327,
0.010329119861125946,
0.2068817913532257,
-0.29167336225509644,
-0.03090876340866089,
0.24033492803573608,
-0.11940084397792816,
0.10904709249734879,
-0.27650582790374756,
-0.26970374584198,
-0.49192121624946594,
0.17864221334457397,
0.05129951611161232,
0.48496031761169434,
-0.008755091577768326,
-0.08701664954423904,
0.2997877597808838,
0.39124879240989685,
-0.11880902945995331,
-0.3205811679363251,
0.11166104674339294,
-0.0021976064890623093,
-0.16492031514644623,
-0.35923901200294495,
0.5168806910514832,
0.21017169952392578,
-0.008701598271727562,
-0.1274029016494751,
-0.04566941410303116,
0.005072888918220997,
0.08217810839414597,
-0.25943881273269653,
0.08567062765359879,
0.10755650699138641,
0.14894163608551025,
0.032679490745067596,
0.1141880452632904,
-0.03314945101737976,
-0.2737235128879547,
0.1267448216676712,
0.48298293352127075,
0.3349759876728058,
0.10381120443344116,
-0.0001738220453262329,
-0.08665530383586884,
-0.06366563588380814,
-0.15970763564109802,
-0.22713595628738403,
-0.34744158387184143,
0.25259459018707275,
-0.03174920007586479,
0.4256989657878876,
0.2751820981502533,
-0.04971015825867653,
0.2771766781806946,
0.5075843930244446,
0.18606296181678772,
-0.022791534662246704,
-0.09178218990564346,
-0.01519213616847992,
-0.26299023628234863,
-0.09401455521583557,
0.21855495870113373,
0.5466564893722534,
0.0993313267827034,
0.14615941047668457,
0.18917642533779144,
-0.3211837410926819,
-0.20500105619430542,
-0.029941104352474213,
-0.12286625802516937,
0.06329655647277832,
-0.042650334537029266,
0.37207135558128357,
-0.08435273915529251,
-0.2066480815410614,
0.34665051102638245,
0.1877124160528183,
-0.1285448521375656,
0.037768322974443436,
0.2113196849822998,
-0.23826144635677338,
-0.4322883188724518,
-0.3985510468482971,
-0.20139983296394348,
-0.12059199810028076,
-0.30527982115745544,
0.1275995969772339,
0.30709323287010193,
0.09445148706436157,
0.28941023349761963,
-0.20783571898937225,
0.08653531968593597,
-0.17033296823501587,
-0.15077237784862518,
0.0021730661392211914,
-0.34527069330215454,
-0.31340864300727844,
0.0322800874710083,
-0.016492675989866257,
-0.2743602395057678,
0.2854227125644684,
0.018409589305520058,
-0.1734153777360916,
-0.1414489448070526,
-0.39166513085365295,
0.20791564881801605,
-0.008682787418365479,
-0.20053015649318695,
-0.19862213730812073,
-0.36847949028015137,
0.09001211822032928,
0.012220765464007854,
0.3374744951725006,
-0.3655262291431427,
-0.24376414716243744,
0.055022671818733215,
-0.08614634722471237,
0.10925304889678955,
-0.27967268228530884,
-0.10740382224321365,
-0.1448773294687271,
-0.04877806454896927,
0.20083214342594147,
-0.28256672620773315,
0.25015515089035034,
0.3470872640609741,
-0.2549815773963928,
-0.09772158414125443,
-0.1596534103155136,
-0.16263175010681152,
-0.4625169634819031,
-0.036857955157756805,
0.21641843020915985,
-0.31619617342948914,
-0.189056396484375,
-0.38392314314842224,
-0.3472077250480652,
0.26691100001335144,
0.17019525170326233,
-0.43564140796661377,
-0.433349609375,
-0.061189547181129456,
0.073504239320755,
0.17087775468826294,
0.04932292923331261,
0.38772496581077576,
-0.17816810309886932,
-0.01823333650827408,
-0.1533551812171936,
-0.3007078170776367,
0.20788156986236572,
0.39638322591781616,
0.35678884387016296,
-0.17569974064826965,
0.22636640071868896,
0.13107015192508698,
0.5557451844215393,
0.631463348865509,
0.06918303668498993,
0.3732171654701233,
-0.013673929497599602,
0.21526825428009033,
-0.26185548305511475,
-0.1999867707490921,
0.1839580535888672,
-0.1526450514793396,
-0.2572273910045624,
0.1832875907421112,
0.17619872093200684,
-0.5797118544578552,
-0.06663401424884796,
0.16522251069545746,
-0.27863410115242004,
-0.3541930317878723,
0.09116494655609131,
-0.3137050271034241,
0.22862017154693604,
0.31083017587661743,
0.23395311832427979,
-0.41848793625831604,
-0.11604499816894531,
-0.1248803436756134,
-0.3066101670265198,
0.14552704989910126,
0.09425295889377594,
-0.09625327587127686,
-0.24743661284446716,
-0.4561161994934082,
0.20617571473121643,
0.24228781461715698,
0.1278308480978012,
0.02266521379351616,
-0.23083919286727905,
0.0699959322810173,
0.01940467767417431,
0.4736870527267456,
-0.03395918756723404,
-0.003952924162149429,
0.1012185662984848,
-0.0711037889122963,
-0.40342977643013,
-0.2792932689189911,
0.23190394043922424,
0.4614938795566559,
0.4238910377025604,
0.2808866500854492,
-0.21179400384426117,
-0.10709019005298615,
-0.0721648633480072,
0.13284051418304443,
-0.23876851797103882,
-0.39052367210388184,
-0.23795627057552338,
-0.06291764229536057,
0.06605026870965958,
0.07129471004009247,
-0.12635430693626404,
-0.18954648077487946,
-0.19810256361961365,
-0.0718088448047638,
0.19534069299697876,
-0.03914891555905342,
0.03154459595680237,
0.24644117057323456,
0.2672863006591797,
-0.1262178122997284,
0.17920629680156708,
0.17825369536876678,
-0.10764861106872559,
-0.4886571168899536,
0.4111676514148712,
-0.18163657188415527,
0.3603590130805969,
0.18541860580444336,
-0.05674787610769272,
-0.020053081214427948,
0.4066050350666046,
0.19946922361850739,
0.14544135332107544,
-0.07756063342094421,
-0.07732506096363068,
-0.026072043925523758,
-0.22639605402946472,
0.32063502073287964,
0.0029674163088202477,
-0.2382083386182785,
-0.455353319644928,
0.23632293939590454,
0.15792149305343628,
-0.14968989789485931,
0.228380486369133,
-0.6113734245300293,
-0.11635462939739227,
0.3909173011779785,
-0.19715052843093872,
0.7841208577156067,
0.02420204132795334,
0.47903695702552795,
0.22325578331947327,
-0.05244646593928337,
0.38019251823425293,
-0.046632565557956696,
0.36362510919570923,
-0.3955558240413666,
0.18653632700443268,
0.12171317636966705,
-0.17433662712574005,
-0.33306577801704407,
0.02130279317498207,
0.06636716425418854,
0.4315521717071533,
0.2073076218366623,
0.48412686586380005,
0.020280152559280396,
-0.21137654781341553,
0.20552682876586914,
0.020140070468187332,
-0.32142817974090576,
0.17260445654392242,
0.051495250314474106,
0.24724841117858887,
-0.06316383928060532,
-0.22587215900421143,
-0.07192140817642212,
-0.1654232293367386,
-0.031881194561719894,
0.2956010401248932,
-0.13948577642440796,
0.4080139994621277,
0.3562556803226471,
-0.2011677324771881,
-0.6638270616531372,
0.09609924256801605,
0.13754159212112427,
-0.39595749974250793,
-0.01546795479953289,
-0.11183474957942963,
0.47419649362564087,
0.4154973030090332,
-0.05152217671275139,
-0.2530066967010498,
0.36641138792037964,
-0.07084521651268005,
-0.04830094426870346,
-0.0550028532743454,
-0.00859941728413105,
-0.4087691903114319,
-0.2352360486984253,
0.31752216815948486,
-0.3334673047065735,
0.05075538158416748,
0.13472510874271393,
0.183037668466568,
-0.07473671436309814,
-0.11483460664749146,
0.11003774404525757,
0.07397682964801788,
-0.12934610247612,
0.35186007618904114,
-0.3545050323009491,
-0.10786082595586777,
0.03488881140947342,
0.2857210636138916,
0.28677165508270264,
0.08036516606807709,
0.36261308193206787,
-0.2709963619709015,
0.06172808259725571,
-0.03672278672456741,
-0.3326627016067505,
-0.31491518020629883,
-0.3201562762260437,
0.10790367424488068,
-0.2535044252872467,
-0.18748363852500916,
0.1025049015879631,
0.0071214064955711365,
0.12069103866815567,
0.37156054377555847,
-0.08053518831729889,
-0.1893053650856018,
-0.5517704486846924,
-0.053989216685295105,
-0.10335403680801392,
0.1609768122434616,
-0.017603058367967606,
0.6225500106811523,
0.07026728987693787,
0.393542617559433,
-0.2894585132598877,
-0.020572105422616005,
-0.015657247975468636,
0.22764621675014496,
-0.1329174041748047,
-0.40480247139930725,
-0.054158762097358704,
0.14537955820560455,
0.04365754872560501,
0.33607935905456543,
-0.48687177896499634,
-0.2018183469772339,
-0.16914990544319153,
0.1019672229886055,
0.1467081606388092,
0.1432410031557083,
-0.25145378708839417,
0.1305127888917923,
0.3261987268924713,
-0.34623968601226807,
0.1161704808473587,
0.16987422108650208,
0.022485069930553436,
0.19154703617095947,
0.16412422060966492,
0.06718472391366959,
0.14418566226959229,
0.11707310378551483,
-0.14140509068965912,
-0.05994516611099243,
0.16280727088451385,
0.18861621618270874,
-0.13985148072242737,
0.15012964606285095,
-0.1367889642715454,
-0.16258308291435242,
-0.11337688565254211,
-0.07932806015014648,
-0.100755475461483,
-0.2714381814002991,
-0.12925609946250916,
0.07303940504789352,
0.2117285579442978,
0.22056759893894196,
-0.08022291213274002,
-0.1748630702495575,
-0.10348450392484665,
0.16781757771968842,
0.06923595070838928,
0.10698181390762329,
0.3573373556137085,
0.20533929765224457,
0.07064777612686157,
0.3598752021789551,
0.41936129331588745,
-0.00026047229766845703,
0.4682632088661194,
0.034650932997465134,
-0.08014567941427231,
-0.4715932011604309,
0.26750680804252625,
0.010570377111434937,
0.19505776464939117,
0.08407611399888992,
0.34856468439102173,
-0.2840741276741028,
-0.07184205204248428,
0.06369417160749435,
0.2873607277870178,
0.16066107153892517,
-0.029453180730342865,
-0.07150281965732574,
0.08202341943979263,
0.019564740359783173,
-0.2752048671245575,
0.02920675277709961,
-0.09377898275852203,
0.2505137324333191,
0.04363768547773361,
0.3715869188308716,
-0.15463951230049133,
-0.18234413862228394,
-0.42075103521347046,
0.31654927134513855,
-0.2892088294029236,
-0.28602924942970276,
0.2699078917503357,
-0.3006247580051422,
0.2749161124229431,
0.14489153027534485,
-0.04462624713778496,
0.1926157921552658,
0.7117822170257568,
0.060089126229286194,
-0.027329452335834503,
-0.15319854021072388,
-0.31560954451560974,
0.2999636232852936,
0.3962077498435974,
-0.10624181479215622,
0.34747663140296936,
0.06683951616287231,
-0.34605440497398376,
-0.15965640544891357,
0.1851087510585785,
0.3952050507068634,
0.2746729254722595,
-0.28492045402526855,
0.16531166434288025,
0.31191620230674744,
0.0437198132276535,
-0.14279255270957947,
0.28440606594085693,
0.46444469690322876,
-0.275371253490448,
0.10013259947299957,
0.07736312597990036,
-0.16198547184467316,
0.33745381236076355,
0.09224112331867218,
0.262637734413147,
-0.2047155797481537,
0.5761634707450867,
-0.055060602724552155,
-0.07937566936016083,
0.008969021961092949,
0.20302975177764893,
-0.5066409111022949,
-0.1221209466457367,
0.06195889785885811,
0.057623136788606644,
0.1631636917591095,
-0.22196754813194275,
0.09016378223896027,
0.10871443152427673,
0.3901248276233673,
0.1252451092004776,
0.13043203949928284,
-0.2856214940547943,
-0.016744092106819153,
-0.5698694586753845,
0.33293038606643677,
-0.38900381326675415,
0.24580830335617065,
-0.18367385864257812,
0.27481552958488464,
-0.26683565974235535,
0.0394250825047493,
0.14697884023189545,
-0.2107890099287033,
0.18485155701637268,
0.10188579559326172,
-0.45321252942085266,
0.025243131443858147,
0.07228796184062958,
-0.19550500810146332,
0.2549091577529907,
-0.23168110847473145,
0.021740082651376724,
-0.019082754850387573,
0.13105076551437378,
0.003731008619070053,
-0.003355499356985092,
0.2672176957130432,
0.5061380863189697,
0.2889290750026703,
0.4251261055469513,
0.20019441843032837,
0.040501877665519714,
-0.18851475417613983,
-0.3905116319656372,
0.03260090947151184,
-0.03158155456185341,
-0.24561229348182678,
-0.06935802102088928,
0.3341864347457886,
-0.31259843707084656,
-0.1130521297454834,
-0.28429922461509705,
0.22645722329616547,
0.08093833923339844,
-0.39334407448768616,
0.1780988872051239,
-0.03644590079784393,
-0.12942680716514587,
0.06052616238594055,
0.030793573707342148,
0.7254053354263306,
0.016145382076501846,
0.4419616758823395,
-0.18536314368247986,
-0.2571273148059845,
0.381931334733963,
-0.6724093556404114,
-0.2614430785179138,
0.003796197474002838,
0.3030821681022644,
0.09342258423566818,
-0.17738240957260132,
-0.530910849571228,
-0.12437977641820908,
0.17773990333080292,
-0.16756942868232727,
-0.12121240794658661,
0.18059678375720978,
-0.19370520114898682,
-0.035032834857702255,
-0.010602939873933792,
0.16422662138938904,
0.0944303572177887,
-0.26849400997161865,
0.27279290556907654,
-0.2511070966720581
] |
https://github.com/huggingface/datasets/issues/183 | [Bug] labels of glue/ax are all -1 | This is the test set given by the Glue benchmark. The labels are not provided, and therefore set to -1. | ```
ax = nlp.load_dataset('glue', 'ax')
for i in range(30): print(ax['test'][i]['label'], end=', ')
```
```
-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
``` | 20 | [Bug] labels of glue/ax are all -1
```
ax = nlp.load_dataset('glue', 'ax')
for i in range(30): print(ax['test'][i]['label'], end=', ')
```
```
-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
```
This is the test set given by the Glue benchmark. The labels are not provided, and therefore set to -1. | [
0.2502775192260742,
-0.3640769124031067,
-0.061697736382484436,
0.13931091129779816,
-0.06844886392354965,
-0.07843451201915741,
0.34460073709487915,
0.2630481719970703,
0.37012946605682373,
0.19107209146022797,
-0.27151840925216675,
0.684173583984375,
-0.06559266149997711,
0.11889613419771194,
0.1820763349533081,
-0.112140953540802,
-0.10166793316602707,
0.3471294045448303,
-0.15045125782489777,
-0.12176007032394409,
-0.26120519638061523,
0.37858524918556213,
-0.25765156745910645,
0.14147379994392395,
-0.179623082280159,
-0.10173977166414261,
-0.15014256536960602,
0.07673320919275284,
-0.0330740362405777,
-0.40146899223327637,
0.10599252581596375,
0.14746442437171936,
-0.10761848837137222,
-0.12033400684595108,
-0.0001057189583661966,
-0.28695642948150635,
0.2894555628299713,
0.0716744065284729,
0.0324568934738636,
0.12928733229637146,
-0.14674878120422363,
-0.29723060131073,
-0.03970751166343689,
-0.38646867871284485,
-0.05714061111211777,
-0.0009069684892892838,
0.045928142964839935,
-0.1283685564994812,
0.16652294993400574,
0.16479021310806274,
0.24084722995758057,
0.1582946479320526,
0.08807916939258575,
0.13617266714572906,
0.4565761387348175,
-0.47681695222854614,
0.04431554675102234,
0.2460300773382187,
0.09880662709474564,
-0.34286826848983765,
-0.016030214726924896,
0.45544931292533875,
0.12964686751365662,
0.12535879015922546,
0.03968103229999542,
0.14423763751983643,
0.03318917006254196,
-0.35992300510406494,
-0.08387000858783722,
0.42646485567092896,
0.1315077543258667,
-0.35245177149772644,
-0.31000691652297974,
-0.20165613293647766,
0.21391212940216064,
-0.31251105666160583,
-0.06473945826292038,
0.14203594624996185,
-0.016297195106744766,
0.009707011282444,
0.03766291216015816,
0.10280214250087738,
-0.12196803838014603,
0.13918480277061462,
0.1389048546552658,
0.58426833152771,
-0.020311597734689713,
0.06995426118373871,
0.369263619184494,
-0.029156841337680817,
-0.1850247085094452,
0.09218508005142212,
-0.020080607384443283,
0.17599333822727203,
-0.28078657388687134,
-0.1972288191318512,
0.10954360663890839,
0.10077453404664993,
0.021074973046779633,
0.04459695890545845,
0.2250237762928009,
0.03807013854384422,
0.20733889937400818,
0.164203479886055,
0.0804491639137268,
0.28569498658180237,
0.3848165273666382,
0.2837710678577423,
0.028996579349040985,
0.06244755908846855,
-0.12825216352939606,
0.208902508020401,
-0.014154279604554176,
-0.10459042340517044,
0.2733452618122101,
-0.09539482742547989,
-0.07485391199588776,
-0.12386596202850342,
-0.31944164633750916,
-0.025793492794036865,
-0.2851245403289795,
0.002068644855171442,
-0.179657980799675,
0.24445262551307678,
0.02786293253302574,
0.015347061678767204,
-0.034648630768060684,
0.09597478061914444,
-0.15768174827098846,
-0.1615324318408966,
-0.29697129130363464,
0.37302109599113464,
-0.2329164296388626,
-0.25091123580932617,
0.14201562106609344,
0.2079273760318756,
0.28334131836891174,
0.02848684787750244,
-0.13069741427898407,
0.03727928549051285,
0.14972732961177826,
-0.020442385226488113,
0.2775792181491852,
0.1166960820555687,
-0.06863987445831299,
0.10494784265756607,
-0.010465957224369049,
-0.3798036575317383,
-0.27660971879959106,
-0.0801539346575737,
0.09214653819799423,
0.07429817318916321,
0.023173747584223747,
0.2386457622051239,
-0.17580591142177582,
0.027032241225242615,
0.18054483830928802,
0.09859307110309601,
-0.09635759145021439,
0.2063305526971817,
0.14499212801456451,
-0.14029499888420105,
-0.11530124396085739,
-0.189780130982399,
0.29160141944885254,
0.20183679461479187,
-0.30105796456336975,
-0.11395061016082764,
0.08180488646030426,
-0.035246532410383224,
-0.12665051221847534,
0.05246239900588989,
0.22159940004348755,
0.005408667027950287,
-0.26821568608283997,
0.22214002907276154,
0.2920093238353729,
-0.5699788331985474,
-0.4601467549800873,
0.026117650792002678,
-0.09821595996618271,
-0.11541444063186646,
0.08403828740119934,
0.07993172854185104,
-0.02733754739165306,
0.20734506845474243,
0.3057432174682617,
0.2759208679199219,
0.1464020311832428,
-0.01405496895313263,
-0.33543702960014343,
0.14553837478160858,
0.3818058371543884,
0.14466899633407593,
-0.172483429312706,
-0.1629219949245453,
-0.20003029704093933,
-0.16491568088531494,
0.26382991671562195,
0.11475236713886261,
-0.08811499178409576,
0.26813000440597534,
0.012011706829071045,
-0.35355842113494873,
0.12525106966495514,
-0.14601200819015503,
-0.23448625206947327,
0.24857288599014282,
-0.23344555497169495,
0.39037951827049255,
0.2793833911418915,
-0.13543885946273804,
-0.39104709029197693,
-0.009539967402815819,
-0.021591123193502426,
-0.22261112928390503,
0.27640199661254883,
0.022156011313199997,
0.3353922665119171,
0.06124608591198921,
-0.09688166528940201,
0.3609965443611145,
0.09802190959453583,
0.04160770773887634,
-0.36970967054367065,
0.09687409549951553,
-0.059088364243507385,
-0.0400339812040329,
0.2472638189792633,
0.5104691386222839,
0.2441360056400299,
-0.053404368460178375,
0.13028821349143982,
0.3582194745540619,
-0.023660508915781975,
0.012895934283733368,
0.08358973264694214,
-0.017382413148880005,
-0.042964912950992584,
-0.29577168822288513,
0.09626911580562592,
0.167236328125,
0.08046390861272812,
-0.04020093381404877,
-0.15581396222114563,
0.3673761188983917,
0.09383880347013474,
0.051863525062799454,
0.11298194527626038,
0.09805752336978912,
-0.09670708328485489,
-0.29650333523750305,
-0.3145450949668884,
-0.13945330679416656,
0.33484065532684326,
-0.22544245421886444,
0.35534876585006714,
0.0405212827026844,
-0.2502377927303314,
0.20897047221660614,
0.4467064142227173,
0.02467864751815796,
0.20379221439361572,
-0.11887644976377487,
-0.28534436225891113,
-0.10063870996236801,
0.05481969565153122,
0.521816074848175,
0.16740722954273224,
0.4208611845970154,
0.017650090157985687,
-0.059704579412937164,
-0.39394035935401917,
-0.073459692299366,
0.1677398681640625,
-0.08496889472007751,
0.07969314604997635,
-0.08924082666635513,
0.20133481919765472,
-0.14826007187366486,
-0.18963688611984253,
0.055628422647714615,
-0.24803262948989868,
0.23431752622127533,
-0.262809693813324,
-0.1954481601715088,
-0.08484265208244324,
-0.49717023968696594,
-0.2795579731464386,
-0.2954830527305603,
-0.14680330455303192,
-0.5272935032844543,
0.1358085572719574,
-0.2413761019706726,
-0.020685074850916862,
0.2252945899963379,
0.05436110123991966,
0.16111983358860016,
-0.1830400824546814,
0.07843844592571259,
-0.20593924820423126,
-0.13555596768856049,
-0.21072593331336975,
0.1599218249320984,
-0.2740514576435089,
0.5203291773796082,
0.3989133834838867,
-0.09670913964509964,
0.07538843154907227,
0.319004088640213,
-0.21436789631843567,
-0.0005631670355796814,
-0.1737833470106125,
0.24654264748096466,
0.41369199752807617,
0.001874573528766632,
-0.1277114450931549,
-0.012992790900170803,
0.24294744431972504,
-0.4388088583946228,
-0.005683007650077343,
-0.06721718609333038,
0.20725557208061218,
-0.03914029896259308,
-0.14822210371494293,
-0.4048267602920532,
-0.3648366630077362,
-0.22121040523052216,
0.23954297602176666,
0.2358979433774948,
0.2596205472946167,
0.11519569158554077,
-0.33117005228996277,
0.32700514793395996,
-0.16804878413677216,
-0.03360198438167572,
-0.15168629586696625,
-0.05473499745130539,
0.24902060627937317,
-0.10521747171878815,
-0.29829567670822144,
-0.24963794648647308,
-0.1970977634191513,
0.22305834293365479,
-0.29266560077667236,
-0.21160583198070526,
-0.17701636254787445,
-0.07415030896663666,
-0.140194371342659,
0.027845121920108795,
0.22281573712825775,
0.11768673360347748,
0.032634586095809937,
-0.15178067982196808,
-0.14525485038757324,
-0.24856722354888916,
0.33657920360565186,
0.05205577611923218,
-0.14087173342704773,
0.03853772208094597,
0.035232655704021454,
0.0140007846057415,
0.17996056377887726,
0.11784464120864868,
-0.12312307953834534,
0.19788864254951477,
-0.27885881066322327,
0.2952500879764557,
0.23055246472358704,
-0.2540300190448761,
0.010372409597039223,
0.31672489643096924,
0.2669713497161865,
0.13920292258262634,
0.11716970056295395,
-0.32901597023010254,
-0.0998944491147995,
0.11832112073898315,
-0.2628355324268341,
-0.05908047407865524,
0.03934847563505173,
-0.1033320426940918,
-0.21532243490219116,
0.020679865032434464,
-0.03607349470257759,
-0.10807126760482788,
-0.1725042164325714,
-0.042756009846925735,
-0.39986807107925415,
-0.08388235419988632,
-0.0383346863090992,
-0.6121565103530884,
-0.12144096195697784,
-0.519475519657135,
0.15431669354438782,
0.04839468374848366,
0.47348707914352417,
-0.010718386620283127,
-0.09485802054405212,
-0.0313771516084671,
0.030421389266848564,
0.5715874433517456,
-0.41469699144363403,
0.2131909281015396,
0.4603511393070221,
0.18213927745819092,
-0.6949966549873352,
0.0056409090757369995,
-0.5489997267723083,
-0.1169113740324974,
0.628441572189331,
0.26226311922073364,
-0.2489963173866272,
-0.15028288960456848,
0.27377182245254517,
0.01633814349770546,
-0.09192781150341034,
-0.1665167510509491,
-0.29358014464378357,
-0.2230232059955597,
-0.03679610416293144,
0.14788085222244263,
-0.009105484001338482,
0.2636672258377075,
0.1972573697566986,
-0.07814471423625946,
0.05830570310354233,
-0.2125874161720276,
0.14469707012176514,
0.22399543225765228,
0.29998311400413513,
0.0681437999010086,
-0.03851299360394478,
0.11713027954101562,
0.21222658455371857,
-0.6786831021308899,
0.12109183520078659,
-0.520142138004303,
0.3546111583709717,
-0.21757519245147705,
-0.2540557086467743,
0.46517059206962585,
0.16192726790905,
0.04661724343895912,
-0.1614825427532196,
-0.5788977146148682,
0.21016110479831696,
-0.04784177243709564,
0.020870104432106018,
0.20848537981510162,
0.16397525370121002,
-0.23401446640491486,
-0.07566914707422256,
0.5497063994407654,
0.06847737729549408,
-0.22469213604927063,
0.33281785249710083,
0.19439521431922913,
-0.3568422496318817,
0.41191208362579346,
-0.08889146894216537,
0.9092602133750916,
-0.0902237594127655,
-0.007592473179101944,
0.25458449125289917,
-0.36367470026016235,
0.6806232929229736,
0.14083079993724823,
0.12344540655612946,
-0.5268474817276001,
-0.3948061466217041,
0.06874201446771622,
-0.08320694416761398,
-0.1278975009918213,
0.27551499009132385,
-0.22262030839920044,
0.41558215022087097,
0.07301349937915802,
-0.19334717094898224,
0.022332414984703064,
0.3862771689891815,
0.0031906133517622948,
-0.10484971106052399,
-0.34154435992240906,
0.15480966866016388,
-0.03297057002782822,
0.1674894392490387,
-0.061462417244911194,
-0.019678330048918724,
-0.1323699802160263,
-0.21145224571228027,
-0.0483417809009552,
0.19770094752311707,
-0.2182677984237671,
-0.16570232808589935,
0.3732075095176697,
-0.030512623488903046,
-0.4524395167827606,
0.13093191385269165,
0.18288502097129822,
0.12453879415988922,
0.006406888365745544,
0.05262470245361328,
0.1765984296798706,
0.0018503903411328793,
0.5183125734329224,
0.2572227120399475,
0.29605740308761597,
-0.10177106410264969,
-0.057917073369026184,
-0.10081515461206436,
0.08597951382398605,
-0.1053326278924942,
-0.06399112939834595,
0.058669161051511765,
-0.05259709805250168,
-0.14442995190620422,
-0.34001415967941284,
0.06040734052658081,
-0.013500288128852844,
-0.1976650208234787,
0.19822053611278534,
0.09399652481079102,
-0.41108354926109314,
0.27004361152648926,
0.09358696639537811,
-0.3252710700035095,
-0.03686972334980965,
0.3700680732727051,
-0.0598650723695755,
0.4367310106754303,
0.17269816994667053,
0.02936570718884468,
-0.016895389184355736,
-0.28269121050834656,
-0.06539274007081985,
0.3214573860168457,
-0.22965207695960999,
0.0666491910815239,
-0.12342483550310135,
-0.10889684408903122,
-0.02172115258872509,
0.0352230966091156,
0.19642804563045502,
0.17936421930789948,
0.09442651271820068,
-0.46983906626701355,
-0.12708443403244019,
0.16168776154518127,
0.06652915477752686,
0.3171401023864746,
0.0377875417470932,
-0.09414584934711456,
0.2179001122713089,
0.35001426935195923,
-0.4358421862125397,
-0.02367055043578148,
-0.20669178664684296,
-0.07812841981649399,
0.4145662784576416,
-0.023621082305908203,
0.07423576712608337,
0.05426991358399391,
0.31571969389915466,
0.07997889816761017,
-0.09340900182723999,
-0.3097279965877533,
-0.18688155710697174,
0.01974952220916748,
-0.07820963859558105,
-0.011730499565601349,
0.02576456591486931,
-0.12001354992389679,
-0.07672470808029175,
-0.06595675647258759,
-0.09149377048015594,
-0.1465875208377838,
0.007814858108758926,
0.44732120633125305,
0.00041973963379859924,
0.09699159860610962,
0.06402929127216339,
0.11668185889720917,
-0.02109866589307785,
-0.2281688004732132,
0.03219006955623627,
0.1621513068675995,
-0.051699306815862656,
-0.09866438060998917,
-0.15055562555789948,
-0.04716537147760391,
-0.3882819414138794,
-0.06876557320356369,
0.006776086986064911,
-0.1605016142129898,
-0.09582380950450897,
0.07739389687776566,
0.6340235471725464,
0.010784368962049484,
-0.29655274748802185,
-0.19216448068618774,
0.02798072062432766,
0.3456474244594574,
-0.3949342370033264,
-0.12690258026123047,
0.45424744486808777,
0.24674122035503387,
0.26460975408554077,
0.3529655337333679,
0.1391114592552185,
-0.08405223488807678,
-0.1915549784898758,
0.004000389948487282,
0.29133230447769165,
-0.4078513979911804,
-0.16344201564788818,
0.17371073365211487,
-0.14265118539333344,
-0.16981899738311768,
0.32067832350730896,
0.057864993810653687,
0.16803519427776337,
0.0838930606842041,
0.3906581699848175,
0.5761868953704834,
0.1416967213153839,
0.03042634017765522,
-0.057727061212062836,
0.11515700817108154,
-0.07071809470653534,
0.5745166540145874,
-0.027649804949760437,
0.2495676577091217,
0.15678000450134277,
0.5897642374038696,
-0.2613559365272522,
-0.21765758097171783,
-0.04092089459300041,
0.21259534358978271,
-0.03424641489982605,
-0.21949529647827148,
0.13715526461601257,
-0.07145743072032928,
-0.3883407711982727,
-0.004371333867311478,
0.014580883085727692,
-0.23136065900325775,
0.3803726136684418,
-0.04845938831567764,
0.12761947512626648,
-0.2602132260799408,
-0.11909803003072739,
0.024867886677384377,
0.4030858874320984,
-0.39799317717552185,
0.06432206183671951,
-0.25062912702560425,
0.09554294496774673,
-0.017598174512386322,
0.3547402024269104,
0.1716810166835785,
0.01775120571255684,
-0.251244455575943,
-0.08426274359226227,
-0.1949606090784073,
-0.11999738961458206,
-0.20278146862983704,
0.22799235582351685,
0.24091899394989014,
0.018384048715233803,
0.4225250482559204,
0.1816043108701706,
-0.22556337714195251,
0.04913727194070816,
0.16723473370075226,
0.09844847023487091,
-0.007039850112050772,
0.4931473731994629,
-0.10184995830059052,
-0.2557195723056793,
-0.2666807770729065,
-0.051310501992702484,
-0.40269023180007935,
-0.06665518134832382,
-0.11750084161758423,
-0.03085355833172798,
0.1739559769630432,
-0.3835698366165161,
0.14161598682403564,
-0.04973557963967323,
0.44530877470970154,
0.012515820562839508,
0.2989167273044586,
-0.2112409472465515,
-0.21040134131908417,
-0.6262401342391968,
-0.02299164980649948,
-0.09374164044857025,
-0.5266145467758179,
0.21520569920539856,
0.029598353430628777,
-0.06426141411066055,
0.020876767113804817,
0.042776159942150116,
0.5819962620735168,
-0.1631898134946823,
-0.10652980208396912,
-0.42306703329086304,
0.11542114615440369,
-0.18298102915287018,
-0.05020345002412796,
0.14122669398784637,
-0.29087498784065247,
0.011113103479146957,
-0.23848843574523926,
0.19092661142349243,
0.07287663221359253,
0.025542572140693665,
0.06769707798957825,
0.27018457651138306,
0.1387310028076172,
0.04367171972990036,
0.26167649030685425,
-0.14459040760993958,
0.08573254197835922,
-0.1028868705034256,
-0.016846153885126114,
-0.2982347309589386,
0.03944222629070282,
0.10759301483631134,
0.33385246992111206,
0.04120609164237976,
0.021992461755871773,
-0.072879359126091,
0.09334103018045425,
0.1682973951101303,
0.2568713128566742,
0.03382617235183716,
0.19437940418720245,
0.14239341020584106,
-0.041015639901161194,
0.09539620578289032,
0.3407485783100128,
0.00537433847784996,
0.055003829300403595,
-0.012975223362445831,
-0.3489196300506592,
0.4604702591896057,
-0.32872405648231506,
-0.1328895092010498,
0.0940818265080452,
0.3477376103401184,
0.26250338554382324,
-0.24081814289093018,
-0.5395858287811279,
-0.1369069516658783,
0.3368121087551117,
0.042628079652786255,
-0.29551711678504944,
0.3126370310783386,
-0.04802190884947777,
0.12107129395008087,
0.054204311221838,
-0.015983998775482178,
0.2987123727798462,
-0.2579358220100403,
-0.10434575378894806,
-0.25383806228637695
] |
https://github.com/huggingface/datasets/issues/181 | Cannot upload my own dataset | It's my misunderstanding. I cannot just upload a csv. I need to write a dataset loading script too. | I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
``` | 18 | Cannot upload my own dataset
I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
```
It's my misunderstanding. I cannot just upload a csv. I need to write a dataset loading script too. | [
0.13189557194709778,
-0.12678326666355133,
0.05668975040316582,
-0.02853645384311676,
0.11699807643890381,
-0.15414652228355408,
0.39699190855026245,
-0.062105778604745865,
-0.2148279994726181,
0.2518129348754883,
-0.08670718222856522,
0.1588992327451706,
-0.17179957032203674,
0.2942127287387848,
0.3824805021286011,
0.1044841781258583,
0.09072622656822205,
0.31321364641189575,
0.039623599499464035,
-0.1279827356338501,
-0.2627106010913849,
0.05864565074443817,
-0.0162038616836071,
-0.07316631078720093,
-0.0752854198217392,
-0.186767116189003,
-0.13502033054828644,
0.2678755223751068,
-0.22584228217601776,
-0.3100969195365906,
0.4256783425807953,
0.20961831510066986,
0.34658485651016235,
0.5284520983695984,
-0.00012068286014255136,
-0.06405109167098999,
0.17346450686454773,
-0.24845093488693237,
-0.5683867335319519,
-0.3589860796928406,
0.08358649164438248,
-0.13413137197494507,
0.08103309571743011,
-0.286552757024765,
0.22721758484840393,
0.05291748046875,
0.050873033702373505,
0.13236527144908905,
0.5366085171699524,
0.40950727462768555,
0.12447778880596161,
0.06690997630357742,
-0.21695269644260406,
-0.10151143372058868,
0.008197188377380371,
0.16872510313987732,
-0.03125625476241112,
0.29346412420272827,
0.31920769810676575,
-0.4081132709980011,
0.29175901412963867,
-0.24268227815628052,
-0.03904249891638756,
-0.007286045700311661,
0.5370670557022095,
0.05455385893583298,
-0.05379808694124222,
-0.4257262647151947,
0.004693884402513504,
0.15714409947395325,
0.28184232115745544,
0.03364906460046768,
-0.32898184657096863,
-0.1129494309425354,
0.11158498376607895,
-0.5599852204322815,
0.20915251970291138,
0.30534711480140686,
-0.425655335187912,
-0.03852710500359535,
-0.2067476511001587,
0.33666813373565674,
-0.3919665515422821,
0.47593575716018677,
0.11568908393383026,
0.3350135385990143,
-0.037230268120765686,
0.1301805078983307,
0.2861829102039337,
-0.09340396523475647,
-0.009625946171581745,
0.07325896620750427,
0.025191180408000946,
0.29447171092033386,
-0.1664421558380127,
-0.18143440783023834,
-0.030567705631256104,
-0.2799895703792572,
-0.11502810567617416,
0.09093773365020752,
0.4687071442604065,
-0.18926206231117249,
-0.21843667328357697,
0.1630101203918457,
0.11493547260761261,
0.3294888436794281,
-0.02343813329935074,
0.05227089673280716,
0.10152753442525864,
-0.0250001922249794,
0.31006181240081787,
-0.08968452364206314,
-0.2538239657878876,
-0.10262657701969147,
-0.1475948989391327,
-0.023878667503595352,
0.27968502044677734,
0.12876714766025543,
0.012593811377882957,
-0.1362917274236679,
0.055091097950935364,
0.06330811977386475,
-0.16161300241947174,
0.3230098783969879,
-0.08835256844758987,
-0.2684031128883362,
0.0020211413502693176,
0.27830955386161804,
0.16045379638671875,
-0.29687362909317017,
0.1016654521226883,
0.33483922481536865,
-0.10520203411579132,
-0.15593469142913818,
0.38596123456954956,
0.026123058050870895,
0.18523725867271423,
-0.05975525453686714,
0.22655539214611053,
-0.14647191762924194,
0.022025955840945244,
-0.03487211465835571,
-0.16940507292747498,
0.01491536945104599,
0.23729723691940308,
0.3928617835044861,
-0.03909881040453911,
-0.5896609425544739,
-0.11377360671758652,
0.09599334746599197,
-0.4078333377838135,
-0.3410404324531555,
-0.45826658606529236,
0.05670671910047531,
0.047931917011737823,
-0.18805880844593048,
-0.35080015659332275,
-0.13403929769992828,
0.10075756162405014,
-0.2789129614830017,
-0.09075621515512466,
0.01032448373734951,
-0.08747869729995728,
-0.1320457011461258,
0.06136983633041382,
0.04111156612634659,
-0.5356754660606384,
0.26288190484046936,
-0.08810169249773026,
0.5520693063735962,
0.3589295446872711,
0.29697832465171814,
-0.31327173113822937,
0.3023737967014313,
-0.043867308646440506,
0.17262260615825653,
0.5356279015541077,
-0.4726383090019226,
-0.22461479902267456,
0.007903169840574265,
-0.036810435354709625,
-0.1761104315519333,
0.11352550983428955,
0.19710120558738708,
0.12219541519880295,
-0.06313978135585785,
0.09179738909006119,
0.38595670461654663,
0.050373680889606476,
0.018724409863352776,
-0.1974925547838211,
-0.16739946603775024,
0.2501932382583618,
-0.026913408190011978,
-0.168757826089859,
0.11825580894947052,
0.26363605260849,
0.028966180980205536,
0.030211206525564194,
-0.3133379817008972,
0.1195906326174736,
0.21816334128379822,
0.336930513381958,
-0.18201304972171783,
-0.1540909856557846,
0.2823061943054199,
-0.40281227231025696,
0.16599223017692566,
0.1726563572883606,
0.34748575091362,
-0.055268168449401855,
-0.04414612054824829,
-0.4338451027870178,
-0.11113899946212769,
-0.020370300859212875,
-0.02535172551870346,
0.045775607228279114,
0.1155954971909523,
0.02293524518609047,
-0.23246537148952484,
-0.2718803584575653,
0.10688915103673935,
-0.26044517755508423,
0.04938431829214096,
-0.21144266426563263,
-0.039563290774822235,
-0.3254668414592743,
-0.0634855404496193,
0.25599977374076843,
0.11972060054540634,
0.20380091667175293,
-0.012565569020807743,
-0.1673872470855713,
0.10784434527158737,
-0.42461252212524414,
0.2669956088066101,
-0.030855342745780945,
0.11985543370246887,
0.007746268063783646,
-0.006525103002786636,
-0.25970226526260376,
-0.07866546511650085,
0.22222746908664703,
-0.20514318346977234,
-0.38404104113578796,
0.16649064421653748,
-0.00962015613913536,
0.0653088241815567,
0.12813536822795868,
0.00844607688486576,
0.2979525625705719,
-0.18777604401111603,
0.06347161531448364,
0.1433505415916443,
0.3599367141723633,
0.11930444836616516,
0.380616158246994,
-0.02155371569097042,
-0.12040473520755768,
-0.15498527884483337,
0.16857118904590607,
0.010845199227333069,
0.13222718238830566,
0.058391839265823364,
0.06193959712982178,
-0.07862596213817596,
0.32469508051872253,
0.5969869494438171,
0.384693443775177,
0.035543277859687805,
-0.06499974429607391,
-0.008059078827500343,
-0.10091213881969452,
-0.23450496792793274,
-0.025495924055576324,
-0.04307097941637039,
0.042327675968408585,
0.16191382706165314,
0.3972325325012207,
0.22959718108177185,
-0.09001210331916809,
0.027445081621408463,
0.13210558891296387,
0.42635661363601685,
-0.2129417210817337,
0.2630130648612976,
-0.10497573018074036,
-0.41205835342407227,
0.28124183416366577,
-0.24620558321475983,
-0.06726276874542236,
-0.15471282601356506,
-0.1818927675485611,
0.13285918533802032,
0.10234750807285309,
-0.14528951048851013,
0.15610329806804657,
0.3768150210380554,
-0.11184241622686386,
-0.25870564579963684,
-0.23002561926841736,
-0.09443660825490952,
-0.20480453968048096,
0.022891487926244736,
0.28228190541267395,
-0.07962040603160858,
0.3960428535938263,
0.29778948426246643,
0.05912502110004425,
0.0036392370238900185,
-0.30800023674964905,
-0.018483616411685944,
-0.044878169894218445,
0.10120940953493118,
0.09834799915552139,
0.3818156123161316,
0.0118325874209404,
-0.528057873249054,
0.14642761647701263,
0.07743369042873383,
-0.27657240629196167,
0.24847862124443054,
-0.021304728463292122,
-0.35785606503486633,
-0.48331716656684875,
-0.025970757007598877,
-0.23736806213855743,
-0.3723588287830353,
0.23394285142421722,
0.34234634041786194,
0.20104345679283142,
0.6263754963874817,
0.033080752938985825,
0.10552358627319336,
0.36732491850852966,
0.15832485258579254,
0.0377814918756485,
-0.14254775643348694,
0.48901185393333435,
-0.21970714628696442,
-0.41547125577926636,
0.14479434490203857,
-0.15794141590595245,
0.5447531342506409,
-0.07129579782485962,
-0.35194599628448486,
-0.1823221743106842,
0.08118394762277603,
0.14644116163253784,
-0.03778723627328873,
-0.03920012712478638,
0.3170751631259918,
-0.2450891137123108,
0.06349536031484604,
-0.07407765090465546,
-0.3456256091594696,
0.11119922995567322,
0.6317628026008606,
0.26698553562164307,
0.001901073381304741,
0.46685704588890076,
0.0014615021646022797,
0.7395951151847839,
0.07472380995750427,
-0.2926449179649353,
0.4109627306461334,
-0.1004679724574089,
0.25575876235961914,
-0.17619848251342773,
-0.3271777331829071,
0.02762286178767681,
0.18094253540039062,
-0.12938284873962402,
0.1223585233092308,
-0.056772276759147644,
-0.07398992776870728,
-0.4756854772567749,
0.30633044242858887,
-0.2941302955150604,
0.049686674028635025,
0.010089896619319916,
0.10700774192810059,
-0.009691186249256134,
-0.0785011351108551,
-0.2286146879196167,
-0.33661964535713196,
-0.48897460103034973,
-0.18894588947296143,
0.2726052403450012,
-0.21989968419075012,
0.17207551002502441,
-0.6565858721733093,
-0.13269878923892975,
-0.6450006365776062,
0.30821236968040466,
-0.1679040789604187,
0.3023477792739868,
-0.18335309624671936,
0.18022412061691284,
0.17021030187606812,
-0.06942994892597198,
0.14790436625480652,
-0.3889729082584381,
-0.20179714262485504,
-0.1040051281452179,
0.3181891143321991,
-0.4269338548183441,
-0.06536213308572769,
-0.07279998809099197,
0.0820639505982399,
0.48182615637779236,
0.20355457067489624,
-0.014485858380794525,
0.0970020741224289,
-0.19211557507514954,
-0.1825750172138214,
-0.20688699185848236,
-0.21783868968486786,
-0.08103419840335846,
-0.6945075988769531,
-0.36786046624183655,
-0.501621425151825,
0.12273717671632767,
0.1390097588300705,
0.14689327776432037,
-0.03024246171116829,
0.2109568566083908,
0.08789141476154327,
0.4853430390357971,
0.004931243136525154,
-0.0599362850189209,
0.6008954644203186,
-0.1651570200920105,
-0.4717911183834076,
0.49630558490753174,
-0.11771067976951599,
0.3781425654888153,
0.09147711098194122,
-0.15693682432174683,
-0.13820087909698486,
-0.32531216740608215,
0.4744024872779846,
0.23392300307750702,
0.1031668409705162,
0.28175362944602966,
-0.0628662034869194,
0.02600932866334915,
-0.15068195760250092,
0.4732237756252289,
0.34279608726501465,
-0.1364433914422989,
-0.3455304205417633,
-0.14745070040225983,
0.48506808280944824,
-0.2086663395166397,
-0.06152798607945442,
0.22016724944114685,
-0.20480971038341522,
-0.2317996472120285,
0.21763405203819275,
0.1648198515176773,
1.2438884973526,
-0.05959595739841461,
0.4256584346294403,
0.07456724345684052,
-0.03276018798351288,
0.7743026614189148,
-0.1663348376750946,
0.06815848499536514,
-0.23189301788806915,
0.1349938064813614,
-0.14140063524246216,
-0.06125308573246002,
-0.11390981823205948,
0.1102670356631279,
-0.22976121306419373,
0.1084144115447998,
-0.11354091763496399,
-0.04289843514561653,
0.0006191423162817955,
0.4512530565261841,
0.10172717273235321,
-0.34147435426712036,
-0.17380934953689575,
0.061344318091869354,
-0.2538866400718689,
0.31335511803627014,
-0.17983421683311462,
-0.21803924441337585,
-0.3014184534549713,
-0.23261982202529907,
-0.1817784309387207,
0.24452084302902222,
-0.26989036798477173,
0.07795178890228271,
0.0035698264837265015,
-0.32298940420150757,
0.17310534417629242,
0.4630565643310547,
0.5105307102203369,
-0.06357783079147339,
-0.06871569901704788,
-0.009666115045547485,
-0.0855763778090477,
-0.042368341237306595,
-0.09295277297496796,
0.06018524616956711,
0.13630156219005585,
-0.29558858275413513,
0.07367678731679916,
0.3211551606655121,
-0.08515811711549759,
-0.37327325344085693,
-0.21020714938640594,
0.19486314058303833,
0.05941276624798775,
-0.1340414434671402,
-0.3536511957645416,
0.06596338003873825,
-0.21248839795589447,
-0.01574072428047657,
0.004534289240837097,
0.033151160925626755,
0.08300954848527908,
-0.09015639871358871,
0.08961185812950134,
-0.19795191287994385,
0.09447424113750458,
0.06312532722949982,
-0.04164844751358032,
-0.04899197071790695,
0.700760006904602,
-0.12110793590545654,
0.08024638146162033,
-0.04312053322792053,
-0.20529380440711975,
-0.3344261050224304,
-0.14639444649219513,
-0.07787778973579407,
0.31912145018577576,
-0.030446283519268036,
0.03915878385305405,
0.6615256667137146,
0.39813387393951416,
0.18721811473369598,
0.06805628538131714,
-0.1111069917678833,
-0.32315707206726074,
-0.3133423924446106,
-0.03441209718585014,
0.20288443565368652,
-0.025104040279984474,
0.2131599634885788,
0.20983272790908813,
0.29661574959754944,
-0.21475595235824585,
-0.1815822720527649,
-0.2030603140592575,
0.17764772474765778,
0.7618895769119263,
-0.013123616576194763,
-0.11110197752714157,
-0.01039477065205574,
-0.033159658312797546,
0.009593192487955093,
-0.14806410670280457,
-0.10335216671228409,
-0.3793177306652069,
0.18479835987091064,
0.5306533575057983,
-0.1196054145693779,
-0.014834612607955933,
-0.23938070237636566,
-0.11199536919593811,
-0.12136735022068024,
-0.32977530360221863,
0.04165046662092209,
-0.014645189046859741,
0.20553617179393768,
-0.3102738857269287,
0.3925665318965912,
-0.1536860167980194,
0.1730085164308548,
0.020328618586063385,
0.2511637806892395,
0.06056476756930351,
-0.052163735032081604,
0.15323297679424286,
0.0744905024766922,
-0.39298906922340393,
0.006554029881954193,
-0.17752008140087128,
-0.09909840673208237,
0.025729719549417496,
-0.4181019067764282,
0.15793122351169586,
-0.22159242630004883,
0.022271227091550827,
0.04608551412820816,
-0.5020123720169067,
0.2189575880765915,
0.4416903257369995,
0.08857264369726181,
0.04070451855659485,
0.16635048389434814,
0.07060461491346359,
0.21389895677566528,
0.024117764085531235,
0.2750561535358429,
-0.0007002539932727814,
-0.3031476140022278,
-0.04899744689464569,
-0.22703415155410767,
-0.11426685750484467,
-0.2721330523490906,
0.043390631675720215,
-0.060880016535520554,
-0.4242880344390869,
0.004609048366546631,
0.17042632400989532,
0.1590813249349594,
-0.10351177304983139,
0.15583407878875732,
-0.19883909821510315,
0.09525345265865326,
0.05639883130788803,
-0.11588490009307861,
0.18386025726795197,
-0.23433218896389008,
0.12833602726459503,
-0.04518181085586548,
-0.007981568574905396,
0.33807313442230225,
0.16224393248558044,
0.6163569688796997,
-0.34986600279808044,
-0.011332513764500618,
-0.26698699593544006,
0.0580330416560173,
0.023866988718509674,
0.17970961332321167,
-0.66041499376297,
-0.005375497043132782,
0.0684242695569992,
-0.08650712668895721,
0.03860250860452652,
-0.3267977833747864,
-0.05037975311279297,
0.2629709243774414,
-0.1634490042924881,
0.10786832123994827,
-0.1304248869419098,
0.19259408116340637,
0.13164880871772766,
-0.11263614892959595,
0.3684447705745697,
0.003190934658050537,
-0.03597176820039749,
-0.06830348074436188,
0.05866541713476181,
0.5559294819831848,
0.6175879836082458,
0.16811425983905792,
0.27055463194847107,
0.23017127811908722,
-0.0069065578281879425,
0.0774819478392601,
0.16673247516155243,
0.4616715610027313,
0.30198201537132263,
0.12015050649642944,
0.030812913551926613,
-0.12133515626192093,
0.14843037724494934,
0.053318850696086884,
0.09564624726772308,
-0.3158126771450043,
0.22804582118988037,
-0.029106397181749344,
-0.39975622296333313,
-0.15640880167484283,
0.40171706676483154,
-0.45790690183639526,
-0.014089287258684635,
0.1900971531867981,
0.1823270320892334,
0.3674246668815613,
-0.23387150466442108,
0.022305496037006378,
-0.1849544197320938,
0.3975655138492584,
0.4656144678592682,
-0.036127567291259766,
-0.14645622670650482,
-0.21958984434604645,
-0.48715439438819885,
0.17760160565376282,
-0.22294235229492188,
-0.2007375806570053,
-0.37588945031166077,
0.17404340207576752,
0.06222350895404816,
-0.01866282895207405,
0.07831208407878876,
0.08619526028633118,
-0.2741774618625641,
0.023239172995090485,
-0.3622928857803345,
-0.02059972658753395,
-0.12250666320323944,
-0.002512466162443161,
-0.07682991772890091,
-0.16656631231307983,
0.039569176733493805,
0.1100979670882225,
0.01287674531340599,
0.024147765710949898,
0.24240949749946594,
0.1370498687028885,
0.3673099875450134,
0.4786677956581116,
-0.07187215238809586,
0.7685264348983765,
0.06704555451869965,
0.02057444490492344,
0.04930085316300392,
-0.04225849360227585,
-0.1771257072687149,
-0.0018190070986747742,
0.17840667068958282,
0.37813428044319153,
-0.058838121592998505,
0.34986403584480286,
-0.19776242971420288,
0.06250464171171188,
-0.022588256746530533,
-0.5348160862922668,
0.05529928207397461,
-0.006339428015053272,
-0.08719682693481445,
0.23023784160614014,
0.42383113503456116,
0.08845043182373047,
0.07060220837593079,
-0.1437549591064453,
-0.43358665704727173,
-0.2854061424732208,
0.4140363931655884,
-0.5086387991905212,
-0.30031147599220276,
0.2236095815896988,
0.23953387141227722,
-0.02934328466653824,
0.05272877961397171,
-0.22304341197013855,
-0.0850505456328392,
0.135616272687912,
-0.2508601248264313,
-0.05188954994082451,
0.32419660687446594,
-0.5186461210250854,
0.01627274975180626,
-0.055287428200244904,
0.3049897849559784,
0.20241886377334595,
-0.37965095043182373,
-0.07080521434545517,
-0.21507976949214935
] |
https://github.com/huggingface/datasets/issues/181 | Cannot upload my own dataset | I now try with the sample `datasets/csv` folder.
nlp-cli upload csv
The error is still the same
```
2020-05-21 17:20:56.394659: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/csv/csv.py to S3 under filename csv/csv.py and namespace korakot
About to upload file /content/csv/dummy/0.0.0/dummy_data.zip to S3 under filename csv/dummy/0.0.0/dummy_data.zip and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
```
| I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
``` | 116 | Cannot upload my own dataset
I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
```
I now try with the sample `datasets/csv` folder.
nlp-cli upload csv
The error is still the same
```
2020-05-21 17:20:56.394659: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/csv/csv.py to S3 under filename csv/csv.py and namespace korakot
About to upload file /content/csv/dummy/0.0.0/dummy_data.zip to S3 under filename csv/dummy/0.0.0/dummy_data.zip and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
```
| [
0.05260493978857994,
-0.02810990810394287,
0.05533044412732124,
-0.0020758435130119324,
0.14557740092277527,
-0.18475821614265442,
0.33769673109054565,
-0.04772265627980232,
-0.19266782701015472,
0.1797221302986145,
-0.1303306519985199,
0.24369043111801147,
-0.21156124770641327,
0.2791500985622406,
0.3693567216396332,
0.06986403465270996,
0.013265587389469147,
0.28722038865089417,
0.0126219242811203,
-0.1083281934261322,
-0.25431978702545166,
0.09193598479032516,
-0.01930972933769226,
-0.08095788955688477,
-0.12342613190412521,
-0.19380062818527222,
-0.08119546622037888,
0.2602364122867584,
-0.22382165491580963,
-0.36161258816719055,
0.491118848323822,
0.234791561961174,
0.36471027135849,
0.5793417096138,
-0.00011945605365326628,
-0.048161353915929794,
0.16207453608512878,
-0.22125189006328583,
-0.6242919564247131,
-0.407953679561615,
0.020531892776489258,
-0.151094451546669,
0.07041076570749283,
-0.25698909163475037,
0.18926122784614563,
0.023185856640338898,
0.02170673757791519,
0.047051042318344116,
0.48964202404022217,
0.4066980481147766,
0.13775835931301117,
0.12786923348903656,
-0.22636933624744415,
-0.1397721767425537,
0.007812626659870148,
0.17320725321769714,
-0.058755140751600266,
0.2595108449459076,
0.3348256051540375,
-0.40046218037605286,
0.2734430432319641,
-0.19609782099723816,
0.012751845642924309,
-0.03790637105703354,
0.4887402653694153,
-0.021754182875156403,
-0.06072574108839035,
-0.3897158205509186,
-0.011177632957696915,
0.1542045772075653,
0.3593454658985138,
-0.017493337392807007,
-0.390593022108078,
-0.12496654689311981,
0.13513121008872986,
-0.4883081614971161,
0.24852344393730164,
0.2740962505340576,
-0.40215224027633667,
-0.027209419757127762,
-0.2619933784008026,
0.3479141592979431,
-0.4030788242816925,
0.44457709789276123,
0.10771401226520538,
0.37084731459617615,
-0.03705957159399986,
0.09139961749315262,
0.2884838581085205,
-0.15400105714797974,
0.022261077538132668,
0.038142286241054535,
0.028013093397021294,
0.2681345045566559,
-0.21565796434879303,
-0.1543159782886505,
0.011639691889286041,
-0.23738548159599304,
-0.08751183748245239,
0.11485089361667633,
0.42785075306892395,
-0.1259317696094513,
-0.24697113037109375,
0.14052718877792358,
0.10184241831302643,
0.3375077545642853,
0.023061472922563553,
0.1245047077536583,
0.13154982030391693,
0.0036603191401809454,
0.24482887983322144,
-0.07746654003858566,
-0.29436543583869934,
-0.0886225551366806,
-0.11200898885726929,
-0.05211998522281647,
0.26885515451431274,
0.07469941675662994,
-0.00757841020822525,
-0.10847916454076767,
0.07862361520528793,
0.04231101647019386,
-0.08323121815919876,
0.3526007831096649,
-0.0594031997025013,
-0.236591637134552,
-0.020166635513305664,
0.2576301097869873,
0.1414344310760498,
-0.2609562575817108,
0.06589063256978989,
0.29550161957740784,
-0.12431095540523529,
-0.14895284175872803,
0.4141158163547516,
0.023555435240268707,
0.19150908291339874,
-0.06857933849096298,
0.21296444535255432,
-0.11405246704816818,
0.05686989426612854,
0.029537595808506012,
-0.164823979139328,
0.017245955765247345,
0.22356146574020386,
0.3928877115249634,
-0.05233893170952797,
-0.5404902100563049,
-0.1403445154428482,
0.02345065027475357,
-0.34771981835365295,
-0.35778993368148804,
-0.42381608486175537,
0.07509461790323257,
0.020578566938638687,
-0.24025288224220276,
-0.3375001549720764,
-0.09723281860351562,
0.0914815217256546,
-0.28204506635665894,
-0.09507935494184494,
-0.045188285410404205,
-0.15627175569534302,
-0.11636000871658325,
0.11207837611436844,
0.06296399980783463,
-0.49924236536026,
0.21195179224014282,
-0.07937294244766235,
0.5196447372436523,
0.27601712942123413,
0.3038299083709717,
-0.3427072763442993,
0.23301392793655396,
-0.06637683510780334,
0.18478022515773773,
0.5762104392051697,
-0.49689874053001404,
-0.31175607442855835,
0.046711888164281845,
-0.03056374564766884,
-0.11799081414937973,
0.07224185764789581,
0.17157939076423645,
0.11363708227872849,
-0.08424391597509384,
0.10218079388141632,
0.43852120637893677,
0.06725264340639114,
0.04018282890319824,
-0.22083240747451782,
-0.15429767966270447,
0.2543807625770569,
0.03698397055268288,
-0.15067903697490692,
0.08312258124351501,
0.26047420501708984,
0.06287041306495667,
0.01045648381114006,
-0.32887956500053406,
0.14159715175628662,
0.21016967296600342,
0.35805806517601013,
-0.1686781942844391,
-0.12786760926246643,
0.21730640530586243,
-0.4310542643070221,
0.21843907237052917,
0.1891905814409256,
0.34858307242393494,
-0.13365566730499268,
-0.03646417707204819,
-0.43643516302108765,
-0.10224456340074539,
-0.1047709584236145,
-0.04856086149811745,
0.04172849655151367,
0.12958484888076782,
0.07387520372867584,
-0.18000899255275726,
-0.22281411290168762,
0.15982894599437714,
-0.2588525712490082,
0.0683702826499939,
-0.21001917123794556,
0.03586208075284958,
-0.2738802134990692,
-0.09568630158901215,
0.2633073329925537,
0.167036771774292,
0.21565210819244385,
-0.015994008630514145,
-0.2017110288143158,
0.09329313039779663,
-0.4534428119659424,
0.285800039768219,
0.017558999359607697,
0.10015590488910675,
0.036241769790649414,
-0.055206049233675,
-0.21381981670856476,
-0.1098799854516983,
0.17156237363815308,
-0.15249350666999817,
-0.3677257001399994,
0.17456935346126556,
-0.0044889748096466064,
0.03608394041657448,
0.1666366308927536,
0.010147880762815475,
0.29598456621170044,
-0.1779492199420929,
0.09211891889572144,
0.0983789712190628,
0.4174831211566925,
0.09317228198051453,
0.40335720777511597,
-0.011018628254532814,
-0.1426611691713333,
-0.08572553843259811,
0.16825538873672485,
-0.0006488393992185593,
0.1505850851535797,
0.07491092383861542,
0.024227645248174667,
-0.0512586385011673,
0.30666765570640564,
0.6624006628990173,
0.3770543932914734,
0.08588339388370514,
-0.026365477591753006,
-0.05196020007133484,
-0.12508489191532135,
-0.2106570303440094,
-0.04003196209669113,
-0.07790277898311615,
0.05889182165265083,
0.1829155683517456,
0.44176435470581055,
0.23638848960399628,
-0.13617059588432312,
-0.048412010073661804,
0.15327373147010803,
0.4534132778644562,
-0.19562536478042603,
0.2583773136138916,
-0.16094234585762024,
-0.42994067072868347,
0.2424887865781784,
-0.25551632046699524,
-0.06268537044525146,
-0.18169525265693665,
-0.21708352863788605,
0.14613737165927887,
0.10717156529426575,
-0.08416202664375305,
0.10070210695266724,
0.33156874775886536,
-0.10592744499444962,
-0.28663909435272217,
-0.25440698862075806,
-0.11374913901090622,
-0.19180315732955933,
0.027764219790697098,
0.32500773668289185,
-0.08840072154998779,
0.41247642040252686,
0.3248803913593292,
0.08864571154117584,
-0.04613993316888809,
-0.32683849334716797,
-0.004596970975399017,
-0.03740953654050827,
0.12089180946350098,
0.12138736248016357,
0.35637176036834717,
0.00866468995809555,
-0.5445621609687805,
0.1948816180229187,
0.07846416532993317,
-0.24362555146217346,
0.25166013836860657,
-0.032538991421461105,
-0.3485890030860901,
-0.4676506221294403,
-0.020827285945415497,
-0.2737122178077698,
-0.3687703311443329,
0.23967094719409943,
0.29409345984458923,
0.20991727709770203,
0.5754039287567139,
0.01771211251616478,
0.12528333067893982,
0.3206275403499603,
0.12391521036624908,
0.06834226846694946,
-0.18604694306850433,
0.5255687236785889,
-0.2455926537513733,
-0.42524829506874084,
0.10256612300872803,
-0.16349107027053833,
0.5601885318756104,
-0.009718913584947586,
-0.3501392602920532,
-0.17843422293663025,
0.059479184448719025,
0.21830520033836365,
-0.023407310247421265,
-0.06744977831840515,
0.2789643406867981,
-0.20497199892997742,
0.06126336753368378,
-0.0819353312253952,
-0.33696842193603516,
0.1344735324382782,
0.6249410510063171,
0.2558962404727936,
-0.04228174686431885,
0.44199538230895996,
0.03808283433318138,
0.7028172612190247,
0.10719972848892212,
-0.33854764699935913,
0.4494321942329407,
-0.03851468861103058,
0.18772760033607483,
-0.13236775994300842,
-0.369392991065979,
0.06506086885929108,
0.22544598579406738,
-0.06130904331803322,
0.13972710072994232,
-0.02224118635058403,
-0.10212033987045288,
-0.4349319040775299,
0.23016834259033203,
-0.25660964846611023,
0.04861299321055412,
-0.005603514611721039,
0.10512038320302963,
0.05551033467054367,
-0.06783266365528107,
-0.21281301975250244,
-0.3788440525531769,
-0.48297104239463806,
-0.16287319362163544,
0.2749961018562317,
-0.23916330933570862,
0.1747974306344986,
-0.6903297305107117,
-0.09328945726156235,
-0.6602327823638916,
0.3001747131347656,
-0.1387222707271576,
0.3314149081707001,
-0.20235322415828705,
0.20676812529563904,
0.11336015164852142,
-0.0766509547829628,
0.1280318647623062,
-0.46501556038856506,
-0.16797992587089539,
-0.07704339921474457,
0.27476781606674194,
-0.472359299659729,
-0.04191281273961067,
-0.027604926377534866,
0.07491299510002136,
0.43653425574302673,
0.23509682714939117,
0.018999427556991577,
0.07955583930015564,
-0.1766325831413269,
-0.20306070148944855,
-0.15370070934295654,
-0.22335879504680634,
-0.03689347952604294,
-0.6711584329605103,
-0.35238784551620483,
-0.4475812315940857,
0.06721355766057968,
0.1456536054611206,
0.14058202505111694,
-0.037643399089574814,
0.1860169619321823,
0.11092222481966019,
0.5076406598091125,
0.042842406779527664,
-0.04625977948307991,
0.629524290561676,
-0.09305115044116974,
-0.45713672041893005,
0.472504198551178,
-0.009942961856722832,
0.38947993516921997,
0.03559476137161255,
-0.19427186250686646,
-0.1696309745311737,
-0.2850334048271179,
0.45783284306526184,
0.1723031848669052,
0.08548004180192947,
0.21727722883224487,
-0.10695026814937592,
0.028125490993261337,
-0.1549404263496399,
0.46995577216148376,
0.33896535634994507,
-0.0914730653166771,
-0.4181351363658905,
-0.18395131826400757,
0.44957301020622253,
-0.17907273769378662,
-0.03373924270272255,
0.24281132221221924,
-0.19249631464481354,
-0.2763460576534271,
0.2006179541349411,
0.11939811706542969,
1.091148018836975,
-0.07678566873073578,
0.37884485721588135,
0.12213318794965744,
-0.0487479567527771,
0.7742531299591064,
-0.14554890990257263,
0.045702870935201645,
-0.23358836770057678,
0.1004330962896347,
-0.11330718547105789,
-0.05880850553512573,
-0.06760469824075699,
0.1411709487438202,
-0.23739971220493317,
0.08419743925333023,
-0.04000561311841011,
-0.11120772361755371,
0.0072576808743178844,
0.5523278117179871,
0.07271003723144531,
-0.39419955015182495,
-0.22025981545448303,
0.0838499367237091,
-0.31129831075668335,
0.30938011407852173,
-0.16995719075202942,
-0.2196555733680725,
-0.28573909401893616,
-0.18248267471790314,
-0.20725451409816742,
0.2760235071182251,
-0.25142884254455566,
0.09939274936914444,
0.04887313395738602,
-0.35540109872817993,
0.3192008137702942,
0.4633541405200958,
0.524256706237793,
-0.07650457322597504,
-0.09716552495956421,
0.04989174008369446,
-0.1302095651626587,
-0.014176782220602036,
-0.03877822682261467,
0.030591942369937897,
0.19029146432876587,
-0.26959821581840515,
0.04275324195623398,
0.25302842259407043,
-0.02574026957154274,
-0.3122658133506775,
-0.17742237448692322,
0.14603468775749207,
0.046734996140003204,
-0.16329124569892883,
-0.3530453145503998,
0.0866529569029808,
-0.17310136556625366,
-0.04445986822247505,
0.027808688580989838,
0.028734590858221054,
0.07372549176216125,
-0.06803662329912186,
0.09252879023551941,
-0.20078012347221375,
0.0808694064617157,
0.10644624382257462,
-0.11565140634775162,
-0.05883951112627983,
0.7411611080169678,
-0.06006147339940071,
0.07929187268018723,
-0.085643470287323,
-0.19852131605148315,
-0.3181910216808319,
-0.14075693488121033,
-0.08977296203374863,
0.2795100510120392,
-0.030942685902118683,
0.08318276703357697,
0.6403139233589172,
0.3384789824485779,
0.10922135412693024,
0.16181769967079163,
-0.14827968180179596,
-0.3228500783443451,
-0.3060607314109802,
-0.04380908980965614,
0.1931377351284027,
-0.10730212926864624,
0.19159775972366333,
0.20194736123085022,
0.29810240864753723,
-0.22825750708580017,
-0.1637888103723526,
-0.20056785643100739,
0.1670415699481964,
0.754091739654541,
-0.011614255607128143,
-0.06655439734458923,
-0.036773066967725754,
-0.01890009641647339,
0.0023950282484292984,
-0.16107885539531708,
-0.1169770359992981,
-0.3814639151096344,
0.17557679116725922,
0.4809395670890808,
-0.18953633308410645,
-0.04248196631669998,
-0.24042126536369324,
-0.0995074212551117,
-0.1417813003063202,
-0.2967749238014221,
0.0675632581114769,
-0.03371056914329529,
0.24088989198207855,
-0.26430997252464294,
0.33600613474845886,
-0.09664463251829147,
0.21474194526672363,
0.006567113101482391,
0.1791645586490631,
0.0874752402305603,
-0.022731199860572815,
0.19590207934379578,
0.077484130859375,
-0.37948134541511536,
-0.038136936724185944,
-0.20470307767391205,
-0.06822095066308975,
0.028972072526812553,
-0.4525882601737976,
0.13075196743011475,
-0.11226868629455566,
0.04397562891244888,
0.035784728825092316,
-0.4939000904560089,
0.16325348615646362,
0.3917882442474365,
0.10325777530670166,
0.014925528317689896,
0.11850061267614365,
0.16980460286140442,
0.20384256541728973,
0.020077425986528397,
0.244547039270401,
0.03487822785973549,
-0.29139673709869385,
-0.05173569917678833,
-0.20435792207717896,
-0.05848463997244835,
-0.26753944158554077,
0.121254563331604,
-0.09284739196300507,
-0.3782729208469391,
-0.043263692408800125,
0.1533951312303543,
0.18866701424121857,
-0.1023828312754631,
0.19348876178264618,
-0.20576730370521545,
0.1222844272851944,
0.03275245428085327,
-0.07289662957191467,
0.2181718647480011,
-0.2738104462623596,
0.11131155490875244,
-0.06723922491073608,
-0.02377428114414215,
0.3217807710170746,
0.1499323844909668,
0.6510177254676819,
-0.35149484872817993,
-0.005461741704493761,
-0.26742199063301086,
0.11025910079479218,
0.009168919175863266,
0.1439594179391861,
-0.6295010447502136,
-0.025503255426883698,
0.054359883069992065,
-0.08338461071252823,
0.0133439302444458,
-0.3383152484893799,
-0.03636631369590759,
0.2841479182243347,
-0.14115643501281738,
0.05001092702150345,
-0.10629687458276749,
0.2101648449897766,
0.12682895362377167,
-0.15633127093315125,
0.41823020577430725,
0.017136946320533752,
-0.1046929806470871,
-0.04810387268662453,
0.07154323160648346,
0.5066620111465454,
0.5816254019737244,
0.13121725618839264,
0.28301841020584106,
0.18137682974338531,
0.03374314308166504,
0.06061127781867981,
0.19215212762355804,
0.4136762022972107,
0.2930328845977783,
0.14628487825393677,
0.02923169545829296,
-0.11405077576637268,
0.07913732528686523,
0.04990002140402794,
0.0570765882730484,
-0.3188937306404114,
0.2812897562980652,
-0.031187504529953003,
-0.336191862821579,
-0.16785858571529388,
0.3929540812969208,
-0.4424988627433777,
0.011144447140395641,
0.2605806887149811,
0.22482039034366608,
0.3537737727165222,
-0.2567600905895233,
0.024390485137701035,
-0.16960233449935913,
0.4160141050815582,
0.48843076825141907,
-0.07816924899816513,
-0.14322052896022797,
-0.2934461832046509,
-0.5263962745666504,
0.16106991469860077,
-0.2162843942642212,
-0.23151743412017822,
-0.3568779230117798,
0.18111085891723633,
0.05725971236824989,
-0.09626960754394531,
0.0581553652882576,
0.14493922889232635,
-0.23265406489372253,
-0.004405803978443146,
-0.44343671202659607,
0.014719972386956215,
-0.153797909617424,
-0.014265863224864006,
-0.038493234664201736,
-0.16828292608261108,
0.029524514451622963,
0.0920230969786644,
0.018767893314361572,
-0.0066742803901433945,
0.22007080912590027,
0.1332624852657318,
0.3443257510662079,
0.4730617105960846,
-0.09442443400621414,
0.7783323526382446,
0.09284857660531998,
0.004618408158421516,
-0.006963711231946945,
-0.06584223359823227,
-0.16452109813690186,
0.02516850084066391,
0.13609915971755981,
0.4669879674911499,
-0.08531725406646729,
0.37317198514938354,
-0.2298850268125534,
0.03581182658672333,
-0.03140724450349808,
-0.5221918821334839,
0.07673229277133942,
0.009968927130103111,
-0.06821577996015549,
0.24942481517791748,
0.4241013824939728,
0.13799181580543518,
0.0984186977148056,
-0.10654041916131973,
-0.42790061235427856,
-0.3111042082309723,
0.41429752111434937,
-0.5499926209449768,
-0.33335116505622864,
0.19432814419269562,
0.22382161021232605,
-0.05248164385557175,
0.022693302482366562,
-0.28314080834388733,
-0.07024005055427551,
0.15611465275287628,
-0.23596206307411194,
-0.019298363476991653,
0.3056490123271942,
-0.431890070438385,
0.07046492397785187,
-0.052911415696144104,
0.31289142370224,
0.19471442699432373,
-0.3801869750022888,
-0.04024699330329895,
-0.16324961185455322
] |
https://github.com/huggingface/datasets/issues/181 | Cannot upload my own dataset | We haven't tested the dataset upload feature yet cc @julien-c
This is on our short/mid-term roadmap though | I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
``` | 17 | Cannot upload my own dataset
I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
```
We haven't tested the dataset upload feature yet cc @julien-c
This is on our short/mid-term roadmap though | [
0.010165128856897354,
-0.014697805047035217,
0.06399784982204437,
-0.04725117236375809,
0.13680770993232727,
-0.1440621018409729,
0.3703484535217285,
-0.0352640338242054,
-0.17155125737190247,
0.1538785994052887,
-0.10310790687799454,
0.25897887349128723,
-0.23088781535625458,
0.31687358021736145,
0.37554576992988586,
0.09489145874977112,
0.019372418522834778,
0.27177363634109497,
-0.020116537809371948,
-0.09850377589464188,
-0.22678780555725098,
0.07013359665870667,
-0.002222903072834015,
-0.09574879705905914,
-0.14261746406555176,
-0.21162621676921844,
-0.090327687561512,
0.2581224739551544,
-0.23455409705638885,
-0.34122946858406067,
0.48685991764068604,
0.23599064350128174,
0.34359246492385864,
0.5804957151412964,
-0.00011795770842581987,
-0.051996178925037384,
0.17183172702789307,
-0.21570520102977753,
-0.6393759250640869,
-0.3554881811141968,
-0.006130743771791458,
-0.13421714305877686,
0.060677528381347656,
-0.25174057483673096,
0.19287467002868652,
0.027462057769298553,
0.03491725027561188,
0.03088005632162094,
0.4822887182235718,
0.4076220393180847,
0.14891520142555237,
0.145722433924675,
-0.17812110483646393,
-0.15002450346946716,
-0.0028320401906967163,
0.18243561685085297,
-0.05897195637226105,
0.25395676493644714,
0.35869622230529785,
-0.4081469774246216,
0.2644426226615906,
-0.19958709180355072,
0.03678107261657715,
-0.04424070194363594,
0.48748522996902466,
-0.009249689988791943,
-0.07491926103830338,
-0.4059666693210602,
-0.004839859902858734,
0.17713764309883118,
0.3769998848438263,
-0.06002657115459442,
-0.3945048451423645,
-0.14569073915481567,
0.15505413711071014,
-0.4790176451206207,
0.25372353196144104,
0.27886900305747986,
-0.42470577359199524,
-0.022530261427164078,
-0.27115684747695923,
0.3137443959712982,
-0.409356027841568,
0.4221656918525696,
0.10564929246902466,
0.35269659757614136,
-0.03370986506342888,
0.0666821226477623,
0.24374662339687347,
-0.1536940336227417,
0.011768709868192673,
0.06547368317842484,
0.021466810256242752,
0.2782633602619171,
-0.2166644185781479,
-0.1950293630361557,
0.002793125808238983,
-0.24058520793914795,
-0.05818124860525131,
0.12915544211864471,
0.4047309458255768,
-0.12968289852142334,
-0.24420079588890076,
0.15063321590423584,
0.13368673622608185,
0.32412484288215637,
0.0014830529689788818,
0.12236370891332626,
0.12233429402112961,
-0.005845783744007349,
0.2769152522087097,
-0.051742419600486755,
-0.2742708921432495,
-0.050802651792764664,
-0.11301049590110779,
-0.06884722411632538,
0.2920278310775757,
0.06772629916667938,
-0.00554061122238636,
-0.12934675812721252,
0.09735853224992752,
0.016586599871516228,
-0.10256070643663406,
0.3439236879348755,
-0.08194633573293686,
-0.261303186416626,
-0.05380438268184662,
0.2326335608959198,
0.13708706200122833,
-0.290010005235672,
0.05705765262246132,
0.27582848072052,
-0.11549268662929535,
-0.1544322967529297,
0.43567249178886414,
0.012411205098032951,
0.1956508308649063,
-0.054452311247587204,
0.2021941840648651,
-0.06608017534017563,
0.07224203646183014,
0.011986557394266129,
-0.16288024187088013,
0.008681721985340118,
0.21959316730499268,
0.3847878873348236,
-0.06849811971187592,
-0.5333330631256104,
-0.14358171820640564,
0.02616080269217491,
-0.3532375395298004,
-0.3473283052444458,
-0.45941486954689026,
0.08847416192293167,
0.0037650354206562042,
-0.2817482054233551,
-0.32444483041763306,
-0.07150520384311676,
0.08965375274419785,
-0.25171083211898804,
-0.09521683305501938,
-0.04630006104707718,
-0.14219067990779877,
-0.12248457223176956,
0.12956251204013824,
0.08803869783878326,
-0.5273423790931702,
0.18487200140953064,
-0.08601373434066772,
0.489278644323349,
0.27127566933631897,
0.2785509526729584,
-0.3086808919906616,
0.24388495087623596,
-0.0801139548420906,
0.18975184857845306,
0.5997768044471741,
-0.48072585463523865,
-0.3346844017505646,
0.04278600960969925,
-0.03731606900691986,
-0.09002774953842163,
0.03727872669696808,
0.1934349685907364,
0.10801922529935837,
-0.09636010229587555,
0.09529425948858261,
0.4479227066040039,
0.04567858204245567,
0.016692688688635826,
-0.216155543923378,
-0.16694766283035278,
0.2624109983444214,
0.040792372077703476,
-0.1555020660161972,
0.07853058725595474,
0.2734294533729553,
0.08999688178300858,
0.024154886603355408,
-0.3324548900127411,
0.1537162959575653,
0.1996031403541565,
0.3573833107948303,
-0.17576824128627777,
-0.1370927095413208,
0.20602956414222717,
-0.469605028629303,
0.217020183801651,
0.18055641651153564,
0.34908393025398254,
-0.12102635204792023,
-0.01830347627401352,
-0.4437151849269867,
-0.10057184100151062,
-0.12403099238872528,
-0.058668527752161026,
0.049087829887866974,
0.11639866232872009,
0.05498087778687477,
-0.17006069421768188,
-0.2535091042518616,
0.18731676042079926,
-0.2769075036048889,
0.061252862215042114,
-0.2197422981262207,
0.04505927860736847,
-0.26968783140182495,
-0.12417362630367279,
0.2587276101112366,
0.18245284259319305,
0.16576704382896423,
0.006094574462622404,
-0.18364930152893066,
0.10668765753507614,
-0.47848546504974365,
0.2623986601829529,
0.033690545707941055,
0.1265527456998825,
0.0412624217569828,
-0.06761729717254639,
-0.18328449130058289,
-0.14366233348846436,
0.1708056628704071,
-0.14655131101608276,
-0.4013840854167938,
0.14321789145469666,
-0.027938369661569595,
0.004520796239376068,
0.16433124244213104,
0.00042167119681835175,
0.2795955538749695,
-0.1793309599161148,
0.11594351381063461,
0.10681833326816559,
0.3852042555809021,
0.06651086360216141,
0.4020828604698181,
-0.04134408384561539,
-0.12613633275032043,
-0.03238102048635483,
0.2109304815530777,
0.019254609942436218,
0.1892593950033188,
0.07365372776985168,
0.013792533427476883,
-0.08014346659183502,
0.2915307581424713,
0.6511791348457336,
0.3804545998573303,
0.11107791215181351,
-0.03202156350016594,
-0.05627492070198059,
-0.10829666256904602,
-0.18812237679958344,
-0.06301780790090561,
-0.11955749988555908,
0.07156787067651749,
0.1802181601524353,
0.42369550466537476,
0.25452080368995667,
-0.13882160186767578,
-0.03602667152881622,
0.1298334151506424,
0.4580765962600708,
-0.19086547195911407,
0.23381786048412323,
-0.13966137170791626,
-0.43804100155830383,
0.24693119525909424,
-0.22983141243457794,
-0.09044496715068817,
-0.16917309165000916,
-0.20334893465042114,
0.13439375162124634,
0.14506080746650696,
-0.0874411016702652,
0.11892323195934296,
0.337837815284729,
-0.08473843336105347,
-0.28900524973869324,
-0.26066452264785767,
-0.09300477802753448,
-0.2001829743385315,
0.053276125341653824,
0.3222638964653015,
-0.10707593709230423,
0.4432598948478699,
0.3364589214324951,
0.08638136088848114,
-0.05491837114095688,
-0.3232802450656891,
0.00857200101017952,
-0.06074152886867523,
0.12722769379615784,
0.10323647409677505,
0.34343206882476807,
-0.0030989758670330048,
-0.5138470530509949,
0.1799706071615219,
0.06420611590147018,
-0.2702476382255554,
0.22155006229877472,
-0.02242940478026867,
-0.31593844294548035,
-0.44382137060165405,
-0.05534747987985611,
-0.2909521460533142,
-0.33917292952537537,
0.2574867904186249,
0.32961487770080566,
0.19983582198619843,
0.583056628704071,
0.027132075279951096,
0.13877174258232117,
0.321448415517807,
0.10150288045406342,
0.04909181594848633,
-0.2018526792526245,
0.5142779350280762,
-0.2508528530597687,
-0.46681079268455505,
0.12727035582065582,
-0.1354219615459442,
0.5388175845146179,
-0.026185207068920135,
-0.3549956679344177,
-0.20387734472751617,
0.06519965827465057,
0.2458014190196991,
-0.036645978689193726,
-0.05192917585372925,
0.2837883234024048,
-0.19145289063453674,
0.04438886046409607,
-0.07229115813970566,
-0.33189117908477783,
0.1452784538269043,
0.6041277647018433,
0.2712108790874481,
-0.058542825281620026,
0.43397361040115356,
0.043424587696790695,
0.7070649862289429,
0.132707417011261,
-0.3311067223548889,
0.44850122928619385,
-0.06909222900867462,
0.20655706524848938,
-0.14012011885643005,
-0.37472620606422424,
0.13324420154094696,
0.23546567559242249,
-0.033650998026132584,
0.11279840022325516,
-0.03097517415881157,
-0.08227454870939255,
-0.41568055748939514,
0.22088682651519775,
-0.23390769958496094,
0.04839261993765831,
-0.016792142763733864,
0.11899576336145401,
0.04606027528643608,
-0.08111147582530975,
-0.22336795926094055,
-0.3637562096118927,
-0.5096311569213867,
-0.12451796233654022,
0.24588915705680847,
-0.24647220969200134,
0.21042367815971375,
-0.6700917482376099,
-0.05532325804233551,
-0.6859089732170105,
0.2873028516769409,
-0.1499042809009552,
0.3086010217666626,
-0.21619319915771484,
0.19936713576316833,
0.094112828373909,
-0.08231562376022339,
0.150537371635437,
-0.47544893622398376,
-0.15888743102550507,
-0.08539849519729614,
0.2848472595214844,
-0.47482746839523315,
-0.026424815878272057,
-0.05132071301341057,
0.07265022397041321,
0.4124598503112793,
0.19209975004196167,
0.03950861841440201,
0.07596605271100998,
-0.14139607548713684,
-0.21616972982883453,
-0.17694474756717682,
-0.22804751992225647,
-0.04577102139592171,
-0.6439384818077087,
-0.33588743209838867,
-0.46366727352142334,
0.056370772421360016,
0.1376708745956421,
0.16398774087429047,
-0.06866595149040222,
0.15550364553928375,
0.09471671283245087,
0.5056183338165283,
0.047923874109983444,
-0.066242516040802,
0.638486385345459,
-0.09328266978263855,
-0.42609381675720215,
0.485016405582428,
0.0034874696284532547,
0.3892187774181366,
0.028055738657712936,
-0.14984765648841858,
-0.15592554211616516,
-0.2998329997062683,
0.47131356596946716,
0.13734591007232666,
0.08705980330705643,
0.18480390310287476,
-0.09927674382925034,
0.02812296152114868,
-0.19187159836292267,
0.5012048482894897,
0.3349218964576721,
-0.08053115010261536,
-0.4222892224788666,
-0.18815913796424866,
0.4366787374019623,
-0.16746795177459717,
-0.002293229103088379,
0.24263334274291992,
-0.18027828633785248,
-0.26839780807495117,
0.1748557984828949,
0.14205573499202728,
1.0450079441070557,
-0.09819291532039642,
0.3577185273170471,
0.11459758877754211,
-0.030823538079857826,
0.7806406617164612,
-0.1800108700990677,
0.04540562629699707,
-0.2553688883781433,
0.09904008358716965,
-0.11995568126440048,
-0.04338899254798889,
-0.04568786919116974,
0.13680106401443481,
-0.2528732120990753,
0.08574341982603073,
-0.029485352337360382,
-0.14704395830631256,
0.005725708790123463,
0.5664041638374329,
0.06178762763738632,
-0.3942602276802063,
-0.20463372766971588,
0.10850328207015991,
-0.31704938411712646,
0.2979927957057953,
-0.1628500521183014,
-0.20761960744857788,
-0.28265658020973206,
-0.15511317551136017,
-0.22094181180000305,
0.30353090167045593,
-0.23986969888210297,
0.07949524372816086,
0.05891779810190201,
-0.319892942905426,
0.3326181173324585,
0.46785664558410645,
0.5250080823898315,
-0.08236932754516602,
-0.10083150863647461,
0.037575770169496536,
-0.167093425989151,
-0.027053849771618843,
0.009089290164411068,
0.05029284209012985,
0.22911930084228516,
-0.290698379278183,
0.03021179884672165,
0.2814527750015259,
-0.0009340867400169373,
-0.30204153060913086,
-0.17566703259944916,
0.13425405323505402,
0.07122749090194702,
-0.16748592257499695,
-0.3050804138183594,
0.10473191738128662,
-0.13321731984615326,
-0.039233628660440445,
0.0401461198925972,
0.04761671647429466,
0.06888840347528458,
-0.028613664209842682,
0.07775548100471497,
-0.18398180603981018,
0.057182833552360535,
0.11787647008895874,
-0.11957670003175735,
-0.07269173860549927,
0.7520657777786255,
-0.053994070738554,
0.09325073659420013,
-0.10994230210781097,
-0.18213312327861786,
-0.273678183555603,
-0.13815313577651978,
-0.09949136525392532,
0.2768901586532593,
-0.020947933197021484,
0.09042224287986755,
0.6383234858512878,
0.3213026523590088,
0.09763477742671967,
0.13834625482559204,
-0.1498948335647583,
-0.3523445427417755,
-0.33584898710250854,
-0.020538460463285446,
0.1858692467212677,
-0.12017836421728134,
0.14587904512882233,
0.2181803286075592,
0.31043580174446106,
-0.25146135687828064,
-0.1950041800737381,
-0.19985800981521606,
0.15835464000701904,
0.7369635105133057,
-0.01766325533390045,
-0.012900841422379017,
-0.06114561855792999,
0.006987877190113068,
-0.03010920062661171,
-0.17383694648742676,
-0.1364712119102478,
-0.36932259798049927,
0.16456398367881775,
0.46165916323661804,
-0.19141323864459991,
-0.056230101734399796,
-0.21856941282749176,
-0.12847858667373657,
-0.13379023969173431,
-0.2693403959274292,
0.06040240824222565,
-0.057562947273254395,
0.2415003627538681,
-0.22885139286518097,
0.32027676701545715,
-0.08825058490037918,
0.17375975847244263,
0.03331265226006508,
0.16573955118656158,
0.07580462098121643,
-0.019646011292934418,
0.19066877663135529,
0.07480838894844055,
-0.3352307677268982,
-0.02620074898004532,
-0.1774321049451828,
-0.0726977214217186,
0.017780333757400513,
-0.47883278131484985,
0.10806423425674438,
-0.13837334513664246,
0.05096103996038437,
0.022260237485170364,
-0.4982840418815613,
0.13783924281597137,
0.38783401250839233,
0.11959435045719147,
-0.0020742658525705338,
0.11066970229148865,
0.20888091623783112,
0.2025485336780548,
0.013452615588903427,
0.2371889054775238,
0.0218781940639019,
-0.2497704029083252,
-0.0744701474905014,
-0.19819730520248413,
-0.07921246439218521,
-0.28159695863723755,
0.09921444952487946,
-0.11246882379055023,
-0.3867097496986389,
-0.0492035411298275,
0.1662590652704239,
0.19723787903785706,
-0.09329438954591751,
0.21389196813106537,
-0.20517244935035706,
0.11387556046247482,
0.032077886164188385,
-0.06195525452494621,
0.2281331717967987,
-0.2797221541404724,
0.1353696882724762,
-0.09851956367492676,
0.005143940448760986,
0.3340870440006256,
0.14589402079582214,
0.6321766972541809,
-0.31623148918151855,
-0.01611216738820076,
-0.24867364764213562,
0.07460862398147583,
0.01759660243988037,
0.16787521541118622,
-0.6061632037162781,
-0.02913285791873932,
0.05296070873737335,
-0.08525784313678741,
0.01077720895409584,
-0.36782461404800415,
-0.04822459816932678,
0.2759411931037903,
-0.15788498520851135,
0.05883438140153885,
-0.09755999594926834,
0.19536921381950378,
0.13777554035186768,
-0.1273939162492752,
0.40262725949287415,
-0.008652724325656891,
-0.09197324514389038,
-0.05486853048205376,
0.11255726963281631,
0.46995019912719727,
0.579823911190033,
0.14910875260829926,
0.3191978931427002,
0.20295307040214539,
0.03397442400455475,
0.06528585404157639,
0.183114156126976,
0.3685245215892792,
0.2624918520450592,
0.13088898360729218,
0.040757112205028534,
-0.10797838866710663,
0.059256549924612045,
0.027628939598798752,
0.07058069109916687,
-0.308167964220047,
0.2848705053329468,
-0.01995892822742462,
-0.3238849937915802,
-0.17790156602859497,
0.397659033536911,
-0.42802703380584717,
0.008006664924323559,
0.3059368133544922,
0.2120257019996643,
0.3255811631679535,
-0.27194514870643616,
0.033614348620176315,
-0.18920110166072845,
0.45011478662490845,
0.4820158779621124,
-0.09710150212049484,
-0.10160064697265625,
-0.25178587436676025,
-0.5138525366783142,
0.1598954200744629,
-0.19470663368701935,
-0.26225218176841736,
-0.3417937159538269,
0.1898447722196579,
0.036116696894168854,
-0.08899536728858948,
0.10701452940702438,
0.13900624215602875,
-0.21020136773586273,
-0.02003651112318039,
-0.46240222454071045,
0.013604216277599335,
-0.15904930233955383,
0.009875490330159664,
-0.02020547166466713,
-0.17562425136566162,
0.043981000781059265,
0.06408044695854187,
0.01580042392015457,
-0.0002460945397615433,
0.18995270133018494,
0.11839324235916138,
0.32662031054496765,
0.4968593418598175,
-0.10089100152254105,
0.7589023113250732,
0.10915186256170273,
-0.008116360753774643,
-0.012253377586603165,
-0.06070781126618385,
-0.2116783708333969,
0.07008427381515503,
0.12792526185512543,
0.4384544789791107,
-0.0824115201830864,
0.3603610694408417,
-0.22094301879405975,
0.07509887963533401,
-0.033126525580883026,
-0.5146056413650513,
0.08451104164123535,
0.02284649945795536,
-0.04442755877971649,
0.2764641344547272,
0.41493144631385803,
0.09248562157154083,
0.09413083642721176,
-0.09509802609682083,
-0.4262844920158386,
-0.2746139168739319,
0.39774632453918457,
-0.5510282516479492,
-0.29202577471733093,
0.1532038152217865,
0.21421507000923157,
-0.032668761909008026,
-0.009405512362718582,
-0.3166782259941101,
-0.06710265576839447,
0.17874471843242645,
-0.22816726565361023,
-0.011713536456227303,
0.2962084412574768,
-0.4524925947189331,
0.09072346985340118,
-0.046880509704351425,
0.3302346169948578,
0.17732536792755127,
-0.3714454174041748,
-0.016200726851820946,
-0.14145897328853607
] |
https://github.com/huggingface/datasets/issues/181 | Cannot upload my own dataset | Even if I fix the `TypeError: __init__() got an unexpected keyword argument 'cdn'` error, it looks like it still uploads to `https://s3.amazonaws.com/models.huggingface.co/bert/<namespace>/<dataset_name>` instead of `https://s3.amazonaws.com/datasets.huggingface.co/nlp/<namespace>/<dataset_name>` | I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
``` | 25 | Cannot upload my own dataset
I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
```
Even if I fix the `TypeError: __init__() got an unexpected keyword argument 'cdn'` error, it looks like it still uploads to `https://s3.amazonaws.com/models.huggingface.co/bert/<namespace>/<dataset_name>` instead of `https://s3.amazonaws.com/datasets.huggingface.co/nlp/<namespace>/<dataset_name>` | [
0.07664860785007477,
-0.05189128220081329,
0.05664337798953056,
-0.013380460441112518,
0.1621718555688858,
-0.1869213581085205,
0.3156285285949707,
-0.02782139927148819,
-0.19460216164588928,
0.19591796398162842,
-0.1271069049835205,
0.23585718870162964,
-0.22072944045066833,
0.292635053396225,
0.3533962070941925,
0.07266484946012497,
0.005575597286224365,
0.2951040267944336,
0.009004920721054077,
-0.09385786950588226,
-0.21986123919487,
0.09480921179056168,
0.019349902868270874,
-0.07987074553966522,
-0.13481725752353668,
-0.1881403625011444,
-0.07919929921627045,
0.27564123272895813,
-0.19723261892795563,
-0.33476564288139343,
0.4486151337623596,
0.2227426916360855,
0.3325243592262268,
0.6002951264381409,
-0.00011811569856945425,
-0.05863648280501366,
0.16570237278938293,
-0.22807450592517853,
-0.6185938715934753,
-0.37377268075942993,
0.07301405817270279,
-0.14274385571479797,
0.0919017344713211,
-0.2383846640586853,
0.18933576345443726,
0.03741716966032982,
0.016469644382596016,
0.06538467854261398,
0.52815842628479,
0.37782976031303406,
0.14735276997089386,
0.1031377837061882,
-0.17057590186595917,
-0.09499382227659225,
0.027344077825546265,
0.18931761384010315,
-0.05604257434606552,
0.29447856545448303,
0.33864349126815796,
-0.3992345631122589,
0.2927800118923187,
-0.19877883791923523,
-0.00343981571495533,
-0.06038891151547432,
0.48242419958114624,
-0.027946360409259796,
0.0078292116522789,
-0.4104381203651428,
-0.029902271926403046,
0.17739379405975342,
0.30182331800460815,
-0.030178628861904144,
-0.3591754734516144,
-0.11387863755226135,
0.16878533363342285,
-0.4841402471065521,
0.25605514645576477,
0.27259162068367004,
-0.41021379828453064,
-0.03852648660540581,
-0.25709426403045654,
0.32797667384147644,
-0.4180815815925598,
0.44269436597824097,
0.1196066290140152,
0.3393747806549072,
-0.022680915892124176,
0.07667822390794754,
0.2550285756587982,
-0.1277889609336853,
0.007880826480686665,
0.09094315767288208,
0.021747460588812828,
0.2719120383262634,
-0.19632475078105927,
-0.18465973436832428,
-0.02068992704153061,
-0.2897568941116333,
-0.10948570817708969,
0.09983215481042862,
0.4507439434528351,
-0.1309795081615448,
-0.2473733127117157,
0.14947140216827393,
0.09313434362411499,
0.32917824387550354,
-0.007071547210216522,
0.09553524106740952,
0.12827558815479279,
0.021282576024532318,
0.27535539865493774,
-0.066107377409935,
-0.2871696352958679,
-0.07212265580892563,
-0.12615810334682465,
-0.04732624441385269,
0.27471923828125,
0.08483269810676575,
0.011768626049160957,
-0.09488480538129807,
0.07253137230873108,
0.060445889830589294,
-0.0801716074347496,
0.3419950604438782,
-0.11174273490905762,
-0.24170127511024475,
0.005972001701593399,
0.23593328893184662,
0.13921090960502625,
-0.26889768242836,
0.07524190843105316,
0.30232560634613037,
-0.11196798086166382,
-0.14454683661460876,
0.4047555923461914,
0.008399376645684242,
0.1989605575799942,
-0.046806368976831436,
0.18748703598976135,
-0.13644537329673767,
0.06247740238904953,
0.006645042449235916,
-0.1763249635696411,
0.03343529999256134,
0.22955000400543213,
0.38577964901924133,
-0.06581887602806091,
-0.5420820116996765,
-0.13114003837108612,
0.03096667304635048,
-0.37687376141548157,
-0.3573206067085266,
-0.44525375962257385,
0.08834989368915558,
0.04142218828201294,
-0.2367771863937378,
-0.307137131690979,
-0.1186676174402237,
0.09791091084480286,
-0.2934206426143646,
-0.09514971822500229,
-0.04661904275417328,
-0.1209682747721672,
-0.13289496302604675,
0.11520536988973618,
0.04702848941087723,
-0.47550541162490845,
0.21962383389472961,
-0.08374617993831635,
0.512432336807251,
0.32623007893562317,
0.29876676201820374,
-0.3122524321079254,
0.271157830953598,
-0.06317339092493057,
0.17326487600803375,
0.5793401002883911,
-0.47124627232551575,
-0.2747647166252136,
0.027949489653110504,
-0.03406146541237831,
-0.10284287482500076,
0.05465691164135933,
0.17109650373458862,
0.08083709329366684,
-0.09934062510728836,
0.07489281892776489,
0.44040703773498535,
0.07226992398500443,
0.04624674469232559,
-0.23941278457641602,
-0.16745544970035553,
0.258391797542572,
0.03397069498896599,
-0.16789847612380981,
0.07635146379470825,
0.24125459790229797,
0.08969418704509735,
0.0238095261156559,
-0.33165550231933594,
0.1337258666753769,
0.20273829996585846,
0.3554898500442505,
-0.1569676250219345,
-0.14370864629745483,
0.2355039119720459,
-0.40783828496932983,
0.18856623768806458,
0.12364427745342255,
0.3522772490978241,
-0.10161960124969482,
-0.010192330926656723,
-0.41855716705322266,
-0.0969458520412445,
-0.09851209819316864,
-0.023751594126224518,
0.06040218472480774,
0.10851233452558517,
0.05050450190901756,
-0.18064525723457336,
-0.22650733590126038,
0.14043653011322021,
-0.30637800693511963,
0.05729084834456444,
-0.2142498642206192,
0.0430721640586853,
-0.28264400362968445,
-0.11205196380615234,
0.253186970949173,
0.1754760891199112,
0.1947956085205078,
-0.015051346272230148,
-0.19718411564826965,
0.0930892676115036,
-0.4591653347015381,
0.3227218985557556,
-0.002345513552427292,
0.13259637355804443,
0.03050420992076397,
-0.022738121449947357,
-0.23679900169372559,
-0.09179329872131348,
0.1783350557088852,
-0.16936469078063965,
-0.33602118492126465,
0.13825173676013947,
-0.029993291944265366,
0.016736023128032684,
0.15873317420482635,
0.0029885340481996536,
0.28925013542175293,
-0.18946008384227753,
0.11126898974180222,
0.13147734105587006,
0.4015832841396332,
0.09714187681674957,
0.3815452754497528,
-0.04512950778007507,
-0.13328233361244202,
-0.08486033231019974,
0.18308381736278534,
0.023189224302768707,
0.16448454558849335,
0.07439347356557846,
0.020963281393051147,
-0.0921829491853714,
0.30198606848716736,
0.5998583436012268,
0.3605665862560272,
0.07620026916265488,
-0.05645529553294182,
-0.06078985333442688,
-0.1149052232503891,
-0.22583210468292236,
-0.03621252626180649,
-0.08589228987693787,
0.06461302936077118,
0.2199166715145111,
0.43957406282424927,
0.26594144105911255,
-0.13194306194782257,
-0.011397767812013626,
0.10586436837911606,
0.4606073498725891,
-0.19288797676563263,
0.24376700818538666,
-0.1272561252117157,
-0.4152642488479614,
0.24683064222335815,
-0.2743428349494934,
-0.08276297152042389,
-0.17546343803405762,
-0.199441596865654,
0.15085017681121826,
0.09969285130500793,
-0.11422117799520493,
0.17351354658603668,
0.32977747917175293,
-0.10300754010677338,
-0.2672959268093109,
-0.28693437576293945,
-0.08144953846931458,
-0.20950135588645935,
0.043896693736314774,
0.33913376927375793,
-0.10610567033290863,
0.42552557587623596,
0.33081158995628357,
0.05794121325016022,
-0.031525470316410065,
-0.3174516558647156,
-0.012977927923202515,
-0.038392044603824615,
0.09033845365047455,
0.08890723437070847,
0.3747074007987976,
0.01147523894906044,
-0.5478421449661255,
0.19541172683238983,
0.05433341860771179,
-0.25022077560424805,
0.2478959858417511,
-0.031557921320199966,
-0.31541746854782104,
-0.47585931420326233,
0.002425380051136017,
-0.26761865615844727,
-0.3631879389286041,
0.24924412369728088,
0.3301575183868408,
0.2313889116048813,
0.5911978483200073,
0.019704103469848633,
0.13168871402740479,
0.3197172284126282,
0.1506917029619217,
0.045514725148677826,
-0.18698321282863617,
0.49666300415992737,
-0.2360728681087494,
-0.42654773592948914,
0.10766628384590149,
-0.14385582506656647,
0.5702795386314392,
-0.04440854489803314,
-0.3675757646560669,
-0.18725848197937012,
0.08487427979707718,
0.17660599946975708,
-0.07252096384763718,
-0.07167656719684601,
0.29713717103004456,
-0.19216713309288025,
0.0524093434214592,
-0.05853378027677536,
-0.29756587743759155,
0.1311010718345642,
0.6311604380607605,
0.2633405029773712,
-0.05882040411233902,
0.4399247169494629,
0.01797991245985031,
0.6985477805137634,
0.10503318905830383,
-0.3126603066921234,
0.44941115379333496,
-0.038286007940769196,
0.18113131821155548,
-0.1402672827243805,
-0.3474927544593811,
0.08872711658477783,
0.23850512504577637,
-0.042701371014118195,
0.1445247232913971,
-0.0436849370598793,
-0.0786023736000061,
-0.44182536005973816,
0.24700278043746948,
-0.2635873556137085,
0.05894371494650841,
0.009580896236002445,
0.10640180110931396,
0.037593960762023926,
-0.10671721398830414,
-0.24084511399269104,
-0.34414172172546387,
-0.5165199041366577,
-0.1217706948518753,
0.26317548751831055,
-0.24034827947616577,
0.18618836998939514,
-0.6647051572799683,
-0.12223074585199356,
-0.6593774557113647,
0.3021116554737091,
-0.1535392850637436,
0.2957099378108978,
-0.20639866590499878,
0.18639734387397766,
0.1276567280292511,
-0.0775057002902031,
0.1092493087053299,
-0.4198964238166809,
-0.1877129077911377,
-0.09577645361423492,
0.2693746089935303,
-0.4779631197452545,
-0.05513397231698036,
-0.0379420630633831,
0.08147379010915756,
0.4557524621486664,
0.2085588425397873,
0.012649916112422943,
0.09506552666425705,
-0.16743123531341553,
-0.22884663939476013,
-0.17120373249053955,
-0.24247993528842926,
-0.047817058861255646,
-0.638192355632782,
-0.34167706966400146,
-0.48311924934387207,
0.04853607714176178,
0.16847625374794006,
0.15164008736610413,
-0.0745968297123909,
0.1877347081899643,
0.09917943924665451,
0.4985141158103943,
0.021204393357038498,
-0.057446740567684174,
0.6246477365493774,
-0.11789751052856445,
-0.44503387808799744,
0.4890882968902588,
-0.035323888063430786,
0.35839998722076416,
0.06729531288146973,
-0.14457662403583527,
-0.1746768057346344,
-0.2812870144844055,
0.44760602712631226,
0.1807999610900879,
0.10797969251871109,
0.21889814734458923,
-0.11514140665531158,
0.04811500757932663,
-0.1877969205379486,
0.4967009127140045,
0.3341120183467865,
-0.09505445510149002,
-0.3954765796661377,
-0.15638874471187592,
0.4564093351364136,
-0.19788669049739838,
-0.0036152824759483337,
0.2535567581653595,
-0.22835589945316315,
-0.281291127204895,
0.20379826426506042,
0.1643548309803009,
1.138471245765686,
-0.09754566848278046,
0.3732185661792755,
0.12780284881591797,
-0.0374407134950161,
0.7614163756370544,
-0.18077364563941956,
0.05255858227610588,
-0.256600022315979,
0.14564953744411469,
-0.10637672990560532,
-0.05241217091679573,
-0.08326361328363419,
0.08725977689027786,
-0.23801003396511078,
0.07538589090108871,
-0.06170376390218735,
-0.13530021905899048,
-0.005106111988425255,
0.5711607336997986,
0.10040029883384705,
-0.3970246911048889,
-0.21205256879329681,
0.09203217178583145,
-0.3342668414115906,
0.3082551956176758,
-0.16845157742500305,
-0.23394064605236053,
-0.3076724410057068,
-0.14399370551109314,
-0.18095362186431885,
0.28737279772758484,
-0.2535722553730011,
0.07502125203609467,
0.06265754997730255,
-0.33089619874954224,
0.2630811631679535,
0.4393528699874878,
0.5037201642990112,
-0.07716363668441772,
-0.09232001006603241,
0.02560356631875038,
-0.13528934121131897,
-0.04990985617041588,
-0.026900609955191612,
0.07493158429861069,
0.191163569688797,
-0.31154924631118774,
0.07954157143831253,
0.2915780544281006,
-0.02502903901040554,
-0.3022928833961487,
-0.1862049400806427,
0.15034270286560059,
0.0951574295759201,
-0.14537625014781952,
-0.33030492067337036,
0.09154897928237915,
-0.18308109045028687,
-0.03186061233282089,
0.040296826511621475,
0.05976008251309395,
0.04360241815447807,
-0.06491034477949142,
0.09557205438613892,
-0.18126699328422546,
0.07074012607336044,
0.09366314113140106,
-0.09329038113355637,
-0.05471434444189072,
0.755597710609436,
-0.07153280079364777,
0.09503118693828583,
-0.08538438379764557,
-0.21003076434135437,
-0.3262542486190796,
-0.15901440382003784,
-0.0998723953962326,
0.2788127064704895,
-0.051781632006168365,
0.08019936084747314,
0.6546950936317444,
0.3361327648162842,
0.12761613726615906,
0.1409851461648941,
-0.1391994059085846,
-0.3442883789539337,
-0.333631694316864,
-0.02599933370947838,
0.17864908277988434,
-0.10025950521230698,
0.20802272856235504,
0.19337491691112518,
0.3369990289211273,
-0.2439340502023697,
-0.18857669830322266,
-0.19681774079799652,
0.1518172323703766,
0.7084043025970459,
-0.03436862677335739,
-0.06733915954828262,
-0.02548118680715561,
-0.0026783663779497147,
-0.02516811341047287,
-0.17077355086803436,
-0.12747356295585632,
-0.37970876693725586,
0.16888132691383362,
0.48321598768234253,
-0.1887608915567398,
-0.06686544418334961,
-0.21625450253486633,
-0.10766865313053131,
-0.1371471881866455,
-0.3264840841293335,
0.03570879250764847,
-0.04568508267402649,
0.20570193231105804,
-0.2262984663248062,
0.3478628396987915,
-0.09009246528148651,
0.2073937952518463,
0.017075777053833008,
0.18031837046146393,
0.05808906629681587,
-0.04084564745426178,
0.17120876908302307,
0.06229694187641144,
-0.3547435402870178,
-0.03789883852005005,
-0.18474037945270538,
-0.10040662437677383,
0.025786247104406357,
-0.43826913833618164,
0.1099516749382019,
-0.15907278656959534,
0.043411001563072205,
0.03248404338955879,
-0.5039010643959045,
0.15125025808811188,
0.39393386244773865,
0.10969085991382599,
0.04253868758678436,
0.12714213132858276,
0.1619914472103119,
0.20843978226184845,
-0.017391681671142578,
0.22560808062553406,
0.039039161056280136,
-0.2658630311489105,
-0.052080437541007996,
-0.16882598400115967,
-0.12271874397993088,
-0.2723003029823303,
0.07296204566955566,
-0.14059127867221832,
-0.4185332953929901,
-0.059193868190050125,
0.1482294648885727,
0.16802509129047394,
-0.10553344339132309,
0.15312913060188293,
-0.20561042428016663,
0.08979486674070358,
0.018970036879181862,
-0.08495743572711945,
0.23121878504753113,
-0.2662840187549591,
0.07315874844789505,
-0.08859777450561523,
-0.032751381397247314,
0.33546701073646545,
0.14241033792495728,
0.6379615664482117,
-0.32824769616127014,
-0.02502352185547352,
-0.24423660337924957,
0.1070641428232193,
0.005122607573866844,
0.1822264939546585,
-0.6148508191108704,
-0.019356362521648407,
0.04265167564153671,
-0.10466176271438599,
0.030356280505657196,
-0.3352682590484619,
-0.06210431456565857,
0.3056540787220001,
-0.17846320569515228,
0.09636440128087997,
-0.14240166544914246,
0.2184900939464569,
0.16331420838832855,
-0.16216038167476654,
0.40879136323928833,
0.03424454480409622,
-0.10550744831562042,
-0.08757491409778595,
0.08006279915571213,
0.49889031052589417,
0.5946881175041199,
0.11233998835086823,
0.30674824118614197,
0.21389813721179962,
0.03758193552494049,
0.0789858028292656,
0.20481666922569275,
0.43595924973487854,
0.28090909123420715,
0.114513099193573,
0.04079467058181763,
-0.1263175755739212,
0.07522377371788025,
0.031144484877586365,
0.1062246561050415,
-0.292772501707077,
0.3019169569015503,
-0.010781370103359222,
-0.3658282160758972,
-0.17470884323120117,
0.38556450605392456,
-0.4677879810333252,
0.023127175867557526,
0.24933668971061707,
0.21936671435832977,
0.3385199308395386,
-0.2580972909927368,
0.03067830577492714,
-0.17712639272212982,
0.4321080446243286,
0.48943403363227844,
-0.08823614567518234,
-0.12464950233697891,
-0.28623396158218384,
-0.47932541370391846,
0.18860946595668793,
-0.1928073912858963,
-0.21018359065055847,
-0.3527606129646301,
0.18883012235164642,
0.04558246582746506,
-0.10253976285457611,
0.07314872741699219,
0.0991477370262146,
-0.22263728082180023,
-0.02926824986934662,
-0.45445024967193604,
0.049344249069690704,
-0.17575670778751373,
-0.03394394367933273,
-0.028623457998037338,
-0.1621444970369339,
0.07061208039522171,
0.059837374836206436,
0.03442052751779556,
0.020242618396878242,
0.22016996145248413,
0.11978629231452942,
0.3783562481403351,
0.47854748368263245,
-0.09864504635334015,
0.7240331172943115,
0.0831502377986908,
-0.009448787197470665,
0.026825491338968277,
-0.05517902225255966,
-0.17598721385002136,
0.03951149433851242,
0.1294780969619751,
0.4713501036167145,
-0.07734829932451248,
0.35965675115585327,
-0.24028164148330688,
0.07416467368602753,
-0.05003424361348152,
-0.537612795829773,
0.08918238431215286,
-0.004219084046781063,
-0.044237785041332245,
0.2662244439125061,
0.4257829487323761,
0.11622225493192673,
0.11474072933197021,
-0.12512779235839844,
-0.46675992012023926,
-0.28307726979255676,
0.41881105303764343,
-0.5340771675109863,
-0.3015989363193512,
0.19961611926555634,
0.2269032597541809,
-0.06853408366441727,
0.050434861332178116,
-0.30186235904693604,
-0.06729238480329514,
0.163137286901474,
-0.22798311710357666,
-0.01558799110352993,
0.31345662474632263,
-0.47143709659576416,
0.0794144868850708,
-0.03801819682121277,
0.279806911945343,
0.20968550443649292,
-0.3522428274154663,
-0.04154529049992561,
-0.15494854748249054
] |
https://github.com/huggingface/datasets/issues/181 | Cannot upload my own dataset | @lhoestq The endpoints in https://github.com/huggingface/nlp/blob/master/src/nlp/hf_api.py should be (depending on the type of file):
```
POST /api/datasets/presign
GET /api/datasets/listObjs
DELETE /api/datasets/deleteObj
POST /api/metrics/presign
GET /api/metrics/listObjs
DELETE /api/metrics/deleteObj
```
In addition to this, @thomwolf cleaned up the objects with dataclasses but you should revert this and re-align to the hf_api that's in this branch of transformers: https://github.com/huggingface/transformers/pull/4632 (so that potential new JSON attributes in the API output don't break existing versions of any library) | I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
``` | 72 | Cannot upload my own dataset
I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
```
@lhoestq The endpoints in https://github.com/huggingface/nlp/blob/master/src/nlp/hf_api.py should be (depending on the type of file):
```
POST /api/datasets/presign
GET /api/datasets/listObjs
DELETE /api/datasets/deleteObj
POST /api/metrics/presign
GET /api/metrics/listObjs
DELETE /api/metrics/deleteObj
```
In addition to this, @thomwolf cleaned up the objects with dataclasses but you should revert this and re-align to the hf_api that's in this branch of transformers: https://github.com/huggingface/transformers/pull/4632 (so that potential new JSON attributes in the API output don't break existing versions of any library) | [
0.09444819390773773,
-0.03021540492773056,
0.04769307002425194,
-0.02157311886548996,
0.15865458548069,
-0.19878631830215454,
0.3093152642250061,
-0.028614450246095657,
-0.2004597783088684,
0.17955026030540466,
-0.14158895611763,
0.26486989855766296,
-0.21903859078884125,
0.2876114845275879,
0.3653639853000641,
0.08437439799308777,
-0.012491606175899506,
0.2811937928199768,
-0.014133051037788391,
-0.09843245148658752,
-0.21194221079349518,
0.10448246449232101,
0.03202156722545624,
-0.04935638606548309,
-0.11954204738140106,
-0.17534485459327698,
-0.09639161080121994,
0.2744736969470978,
-0.20591849088668823,
-0.32282862067222595,
0.44809550046920776,
0.22257763147354126,
0.30274730920791626,
0.5770042538642883,
-0.0001172610791400075,
-0.04289437085390091,
0.14301031827926636,
-0.22344990074634552,
-0.6293326020240784,
-0.382637083530426,
0.07990779727697372,
-0.13676342368125916,
0.07053136080503464,
-0.25299200415611267,
0.19080787897109985,
0.04170547053217888,
0.0007065478712320328,
0.0639595165848732,
0.5112634301185608,
0.3838019371032715,
0.1552751660346985,
0.08335160464048386,
-0.19444243609905243,
-0.0838209018111229,
0.03142506256699562,
0.18943168222904205,
-0.04444887861609459,
0.2973892390727997,
0.36469703912734985,
-0.3999795615673065,
0.28799811005592346,
-0.19582900404930115,
-0.004944635555148125,
-0.09528373181819916,
0.4774853587150574,
-0.02443009614944458,
0.002210259437561035,
-0.4087410867214203,
-0.004733026027679443,
0.14790241420269012,
0.2761026620864868,
-0.044267818331718445,
-0.34744542837142944,
-0.10563983023166656,
0.1462830901145935,
-0.48935994505882263,
0.25155404210090637,
0.3014514744281769,
-0.42473962903022766,
-0.029061753302812576,
-0.2817878723144531,
0.32458654046058655,
-0.4137301445007324,
0.43699783086776733,
0.11532680690288544,
0.354594886302948,
-0.021374192088842392,
0.07461950927972794,
0.23075909912586212,
-0.13691918551921844,
-0.022248752415180206,
0.07378741353750229,
0.012209251523017883,
0.2807027995586395,
-0.18891213834285736,
-0.18761013448238373,
-0.018634609878063202,
-0.2808479964733124,
-0.09787112474441528,
0.11185141652822495,
0.4561227858066559,
-0.13783910870552063,
-0.2397993803024292,
0.15594863891601562,
0.09088344871997833,
0.3234420120716095,
-0.006549075245857239,
0.09779709577560425,
0.12052936106920242,
0.00033426645677536726,
0.28369003534317017,
-0.0605228915810585,
-0.2795400023460388,
-0.07793854922056198,
-0.14036278426647186,
-0.03552112728357315,
0.2655668258666992,
0.08274981379508972,
-0.0020336154848337173,
-0.0889303907752037,
0.06567001342773438,
0.06152743846178055,
-0.08327458053827286,
0.3429432809352875,
-0.08083135634660721,
-0.25687673687934875,
-0.004063107073307037,
0.25254517793655396,
0.14727067947387695,
-0.26811474561691284,
0.0705912634730339,
0.322195827960968,
-0.12113502621650696,
-0.14960487186908722,
0.40277257561683655,
0.016711529344320297,
0.20685160160064697,
-0.05475427210330963,
0.16550320386886597,
-0.14268727600574493,
0.06256703287363052,
0.01568053849041462,
-0.1528286337852478,
0.03313666954636574,
0.2373732328414917,
0.3591506779193878,
-0.07919710874557495,
-0.5343109965324402,
-0.12540274858474731,
0.04936794191598892,
-0.38119059801101685,
-0.3526667356491089,
-0.4539191722869873,
0.09591706842184067,
0.04416888952255249,
-0.22488164901733398,
-0.32030734419822693,
-0.10148513317108154,
0.09989187121391296,
-0.2611241340637207,
-0.07177598029375076,
-0.026748213917016983,
-0.1189921498298645,
-0.12630946934223175,
0.12081434577703476,
0.03390306979417801,
-0.4636046886444092,
0.20927631855010986,
-0.04615643620491028,
0.5230317115783691,
0.2966090440750122,
0.28856390714645386,
-0.3173558712005615,
0.26712968945503235,
-0.06915789097547531,
0.18908892571926117,
0.5893789529800415,
-0.4831956624984741,
-0.25311359763145447,
0.0503125824034214,
-0.037071049213409424,
-0.1145578920841217,
0.02929721772670746,
0.1607622355222702,
0.08552613109350204,
-0.0990605279803276,
0.07839181274175644,
0.42903363704681396,
0.07837413996458054,
0.04569486528635025,
-0.24622958898544312,
-0.1808585375547409,
0.22457720339298248,
0.03091520071029663,
-0.1713448166847229,
0.07902853190898895,
0.2619319558143616,
0.05616098642349243,
0.02804422751069069,
-0.3400058150291443,
0.14545096457004547,
0.19515591859817505,
0.33123913407325745,
-0.16132642328739166,
-0.1434578150510788,
0.24710294604301453,
-0.40864309668540955,
0.1843581199645996,
0.11572976410388947,
0.361627459526062,
-0.14487531781196594,
0.0029637105762958527,
-0.4288193881511688,
-0.09242089837789536,
-0.08533722162246704,
-0.03767777606844902,
0.06950782984495163,
0.09063811600208282,
0.06854411959648132,
-0.16730563342571259,
-0.22225067019462585,
0.11700507998466492,
-0.30204761028289795,
0.05609985440969467,
-0.18788982927799225,
0.06197626143693924,
-0.28403085470199585,
-0.11223077774047852,
0.22809478640556335,
0.18706172704696655,
0.20362785458564758,
-0.01500997319817543,
-0.1789759397506714,
0.0905495136976242,
-0.4720057249069214,
0.3271068334579468,
0.045911043882369995,
0.16948187351226807,
0.023193463683128357,
-0.026097919791936874,
-0.21184656023979187,
-0.11862611770629883,
0.18914373219013214,
-0.15958642959594727,
-0.32982558012008667,
0.15665610134601593,
-0.022238533943891525,
0.008161164820194244,
0.16950006783008575,
0.012336524203419685,
0.28302568197250366,
-0.1977064460515976,
0.11460226029157639,
0.13609112799167633,
0.4101678729057312,
0.09705832600593567,
0.37629246711730957,
-0.03750362992286682,
-0.139716237783432,
-0.07505517452955246,
0.15518182516098022,
0.0004627462476491928,
0.1710679829120636,
0.07220088690519333,
0.025278333574533463,
-0.09470263868570328,
0.2884228229522705,
0.5951279997825623,
0.35346925258636475,
0.07945821434259415,
-0.05248225852847099,
-0.04475101828575134,
-0.1115134209394455,
-0.22755970060825348,
-0.016284100711345673,
-0.07748311758041382,
0.04854606091976166,
0.2117173969745636,
0.43869125843048096,
0.2605527639389038,
-0.13261163234710693,
-0.01688234694302082,
0.11479970067739487,
0.4540281295776367,
-0.19068242609500885,
0.266332745552063,
-0.09921854734420776,
-0.4326513111591339,
0.25927120447158813,
-0.2881087064743042,
-0.08621688187122345,
-0.18278421461582184,
-0.18338346481323242,
0.12537230551242828,
0.0859253853559494,
-0.11140725016593933,
0.1523824781179428,
0.35105255246162415,
-0.09527852386236191,
-0.27169257402420044,
-0.2880839705467224,
-0.10307908803224564,
-0.20516344904899597,
0.04893950745463371,
0.3304883539676666,
-0.11064367741346359,
0.4104601740837097,
0.3433223366737366,
0.06626521050930023,
-0.04624151438474655,
-0.32678037881851196,
-0.0032144710421562195,
-0.04425811022520065,
0.09379170089960098,
0.0913999155163765,
0.3395487666130066,
0.004957783967256546,
-0.5441511869430542,
0.18702395260334015,
0.058574043214321136,
-0.24736620485782623,
0.25977322459220886,
-0.03784012421965599,
-0.31450504064559937,
-0.4980628192424774,
0.010082259774208069,
-0.2758822739124298,
-0.3460386395454407,
0.2394309937953949,
0.33021262288093567,
0.23633964359760284,
0.5939531922340393,
0.018188927322626114,
0.13191567361354828,
0.3163865804672241,
0.1342409998178482,
0.03354417160153389,
-0.20578573644161224,
0.4849308729171753,
-0.2360694408416748,
-0.4347623586654663,
0.10699346661567688,
-0.13748374581336975,
0.5780161023139954,
-0.04567144066095352,
-0.3929758071899414,
-0.19886109232902527,
0.09783370047807693,
0.20639614760875702,
-0.06614221632480621,
-0.08298256993293762,
0.2729760408401489,
-0.19738008081912994,
0.039316438138484955,
-0.06291241943836212,
-0.2984917163848877,
0.15413407981395721,
0.6249303221702576,
0.2360731065273285,
-0.0714835599064827,
0.4156576693058014,
0.050727155059576035,
0.6994937658309937,
0.0851803570985794,
-0.3150876462459564,
0.452667772769928,
-0.031725890934467316,
0.177195742726326,
-0.13752251863479614,
-0.3402392268180847,
0.0954924076795578,
0.237472265958786,
-0.04053609445691109,
0.15654617547988892,
-0.028311729431152344,
-0.08319411426782608,
-0.4500623941421509,
0.2251792550086975,
-0.25933727622032166,
0.04975133761763573,
0.014600490219891071,
0.08145266771316528,
0.0388733446598053,
-0.09079229831695557,
-0.2421228587627411,
-0.3565264940261841,
-0.5098557472229004,
-0.1295813024044037,
0.2505680322647095,
-0.2341906726360321,
0.18313723802566528,
-0.652407705783844,
-0.10370753705501556,
-0.6693298816680908,
0.29620012640953064,
-0.14688852429389954,
0.275445818901062,
-0.21646232903003693,
0.18662288784980774,
0.13347949087619781,
-0.08640041947364807,
0.08926220238208771,
-0.4160813093185425,
-0.17348675429821014,
-0.09920832514762878,
0.2953800559043884,
-0.4609887897968292,
-0.04646923020482063,
-0.03333190828561783,
0.0832534208893776,
0.48458757996559143,
0.21635566651821136,
0.020407967269420624,
0.09795549511909485,
-0.17281484603881836,
-0.2555910646915436,
-0.16451434791088104,
-0.22752930223941803,
-0.03326965123414993,
-0.6557900309562683,
-0.34370648860931396,
-0.4793667197227478,
0.0711589902639389,
0.1532273292541504,
0.15192006528377533,
-0.07051819562911987,
0.22515353560447693,
0.11375264078378677,
0.49375730752944946,
0.017786361277103424,
-0.08321520686149597,
0.6168342232704163,
-0.12393531203269958,
-0.46655580401420593,
0.4901573956012726,
-0.06203443557024002,
0.38743916153907776,
0.07472115755081177,
-0.13771258294582367,
-0.15648922324180603,
-0.30095186829566956,
0.4412569999694824,
0.1783326119184494,
0.10966116189956665,
0.21357375383377075,
-0.13211598992347717,
0.052149541676044464,
-0.19166411459445953,
0.47335904836654663,
0.33841753005981445,
-0.09716370701789856,
-0.3771507740020752,
-0.13972985744476318,
0.44671115279197693,
-0.2157982885837555,
-0.00792153924703598,
0.23950056731700897,
-0.21200771629810333,
-0.28229597210884094,
0.21089628338813782,
0.17036598920822144,
1.136423945426941,
-0.07740247249603271,
0.37175992131233215,
0.13204941153526306,
-0.054556190967559814,
0.756166398525238,
-0.1896362453699112,
0.02476353570818901,
-0.24850235879421234,
0.1745956540107727,
-0.1003190279006958,
-0.04481516778469086,
-0.08898066729307175,
0.11526520550251007,
-0.22819115221500397,
0.05740367993712425,
-0.04674191027879715,
-0.16363725066184998,
0.007388378493487835,
0.541745126247406,
0.09941393882036209,
-0.3780415654182434,
-0.20321010053157806,
0.10226583480834961,
-0.33484190702438354,
0.3006332814693451,
-0.1681475043296814,
-0.23469935357570648,
-0.32431986927986145,
-0.16216182708740234,
-0.1864946484565735,
0.30506080389022827,
-0.23749369382858276,
0.08102436363697052,
0.05311499908566475,
-0.3184688687324524,
0.2553342878818512,
0.4358457326889038,
0.5033403635025024,
-0.10633139312267303,
-0.07909460365772247,
0.030860640108585358,
-0.13777166604995728,
-0.02995627373456955,
0.00021415879018604755,
0.07229562103748322,
0.17591863870620728,
-0.3124390244483948,
0.065276600420475,
0.29665830731391907,
-0.014302889816462994,
-0.3096221089363098,
-0.17401351034641266,
0.1471676081418991,
0.07625976204872131,
-0.14346034824848175,
-0.31247609853744507,
0.0992087796330452,
-0.17771460115909576,
-0.02474302425980568,
0.04121081903576851,
0.06617677956819534,
0.03593987599015236,
-0.0725613459944725,
0.0739264264702797,
-0.1873590499162674,
0.06512042880058289,
0.07385537773370743,
-0.1152709499001503,
-0.06169385835528374,
0.7477415800094604,
-0.06718678772449493,
0.09660480916500092,
-0.09921880066394806,
-0.23556292057037354,
-0.3396826982498169,
-0.18870624899864197,
-0.10450927913188934,
0.2684950828552246,
-0.045154228806495667,
0.0695589929819107,
0.6650158166885376,
0.3328905701637268,
0.1416175812482834,
0.16352134943008423,
-0.15161074697971344,
-0.33256766200065613,
-0.340668261051178,
-0.033449482172727585,
0.16924771666526794,
-0.08269958198070526,
0.19785895943641663,
0.20175224542617798,
0.3437700569629669,
-0.2551347017288208,
-0.17512626945972443,
-0.21311801671981812,
0.1651635468006134,
0.7187833786010742,
-0.05416584759950638,
-0.061099231243133545,
-0.019157908856868744,
0.003239557147026062,
-0.04416728764772415,
-0.16698211431503296,
-0.13342903554439545,
-0.37222737073898315,
0.16226866841316223,
0.4754083454608917,
-0.20718491077423096,
-0.07411116361618042,
-0.2015528529882431,
-0.10357825458049774,
-0.1250372678041458,
-0.31520020961761475,
0.040920644998550415,
-0.05833368003368378,
0.21087133884429932,
-0.24682410061359406,
0.3526257276535034,
-0.08808554708957672,
0.1950051486492157,
0.019292578101158142,
0.18320316076278687,
0.07253194600343704,
-0.024480484426021576,
0.16411766409873962,
0.05056805908679962,
-0.3545888662338257,
-0.031485170125961304,
-0.20351509749889374,
-0.09130924195051193,
0.047117121517658234,
-0.4444262981414795,
0.11381736397743225,
-0.16836635768413544,
0.04783853143453598,
0.02164560556411743,
-0.5189085602760315,
0.14512787759304047,
0.38480237126350403,
0.12011395394802094,
0.04832223057746887,
0.12300294637680054,
0.16844356060028076,
0.21478132903575897,
-0.010158903896808624,
0.23202203214168549,
0.062191080302000046,
-0.27599048614501953,
-0.05973254144191742,
-0.17764469981193542,
-0.10463622957468033,
-0.2630261182785034,
0.0702865868806839,
-0.1269129514694214,
-0.40820831060409546,
-0.051093656569719315,
0.13153283298015594,
0.17131702601909637,
-0.11073245853185654,
0.1462876796722412,
-0.21450954675674438,
0.09462955594062805,
0.02808244712650776,
-0.08880074322223663,
0.2282724678516388,
-0.2685781419277191,
0.0781366154551506,
-0.10730597376823425,
-0.04195278882980347,
0.3354443311691284,
0.14839155972003937,
0.6253676414489746,
-0.30057933926582336,
-0.02767845056951046,
-0.24202121794223785,
0.14442509412765503,
-0.0007230639457702637,
0.176571786403656,
-0.6177634000778198,
-0.02887548878788948,
0.05070360004901886,
-0.10464958846569061,
0.028326144441962242,
-0.34961193799972534,
-0.06082187592983246,
0.30982959270477295,
-0.1774180382490158,
0.11428431421518326,
-0.15285083651542664,
0.21429786086082458,
0.14840368926525116,
-0.15133216977119446,
0.42992523312568665,
0.05962705612182617,
-0.10391737520694733,
-0.08217445015907288,
0.07708925753831863,
0.514744222164154,
0.582910418510437,
0.11593963205814362,
0.31674543023109436,
0.21503444015979767,
0.028208373114466667,
0.07165069878101349,
0.21679043769836426,
0.43436098098754883,
0.2830864191055298,
0.12656116485595703,
0.047754548490047455,
-0.1217484325170517,
0.07318644225597382,
0.05191686376929283,
0.12302322685718536,
-0.27411791682243347,
0.3007913827896118,
0.001267947256565094,
-0.37161657214164734,
-0.192124605178833,
0.3825390338897705,
-0.46314090490341187,
0.03657793626189232,
0.21874840557575226,
0.2108299285173416,
0.3433954417705536,
-0.27728167176246643,
0.03888614475727081,
-0.16345824301242828,
0.436238557100296,
0.4967517554759979,
-0.0677364245057106,
-0.12502843141555786,
-0.28918662667274475,
-0.4506284296512604,
0.18131105601787567,
-0.19864442944526672,
-0.22995272278785706,
-0.35685494542121887,
0.19610658288002014,
0.04848911613225937,
-0.10085813701152802,
0.053834907710552216,
0.09990924596786499,
-0.21706204116344452,
-0.016972936689853668,
-0.4612075686454773,
0.06106337159872055,
-0.15878146886825562,
-0.01481538824737072,
-0.028728902339935303,
-0.14931774139404297,
0.0639244019985199,
0.07336713373661041,
0.04292559623718262,
0.02961556613445282,
0.21092569828033447,
0.10708600282669067,
0.38921472430229187,
0.47182729840278625,
-0.10158546268939972,
0.7334182262420654,
0.08890098333358765,
-0.0027491040527820587,
0.012416567653417587,
-0.05101092532277107,
-0.17123188078403473,
0.029724419116973877,
0.14156678318977356,
0.4371802806854248,
-0.0835019201040268,
0.3541299104690552,
-0.21917669475078583,
0.05322762951254845,
-0.0519561730325222,
-0.5288751125335693,
0.10355675965547562,
-0.00581617746502161,
-0.03416029363870621,
0.2721140384674072,
0.40909668803215027,
0.11103549599647522,
0.11265715211629868,
-0.10881724953651428,
-0.4588083028793335,
-0.28008833527565,
0.39896130561828613,
-0.5402222275733948,
-0.30159831047058105,
0.19581717252731323,
0.23403993248939514,
-0.06005135923624039,
0.04783665016293526,
-0.3058381676673889,
-0.059672996401786804,
0.16777807474136353,
-0.21494102478027344,
-0.00905650109052658,
0.31976640224456787,
-0.47192636132240295,
0.07732565701007843,
-0.032319843769073486,
0.273898184299469,
0.20475369691848755,
-0.3582354485988617,
-0.03778167441487312,
-0.1672145426273346
] |
https://github.com/huggingface/datasets/issues/181 | Cannot upload my own dataset | New commands are
```
nlp-cli upload_dataset <path/to/dataset>
nlp-cli upload_metric <path/to/metric>
nlp-cli s3_datasets {rm, ls}
nlp-cli s3_metrics {rm, ls}
```
Closing this issue. | I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
``` | 22 | Cannot upload my own dataset
I look into `nlp-cli` and `user.py` to learn how to upload my own data.
It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
But I got this error.
```
2020-05-21 16:33:52.722464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
About to upload file /content/ttc/ttc_freq_extra.csv to S3 under filename ttc/ttc_freq_extra.csv and namespace korakot
Proceed? [Y/n] y
Uploading... This might take a while if files are large
Traceback (most recent call last):
File "/usr/local/bin/nlp-cli", line 33, in <module>
service.run()
File "/usr/local/lib/python3.6/dist-packages/nlp/commands/user.py", line 234, in run
token=token, filename=filename, filepath=filepath, organization=self.args.organization
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 141, in presign_and_upload
urls = self.presign(token, filename=filename, organization=organization)
File "/usr/local/lib/python3.6/dist-packages/nlp/hf_api.py", line 132, in presign
return PresignedUrl(**d)
TypeError: __init__() got an unexpected keyword argument 'cdn'
```
New commands are
```
nlp-cli upload_dataset <path/to/dataset>
nlp-cli upload_metric <path/to/metric>
nlp-cli s3_datasets {rm, ls}
nlp-cli s3_metrics {rm, ls}
```
Closing this issue. | [
0.1084665060043335,
-0.044079914689064026,
0.0504009984433651,
-0.02760537713766098,
0.138132244348526,
-0.18117070198059082,
0.32669156789779663,
-0.009185023605823517,
-0.19502247869968414,
0.1800151765346527,
-0.12995530664920807,
0.23764531314373016,
-0.23067624866962433,
0.291965514421463,
0.3679998517036438,
0.07485648989677429,
0.006218485534191132,
0.2890029549598694,
0.01184871792793274,
-0.10124002397060394,
-0.21110135316848755,
0.10817155241966248,
0.03599921613931656,
-0.0665363222360611,
-0.12294409424066544,
-0.17405103147029877,
-0.10020700842142105,
0.2709645926952362,
-0.2011130154132843,
-0.3351973295211792,
0.4402619004249573,
0.2242947369813919,
0.3215375244617462,
0.5771903991699219,
-0.00011768119293265045,
-0.05328431352972984,
0.13914427161216736,
-0.22553709149360657,
-0.6261972188949585,
-0.3673126697540283,
0.08496671169996262,
-0.1735265552997589,
0.08267300575971603,
-0.2572464644908905,
0.18322902917861938,
0.025091547518968582,
0.008598476648330688,
0.07702229917049408,
0.5234442353248596,
0.36876606941223145,
0.154951274394989,
0.0958213210105896,
-0.18301622569561005,
-0.09871860593557358,
0.029122356325387955,
0.18727988004684448,
-0.04247978329658508,
0.2965947985649109,
0.36872488260269165,
-0.39618468284606934,
0.30293774604797363,
-0.1861633062362671,
-0.008991852402687073,
-0.0887327790260315,
0.48444414138793945,
-0.022030655294656754,
0.00685080885887146,
-0.40278056263923645,
-0.008083105087280273,
0.1580434888601303,
0.2721641957759857,
-0.03827735036611557,
-0.34664639830589294,
-0.11687016487121582,
0.1563587188720703,
-0.4871675968170166,
0.24212101101875305,
0.283277690410614,
-0.4218556582927704,
-0.04651624336838722,
-0.2582417130470276,
0.3114124834537506,
-0.4107930660247803,
0.4234354496002197,
0.12531885504722595,
0.3503040373325348,
-0.026141155511140823,
0.0610152892768383,
0.25930115580558777,
-0.1453033983707428,
-0.021243542432785034,
0.0925709456205368,
0.017637968063354492,
0.28195831179618835,
-0.19193212687969208,
-0.1905704289674759,
-0.021574191749095917,
-0.2899375557899475,
-0.10397440195083618,
0.1091003343462944,
0.4545277953147888,
-0.1308465600013733,
-0.22314785420894623,
0.15165236592292786,
0.08718313276767731,
0.3312406539916992,
0.008624903857707977,
0.07960406690835953,
0.11092212796211243,
0.01273290440440178,
0.2880062758922577,
-0.0693008080124855,
-0.27576762437820435,
-0.07849974185228348,
-0.13718947768211365,
-0.048890382051467896,
0.2654901146888733,
0.0865570604801178,
0.0027185995131731033,
-0.08611766248941422,
0.07163922488689423,
0.03991120681166649,
-0.07255170494318008,
0.3346664309501648,
-0.09973806887865067,
-0.2767598330974579,
0.008246410638093948,
0.24410714209079742,
0.12901820242404938,
-0.2690316140651703,
0.07090892642736435,
0.3014501631259918,
-0.12323862314224243,
-0.14110568165779114,
0.41318556666374207,
0.0026035141199827194,
0.19098681211471558,
-0.0497686043381691,
0.17416974902153015,
-0.11572152376174927,
0.07259533554315567,
0.026877503842115402,
-0.1545821726322174,
0.026117458939552307,
0.23558557033538818,
0.3750022351741791,
-0.07226434350013733,
-0.5426658987998962,
-0.1255454421043396,
0.04687352478504181,
-0.37620729207992554,
-0.3481234908103943,
-0.44942307472229004,
0.09366775304079056,
0.03533300384879112,
-0.2343597114086151,
-0.2903655171394348,
-0.0844537615776062,
0.09920261800289154,
-0.2737710475921631,
-0.08804372698068619,
-0.01781938597559929,
-0.10808943212032318,
-0.14024388790130615,
0.11493652313947678,
0.05398008972406387,
-0.48611342906951904,
0.20890986919403076,
-0.06266934424638748,
0.5137913823127747,
0.3013725280761719,
0.2810112237930298,
-0.3043970465660095,
0.25999101996421814,
-0.06236653029918671,
0.1773788183927536,
0.5754057168960571,
-0.4743399918079376,
-0.2507370710372925,
0.03427904471755028,
-0.0365610271692276,
-0.10301307588815689,
0.05468665063381195,
0.16820453107357025,
0.08836285769939423,
-0.10266026854515076,
0.07413911074399948,
0.40953683853149414,
0.07595818489789963,
0.030012978240847588,
-0.22451412677764893,
-0.17478139698505402,
0.2542687654495239,
0.012387309223413467,
-0.1504034847021103,
0.07483947277069092,
0.2523055374622345,
0.08474501222372055,
0.03077039122581482,
-0.33520933985710144,
0.1500527262687683,
0.20149922370910645,
0.33596470952033997,
-0.13525721430778503,
-0.13722960650920868,
0.2380940318107605,
-0.4048444926738739,
0.19656231999397278,
0.12716268002986908,
0.35962817072868347,
-0.11083972454071045,
0.006236918270587921,
-0.42009249329566956,
-0.11388057470321655,
-0.09573781490325928,
-0.031772542744874954,
0.06666681170463562,
0.0963793694972992,
0.0702921450138092,
-0.1855904757976532,
-0.23020364344120026,
0.12882034480571747,
-0.3153885006904602,
0.0610581673681736,
-0.1971268504858017,
0.05917049199342728,
-0.2863607108592987,
-0.11160078644752502,
0.2181827425956726,
0.17532090842723846,
0.2073209285736084,
-0.01801915466785431,
-0.17255359888076782,
0.08949821442365646,
-0.46536678075790405,
0.3087373375892639,
0.012427110224962234,
0.1415526568889618,
0.03356895595788956,
-0.021583683788776398,
-0.1996210217475891,
-0.11788231134414673,
0.1772724688053131,
-0.1705971658229828,
-0.3431077003479004,
0.14997297525405884,
-0.03314923122525215,
0.019479043781757355,
0.166823610663414,
-0.002482302486896515,
0.27056747674942017,
-0.1924484372138977,
0.1081031784415245,
0.11901304125785828,
0.3931277096271515,
0.1005677580833435,
0.37359166145324707,
-0.06235010176897049,
-0.12617242336273193,
-0.08031881600618362,
0.17376305162906647,
0.014593619853258133,
0.15850797295570374,
0.0684889629483223,
0.033259306102991104,
-0.07810258865356445,
0.286007821559906,
0.6209808588027954,
0.3515610992908478,
0.09832146763801575,
-0.04840387776494026,
-0.050611890852451324,
-0.11802095919847488,
-0.22260472178459167,
-0.03233370929956436,
-0.08653303980827332,
0.0450492687523365,
0.2136896252632141,
0.429272323846817,
0.2628838121891022,
-0.13860444724559784,
0.002830352634191513,
0.11219204217195511,
0.44106993079185486,
-0.18067596852779388,
0.24720104038715363,
-0.11076143383979797,
-0.4309421181678772,
0.23817774653434753,
-0.28240883350372314,
-0.08930563926696777,
-0.16441914439201355,
-0.19531381130218506,
0.11842580139636993,
0.1135321706533432,
-0.12695875763893127,
0.16629987955093384,
0.3391779661178589,
-0.11040570586919785,
-0.2544940710067749,
-0.27940356731414795,
-0.0882849171757698,
-0.20852869749069214,
0.052959781140089035,
0.3282940983772278,
-0.11787300556898117,
0.4269642233848572,
0.3558061420917511,
0.06698235869407654,
-0.0482543408870697,
-0.34660592675209045,
-0.012719795107841492,
-0.06370146572589874,
0.07861366868019104,
0.08492837101221085,
0.34389036893844604,
-0.0008335113525390625,
-0.5517429709434509,
0.1905890703201294,
0.06303217262029648,
-0.2525031268596649,
0.2460184097290039,
-0.02194218523800373,
-0.3063017725944519,
-0.4941287636756897,
-0.007458776235580444,
-0.2783518433570862,
-0.3438790738582611,
0.2504080533981323,
0.35123640298843384,
0.2351839542388916,
0.6135790348052979,
0.02082943171262741,
0.13948358595371246,
0.3170113265514374,
0.15296348929405212,
0.03316979855298996,
-0.1874237060546875,
0.4657979905605316,
-0.253059983253479,
-0.43299925327301025,
0.11046834290027618,
-0.13290530443191528,
0.5748026371002197,
-0.04160178080201149,
-0.3659118413925171,
-0.19975851476192474,
0.09144090861082077,
0.18816472589969635,
-0.07725890725851059,
-0.06613492965698242,
0.285658597946167,
-0.18216541409492493,
0.042108096182346344,
-0.05911857634782791,
-0.31170493364334106,
0.15016894042491913,
0.6340498924255371,
0.2549777328968048,
-0.07658519595861435,
0.42161300778388977,
0.04242275282740593,
0.7029532790184021,
0.08945327997207642,
-0.3097898066043854,
0.4549664556980133,
-0.02821935899555683,
0.19479677081108093,
-0.13296857476234436,
-0.35792699456214905,
0.09596803784370422,
0.23466458916664124,
-0.030786124989390373,
0.13775259256362915,
-0.027219802141189575,
-0.06776422262191772,
-0.4466431438922882,
0.24750655889511108,
-0.25212863087654114,
0.06079145893454552,
-0.001671820878982544,
0.10914751887321472,
0.04245893284678459,
-0.10231339931488037,
-0.23655301332473755,
-0.36565423011779785,
-0.5041987895965576,
-0.1292748749256134,
0.24986596405506134,
-0.2540324926376343,
0.196914941072464,
-0.6588920950889587,
-0.12374027073383331,
-0.6575385332107544,
0.2880603075027466,
-0.14811068773269653,
0.259455144405365,
-0.21375088393688202,
0.17713740468025208,
0.13104259967803955,
-0.08934599161148071,
0.11717312783002853,
-0.41821685433387756,
-0.1867833435535431,
-0.09565195441246033,
0.2866274416446686,
-0.47739729285240173,
-0.053471412509679794,
-0.043761562556028366,
0.08510807156562805,
0.46540355682373047,
0.22015412151813507,
0.03126198798418045,
0.09527502954006195,
-0.1582922786474228,
-0.24406841397285461,
-0.1730845719575882,
-0.23456303775310516,
-0.04078027978539467,
-0.6392326354980469,
-0.337543785572052,
-0.48867690563201904,
0.04947779327630997,
0.15704035758972168,
0.16081547737121582,
-0.07531023025512695,
0.2124437689781189,
0.11879842728376389,
0.4977753758430481,
0.022433698177337646,
-0.06972028315067291,
0.6355297565460205,
-0.12254385650157928,
-0.44986554980278015,
0.48968544602394104,
-0.05355869233608246,
0.3719123303890228,
0.050603754818439484,
-0.12606185674667358,
-0.18033042550086975,
-0.2989444136619568,
0.46419769525527954,
0.18745748698711395,
0.1153121218085289,
0.2137036919593811,
-0.11608603596687317,
0.04945141077041626,
-0.18874646723270416,
0.47350189089775085,
0.3472863435745239,
-0.09278992563486099,
-0.37483134865760803,
-0.16618876159191132,
0.44636306166648865,
-0.18877369165420532,
-0.0016305968165397644,
0.2298571616411209,
-0.20053787529468536,
-0.28849026560783386,
0.19627487659454346,
0.17903289198875427,
1.135075330734253,
-0.09616318345069885,
0.3786777853965759,
0.13602018356323242,
-0.05242539197206497,
0.7858077883720398,
-0.18570801615715027,
0.03413783758878708,
-0.24208010733127594,
0.16550885140895844,
-0.102665975689888,
-0.03763774782419205,
-0.08714558929204941,
0.10502208769321442,
-0.239122673869133,
0.0672181248664856,
-0.057275936007499695,
-0.1655508577823639,
-0.006034396588802338,
0.5472075939178467,
0.09571055322885513,
-0.3948436379432678,
-0.19912922382354736,
0.10654103755950928,
-0.33136850595474243,
0.29732832312583923,
-0.1884973645210266,
-0.2347911149263382,
-0.2989426553249359,
-0.15512239933013916,
-0.1712501049041748,
0.3010401129722595,
-0.23888637125492096,
0.08907851576805115,
0.05478129908442497,
-0.32584255933761597,
0.2452925741672516,
0.42029932141304016,
0.5057651400566101,
-0.09477053582668304,
-0.07163000851869583,
0.015904512256383896,
-0.12948498129844666,
-0.058059338480234146,
-0.0169940534979105,
0.07856112718582153,
0.20451369881629944,
-0.3050251603126526,
0.06459299474954605,
0.2832258343696594,
-0.004202867858111858,
-0.2958987057209015,
-0.1927383840084076,
0.17007604241371155,
0.1059855967760086,
-0.1450621485710144,
-0.32288140058517456,
0.10752259194850922,
-0.1985766589641571,
-0.023928284645080566,
0.043140217661857605,
0.052143506705760956,
0.02309335023164749,
-0.06285258382558823,
0.07580910623073578,
-0.18461138010025024,
0.06752069294452667,
0.09131070226430893,
-0.08641165494918823,
-0.08536329865455627,
0.7531559467315674,
-0.06545592844486237,
0.10210259258747101,
-0.09430181980133057,
-0.23572054505348206,
-0.34444108605384827,
-0.16373026371002197,
-0.10431723296642303,
0.2887050211429596,
-0.04541238397359848,
0.10916142910718918,
0.6310181021690369,
0.3479662537574768,
0.11863772571086884,
0.14224323630332947,
-0.13004641234874725,
-0.33897319436073303,
-0.3504675626754761,
-0.02279360219836235,
0.17645163834095,
-0.09358379244804382,
0.19203655421733856,
0.20667418837547302,
0.33863088488578796,
-0.25417274236679077,
-0.18684646487236023,
-0.18249282240867615,
0.1629965603351593,
0.7249685525894165,
-0.04661892354488373,
-0.06739471852779388,
-0.02037668228149414,
0.001918857917189598,
-0.04075629264116287,
-0.16854192316532135,
-0.13428905606269836,
-0.3807846009731293,
0.16128723323345184,
0.479666143655777,
-0.20250077545642853,
-0.07540307939052582,
-0.20506326854228973,
-0.09480388462543488,
-0.11984419822692871,
-0.30565738677978516,
0.04392385482788086,
-0.04808367043733597,
0.22156155109405518,
-0.23215968906879425,
0.3371523320674896,
-0.0559341162443161,
0.18995903432369232,
0.030670665204524994,
0.17264893651008606,
0.07241877168416977,
-0.034020863473415375,
0.16806046664714813,
0.05748865008354187,
-0.35415589809417725,
-0.032752133905887604,
-0.1912262886762619,
-0.10384615510702133,
0.029014982283115387,
-0.4462992548942566,
0.10618840157985687,
-0.17603501677513123,
0.0497995987534523,
0.022434327751398087,
-0.4888646602630615,
0.13809168338775635,
0.38951027393341064,
0.11818037182092667,
0.03648409992456436,
0.11728770285844803,
0.1646391749382019,
0.21876661479473114,
-0.018171388655900955,
0.22868025302886963,
0.04256518557667732,
-0.26980364322662354,
-0.0645267516374588,
-0.1723543405532837,
-0.12308385223150253,
-0.2726885676383972,
0.0867752730846405,
-0.11697190999984741,
-0.3999551832675934,
-0.06926880776882172,
0.15473796427249908,
0.1715613603591919,
-0.09740515798330307,
0.1438145637512207,
-0.2051553726196289,
0.10718590021133423,
0.03388480469584465,
-0.08608280122280121,
0.2209549844264984,
-0.27044281363487244,
0.08013659715652466,
-0.08750225603580475,
-0.02710743248462677,
0.3488439619541168,
0.14098060131072998,
0.6430832147598267,
-0.3007907271385193,
-0.03844211995601654,
-0.23728394508361816,
0.12414363026618958,
-0.0008916668593883514,
0.19300581514835358,
-0.6118700504302979,
-0.016115702688694,
0.040175892412662506,
-0.10860534012317657,
0.03986580669879913,
-0.354142963886261,
-0.06759509444236755,
0.30947357416152954,
-0.17172743380069733,
0.113868348300457,
-0.16982093453407288,
0.20617780089378357,
0.14696474373340607,
-0.1484517753124237,
0.39706525206565857,
0.05424065515398979,
-0.103056401014328,
-0.07449620962142944,
0.08739249408245087,
0.5002301931381226,
0.6005567312240601,
0.11638952791690826,
0.32311075925827026,
0.201610267162323,
0.038133375346660614,
0.07256466895341873,
0.20181415975093842,
0.4283694922924042,
0.2745617926120758,
0.10998043417930603,
0.04795938730239868,
-0.12619179487228394,
0.06361710280179977,
0.04795245826244354,
0.09902055561542511,
-0.29639700055122375,
0.29422900080680847,
0.0014723017811775208,
-0.3734475374221802,
-0.19348110258579254,
0.38225844502449036,
-0.4880560636520386,
0.0280253104865551,
0.2486959993839264,
0.21553656458854675,
0.33565667271614075,
-0.2708441913127899,
0.03663018345832825,
-0.16707256436347961,
0.4374946355819702,
0.482622891664505,
-0.09399565309286118,
-0.12573982775211334,
-0.2834654152393341,
-0.4656837582588196,
0.17053553462028503,
-0.1989501565694809,
-0.22324541211128235,
-0.3570995330810547,
0.20041115581989288,
0.04286929592490196,
-0.1253056675195694,
0.07186217606067657,
0.0930996760725975,
-0.22871442139148712,
-0.058963850140571594,
-0.4724920392036438,
0.05648234859108925,
-0.13548052310943604,
-0.021281642839312553,
-0.02528080716729164,
-0.137778639793396,
0.050760988146066666,
0.05550025776028633,
0.034974582493305206,
0.02594171278178692,
0.21244016289710999,
0.10449182987213135,
0.3972402811050415,
0.4888581931591034,
-0.1169951856136322,
0.7418338060379028,
0.09344252198934555,
-0.010376179590821266,
0.01193920150399208,
-0.037465810775756836,
-0.1898796558380127,
0.05390319973230362,
0.12369830906391144,
0.45055848360061646,
-0.09263259917497635,
0.34791991114616394,
-0.2200065404176712,
0.07006774097681046,
-0.04054585099220276,
-0.5381631851196289,
0.11118822544813156,
-0.003120427019894123,
-0.031219709664583206,
0.26711276173591614,
0.4321092367172241,
0.12411181628704071,
0.11082868278026581,
-0.10501448065042496,
-0.4677984118461609,
-0.2764584422111511,
0.40621381998062134,
-0.5333334803581238,
-0.29643017053604126,
0.18773044645786285,
0.23693424463272095,
-0.08291321247816086,
0.03613553196191788,
-0.2994180917739868,
-0.07017689943313599,
0.16325369477272034,
-0.22941243648529053,
-0.012820586562156677,
0.32174599170684814,
-0.4839877784252167,
0.06313890218734741,
-0.036177389323711395,
0.24127407371997833,
0.22410348057746887,
-0.35660433769226074,
-0.03303779661655426,
-0.15160374343395233
] |
https://github.com/huggingface/datasets/issues/179 | [Feature request] separate split name and split instructions | If your dataset is a collection of sub-datasets, you should probably consider having one config per sub-dataset. For example for Glue, we have sst2, mnli etc.
If you want to have multiple train sets (for example one per stage). The easiest solution would be to name them `nlp.Split("train_stage1")`, `nlp.Split("train_stage2")`, etc. or something like that. | Currently, the name of an nlp.NamedSplit is parsed in arrow_reader.py and used as the instruction.
This makes it impossible to have several training sets, which can occur when:
- A dataset corresponds to a collection of sub-datasets
- A dataset was built in stages, adding new examples at each stage
Would it be possible to have two separate fields in the Split class, a name /instruction and a unique ID that is used as the key in the builder's split_dict ? | 54 | [Feature request] separate split name and split instructions
Currently, the name of an nlp.NamedSplit is parsed in arrow_reader.py and used as the instruction.
This makes it impossible to have several training sets, which can occur when:
- A dataset corresponds to a collection of sub-datasets
- A dataset was built in stages, adding new examples at each stage
Would it be possible to have two separate fields in the Split class, a name /instruction and a unique ID that is used as the key in the builder's split_dict ?
If your dataset is a collection of sub-datasets, you should probably consider having one config per sub-dataset. For example for Glue, we have sst2, mnli etc.
If you want to have multiple train sets (for example one per stage). The easiest solution would be to name them `nlp.Split("train_stage1")`, `nlp.Split("train_stage2")`, etc. or something like that. | [
0.043388914316892624,
-0.198110893368721,
0.030185792595148087,
0.21069124341011047,
0.1068333089351654,
0.08471900969743729,
0.549275815486908,
0.19509577751159668,
-0.014409476891160011,
0.15259361267089844,
0.0023246072232723236,
0.45175233483314514,
-0.27085140347480774,
0.3255721926689148,
0.019077958539128304,
-0.4061383306980133,
-0.06452716141939163,
0.06130611523985863,
0.23302070796489716,
0.10228583216667175,
0.09767566621303558,
0.22732265293598175,
-0.03829368203878403,
0.2814406752586365,
-0.23800937831401825,
-0.2281857430934906,
-0.20587792992591858,
-0.16539832949638367,
0.018803222104907036,
-0.4043419063091278,
0.1754712015390396,
0.1728925257921219,
-0.2417057603597641,
0.03427813947200775,
-0.00011900685785803944,
-0.1262153685092926,
0.21351443231105804,
-0.009097915142774582,
-0.1567249447107315,
-0.17348860204219818,
-0.5583314895629883,
-0.4940270185470581,
0.4417521059513092,
-0.5981582403182983,
-0.004088187590241432,
-0.06665784120559692,
-0.009362993761897087,
0.2533454895019531,
0.5818644165992737,
-0.16109618544578552,
0.09534082561731339,
-0.3728165924549103,
-0.0064572542905807495,
0.12188389152288437,
0.30312296748161316,
0.1706283688545227,
-0.32061243057250977,
-0.33287787437438965,
-0.19216209650039673,
0.01641998067498207,
-0.014343135058879852,
0.2186739593744278,
0.0672658309340477,
-0.14753015339374542,
0.12505751848220825,
0.20889079570770264,
-0.18132513761520386,
-0.16720527410507202,
-0.06251548230648041,
0.3708769381046295,
-0.165843665599823,
-0.1862097680568695,
-0.21817892789840698,
-0.7446471452713013,
0.192808598279953,
-0.3991025388240814,
0.009476587176322937,
0.2820800840854645,
-0.02325771376490593,
0.056905366480350494,
0.2280941605567932,
-0.3026104271411896,
-0.17334744334220886,
0.07937277853488922,
0.15809093415737152,
0.614372968673706,
0.08293669670820236,
0.20643454790115356,
0.19808414578437805,
0.0196453295648098,
0.19974549114704132,
0.13025815784931183,
-0.04197729006409645,
0.18368537724018097,
-0.2608940303325653,
-0.3455762267112732,
-0.39284220337867737,
-0.08230053633451462,
-0.21530193090438843,
0.1477324217557907,
0.2048051804304123,
-0.037261031568050385,
0.08624116331338882,
0.1348695158958435,
0.2460688203573227,
0.07950559258460999,
0.430012971162796,
0.6358774900436401,
0.11269094794988632,
-0.01923733949661255,
-0.360803484916687,
-0.02425123006105423,
-0.06769773364067078,
0.061923712491989136,
-0.17635348439216614,
0.10095915198326111,
-0.09962873160839081,
0.23635709285736084,
-0.0581112802028656,
-0.2936745285987854,
-0.11544933915138245,
-0.29221248626708984,
0.27776002883911133,
-0.007407099008560181,
0.13234083354473114,
0.0555955171585083,
-0.3250805139541626,
0.13766491413116455,
-0.19032758474349976,
-0.4007329046726227,
-0.10605251789093018,
0.12324117124080658,
-0.3039294183254242,
0.2852862775325775,
-0.025047605857253075,
0.08957436680793762,
0.139749675989151,
-0.0239226296544075,
-0.17118701338768005,
-0.26183968782424927,
0.19998784363269806,
-0.030773375183343887,
0.2510841488838196,
0.0799311101436615,
0.016892150044441223,
0.05753538757562637,
-0.09818610548973083,
-0.11058638989925385,
-0.3132472336292267,
-0.004342339932918549,
-0.15221214294433594,
-0.3459358811378479,
0.14371636509895325,
0.05959426239132881,
0.14884132146835327,
0.06756255030632019,
0.28562501072883606,
0.6215516924858093,
0.347048819065094,
-0.11526219546794891,
0.13643139600753784,
0.05871979892253876,
-0.22138524055480957,
-0.2414395958185196,
-0.02082010544836521,
-0.055000826716423035,
0.04045463725924492,
-0.4513779878616333,
-0.2863801419734955,
0.10820047557353973,
-0.10519058257341385,
0.09117934107780457,
-0.22937315702438354,
0.11082299053668976,
-0.026686040684580803,
0.600189208984375,
0.7154178023338318,
-0.2713155448436737,
0.07817188650369644,
0.33046507835388184,
0.07260444760322571,
-0.34571951627731323,
0.4756770133972168,
0.0852038636803627,
0.1321296989917755,
-0.05762256309390068,
-0.3968377113342285,
0.18206700682640076,
-0.38011738657951355,
-0.1711622029542923,
0.20397420227527618,
-0.5321476459503174,
0.16839471459388733,
-0.09095190465450287,
-0.05552608147263527,
-0.3709447383880615,
0.02002197504043579,
0.2963106632232666,
0.46555712819099426,
0.03446836769580841,
0.23717832565307617,
-0.17417502403259277,
-0.07773013412952423,
0.28939032554626465,
-0.17316144704818726,
-0.36931225657463074,
-0.27011463046073914,
-0.010613486170768738,
-0.1732831746339798,
0.05678073689341545,
0.013177722692489624,
-0.40739625692367554,
0.043092742562294006,
-0.27191102504730225,
-0.16464731097221375,
-0.28500720858573914,
0.046643905341625214,
-0.2125971019268036,
-0.05866728723049164,
-0.34646645188331604,
-0.33430343866348267,
0.17123740911483765,
-0.0637914389371872,
0.28379327058792114,
-0.31552478671073914,
-0.1585671454668045,
0.1928495317697525,
0.008334740065038204,
-0.23998507857322693,
0.5741865038871765,
0.2506142258644104,
-0.025338763371109962,
0.0648970976471901,
0.35172754526138306,
0.38948309421539307,
-0.07242327928543091,
0.023375311866402626,
-0.12618188560009003,
0.25394028425216675,
-0.06732706725597382,
-0.08393135666847229,
-0.10601688921451569,
-0.2638683617115021,
-0.14377805590629578,
-0.10177119821310043,
0.5019598007202148,
0.12187337875366211,
0.5909390449523926,
0.2901533842086792,
0.05820636451244354,
-0.06445089727640152,
-0.25854024291038513,
-0.1919446587562561,
-0.4637323319911957,
-0.2635042667388916,
-0.37583598494529724,
0.08257988095283508,
-0.043832436203956604,
-0.2890101671218872,
0.24587520956993103,
0.4475729167461395,
0.14510788023471832,
0.01608213409781456,
-0.23104313015937805,
0.11973906308412552,
0.17330697178840637,
-0.2040422409772873,
0.7559658885002136,
0.1979500949382782,
0.16951493918895721,
-0.09351575374603271,
0.05726432055234909,
-0.04233295097947121,
-0.18957491219043732,
0.27606847882270813,
0.2820304036140442,
0.07955451309680939,
-0.027139633893966675,
-0.16981947422027588,
-0.14319168031215668,
0.10303781181573868,
-0.03333811089396477,
0.22930604219436646,
-0.32859787344932556,
-0.08614987134933472,
-0.07723227888345718,
-0.12501002848148346,
-0.33749672770500183,
-0.6012640595436096,
-0.031781863421201706,
-0.23478984832763672,
-0.24172693490982056,
0.15794692933559418,
-0.08859357237815857,
-0.21088071167469025,
0.14174984395503998,
-0.13971684873104095,
0.13323985040187836,
-0.37389951944351196,
0.039972033351659775,
0.14731816947460175,
-0.38086020946502686,
-0.06988393515348434,
0.02591230720281601,
0.05599711835384369,
0.034937791526317596,
0.26271501183509827,
0.3256538510322571,
-0.280883252620697,
0.1503276228904724,
-0.335971474647522,
0.17685173451900482,
-0.3270226716995239,
-0.28942108154296875,
0.22199629247188568,
-0.3101726770401001,
-0.004219852387905121,
-0.46895065903663635,
0.3010503053665161,
-0.1061420813202858,
-0.10014080256223679,
-0.3176913857460022,
0.32188063859939575,
0.21165882050991058,
-0.12713532149791718,
-0.31906259059906006,
-0.4289039671421051,
-0.14181466400623322,
0.34559130668640137,
-0.07541993260383606,
0.29651618003845215,
0.09804403781890869,
-0.42088618874549866,
-0.029327325522899628,
-0.09281198680400848,
-0.11690005660057068,
0.04345462843775749,
0.1445825845003128,
-0.08969876170158386,
-0.41021329164505005,
0.15662699937820435,
0.05233420804142952,
-0.1368255913257599,
0.33396780490875244,
-0.17611588537693024,
-0.011461332440376282,
0.18883337080478668,
-0.013530848547816277,
-0.034934185445308685,
0.035726144909858704,
0.11508945375680923,
0.15593788027763367,
0.2736527621746063,
0.06651613116264343,
-0.07385837286710739,
-0.23240259289741516,
0.4348661005496979,
0.15245786309242249,
0.15153172612190247,
-0.0900646522641182,
0.024157926440238953,
-0.07993441075086594,
0.6646888256072998,
0.2682938277721405,
0.19962088763713837,
-0.1777927577495575,
-0.0047391075640916824,
-0.34178397059440613,
0.0782979354262352,
-0.21145600080490112,
0.1659894585609436,
-0.003022134304046631,
-0.2993083596229553,
0.3410925269126892,
0.030007313936948776,
-0.061492741107940674,
-0.25075435638427734,
-0.06884309649467468,
-0.03625013306736946,
-0.5644195675849915,
0.0686144083738327,
-0.18404866755008698,
0.21568161249160767,
-0.19991736114025116,
0.05245441198348999,
0.003842836245894432,
0.06245703995227814,
-0.14635202288627625,
-0.15383009612560272,
-0.1487346589565277,
-0.07147318869829178,
-0.11421895027160645,
-0.6203206181526184,
-0.053815729916095734,
-0.042243584990501404,
0.2887144386768341,
-0.1428101807832718,
-0.021646961569786072,
-0.22285938262939453,
0.2955179214477539,
0.30176863074302673,
0.2860284447669983,
-0.09012575447559357,
-0.16662849485874176,
0.09333692491054535,
0.04214923828840256,
0.19225487112998962,
-0.19830764830112457,
0.09100930392742157,
0.029229935258626938,
0.07483071833848953,
0.0393587127327919,
-0.572121798992157,
-0.29482290148735046,
0.5887439250946045,
-0.24235469102859497,
-0.3340775668621063,
0.03839493915438652,
0.03843754157423973,
0.13238531351089478,
0.07342898845672607,
-0.040468014776706696,
0.10366358608007431,
0.12703490257263184,
0.13721337914466858,
0.08338874578475952,
-0.032854288816452026,
-0.23436832427978516,
0.08977630734443665,
0.13432177901268005,
0.021047186106443405,
-0.05372077226638794,
0.08779174089431763,
0.29639896750450134,
0.265729695558548,
-0.3124951422214508,
0.4403763711452484,
-0.4000658392906189,
-0.09892058372497559,
0.009537859819829464,
-0.21707414090633392,
0.538526713848114,
0.3315562605857849,
0.1370118260383606,
0.44719982147216797,
0.005818815901875496,
0.08080242574214935,
-0.20520927011966705,
-0.06846999377012253,
0.2784636616706848,
-0.1718561351299286,
-0.4090304970741272,
-0.7786413431167603,
0.39444875717163086,
0.09553095698356628,
-0.1922818124294281,
0.2213871330022812,
0.1355135291814804,
-0.40848296880722046,
0.575567901134491,
0.01621134579181671,
0.884846031665802,
-0.07890202105045319,
0.21045660972595215,
-0.05240240693092346,
-0.2898176312446594,
0.6745566725730896,
-0.09591862559318542,
0.13303452730178833,
-0.3664886951446533,
0.2945716679096222,
0.057935670018196106,
0.10396677255630493,
0.23142299056053162,
0.4899129271507263,
0.0067724622786045074,
0.23215807974338531,
0.08443000912666321,
0.2629137337207794,
-0.3335978090763092,
0.33951884508132935,
0.14325380325317383,
-0.11598354578018188,
-0.08670628815889359,
-0.04819542542099953,
0.001482393592596054,
-0.24703145027160645,
0.20888113975524902,
-0.19910165667533875,
0.016625676304101944,
0.17032156884670258,
-0.25539788603782654,
-0.006950175389647484,
-0.12027204781770706,
0.2119198739528656,
-0.12011604011058807,
-0.415666401386261,
0.39140909910202026,
0.17767199873924255,
0.23396167159080505,
-0.16502225399017334,
0.019226256757974625,
0.4578539729118347,
-0.042343251407146454,
0.09356638044118881,
-0.1717168092727661,
-0.01251368410885334,
0.3011681139469147,
0.053446538746356964,
0.027400396764278412,
0.031027600169181824,
0.018673676997423172,
-0.08838097751140594,
-0.22427859902381897,
0.23940733075141907,
0.44946640729904175,
-0.515265166759491,
0.20778274536132812,
0.031566496938467026,
0.001956336200237274,
-0.17893292009830475,
0.02122216485440731,
-0.21939076483249664,
-0.24939391016960144,
0.04010827839374542,
-0.17997564375400543,
-0.06843467801809311,
0.004961658269166946,
-0.319285124540329,
0.1781570017337799,
0.007905263453722,
0.38825592398643494,
-0.18148966133594513,
0.1604386866092682,
-0.23996278643608093,
0.14632421731948853,
0.15137812495231628,
-0.2061508595943451,
0.2905280292034149,
0.1530693769454956,
-0.26518458127975464,
0.13528470695018768,
-0.019382257014513016,
0.0580952987074852,
0.6687648892402649,
-0.1800166666507721,
0.03185361623764038,
-0.2208247184753418,
-0.04019639641046524,
-0.10357333719730377,
0.09732288867235184,
0.0068293847143650055,
0.4960913062095642,
-0.12097837775945663,
0.40659427642822266,
-0.1664101928472519,
-0.09653301537036896,
0.20132718980312347,
0.25393733382225037,
-0.10842792689800262,
0.017032146453857422,
0.15272291004657745,
0.1292618364095688,
0.020380837842822075,
-0.05497113615274429,
0.1774236112833023,
-0.08827248215675354,
-0.3262885808944702,
0.11676814407110214,
0.09450903534889221,
0.20274858176708221,
-0.36953088641166687,
-0.14116649329662323,
0.10343480110168457,
-0.15560398995876312,
0.20738093554973602,
0.06280753016471863,
0.26048657298088074,
0.5012200474739075,
0.27072247862815857,
0.010650262236595154,
-0.37880629301071167,
0.21698929369449615,
-0.12480489909648895,
0.3370317816734314,
0.25255095958709717,
0.3109065294265747,
-0.2106352150440216,
0.07289381325244904,
0.13318601250648499,
-0.05577515810728073,
0.1861095130443573,
-0.27954769134521484,
-0.07307413965463638,
0.036065809428691864,
-0.09714667499065399,
-0.14056943356990814,
0.21551014482975006,
0.4737994372844696,
0.13721752166748047,
-0.03496857360005379,
0.22364720702171326,
0.11047765612602234,
-0.07229302823543549,
0.21312935650348663,
0.2800595760345459,
-0.17977799475193024,
0.09948089718818665,
0.5531473755836487,
0.11321595311164856,
0.2622583508491516,
-0.4264291524887085,
-0.06307681649923325,
-0.10696753114461899,
-0.030634194612503052,
0.5049614906311035,
0.8284043073654175,
0.21459437906742096,
-0.06918095052242279,
0.4637245833873749,
-0.18284429609775543,
0.26808011531829834,
0.45255982875823975,
-0.18141058087348938,
0.3613757789134979,
0.3433874845504761,
-0.17254184186458588,
0.5454283952713013,
0.10762101411819458,
-0.3695584535598755,
0.04664392024278641,
-0.058181554079055786,
-0.24876540899276733,
-0.12223467230796814,
0.7737444639205933,
0.04387817531824112,
-0.3321119248867035,
0.17119184136390686,
0.3155762553215027,
0.1680946946144104,
-0.25017011165618896,
-0.1361531913280487,
0.11348176747560501,
-0.3541952073574066,
0.0006027892231941223,
-0.054300371557474136,
-0.22777579724788666,
0.35432401299476624,
0.08226707577705383,
0.30091047286987305,
-0.09902681410312653,
-0.06769798696041107,
0.21079182624816895,
0.4752942621707916,
-0.3517262637615204,
-0.13512469828128815,
-0.01743301749229431,
-0.29152241349220276,
0.1551801860332489,
-0.07194473594427109,
0.0081624835729599,
-0.13468003273010254,
-0.25497835874557495,
-0.2885667085647583,
0.2460688203573227,
-0.10548322647809982,
0.023284662514925003,
-0.06977830082178116,
0.12184923142194748,
0.29119667410850525,
0.21185970306396484,
-0.02308325469493866,
-0.03540932014584541,
-0.20721466839313507,
0.2606799006462097,
-0.018992993980646133,
-0.05991321802139282,
0.5498867034912109,
0.2398156374692917,
-0.187866672873497,
-0.025995541363954544,
0.22880128026008606,
-0.29212087392807007,
-0.01780359074473381,
0.35891595482826233,
-0.06609861552715302,
0.08894039690494537,
-0.16790629923343658,
-0.022721940651535988,
-0.021172359585762024,
0.4855484962463379,
-0.22243981063365936,
-0.20367199182510376,
-0.27540645003318787,
-0.3702969551086426,
-0.022414423525333405,
-0.14031383395195007,
-0.12521381676197052,
-0.2741914391517639,
-0.13138236105442047,
0.16895127296447754,
-0.15706154704093933,
-0.16794607043266296,
0.16192831099033356,
0.04043976590037346,
0.4329414367675781,
0.33852577209472656,
-0.23166562616825104,
0.0057669468224048615,
-0.02158721536397934,
0.14577631652355194,
0.1738491654396057,
0.13576942682266235,
-0.07442143559455872,
0.3656339645385742,
-0.2971503734588623,
0.15661509335041046,
-0.022885922342538834,
0.5849363803863525,
0.13453072309494019,
0.0016774162650108337,
-0.02073596976697445,
0.2275300770998001,
0.029862627387046814,
0.03711678087711334,
0.040696509182453156,
0.012698505073785782,
-0.5554834008216858,
0.4114270806312561,
0.06802884489297867,
0.1626555323600769,
-0.27482008934020996,
0.41206029057502747,
-0.14148388803005219,
0.0037246302235871553,
-0.23200519382953644,
0.10678331553936005,
-0.01392391137778759,
0.19690781831741333,
-0.02301153540611267,
0.29645177721977234,
0.37596166133880615,
0.2861540913581848,
-0.1174602061510086,
-0.06586804240942001,
-0.13472887873649597,
-0.3783159852027893,
0.16204290091991425,
-0.036627303808927536,
-0.09991857409477234,
0.08973997831344604,
0.33894962072372437,
0.19934052228927612,
0.11615044623613358,
-0.7652568221092224,
-0.2747171223163605,
0.18879801034927368,
-0.24032485485076904,
-0.024294890463352203,
0.14281335473060608,
0.2829599678516388,
-0.16623690724372864,
0.01470622792840004,
-0.13825127482414246,
0.27970483899116516,
-0.06312927603721619,
0.030536312609910965,
-0.14354068040847778
] |
https://github.com/huggingface/datasets/issues/179 | [Feature request] separate split name and split instructions | Thanks for the tip! I ended up setting up three different versions of the dataset with their own configs.
for the named splits, I was trying with `nlp.Split("train-stage1")`, which fails. Changing to `nlp.Split("train_stage1")` works :) I looked for examples of what works in the code comments, it may be worth adding some examples of valid/invalid names in there? | Currently, the name of an nlp.NamedSplit is parsed in arrow_reader.py and used as the instruction.
This makes it impossible to have several training sets, which can occur when:
- A dataset corresponds to a collection of sub-datasets
- A dataset was built in stages, adding new examples at each stage
Would it be possible to have two separate fields in the Split class, a name /instruction and a unique ID that is used as the key in the builder's split_dict ? | 58 | [Feature request] separate split name and split instructions
Currently, the name of an nlp.NamedSplit is parsed in arrow_reader.py and used as the instruction.
This makes it impossible to have several training sets, which can occur when:
- A dataset corresponds to a collection of sub-datasets
- A dataset was built in stages, adding new examples at each stage
Would it be possible to have two separate fields in the Split class, a name /instruction and a unique ID that is used as the key in the builder's split_dict ?
Thanks for the tip! I ended up setting up three different versions of the dataset with their own configs.
for the named splits, I was trying with `nlp.Split("train-stage1")`, which fails. Changing to `nlp.Split("train_stage1")` works :) I looked for examples of what works in the code comments, it may be worth adding some examples of valid/invalid names in there? | [
0.10458482801914215,
-0.09824596345424652,
0.027599211782217026,
0.22247891128063202,
0.11074329912662506,
0.1121133491396904,
0.5969955921173096,
0.23253045976161957,
-0.035822078585624695,
0.11198772490024567,
0.01879112422466278,
0.4395623803138733,
-0.21577893197536469,
0.25080645084381104,
-0.04807367920875549,
-0.3708149194717407,
-0.031473927199840546,
0.099583201110363,
0.3009316027164459,
0.110613614320755,
0.07535482197999954,
0.24139271676540375,
-0.04599466919898987,
0.2722318470478058,
-0.21119655668735504,
-0.1831187903881073,
-0.23876826465129852,
-0.15462404489517212,
0.02841603010892868,
-0.4011644721031189,
0.19092701375484467,
0.17102372646331787,
-0.2977710962295532,
0.11503446847200394,
-0.00012200132186990231,
-0.1493762731552124,
0.2697799801826477,
-0.008835399523377419,
-0.17719951272010803,
-0.23157073557376862,
-0.5108581781387329,
-0.47503483295440674,
0.4412977993488312,
-0.6071307063102722,
0.006469763815402985,
-0.16628794372081757,
0.009862657636404037,
0.23457130789756775,
0.5989477634429932,
-0.14206349849700928,
0.07940220832824707,
-0.39332544803619385,
0.004251584410667419,
0.05900344252586365,
0.2985043227672577,
0.25531595945358276,
-0.35816827416419983,
-0.3896653950214386,
-0.13251174986362457,
0.019385769963264465,
0.013584814965724945,
0.19017522037029266,
0.04804027080535889,
-0.15089289844036102,
0.05642222985625267,
0.18820162117481232,
-0.24059054255485535,
-0.10517488420009613,
-0.031474657356739044,
0.3205353021621704,
-0.14700540900230408,
-0.1331748366355896,
-0.22489915788173676,
-0.7789202332496643,
0.12296392768621445,
-0.44449716806411743,
0.023178912699222565,
0.3083992302417755,
-0.08555446565151215,
0.0007131583988666534,
0.15985266864299774,
-0.2577974796295166,
-0.15868929028511047,
0.07997286319732666,
0.1872967928647995,
0.5755347013473511,
0.042686834931373596,
0.21303340792655945,
0.1306547373533249,
0.05146577209234238,
0.24592836201190948,
0.09748344123363495,
0.03707391396164894,
0.14819671213626862,
-0.2402217537164688,
-0.34626346826553345,
-0.36292824149131775,
-0.06122704595327377,
-0.24780452251434326,
0.07276201248168945,
0.1947951763868332,
-0.09304316341876984,
0.03792031481862068,
0.10942426323890686,
0.33250829577445984,
0.0307522751390934,
0.36637812852859497,
0.5928639769554138,
0.09704606235027313,
0.0739007443189621,
-0.33025893568992615,
-0.018299344927072525,
-0.055823132395744324,
0.10930235683917999,
-0.2353014200925827,
0.08426624536514282,
-0.10003908723592758,
0.16355499625205994,
-0.045883048325777054,
-0.25977039337158203,
-0.09913961589336395,
-0.24285975098609924,
0.22444310784339905,
0.03780568391084671,
0.11807219684123993,
0.03906617313623428,
-0.3129241466522217,
0.20334045588970184,
-0.12280918657779694,
-0.4388540983200073,
-0.08893860876560211,
0.09969562292098999,
-0.3002474009990692,
0.2296498417854309,
0.10692672431468964,
0.1424671858549118,
0.18240663409233093,
0.008428710512816906,
-0.14765872061252594,
-0.24537387490272522,
0.15634943544864655,
0.006643891334533691,
0.23175549507141113,
0.04239439591765404,
0.03246494010090828,
0.05623100697994232,
-0.03774191066622734,
-0.07236993312835693,
-0.30212584137916565,
0.017728086560964584,
-0.07856012135744095,
-0.3099417984485626,
0.18636199831962585,
0.040432706475257874,
0.1440340131521225,
0.0619366429746151,
0.36202529072761536,
0.6019584536552429,
0.4055771231651306,
-0.16478456556797028,
0.10734278708696365,
0.03777235746383667,
-0.2596316337585449,
-0.19345679879188538,
-0.04369520768523216,
-0.013956189155578613,
-0.010729439556598663,
-0.4486927092075348,
-0.38156411051750183,
0.16156989336013794,
-0.1280699074268341,
0.07277113199234009,
-0.14765974879264832,
0.05844838172197342,
-0.0028754714876413345,
0.6331416368484497,
0.5671981573104858,
-0.2285178154706955,
0.08923420310020447,
0.33646729588508606,
0.11590470373630524,
-0.3352690041065216,
0.48383769392967224,
0.05015658214688301,
0.1074584349989891,
-0.10666864365339279,
-0.42390814423561096,
0.18046195805072784,
-0.5068798065185547,
-0.22542394697666168,
0.1737489402294159,
-0.5565367937088013,
0.1767486333847046,
-0.07062986493110657,
-0.03899857774376869,
-0.33048513531684875,
-0.002800464630126953,
0.2975156307220459,
0.484963595867157,
0.034014418721199036,
0.2780068516731262,
-0.193300262093544,
-0.06715768575668335,
0.26429852843284607,
-0.1216094046831131,
-0.3572371006011963,
-0.31178978085517883,
-0.04289236664772034,
-0.12129057198762894,
0.03108002245426178,
-0.037856221199035645,
-0.38954925537109375,
-0.012586912140250206,
-0.27908098697662354,
-0.16043080389499664,
-0.27749621868133545,
0.031025007367134094,
-0.2263089418411255,
-0.06190350279211998,
-0.3348512053489685,
-0.3435286283493042,
0.1144687682390213,
-0.08758200705051422,
0.2657090425491333,
-0.32785436511039734,
-0.16811028122901917,
0.2228049337863922,
-0.025595609098672867,
-0.18210676312446594,
0.6047660708427429,
0.28620004653930664,
-0.008092899806797504,
0.062073979526758194,
0.3274427056312561,
0.39119067788124084,
-0.030648797750473022,
0.005734089761972427,
-0.12919311225414276,
0.18323741853237152,
-0.1230173110961914,
-0.052457764744758606,
-0.043942611664533615,
-0.2799319326877594,
-0.20842567086219788,
-0.20216104388237,
0.5459465384483337,
0.02758134715259075,
0.6292759776115417,
0.29110682010650635,
0.04996940493583679,
-0.012831151485443115,
-0.33546561002731323,
-0.1722605675458908,
-0.5019679069519043,
-0.2116854041814804,
-0.41578930616378784,
0.11526750028133392,
-0.13372960686683655,
-0.2776995599269867,
0.23551073670387268,
0.43055224418640137,
0.17799270153045654,
0.03364701569080353,
-0.23415637016296387,
0.13413673639297485,
0.1435289978981018,
-0.19840002059936523,
0.6893718838691711,
0.1891099214553833,
0.15224871039390564,
-0.04077437147498131,
0.08033354580402374,
0.033018745481967926,
-0.18132691085338593,
0.2855430543422699,
0.2572939991950989,
0.08319474756717682,
-0.00174027681350708,
-0.1671253740787506,
-0.13735799491405487,
0.053016968071460724,
0.060680363327264786,
0.22533902525901794,
-0.33681875467300415,
-0.05381298437714577,
-0.07482229918241501,
-0.12956325709819794,
-0.31246545910835266,
-0.554850161075592,
-0.03342394158244133,
-0.18639399111270905,
-0.2262297421693802,
0.20903968811035156,
0.014331009238958359,
-0.21730944514274597,
0.15765073895454407,
-0.1592097282409668,
0.16644924879074097,
-0.4105944037437439,
0.08151502907276154,
0.05014517903327942,
-0.41217392683029175,
-0.03657117486000061,
0.022978369146585464,
0.06295384466648102,
0.013407085090875626,
0.2887689173221588,
0.36025840044021606,
-0.2948746085166931,
0.18425501883029938,
-0.37269872426986694,
0.18451961874961853,
-0.39978164434432983,
-0.2675513029098511,
0.22958457469940186,
-0.3035169839859009,
0.014626704156398773,
-0.4285724461078644,
0.3069131076335907,
-0.16745927929878235,
-0.13079622387886047,
-0.33435046672821045,
0.32829394936561584,
0.19106030464172363,
-0.17773805558681488,
-0.31340306997299194,
-0.4024410545825958,
-0.14577072858810425,
0.39054131507873535,
-0.06979222595691681,
0.27505964040756226,
0.07240894436836243,
-0.47120171785354614,
-0.028921205550432205,
-0.0028675044886767864,
-0.12118388712406158,
0.06887870281934738,
0.2207588255405426,
-0.07444769144058228,
-0.4078602194786072,
0.12987999618053436,
0.08459217846393585,
-0.12469129264354706,
0.3680254817008972,
-0.24733681976795197,
-0.06267524510622025,
0.2727823257446289,
0.0512867346405983,
-0.0616641566157341,
0.16137829422950745,
0.04686148464679718,
0.16062408685684204,
0.2921682298183441,
0.06726719439029694,
-0.1720879077911377,
-0.24137789011001587,
0.3609776198863983,
0.12154173851013184,
0.1340135782957077,
-0.07184866070747375,
0.09102082252502441,
-0.0506044365465641,
0.6642796397209167,
0.2965461015701294,
0.2599329948425293,
-0.15238459408283234,
0.0683135911822319,
-0.3416401743888855,
0.08138628304004669,
-0.2282859981060028,
0.14147549867630005,
-0.05142064392566681,
-0.3744940161705017,
0.3664928078651428,
0.03204856067895889,
-0.13655821979045868,
-0.26294875144958496,
-0.012271646410226822,
-0.08253288269042969,
-0.5328514575958252,
0.008546222932636738,
-0.18302999436855316,
0.26944786310195923,
-0.13070543110370636,
0.06471652537584305,
0.032201122492551804,
-0.03419853374361992,
-0.14848749339580536,
-0.19269607961177826,
-0.09611973911523819,
-0.14421384036540985,
-0.1351083666086197,
-0.5458652973175049,
-0.05232853442430496,
-0.01371203362941742,
0.24540723860263824,
-0.13100899755954742,
-0.04341259226202965,
-0.19963476061820984,
0.2979271411895752,
0.27644407749176025,
0.2861585021018982,
-0.07402962446212769,
-0.1080961674451828,
0.14678698778152466,
0.04686491936445236,
0.19412098824977875,
-0.1502501219511032,
0.07547254860401154,
0.025733720511198044,
0.040008898824453354,
0.02105630189180374,
-0.5988472700119019,
-0.2771078646183014,
0.5790029764175415,
-0.2179686576128006,
-0.3166865408420563,
0.02838323265314102,
0.054655272513628006,
0.1528545618057251,
0.08562319725751877,
-0.028498567640781403,
0.12638422846794128,
0.102929025888443,
0.0625976175069809,
0.13151976466178894,
-0.03761439770460129,
-0.18430200219154358,
0.12430372834205627,
0.12849843502044678,
0.00018762890249490738,
-0.08899036794900894,
0.15551355481147766,
0.23965558409690857,
0.2841665744781494,
-0.3276495933532715,
0.49771326780319214,
-0.3636684715747833,
-0.10032550990581512,
0.02168770134449005,
-0.21436487138271332,
0.5283656120300293,
0.41589781641960144,
0.14213867485523224,
0.3851136267185211,
0.04732169210910797,
0.04736083745956421,
-0.19367410242557526,
-0.11665048450231552,
0.3290862441062927,
-0.2601209878921509,
-0.46221598982810974,
-0.7009153366088867,
0.4129931628704071,
0.07184499502182007,
-0.22511830925941467,
0.2465706467628479,
0.1570991575717926,
-0.3763379156589508,
0.571111261844635,
-0.0197211354970932,
0.8757331967353821,
0.0014640577137470245,
0.1962801069021225,
0.01991446688771248,
-0.28456056118011475,
0.6315013766288757,
-0.015095246955752373,
0.10312175750732422,
-0.3777364492416382,
0.30199331045150757,
0.0610177144408226,
0.08488969504833221,
0.22855684161186218,
0.5355200171470642,
0.013650249689817429,
0.18368718028068542,
0.0637408047914505,
0.27864792943000793,
-0.2928551137447357,
0.3380335867404938,
0.20744100213050842,
-0.08355380594730377,
-0.14133700728416443,
-0.04221634939312935,
0.026887496933341026,
-0.2585872709751129,
0.1981571614742279,
-0.18899011611938477,
-0.02284853532910347,
0.1410934180021286,
-0.276981920003891,
0.06596143543720245,
-0.004031449090689421,
0.11964206397533417,
-0.1257592886686325,
-0.4483075737953186,
0.4320882558822632,
0.16505305469036102,
0.3249998092651367,
-0.18011312186717987,
-0.038074590265750885,
0.47148019075393677,
-0.05818856507539749,
0.09149451553821564,
-0.16750508546829224,
0.02509332448244095,
0.22142207622528076,
0.02951090782880783,
0.10628586262464523,
0.026310499757528305,
-0.02527446672320366,
-0.06378035992383957,
-0.2644971013069153,
0.21506088972091675,
0.4529537558555603,
-0.5559493899345398,
0.17467321455478668,
-0.012984134256839752,
0.052493173629045486,
-0.23507465422153473,
0.01745961606502533,
-0.23933292925357819,
-0.21969947218894958,
0.016380183398723602,
-0.18049491941928864,
-0.04825238510966301,
-0.02668430283665657,
-0.2955889403820038,
0.23804041743278503,
-0.015308177098631859,
0.42816048860549927,
-0.11671416461467743,
0.1651087999343872,
-0.2321612536907196,
0.07606162875890732,
0.17264424264431,
-0.26263248920440674,
0.28448647260665894,
0.11356765031814575,
-0.27455276250839233,
0.15061388909816742,
-0.015604149550199509,
0.052263043820858,
0.6398313641548157,
-0.15392321348190308,
0.015465021133422852,
-0.20868000388145447,
0.004173249006271362,
-0.06663264334201813,
0.06332933902740479,
-0.04518792778253555,
0.46698451042175293,
-0.1915590614080429,
0.4138619601726532,
-0.13755114376544952,
-0.01859290339052677,
0.2807840406894684,
0.2623925507068634,
-0.15228036046028137,
0.009632933884859085,
0.19519390165805817,
0.07528987526893616,
0.0053584277629852295,
-0.006513435393571854,
0.2042776346206665,
-0.060487858951091766,
-0.31543147563934326,
0.12557697296142578,
0.1368718445301056,
0.19400639832019806,
-0.3965693712234497,
-0.16864928603172302,
0.07181931287050247,
-0.15368957817554474,
0.1787271946668625,
0.0668719932436943,
0.28282541036605835,
0.4819812774658203,
0.305769681930542,
0.11160007119178772,
-0.36445021629333496,
0.184103861451149,
-0.1227378249168396,
0.3808993101119995,
0.2149304449558258,
0.2762942910194397,
-0.16513989865779877,
0.09467662870883942,
0.1048569604754448,
-0.04907936602830887,
0.1903131604194641,
-0.3088618218898773,
0.013765502721071243,
0.032846011221408844,
-0.030747124925255775,
-0.14969176054000854,
0.2588711380958557,
0.5672738552093506,
0.12643210589885712,
-0.002587677910923958,
0.22976338863372803,
0.08614946156740189,
-0.09101273119449615,
0.25636425614356995,
0.28159111738204956,
-0.15940628945827484,
0.08424220979213715,
0.554146409034729,
0.12478646636009216,
0.265510231256485,
-0.4000856280326843,
-0.03358306735754013,
-0.05661609396338463,
-0.04436315596103668,
0.5013856887817383,
0.8824547529220581,
0.20604358613491058,
-0.01995519921183586,
0.4297121465206146,
-0.19077296555042267,
0.24227681756019592,
0.49159663915634155,
-0.17309698462486267,
0.33046823740005493,
0.31470343470573425,
-0.1226273626089096,
0.5907777547836304,
0.19488196074962616,
-0.4043387472629547,
-0.0030668526887893677,
-0.01677120476961136,
-0.2341189682483673,
-0.1521470695734024,
0.7617432475090027,
-0.011581952683627605,
-0.3254048824310303,
0.09411849081516266,
0.26180654764175415,
0.1801457405090332,
-0.2026377022266388,
-0.16221767663955688,
0.055055610835552216,
-0.35550713539123535,
0.00861787423491478,
-0.08892384171485901,
-0.20625172555446625,
0.35118499398231506,
0.03732084482908249,
0.26485681533813477,
-0.15261128544807434,
-0.03247227519750595,
0.17793399095535278,
0.5029484033584595,
-0.3182084858417511,
-0.10205728560686111,
-0.0024594739079475403,
-0.2936454713344574,
0.1971895545721054,
-0.0927339568734169,
-0.0056500546634197235,
-0.1405806541442871,
-0.3290480673313141,
-0.3568286597728729,
0.2028418779373169,
-0.14652951061725616,
-0.00009953230619430542,
0.036620721220970154,
0.12525323033332825,
0.30373483896255493,
0.18481414020061493,
-0.04838898032903671,
-0.026214726269245148,
-0.15177975594997406,
0.28189215064048767,
-0.07489265501499176,
-0.04711500555276871,
0.6482118368148804,
0.13582047820091248,
-0.18381652235984802,
0.02307552471756935,
0.17055025696754456,
-0.23163998126983643,
-0.0665179118514061,
0.3410789966583252,
-0.0482519268989563,
0.11722389608621597,
-0.11295083910226822,
-0.03360505402088165,
-0.03483925387263298,
0.40514323115348816,
-0.20681490004062653,
-0.28671562671661377,
-0.26146480441093445,
-0.42668598890304565,
-0.08076158910989761,
-0.07397984713315964,
-0.14937064051628113,
-0.24868905544281006,
-0.09933724254369736,
0.1381153166294098,
-0.08727002888917923,
-0.16104337573051453,
0.11898640543222427,
-0.07627593725919724,
0.3919476866722107,
0.362347275018692,
-0.22487092018127441,
0.006812773644924164,
-0.03206918388605118,
0.1607152670621872,
0.12720413506031036,
0.11123877018690109,
-0.1088411808013916,
0.34477901458740234,
-0.3298475742340088,
0.17180845141410828,
-0.07115071266889572,
0.5625976920127869,
0.20206698775291443,
-0.059335678815841675,
0.01238972321152687,
0.23775723576545715,
0.02985571324825287,
-0.06352116912603378,
0.035342663526535034,
-0.002857648301869631,
-0.539322018623352,
0.5002475380897522,
0.017259713262319565,
0.17635081708431244,
-0.23865637183189392,
0.44471848011016846,
-0.14618802070617676,
-0.04464228078722954,
-0.25948840379714966,
0.165245920419693,
-0.06921359896659851,
0.2242836058139801,
-0.06041460484266281,
0.3944738805294037,
0.4205290973186493,
0.2640945017337799,
-0.12344498932361603,
-0.02524401806294918,
-0.2117692530155182,
-0.35545220971107483,
0.2351643592119217,
-0.0745387151837349,
-0.13716071844100952,
0.10333753377199173,
0.3187505602836609,
0.171633780002594,
0.01623907871544361,
-0.7228697538375854,
-0.26910266280174255,
0.1650715470314026,
-0.2762211263179779,
0.020327262580394745,
0.038657110184431076,
0.23195235431194305,
-0.23970797657966614,
0.013042990118265152,
-0.045807257294654846,
0.2986750900745392,
-0.07945685088634491,
0.06468236446380615,
-0.11545078456401825
] |
https://github.com/huggingface/datasets/issues/168 | Loading 'wikitext' dataset fails | Hi, make sure you have a recent version of pyarrow.
Are you using it in Google Colab? In this case, this error is probably the same as #128 | Loading the 'wikitext' dataset fails with Attribute error:
Code to reproduce (From example notebook):
import nlp
wikitext_dataset = nlp.load_dataset('wikitext')
Error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-d5d9df94b13c> in <module>()
11
12 # Load a dataset and print the first examples in the training set
---> 13 wikitext_dataset = nlp.load_dataset('wikitext')
14 print(wikitext_dataset['train'][0])
6 frames
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=download_mode,
519 ignore_verifications=ignore_verifications,
--> 520 save_infos=save_infos,
521 )
522
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
363 verify_infos = not save_infos and not ignore_verifications
364 self._download_and_prepare(
--> 365 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
366 )
367 # Sync info
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
416 try:
417 # Prepare split will record examples associated to the split
--> 418 self._prepare_split(split_generator, **prepare_split_kwargs)
419 except OSError:
420 raise OSError("Cannot find data file. " + (self.MANUAL_DOWNLOAD_INSTRUCTIONS or ""))
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _prepare_split(self, split_generator)
594 example = self.info.features.encode_example(record)
595 writer.write(example)
--> 596 num_examples, num_bytes = writer.finalize()
597
598 assert num_examples == num_examples, f"Expected to write {split_info.num_examples} but wrote {num_examples}"
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in finalize(self, close_stream)
173 def finalize(self, close_stream=True):
174 if self.pa_writer is not None:
--> 175 self.write_on_file()
176 self.pa_writer.close()
177 if close_stream:
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in write_on_file(self)
124 else:
125 # All good
--> 126 self._write_array_on_file(pa_array)
127 self.current_rows = []
128
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in _write_array_on_file(self, pa_array)
93 def _write_array_on_file(self, pa_array):
94 """Write a PyArrow Array"""
---> 95 pa_batch = pa.RecordBatch.from_struct_array(pa_array)
96 self._num_bytes += pa_array.nbytes
97 self.pa_writer.write_batch(pa_batch)
AttributeError: type object 'pyarrow.lib.RecordBatch' has no attribute 'from_struct_array' | 28 | Loading 'wikitext' dataset fails
Loading the 'wikitext' dataset fails with Attribute error:
Code to reproduce (From example notebook):
import nlp
wikitext_dataset = nlp.load_dataset('wikitext')
Error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-d5d9df94b13c> in <module>()
11
12 # Load a dataset and print the first examples in the training set
---> 13 wikitext_dataset = nlp.load_dataset('wikitext')
14 print(wikitext_dataset['train'][0])
6 frames
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=download_mode,
519 ignore_verifications=ignore_verifications,
--> 520 save_infos=save_infos,
521 )
522
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
363 verify_infos = not save_infos and not ignore_verifications
364 self._download_and_prepare(
--> 365 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
366 )
367 # Sync info
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
416 try:
417 # Prepare split will record examples associated to the split
--> 418 self._prepare_split(split_generator, **prepare_split_kwargs)
419 except OSError:
420 raise OSError("Cannot find data file. " + (self.MANUAL_DOWNLOAD_INSTRUCTIONS or ""))
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _prepare_split(self, split_generator)
594 example = self.info.features.encode_example(record)
595 writer.write(example)
--> 596 num_examples, num_bytes = writer.finalize()
597
598 assert num_examples == num_examples, f"Expected to write {split_info.num_examples} but wrote {num_examples}"
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in finalize(self, close_stream)
173 def finalize(self, close_stream=True):
174 if self.pa_writer is not None:
--> 175 self.write_on_file()
176 self.pa_writer.close()
177 if close_stream:
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in write_on_file(self)
124 else:
125 # All good
--> 126 self._write_array_on_file(pa_array)
127 self.current_rows = []
128
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in _write_array_on_file(self, pa_array)
93 def _write_array_on_file(self, pa_array):
94 """Write a PyArrow Array"""
---> 95 pa_batch = pa.RecordBatch.from_struct_array(pa_array)
96 self._num_bytes += pa_array.nbytes
97 self.pa_writer.write_batch(pa_batch)
AttributeError: type object 'pyarrow.lib.RecordBatch' has no attribute 'from_struct_array'
Hi, make sure you have a recent version of pyarrow.
Are you using it in Google Colab? In this case, this error is probably the same as #128 | [
-0.11933845281600952,
0.08862784504890442,
-0.00897780992090702,
0.21019737422466278,
0.3692678213119507,
0.026059836149215698,
0.4487815499305725,
0.4131021499633789,
0.4330812692642212,
0.012566991150379181,
0.12384359538555145,
0.395429790019989,
-0.15054914355278015,
0.021962707862257957,
0.12090519070625305,
-0.42898982763290405,
-0.03373972326517105,
0.3636728823184967,
-0.041466742753982544,
0.06297364085912704,
-0.1876835823059082,
0.10851715505123138,
-0.2651914358139038,
0.25500577688217163,
-0.30572283267974854,
-0.05702577531337738,
0.2159208357334137,
0.08206366002559662,
-0.07891867309808731,
-0.5590065121650696,
0.2770831286907196,
-0.2170492708683014,
0.06445172429084778,
0.11474639922380447,
-0.00010995571938110515,
0.20530645549297333,
0.33269721269607544,
0.030212881043553352,
-0.5799458026885986,
-0.18957795202732086,
-0.4773316979408264,
-0.11893881857395172,
0.29743173718452454,
-0.2497076690196991,
-0.028513483703136444,
0.05389726161956787,
0.035910993814468384,
-0.07441209256649017,
0.29674679040908813,
0.531506359577179,
0.237888902425766,
0.5236923694610596,
0.15454915165901184,
0.03449363261461258,
-0.07856784015893936,
-0.17057108879089355,
-0.08211500197649002,
0.22396822273731232,
0.07387731224298477,
-0.39154377579689026,
-0.013373926281929016,
0.1269245445728302,
0.15117238461971283,
0.26370200514793396,
0.5083709359169006,
0.014393925666809082,
0.2405235767364502,
-0.15062691271305084,
0.014946820214390755,
0.07640057057142258,
0.3353826403617859,
-0.1649332046508789,
-0.2715998888015747,
-0.2243589460849762,
0.2476661205291748,
-0.33475619554519653,
0.2365303635597229,
-0.03667646646499634,
-0.16220436990261078,
-0.008197136223316193,
-0.26922789216041565,
-0.028147468343377113,
-0.24182075262069702,
0.3526870608329773,
-0.058214087039232254,
0.49964913725852966,
0.043583355844020844,
0.1427474468946457,
-0.05806552246212959,
-0.07545772939920425,
0.14037704467773438,
-0.08709109574556351,
-0.1293005496263504,
0.25781309604644775,
-0.38315531611442566,
-0.036467600613832474,
-0.034946344792842865,
-0.11697594076395035,
-0.031624749302864075,
0.26352018117904663,
0.21998973190784454,
-0.22487351298332214,
0.3238390386104584,
0.3154153525829315,
0.22298845648765564,
0.42046889662742615,
0.07276557385921478,
0.06359237432479858,
-0.08280497789382935,
0.1360260546207428,
-0.23372812569141388,
-0.15548521280288696,
-0.1555362045764923,
-0.1765558421611786,
0.09289798140525818,
-0.15460222959518433,
0.22602073848247528,
-0.07111581414937973,
-0.4984738230705261,
0.11472072452306747,
-0.14340484142303467,
0.046290118247270584,
0.20511485636234283,
0.17948494851589203,
-0.12763413786888123,
0.23223412036895752,
0.14412455260753632,
0.2825669050216675,
-0.25197696685791016,
-0.04313553497195244,
-0.16628961265087128,
0.249213308095932,
-0.23438286781311035,
-0.18224890530109406,
0.24275390803813934,
0.193400040268898,
0.3994784653186798,
-0.10116767883300781,
0.11126405000686646,
-0.2017553448677063,
0.2273758500814438,
-0.04551952704787254,
-0.1288793981075287,
0.25665315985679626,
-0.21606102585792542,
0.1548980474472046,
0.20159120857715607,
-0.2824234366416931,
-0.0848238617181778,
-0.10174446552991867,
-0.27263572812080383,
-0.30809223651885986,
-0.1262514442205429,
0.28141558170318604,
0.147381991147995,
-0.24296480417251587,
-0.15226313471794128,
-0.06118778511881828,
0.14749255776405334,
-0.36872372031211853,
-0.11810629814863205,
-0.4612586498260498,
-0.22063903510570526,
-0.023005738854408264,
0.3976435363292694,
0.20490935444831848,
0.13138674199581146,
-0.1089726984500885,
-0.11542053520679474,
0.07785429060459137,
-0.031797103583812714,
0.1227136105298996,
-0.43835723400115967,
0.5421629548072815,
-0.06105594336986542,
0.118863046169281,
0.64134681224823,
-0.3427872657775879,
-0.4578544795513153,
0.12356892228126526,
-0.014279965311288834,
0.20932787656784058,
-0.22536897659301758,
-0.01672065444290638,
-0.013226330280303955,
-0.1845511645078659,
0.21231377124786377,
0.6192131042480469,
-0.015042958781123161,
0.08247934281826019,
-0.12689706683158875,
-0.01554920244961977,
0.5002195239067078,
0.10985688865184784,
0.09252531826496124,
-0.007928885519504547,
-0.04170481115579605,
0.49664852023124695,
-0.00131293386220932,
-0.12597057223320007,
-0.014860082417726517,
-0.013630155473947525,
-0.06468622386455536,
-0.10460402071475983,
-0.2178265005350113,
-0.07388680428266525,
-0.2776644825935364,
0.30430400371551514,
-0.11754798144102097,
-0.05853193253278732,
-0.04715031385421753,
0.10618656873703003,
-0.34911325573921204,
0.16848869621753693,
-0.42326927185058594,
-0.3773188889026642,
0.17209337651729584,
0.15513363480567932,
-0.01082286611199379,
0.23844115436077118,
-0.20474110543727875,
0.21943674981594086,
-0.2740277051925659,
0.055500876158475876,
-0.21892870962619781,
0.16128991544246674,
-0.05588398873806,
-0.04242202267050743,
-0.009479247033596039,
0.30879634618759155,
0.03833160549402237,
-0.017996493726968765,
-0.3062889277935028,
0.28603029251098633,
-0.12548455595970154,
0.08035629242658615,
-0.03226495534181595,
-0.14337028563022614,
0.06880630552768707,
-0.07154297828674316,
-0.17518453299999237,
0.20819191634655,
0.33195099234580994,
-0.18012642860412598,
-0.04314299672842026,
0.11287609487771988,
0.1272123008966446,
0.0814221054315567,
0.09886433184146881,
0.16397228837013245,
0.14399199187755585,
-0.06582621484994888,
0.1012795940041542,
0.07743129134178162,
0.23370946943759918,
-0.09498715400695801,
0.20471079647541046,
-0.15645107626914978,
-0.1671449989080429,
-0.11880645900964737,
0.3131202161312103,
0.17005868256092072,
0.16741719841957092,
0.08148638904094696,
-0.2752525210380554,
-0.09487432986497879,
0.07855785638093948,
0.14604909718036652,
0.40096497535705566,
-0.0518328957259655,
-0.10834059119224548,
-0.05257079750299454,
-0.4165968596935272,
0.07112551480531693,
0.17070795595645905,
0.03662925213575363,
0.20912905037403107,
0.30185645818710327,
0.04131554812192917,
0.0873207226395607,
-0.2952670454978943,
-0.35701698064804077,
0.2824336886405945,
0.4405299723148346,
-0.22848191857337952,
0.20788007974624634,
-0.03053159825503826,
-0.0025112517178058624,
-0.06784830242395401,
-0.33363378047943115,
-0.18862853944301605,
-0.342993825674057,
-0.12133617699146271,
0.433775395154953,
0.024119451642036438,
0.181004598736763,
-0.3977614641189575,
-0.022051095962524414,
0.19475087523460388,
-0.11478548496961594,
-0.03137951344251633,
-0.3157978653907776,
-0.2693289816379547,
0.04594217613339424,
0.3818606734275818,
0.09107664972543716,
0.3510980010032654,
-0.06677059084177017,
-0.0925356075167656,
-0.007035041227936745,
-0.05841507762670517,
-0.07556726038455963,
-0.18372085690498352,
0.2440476268529892,
0.009521827101707458,
0.2855835258960724,
-0.17702968418598175,
-0.5220333337783813,
0.5017467737197876,
-0.25570181012153625,
-0.057785287499427795,
0.31510666012763977,
0.27111297845840454,
-0.24919047951698303,
-0.07947683334350586,
-0.37468862533569336,
-0.12645035982131958,
-0.28060582280158997,
-0.05946876108646393,
0.07482925057411194,
0.062020909041166306,
0.39746737480163574,
0.07085651159286499,
0.21601088345050812,
-0.0025735688395798206,
0.1134379655122757,
-0.04826278239488602,
-0.09006398171186447,
0.1859847605228424,
-0.31003400683403015,
-0.31731829047203064,
-0.12134282290935516,
0.00993594154715538,
0.3347616195678711,
0.11073551326990128,
-0.3489593267440796,
-0.21413181722164154,
-0.10495822131633759,
0.08531276881694794,
-0.2213253676891327,
-0.04006670415401459,
0.18286007642745972,
0.07230357825756073,
-0.06572244316339493,
-0.08664388954639435,
0.03598948195576668,
0.07124010473489761,
0.15234598517417908,
0.13496194779872894,
-0.006304748356342316,
0.08922688663005829,
-0.08488400280475616,
0.6008991599082947,
0.21869370341300964,
-0.21437688171863556,
0.30028587579727173,
-0.10327673703432083,
0.005144510418176651,
-0.208683580160141,
-0.4398045539855957,
0.26416414976119995,
-0.11523276567459106,
0.18292897939682007,
0.17231473326683044,
-0.07949357479810715,
-0.2247839719057083,
-0.1925591230392456,
0.06885170936584473,
-0.17844745516777039,
-0.27277958393096924,
0.14616836607456207,
-0.21739450097084045,
0.2787109315395355,
-0.06886422634124756,
0.22253704071044922,
-0.20522335171699524,
-0.16798070073127747,
0.06985078752040863,
0.16693411767482758,
-0.09054567664861679,
0.07967513799667358,
-0.24400167167186737,
-0.27610862255096436,
-0.4799582362174988,
-0.02783966064453125,
0.24103179574012756,
0.643750011920929,
-0.08638451993465424,
0.03718879818916321,
0.08072253316640854,
0.08174140751361847,
0.13737376034259796,
-0.2301362007856369,
0.1822635680437088,
0.2891308069229126,
0.03182467073202133,
-0.31974661350250244,
-0.06433149427175522,
-0.14011231064796448,
0.35801658034324646,
0.0766519159078598,
-0.054431721568107605,
-0.03723123297095299,
-0.1676540970802307,
0.1398320496082306,
0.2599392831325531,
-0.1872951090335846,
-0.044113077223300934,
-0.09173431247472763,
-0.08981046825647354,
-0.30776458978652954,
-0.006154969334602356,
-0.009947758167982101,
0.33566054701805115,
0.12296926230192184,
0.26572471857070923,
-0.5462992191314697,
0.11665705591440201,
0.09016524255275726,
0.17458684742450714,
0.09595315158367157,
0.057944219559431076,
0.18724678456783295,
-0.16663400828838348,
0.18321000039577484,
-0.14590442180633545,
0.5633803606033325,
0.14737597107887268,
-0.3307987451553345,
-0.31952953338623047,
0.02166324108839035,
0.16743338108062744,
0.18398034572601318,
-0.01858552172780037,
-0.14112097024917603,
-0.2769453525543213,
-0.06146351993083954,
-0.008708748035132885,
0.3045704662799835,
0.5610411167144775,
0.0026276633143424988,
-0.3271808922290802,
-0.2585407495498657,
0.4828394949436188,
-0.2850031852722168,
0.11732904613018036,
0.3215572237968445,
0.05337715521454811,
-0.3131922781467438,
0.08413887023925781,
0.07783256471157074,
0.6767752766609192,
0.16953882575035095,
0.3111467659473419,
0.3826707899570465,
0.18392826616764069,
0.4142706096172333,
-0.043089497834444046,
0.2847142815589905,
-0.3927357494831085,
-0.13342586159706116,
-0.08068586140871048,
-0.06546270102262497,
0.10708172619342804,
-0.008873388171195984,
-0.02543865703046322,
0.150621235370636,
0.15688925981521606,
-0.0041420795023441315,
0.05714789777994156,
0.4492526650428772,
-0.03878391534090042,
-0.1968192607164383,
-0.3470253050327301,
0.15601636469364166,
-0.21799974143505096,
0.2975102663040161,
-0.09073382616043091,
-0.06648421287536621,
0.05520467087626457,
-0.06735203415155411,
-0.25555843114852905,
0.2574385404586792,
-0.29947492480278015,
0.4594579339027405,
0.05782182514667511,
-0.4756813049316406,
0.1984151303768158,
0.20709790289402008,
0.1756638139486313,
0.0056989602744579315,
-0.29959404468536377,
0.23877887427806854,
-0.2900899052619934,
-0.22186626493930817,
-0.06728766113519669,
0.11194741725921631,
0.4200734496116638,
-0.17255154252052307,
-0.14637798070907593,
0.14794065058231354,
-0.12065417319536209,
-0.24150244891643524,
0.1039588451385498,
0.036866605281829834,
0.3524894714355469,
-0.3925756514072418,
-0.5152195692062378,
-0.0024207234382629395,
-0.18207629024982452,
-0.17491021752357483,
0.17450003325939178,
0.02345065027475357,
-0.18903149664402008,
0.15189561247825623,
0.14982710778713226,
-0.19898000359535217,
0.11640655994415283,
0.24804237484931946,
-0.2495403289794922,
0.14628303050994873,
0.7637573480606079,
0.03394555673003197,
0.01280517503619194,
-0.3138304352760315,
-0.05428845435380936,
0.12508459389209747,
-0.48199987411499023,
-0.1171272024512291,
0.12550412118434906,
0.16912586987018585,
-0.1442466676235199,
0.49836599826812744,
0.06302111595869064,
-0.01884474605321884,
0.24718548357486725,
-0.5424140095710754,
-0.10621928423643112,
-0.043021634221076965,
0.017753619700670242,
0.23777522146701813,
-0.0026239529252052307,
0.11488902568817139,
0.13550958037376404,
0.1033887192606926,
-0.2726374566555023,
0.014254427514970303,
-0.15762582421302795,
0.1379965841770172,
0.21783430874347687,
-0.1565312147140503,
0.22328168153762817,
-0.07694721221923828,
0.15638616681098938,
-0.09584659337997437,
-0.12303443253040314,
-0.24829328060150146,
-0.25483784079551697,
0.10011143982410431,
0.24556711316108704,
-0.1645212471485138,
-0.030679188668727875,
-0.10233347862958908,
0.02367764711380005,
-0.23110505938529968,
-0.00846264511346817,
-0.11772798001766205,
-0.2933427095413208,
0.38943231105804443,
0.04389800876379013,
0.27836859226226807,
-0.11169030517339706,
0.12635567784309387,
-0.30075740814208984,
0.14912036061286926,
-0.01849590800702572,
-0.07522959262132645,
0.27581319212913513,
0.09365326166152954,
-0.4658869206905365,
0.0054205358028411865,
-0.40260517597198486,
0.03714786097407341,
0.3698212504386902,
-0.4551103711128235,
0.15995843708515167,
-0.1316281408071518,
0.09546546638011932,
0.4656829833984375,
-0.27140846848487854,
-0.0036669299006462097,
0.3496653139591217,
0.23784254491329193,
-0.29741764068603516,
-0.1892606019973755,
0.2399907410144806,
0.061345674097537994,
0.03245936706662178,
0.02723889797925949,
0.04666122421622276,
-0.3037486672401428,
-0.32123446464538574,
0.08927963674068451,
-0.029340408742427826,
-0.2656012773513794,
-0.01140776090323925,
0.33932653069496155,
-0.002364441752433777,
-0.05951501801609993,
-0.0500493124127388,
0.21102115511894226,
0.03539281338453293,
0.38269317150115967,
-0.29260092973709106,
0.2069980353116989,
0.05926353484392166,
0.04391039162874222,
-0.11114301532506943,
-0.21921727061271667,
0.05030050128698349,
-0.15784099698066711,
0.03383420407772064,
0.2952827513217926,
0.09981479495763779,
0.1530807912349701,
-0.2855033874511719,
-0.12453707307577133,
-0.20802274346351624,
0.22792446613311768,
-0.17904222011566162,
-0.04890655726194382,
-0.24299554526805878,
0.02101702243089676,
-0.02587638422846794,
-0.09469917416572571,
-0.14167022705078125,
-0.0381786972284317,
0.3095560371875763,
0.2532220482826233,
-0.1722705215215683,
-0.45553502440452576,
0.10826653242111206,
0.3432941436767578,
0.18004727363586426,
-0.24588416516780853,
0.3368532359600067,
0.19381549954414368,
-0.06877827644348145,
-0.01412438228726387,
0.3971101641654968,
0.43576839566230774,
0.3383936583995819,
-0.364220529794693,
0.08116793632507324,
-0.20338064432144165,
-0.05682189017534256,
-0.023260291665792465,
0.2695123851299286,
0.10607316344976425,
0.11737622320652008,
0.46242257952690125,
0.12148632109165192,
-0.1247272789478302,
0.04363914206624031,
-0.08805669844150543,
-0.2605326473712921,
-0.26294705271720886,
0.5191487073898315,
0.1857946217060089,
-0.1143883466720581,
-0.32065102458000183,
0.1899377703666687,
-0.27498704195022583,
-0.08091447502374649,
0.06285165250301361,
0.24058954417705536,
0.11315394192934036,
-0.21382759511470795,
0.07050890475511551,
0.00031514279544353485,
0.7061734795570374,
0.48772192001342773,
-0.017719194293022156,
-0.3658052682876587,
-0.11652375012636185,
-0.5989872217178345,
0.21783632040023804,
-0.3639681041240692,
-0.26901817321777344,
0.2833365499973297,
-0.07233157753944397,
-0.288082480430603,
0.24852731823921204,
0.1276196390390396,
0.15819591283798218,
-0.05727645754814148,
0.09834779053926468,
-0.4907650053501129,
-0.14860455691814423,
-0.030650503933429718,
-0.007675016298890114,
-0.08318105340003967,
-0.25705307722091675,
0.14532306790351868,
-0.4349946677684784,
0.11610303074121475,
0.01198504213243723,
0.06934809684753418,
-0.00023945607244968414,
0.09664029628038406,
0.35442453622817993,
0.1653239130973816,
0.5012482404708862,
-0.03556128963828087,
0.0036574434489011765,
-0.1911543905735016,
-0.1566217541694641,
-0.2289923131465912,
0.13182267546653748,
0.08762918412685394,
0.5133118629455566,
-0.02610740251839161,
-0.06854520738124847,
-0.26402729749679565,
0.40316787362098694,
-0.08100667595863342,
0.08831582963466644,
-0.1350807249546051,
0.0773145779967308,
-0.0703495442867279,
0.2275840938091278,
0.2643648684024811,
0.42454031109809875,
-0.1783217340707779,
0.2022092193365097,
-0.2722919285297394,
-0.46024608612060547,
0.32893532514572144,
-0.661480724811554,
-0.517790675163269,
0.0751224160194397,
0.1161930188536644,
-0.1423342525959015,
0.05819430202245712,
-0.6006339192390442,
0.07056698948144913,
0.24261271953582764,
-0.1114056184887886,
-0.317119836807251,
0.21794511377811432,
0.016542082652449608,
0.08000141382217407,
0.04357365146279335,
0.4483563303947449,
-0.14847293496131897,
-0.15976761281490326,
-0.0049346014857292175,
-0.163252055644989
] |
https://github.com/huggingface/datasets/issues/168 | Loading 'wikitext' dataset fails | Hi,
The squad bug seems to be fixed, but the loading of the 'wikitext' still suffers from this problem (on Colab with pyarrow=0.17.1). | Loading the 'wikitext' dataset fails with Attribute error:
Code to reproduce (From example notebook):
import nlp
wikitext_dataset = nlp.load_dataset('wikitext')
Error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-d5d9df94b13c> in <module>()
11
12 # Load a dataset and print the first examples in the training set
---> 13 wikitext_dataset = nlp.load_dataset('wikitext')
14 print(wikitext_dataset['train'][0])
6 frames
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=download_mode,
519 ignore_verifications=ignore_verifications,
--> 520 save_infos=save_infos,
521 )
522
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
363 verify_infos = not save_infos and not ignore_verifications
364 self._download_and_prepare(
--> 365 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
366 )
367 # Sync info
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
416 try:
417 # Prepare split will record examples associated to the split
--> 418 self._prepare_split(split_generator, **prepare_split_kwargs)
419 except OSError:
420 raise OSError("Cannot find data file. " + (self.MANUAL_DOWNLOAD_INSTRUCTIONS or ""))
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _prepare_split(self, split_generator)
594 example = self.info.features.encode_example(record)
595 writer.write(example)
--> 596 num_examples, num_bytes = writer.finalize()
597
598 assert num_examples == num_examples, f"Expected to write {split_info.num_examples} but wrote {num_examples}"
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in finalize(self, close_stream)
173 def finalize(self, close_stream=True):
174 if self.pa_writer is not None:
--> 175 self.write_on_file()
176 self.pa_writer.close()
177 if close_stream:
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in write_on_file(self)
124 else:
125 # All good
--> 126 self._write_array_on_file(pa_array)
127 self.current_rows = []
128
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in _write_array_on_file(self, pa_array)
93 def _write_array_on_file(self, pa_array):
94 """Write a PyArrow Array"""
---> 95 pa_batch = pa.RecordBatch.from_struct_array(pa_array)
96 self._num_bytes += pa_array.nbytes
97 self.pa_writer.write_batch(pa_batch)
AttributeError: type object 'pyarrow.lib.RecordBatch' has no attribute 'from_struct_array' | 23 | Loading 'wikitext' dataset fails
Loading the 'wikitext' dataset fails with Attribute error:
Code to reproduce (From example notebook):
import nlp
wikitext_dataset = nlp.load_dataset('wikitext')
Error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-d5d9df94b13c> in <module>()
11
12 # Load a dataset and print the first examples in the training set
---> 13 wikitext_dataset = nlp.load_dataset('wikitext')
14 print(wikitext_dataset['train'][0])
6 frames
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=download_mode,
519 ignore_verifications=ignore_verifications,
--> 520 save_infos=save_infos,
521 )
522
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
363 verify_infos = not save_infos and not ignore_verifications
364 self._download_and_prepare(
--> 365 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
366 )
367 # Sync info
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
416 try:
417 # Prepare split will record examples associated to the split
--> 418 self._prepare_split(split_generator, **prepare_split_kwargs)
419 except OSError:
420 raise OSError("Cannot find data file. " + (self.MANUAL_DOWNLOAD_INSTRUCTIONS or ""))
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _prepare_split(self, split_generator)
594 example = self.info.features.encode_example(record)
595 writer.write(example)
--> 596 num_examples, num_bytes = writer.finalize()
597
598 assert num_examples == num_examples, f"Expected to write {split_info.num_examples} but wrote {num_examples}"
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in finalize(self, close_stream)
173 def finalize(self, close_stream=True):
174 if self.pa_writer is not None:
--> 175 self.write_on_file()
176 self.pa_writer.close()
177 if close_stream:
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in write_on_file(self)
124 else:
125 # All good
--> 126 self._write_array_on_file(pa_array)
127 self.current_rows = []
128
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in _write_array_on_file(self, pa_array)
93 def _write_array_on_file(self, pa_array):
94 """Write a PyArrow Array"""
---> 95 pa_batch = pa.RecordBatch.from_struct_array(pa_array)
96 self._num_bytes += pa_array.nbytes
97 self.pa_writer.write_batch(pa_batch)
AttributeError: type object 'pyarrow.lib.RecordBatch' has no attribute 'from_struct_array'
Hi,
The squad bug seems to be fixed, but the loading of the 'wikitext' still suffers from this problem (on Colab with pyarrow=0.17.1). | [
-0.11933845281600952,
0.08862784504890442,
-0.00897780992090702,
0.21019737422466278,
0.3692678213119507,
0.026059836149215698,
0.4487815499305725,
0.4131021499633789,
0.4330812692642212,
0.012566991150379181,
0.12384359538555145,
0.395429790019989,
-0.15054914355278015,
0.021962707862257957,
0.12090519070625305,
-0.42898982763290405,
-0.03373972326517105,
0.3636728823184967,
-0.041466742753982544,
0.06297364085912704,
-0.1876835823059082,
0.10851715505123138,
-0.2651914358139038,
0.25500577688217163,
-0.30572283267974854,
-0.05702577531337738,
0.2159208357334137,
0.08206366002559662,
-0.07891867309808731,
-0.5590065121650696,
0.2770831286907196,
-0.2170492708683014,
0.06445172429084778,
0.11474639922380447,
-0.00010995571938110515,
0.20530645549297333,
0.33269721269607544,
0.030212881043553352,
-0.5799458026885986,
-0.18957795202732086,
-0.4773316979408264,
-0.11893881857395172,
0.29743173718452454,
-0.2497076690196991,
-0.028513483703136444,
0.05389726161956787,
0.035910993814468384,
-0.07441209256649017,
0.29674679040908813,
0.531506359577179,
0.237888902425766,
0.5236923694610596,
0.15454915165901184,
0.03449363261461258,
-0.07856784015893936,
-0.17057108879089355,
-0.08211500197649002,
0.22396822273731232,
0.07387731224298477,
-0.39154377579689026,
-0.013373926281929016,
0.1269245445728302,
0.15117238461971283,
0.26370200514793396,
0.5083709359169006,
0.014393925666809082,
0.2405235767364502,
-0.15062691271305084,
0.014946820214390755,
0.07640057057142258,
0.3353826403617859,
-0.1649332046508789,
-0.2715998888015747,
-0.2243589460849762,
0.2476661205291748,
-0.33475619554519653,
0.2365303635597229,
-0.03667646646499634,
-0.16220436990261078,
-0.008197136223316193,
-0.26922789216041565,
-0.028147468343377113,
-0.24182075262069702,
0.3526870608329773,
-0.058214087039232254,
0.49964913725852966,
0.043583355844020844,
0.1427474468946457,
-0.05806552246212959,
-0.07545772939920425,
0.14037704467773438,
-0.08709109574556351,
-0.1293005496263504,
0.25781309604644775,
-0.38315531611442566,
-0.036467600613832474,
-0.034946344792842865,
-0.11697594076395035,
-0.031624749302864075,
0.26352018117904663,
0.21998973190784454,
-0.22487351298332214,
0.3238390386104584,
0.3154153525829315,
0.22298845648765564,
0.42046889662742615,
0.07276557385921478,
0.06359237432479858,
-0.08280497789382935,
0.1360260546207428,
-0.23372812569141388,
-0.15548521280288696,
-0.1555362045764923,
-0.1765558421611786,
0.09289798140525818,
-0.15460222959518433,
0.22602073848247528,
-0.07111581414937973,
-0.4984738230705261,
0.11472072452306747,
-0.14340484142303467,
0.046290118247270584,
0.20511485636234283,
0.17948494851589203,
-0.12763413786888123,
0.23223412036895752,
0.14412455260753632,
0.2825669050216675,
-0.25197696685791016,
-0.04313553497195244,
-0.16628961265087128,
0.249213308095932,
-0.23438286781311035,
-0.18224890530109406,
0.24275390803813934,
0.193400040268898,
0.3994784653186798,
-0.10116767883300781,
0.11126405000686646,
-0.2017553448677063,
0.2273758500814438,
-0.04551952704787254,
-0.1288793981075287,
0.25665315985679626,
-0.21606102585792542,
0.1548980474472046,
0.20159120857715607,
-0.2824234366416931,
-0.0848238617181778,
-0.10174446552991867,
-0.27263572812080383,
-0.30809223651885986,
-0.1262514442205429,
0.28141558170318604,
0.147381991147995,
-0.24296480417251587,
-0.15226313471794128,
-0.06118778511881828,
0.14749255776405334,
-0.36872372031211853,
-0.11810629814863205,
-0.4612586498260498,
-0.22063903510570526,
-0.023005738854408264,
0.3976435363292694,
0.20490935444831848,
0.13138674199581146,
-0.1089726984500885,
-0.11542053520679474,
0.07785429060459137,
-0.031797103583812714,
0.1227136105298996,
-0.43835723400115967,
0.5421629548072815,
-0.06105594336986542,
0.118863046169281,
0.64134681224823,
-0.3427872657775879,
-0.4578544795513153,
0.12356892228126526,
-0.014279965311288834,
0.20932787656784058,
-0.22536897659301758,
-0.01672065444290638,
-0.013226330280303955,
-0.1845511645078659,
0.21231377124786377,
0.6192131042480469,
-0.015042958781123161,
0.08247934281826019,
-0.12689706683158875,
-0.01554920244961977,
0.5002195239067078,
0.10985688865184784,
0.09252531826496124,
-0.007928885519504547,
-0.04170481115579605,
0.49664852023124695,
-0.00131293386220932,
-0.12597057223320007,
-0.014860082417726517,
-0.013630155473947525,
-0.06468622386455536,
-0.10460402071475983,
-0.2178265005350113,
-0.07388680428266525,
-0.2776644825935364,
0.30430400371551514,
-0.11754798144102097,
-0.05853193253278732,
-0.04715031385421753,
0.10618656873703003,
-0.34911325573921204,
0.16848869621753693,
-0.42326927185058594,
-0.3773188889026642,
0.17209337651729584,
0.15513363480567932,
-0.01082286611199379,
0.23844115436077118,
-0.20474110543727875,
0.21943674981594086,
-0.2740277051925659,
0.055500876158475876,
-0.21892870962619781,
0.16128991544246674,
-0.05588398873806,
-0.04242202267050743,
-0.009479247033596039,
0.30879634618759155,
0.03833160549402237,
-0.017996493726968765,
-0.3062889277935028,
0.28603029251098633,
-0.12548455595970154,
0.08035629242658615,
-0.03226495534181595,
-0.14337028563022614,
0.06880630552768707,
-0.07154297828674316,
-0.17518453299999237,
0.20819191634655,
0.33195099234580994,
-0.18012642860412598,
-0.04314299672842026,
0.11287609487771988,
0.1272123008966446,
0.0814221054315567,
0.09886433184146881,
0.16397228837013245,
0.14399199187755585,
-0.06582621484994888,
0.1012795940041542,
0.07743129134178162,
0.23370946943759918,
-0.09498715400695801,
0.20471079647541046,
-0.15645107626914978,
-0.1671449989080429,
-0.11880645900964737,
0.3131202161312103,
0.17005868256092072,
0.16741719841957092,
0.08148638904094696,
-0.2752525210380554,
-0.09487432986497879,
0.07855785638093948,
0.14604909718036652,
0.40096497535705566,
-0.0518328957259655,
-0.10834059119224548,
-0.05257079750299454,
-0.4165968596935272,
0.07112551480531693,
0.17070795595645905,
0.03662925213575363,
0.20912905037403107,
0.30185645818710327,
0.04131554812192917,
0.0873207226395607,
-0.2952670454978943,
-0.35701698064804077,
0.2824336886405945,
0.4405299723148346,
-0.22848191857337952,
0.20788007974624634,
-0.03053159825503826,
-0.0025112517178058624,
-0.06784830242395401,
-0.33363378047943115,
-0.18862853944301605,
-0.342993825674057,
-0.12133617699146271,
0.433775395154953,
0.024119451642036438,
0.181004598736763,
-0.3977614641189575,
-0.022051095962524414,
0.19475087523460388,
-0.11478548496961594,
-0.03137951344251633,
-0.3157978653907776,
-0.2693289816379547,
0.04594217613339424,
0.3818606734275818,
0.09107664972543716,
0.3510980010032654,
-0.06677059084177017,
-0.0925356075167656,
-0.007035041227936745,
-0.05841507762670517,
-0.07556726038455963,
-0.18372085690498352,
0.2440476268529892,
0.009521827101707458,
0.2855835258960724,
-0.17702968418598175,
-0.5220333337783813,
0.5017467737197876,
-0.25570181012153625,
-0.057785287499427795,
0.31510666012763977,
0.27111297845840454,
-0.24919047951698303,
-0.07947683334350586,
-0.37468862533569336,
-0.12645035982131958,
-0.28060582280158997,
-0.05946876108646393,
0.07482925057411194,
0.062020909041166306,
0.39746737480163574,
0.07085651159286499,
0.21601088345050812,
-0.0025735688395798206,
0.1134379655122757,
-0.04826278239488602,
-0.09006398171186447,
0.1859847605228424,
-0.31003400683403015,
-0.31731829047203064,
-0.12134282290935516,
0.00993594154715538,
0.3347616195678711,
0.11073551326990128,
-0.3489593267440796,
-0.21413181722164154,
-0.10495822131633759,
0.08531276881694794,
-0.2213253676891327,
-0.04006670415401459,
0.18286007642745972,
0.07230357825756073,
-0.06572244316339493,
-0.08664388954639435,
0.03598948195576668,
0.07124010473489761,
0.15234598517417908,
0.13496194779872894,
-0.006304748356342316,
0.08922688663005829,
-0.08488400280475616,
0.6008991599082947,
0.21869370341300964,
-0.21437688171863556,
0.30028587579727173,
-0.10327673703432083,
0.005144510418176651,
-0.208683580160141,
-0.4398045539855957,
0.26416414976119995,
-0.11523276567459106,
0.18292897939682007,
0.17231473326683044,
-0.07949357479810715,
-0.2247839719057083,
-0.1925591230392456,
0.06885170936584473,
-0.17844745516777039,
-0.27277958393096924,
0.14616836607456207,
-0.21739450097084045,
0.2787109315395355,
-0.06886422634124756,
0.22253704071044922,
-0.20522335171699524,
-0.16798070073127747,
0.06985078752040863,
0.16693411767482758,
-0.09054567664861679,
0.07967513799667358,
-0.24400167167186737,
-0.27610862255096436,
-0.4799582362174988,
-0.02783966064453125,
0.24103179574012756,
0.643750011920929,
-0.08638451993465424,
0.03718879818916321,
0.08072253316640854,
0.08174140751361847,
0.13737376034259796,
-0.2301362007856369,
0.1822635680437088,
0.2891308069229126,
0.03182467073202133,
-0.31974661350250244,
-0.06433149427175522,
-0.14011231064796448,
0.35801658034324646,
0.0766519159078598,
-0.054431721568107605,
-0.03723123297095299,
-0.1676540970802307,
0.1398320496082306,
0.2599392831325531,
-0.1872951090335846,
-0.044113077223300934,
-0.09173431247472763,
-0.08981046825647354,
-0.30776458978652954,
-0.006154969334602356,
-0.009947758167982101,
0.33566054701805115,
0.12296926230192184,
0.26572471857070923,
-0.5462992191314697,
0.11665705591440201,
0.09016524255275726,
0.17458684742450714,
0.09595315158367157,
0.057944219559431076,
0.18724678456783295,
-0.16663400828838348,
0.18321000039577484,
-0.14590442180633545,
0.5633803606033325,
0.14737597107887268,
-0.3307987451553345,
-0.31952953338623047,
0.02166324108839035,
0.16743338108062744,
0.18398034572601318,
-0.01858552172780037,
-0.14112097024917603,
-0.2769453525543213,
-0.06146351993083954,
-0.008708748035132885,
0.3045704662799835,
0.5610411167144775,
0.0026276633143424988,
-0.3271808922290802,
-0.2585407495498657,
0.4828394949436188,
-0.2850031852722168,
0.11732904613018036,
0.3215572237968445,
0.05337715521454811,
-0.3131922781467438,
0.08413887023925781,
0.07783256471157074,
0.6767752766609192,
0.16953882575035095,
0.3111467659473419,
0.3826707899570465,
0.18392826616764069,
0.4142706096172333,
-0.043089497834444046,
0.2847142815589905,
-0.3927357494831085,
-0.13342586159706116,
-0.08068586140871048,
-0.06546270102262497,
0.10708172619342804,
-0.008873388171195984,
-0.02543865703046322,
0.150621235370636,
0.15688925981521606,
-0.0041420795023441315,
0.05714789777994156,
0.4492526650428772,
-0.03878391534090042,
-0.1968192607164383,
-0.3470253050327301,
0.15601636469364166,
-0.21799974143505096,
0.2975102663040161,
-0.09073382616043091,
-0.06648421287536621,
0.05520467087626457,
-0.06735203415155411,
-0.25555843114852905,
0.2574385404586792,
-0.29947492480278015,
0.4594579339027405,
0.05782182514667511,
-0.4756813049316406,
0.1984151303768158,
0.20709790289402008,
0.1756638139486313,
0.0056989602744579315,
-0.29959404468536377,
0.23877887427806854,
-0.2900899052619934,
-0.22186626493930817,
-0.06728766113519669,
0.11194741725921631,
0.4200734496116638,
-0.17255154252052307,
-0.14637798070907593,
0.14794065058231354,
-0.12065417319536209,
-0.24150244891643524,
0.1039588451385498,
0.036866605281829834,
0.3524894714355469,
-0.3925756514072418,
-0.5152195692062378,
-0.0024207234382629395,
-0.18207629024982452,
-0.17491021752357483,
0.17450003325939178,
0.02345065027475357,
-0.18903149664402008,
0.15189561247825623,
0.14982710778713226,
-0.19898000359535217,
0.11640655994415283,
0.24804237484931946,
-0.2495403289794922,
0.14628303050994873,
0.7637573480606079,
0.03394555673003197,
0.01280517503619194,
-0.3138304352760315,
-0.05428845435380936,
0.12508459389209747,
-0.48199987411499023,
-0.1171272024512291,
0.12550412118434906,
0.16912586987018585,
-0.1442466676235199,
0.49836599826812744,
0.06302111595869064,
-0.01884474605321884,
0.24718548357486725,
-0.5424140095710754,
-0.10621928423643112,
-0.043021634221076965,
0.017753619700670242,
0.23777522146701813,
-0.0026239529252052307,
0.11488902568817139,
0.13550958037376404,
0.1033887192606926,
-0.2726374566555023,
0.014254427514970303,
-0.15762582421302795,
0.1379965841770172,
0.21783430874347687,
-0.1565312147140503,
0.22328168153762817,
-0.07694721221923828,
0.15638616681098938,
-0.09584659337997437,
-0.12303443253040314,
-0.24829328060150146,
-0.25483784079551697,
0.10011143982410431,
0.24556711316108704,
-0.1645212471485138,
-0.030679188668727875,
-0.10233347862958908,
0.02367764711380005,
-0.23110505938529968,
-0.00846264511346817,
-0.11772798001766205,
-0.2933427095413208,
0.38943231105804443,
0.04389800876379013,
0.27836859226226807,
-0.11169030517339706,
0.12635567784309387,
-0.30075740814208984,
0.14912036061286926,
-0.01849590800702572,
-0.07522959262132645,
0.27581319212913513,
0.09365326166152954,
-0.4658869206905365,
0.0054205358028411865,
-0.40260517597198486,
0.03714786097407341,
0.3698212504386902,
-0.4551103711128235,
0.15995843708515167,
-0.1316281408071518,
0.09546546638011932,
0.4656829833984375,
-0.27140846848487854,
-0.0036669299006462097,
0.3496653139591217,
0.23784254491329193,
-0.29741764068603516,
-0.1892606019973755,
0.2399907410144806,
0.061345674097537994,
0.03245936706662178,
0.02723889797925949,
0.04666122421622276,
-0.3037486672401428,
-0.32123446464538574,
0.08927963674068451,
-0.029340408742427826,
-0.2656012773513794,
-0.01140776090323925,
0.33932653069496155,
-0.002364441752433777,
-0.05951501801609993,
-0.0500493124127388,
0.21102115511894226,
0.03539281338453293,
0.38269317150115967,
-0.29260092973709106,
0.2069980353116989,
0.05926353484392166,
0.04391039162874222,
-0.11114301532506943,
-0.21921727061271667,
0.05030050128698349,
-0.15784099698066711,
0.03383420407772064,
0.2952827513217926,
0.09981479495763779,
0.1530807912349701,
-0.2855033874511719,
-0.12453707307577133,
-0.20802274346351624,
0.22792446613311768,
-0.17904222011566162,
-0.04890655726194382,
-0.24299554526805878,
0.02101702243089676,
-0.02587638422846794,
-0.09469917416572571,
-0.14167022705078125,
-0.0381786972284317,
0.3095560371875763,
0.2532220482826233,
-0.1722705215215683,
-0.45553502440452576,
0.10826653242111206,
0.3432941436767578,
0.18004727363586426,
-0.24588416516780853,
0.3368532359600067,
0.19381549954414368,
-0.06877827644348145,
-0.01412438228726387,
0.3971101641654968,
0.43576839566230774,
0.3383936583995819,
-0.364220529794693,
0.08116793632507324,
-0.20338064432144165,
-0.05682189017534256,
-0.023260291665792465,
0.2695123851299286,
0.10607316344976425,
0.11737622320652008,
0.46242257952690125,
0.12148632109165192,
-0.1247272789478302,
0.04363914206624031,
-0.08805669844150543,
-0.2605326473712921,
-0.26294705271720886,
0.5191487073898315,
0.1857946217060089,
-0.1143883466720581,
-0.32065102458000183,
0.1899377703666687,
-0.27498704195022583,
-0.08091447502374649,
0.06285165250301361,
0.24058954417705536,
0.11315394192934036,
-0.21382759511470795,
0.07050890475511551,
0.00031514279544353485,
0.7061734795570374,
0.48772192001342773,
-0.017719194293022156,
-0.3658052682876587,
-0.11652375012636185,
-0.5989872217178345,
0.21783632040023804,
-0.3639681041240692,
-0.26901817321777344,
0.2833365499973297,
-0.07233157753944397,
-0.288082480430603,
0.24852731823921204,
0.1276196390390396,
0.15819591283798218,
-0.05727645754814148,
0.09834779053926468,
-0.4907650053501129,
-0.14860455691814423,
-0.030650503933429718,
-0.007675016298890114,
-0.08318105340003967,
-0.25705307722091675,
0.14532306790351868,
-0.4349946677684784,
0.11610303074121475,
0.01198504213243723,
0.06934809684753418,
-0.00023945607244968414,
0.09664029628038406,
0.35442453622817993,
0.1653239130973816,
0.5012482404708862,
-0.03556128963828087,
0.0036574434489011765,
-0.1911543905735016,
-0.1566217541694641,
-0.2289923131465912,
0.13182267546653748,
0.08762918412685394,
0.5133118629455566,
-0.02610740251839161,
-0.06854520738124847,
-0.26402729749679565,
0.40316787362098694,
-0.08100667595863342,
0.08831582963466644,
-0.1350807249546051,
0.0773145779967308,
-0.0703495442867279,
0.2275840938091278,
0.2643648684024811,
0.42454031109809875,
-0.1783217340707779,
0.2022092193365097,
-0.2722919285297394,
-0.46024608612060547,
0.32893532514572144,
-0.661480724811554,
-0.517790675163269,
0.0751224160194397,
0.1161930188536644,
-0.1423342525959015,
0.05819430202245712,
-0.6006339192390442,
0.07056698948144913,
0.24261271953582764,
-0.1114056184887886,
-0.317119836807251,
0.21794511377811432,
0.016542082652449608,
0.08000141382217407,
0.04357365146279335,
0.4483563303947449,
-0.14847293496131897,
-0.15976761281490326,
-0.0049346014857292175,
-0.163252055644989
] |
https://github.com/huggingface/datasets/issues/168 | Loading 'wikitext' dataset fails | When you install `nlp` for the first time on a Colab runtime, it updates the `pyarrow` library that was already on colab. This update shows this message on colab:
```
WARNING: The following packages were previously imported in this runtime:
[pyarrow]
You must restart the runtime in order to use newly installed versions.
```
You just have to restart the runtime and it should be fine. | Loading the 'wikitext' dataset fails with Attribute error:
Code to reproduce (From example notebook):
import nlp
wikitext_dataset = nlp.load_dataset('wikitext')
Error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-d5d9df94b13c> in <module>()
11
12 # Load a dataset and print the first examples in the training set
---> 13 wikitext_dataset = nlp.load_dataset('wikitext')
14 print(wikitext_dataset['train'][0])
6 frames
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=download_mode,
519 ignore_verifications=ignore_verifications,
--> 520 save_infos=save_infos,
521 )
522
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
363 verify_infos = not save_infos and not ignore_verifications
364 self._download_and_prepare(
--> 365 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
366 )
367 # Sync info
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
416 try:
417 # Prepare split will record examples associated to the split
--> 418 self._prepare_split(split_generator, **prepare_split_kwargs)
419 except OSError:
420 raise OSError("Cannot find data file. " + (self.MANUAL_DOWNLOAD_INSTRUCTIONS or ""))
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _prepare_split(self, split_generator)
594 example = self.info.features.encode_example(record)
595 writer.write(example)
--> 596 num_examples, num_bytes = writer.finalize()
597
598 assert num_examples == num_examples, f"Expected to write {split_info.num_examples} but wrote {num_examples}"
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in finalize(self, close_stream)
173 def finalize(self, close_stream=True):
174 if self.pa_writer is not None:
--> 175 self.write_on_file()
176 self.pa_writer.close()
177 if close_stream:
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in write_on_file(self)
124 else:
125 # All good
--> 126 self._write_array_on_file(pa_array)
127 self.current_rows = []
128
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in _write_array_on_file(self, pa_array)
93 def _write_array_on_file(self, pa_array):
94 """Write a PyArrow Array"""
---> 95 pa_batch = pa.RecordBatch.from_struct_array(pa_array)
96 self._num_bytes += pa_array.nbytes
97 self.pa_writer.write_batch(pa_batch)
AttributeError: type object 'pyarrow.lib.RecordBatch' has no attribute 'from_struct_array' | 66 | Loading 'wikitext' dataset fails
Loading the 'wikitext' dataset fails with Attribute error:
Code to reproduce (From example notebook):
import nlp
wikitext_dataset = nlp.load_dataset('wikitext')
Error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-d5d9df94b13c> in <module>()
11
12 # Load a dataset and print the first examples in the training set
---> 13 wikitext_dataset = nlp.load_dataset('wikitext')
14 print(wikitext_dataset['train'][0])
6 frames
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=download_mode,
519 ignore_verifications=ignore_verifications,
--> 520 save_infos=save_infos,
521 )
522
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
363 verify_infos = not save_infos and not ignore_verifications
364 self._download_and_prepare(
--> 365 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
366 )
367 # Sync info
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
416 try:
417 # Prepare split will record examples associated to the split
--> 418 self._prepare_split(split_generator, **prepare_split_kwargs)
419 except OSError:
420 raise OSError("Cannot find data file. " + (self.MANUAL_DOWNLOAD_INSTRUCTIONS or ""))
/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _prepare_split(self, split_generator)
594 example = self.info.features.encode_example(record)
595 writer.write(example)
--> 596 num_examples, num_bytes = writer.finalize()
597
598 assert num_examples == num_examples, f"Expected to write {split_info.num_examples} but wrote {num_examples}"
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in finalize(self, close_stream)
173 def finalize(self, close_stream=True):
174 if self.pa_writer is not None:
--> 175 self.write_on_file()
176 self.pa_writer.close()
177 if close_stream:
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in write_on_file(self)
124 else:
125 # All good
--> 126 self._write_array_on_file(pa_array)
127 self.current_rows = []
128
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in _write_array_on_file(self, pa_array)
93 def _write_array_on_file(self, pa_array):
94 """Write a PyArrow Array"""
---> 95 pa_batch = pa.RecordBatch.from_struct_array(pa_array)
96 self._num_bytes += pa_array.nbytes
97 self.pa_writer.write_batch(pa_batch)
AttributeError: type object 'pyarrow.lib.RecordBatch' has no attribute 'from_struct_array'
When you install `nlp` for the first time on a Colab runtime, it updates the `pyarrow` library that was already on colab. This update shows this message on colab:
```
WARNING: The following packages were previously imported in this runtime:
[pyarrow]
You must restart the runtime in order to use newly installed versions.
```
You just have to restart the runtime and it should be fine. | [
-0.11933845281600952,
0.08862784504890442,
-0.00897780992090702,
0.21019737422466278,
0.3692678213119507,
0.026059836149215698,
0.4487815499305725,
0.4131021499633789,
0.4330812692642212,
0.012566991150379181,
0.12384359538555145,
0.395429790019989,
-0.15054914355278015,
0.021962707862257957,
0.12090519070625305,
-0.42898982763290405,
-0.03373972326517105,
0.3636728823184967,
-0.041466742753982544,
0.06297364085912704,
-0.1876835823059082,
0.10851715505123138,
-0.2651914358139038,
0.25500577688217163,
-0.30572283267974854,
-0.05702577531337738,
0.2159208357334137,
0.08206366002559662,
-0.07891867309808731,
-0.5590065121650696,
0.2770831286907196,
-0.2170492708683014,
0.06445172429084778,
0.11474639922380447,
-0.00010995571938110515,
0.20530645549297333,
0.33269721269607544,
0.030212881043553352,
-0.5799458026885986,
-0.18957795202732086,
-0.4773316979408264,
-0.11893881857395172,
0.29743173718452454,
-0.2497076690196991,
-0.028513483703136444,
0.05389726161956787,
0.035910993814468384,
-0.07441209256649017,
0.29674679040908813,
0.531506359577179,
0.237888902425766,
0.5236923694610596,
0.15454915165901184,
0.03449363261461258,
-0.07856784015893936,
-0.17057108879089355,
-0.08211500197649002,
0.22396822273731232,
0.07387731224298477,
-0.39154377579689026,
-0.013373926281929016,
0.1269245445728302,
0.15117238461971283,
0.26370200514793396,
0.5083709359169006,
0.014393925666809082,
0.2405235767364502,
-0.15062691271305084,
0.014946820214390755,
0.07640057057142258,
0.3353826403617859,
-0.1649332046508789,
-0.2715998888015747,
-0.2243589460849762,
0.2476661205291748,
-0.33475619554519653,
0.2365303635597229,
-0.03667646646499634,
-0.16220436990261078,
-0.008197136223316193,
-0.26922789216041565,
-0.028147468343377113,
-0.24182075262069702,
0.3526870608329773,
-0.058214087039232254,
0.49964913725852966,
0.043583355844020844,
0.1427474468946457,
-0.05806552246212959,
-0.07545772939920425,
0.14037704467773438,
-0.08709109574556351,
-0.1293005496263504,
0.25781309604644775,
-0.38315531611442566,
-0.036467600613832474,
-0.034946344792842865,
-0.11697594076395035,
-0.031624749302864075,
0.26352018117904663,
0.21998973190784454,
-0.22487351298332214,
0.3238390386104584,
0.3154153525829315,
0.22298845648765564,
0.42046889662742615,
0.07276557385921478,
0.06359237432479858,
-0.08280497789382935,
0.1360260546207428,
-0.23372812569141388,
-0.15548521280288696,
-0.1555362045764923,
-0.1765558421611786,
0.09289798140525818,
-0.15460222959518433,
0.22602073848247528,
-0.07111581414937973,
-0.4984738230705261,
0.11472072452306747,
-0.14340484142303467,
0.046290118247270584,
0.20511485636234283,
0.17948494851589203,
-0.12763413786888123,
0.23223412036895752,
0.14412455260753632,
0.2825669050216675,
-0.25197696685791016,
-0.04313553497195244,
-0.16628961265087128,
0.249213308095932,
-0.23438286781311035,
-0.18224890530109406,
0.24275390803813934,
0.193400040268898,
0.3994784653186798,
-0.10116767883300781,
0.11126405000686646,
-0.2017553448677063,
0.2273758500814438,
-0.04551952704787254,
-0.1288793981075287,
0.25665315985679626,
-0.21606102585792542,
0.1548980474472046,
0.20159120857715607,
-0.2824234366416931,
-0.0848238617181778,
-0.10174446552991867,
-0.27263572812080383,
-0.30809223651885986,
-0.1262514442205429,
0.28141558170318604,
0.147381991147995,
-0.24296480417251587,
-0.15226313471794128,
-0.06118778511881828,
0.14749255776405334,
-0.36872372031211853,
-0.11810629814863205,
-0.4612586498260498,
-0.22063903510570526,
-0.023005738854408264,
0.3976435363292694,
0.20490935444831848,
0.13138674199581146,
-0.1089726984500885,
-0.11542053520679474,
0.07785429060459137,
-0.031797103583812714,
0.1227136105298996,
-0.43835723400115967,
0.5421629548072815,
-0.06105594336986542,
0.118863046169281,
0.64134681224823,
-0.3427872657775879,
-0.4578544795513153,
0.12356892228126526,
-0.014279965311288834,
0.20932787656784058,
-0.22536897659301758,
-0.01672065444290638,
-0.013226330280303955,
-0.1845511645078659,
0.21231377124786377,
0.6192131042480469,
-0.015042958781123161,
0.08247934281826019,
-0.12689706683158875,
-0.01554920244961977,
0.5002195239067078,
0.10985688865184784,
0.09252531826496124,
-0.007928885519504547,
-0.04170481115579605,
0.49664852023124695,
-0.00131293386220932,
-0.12597057223320007,
-0.014860082417726517,
-0.013630155473947525,
-0.06468622386455536,
-0.10460402071475983,
-0.2178265005350113,
-0.07388680428266525,
-0.2776644825935364,
0.30430400371551514,
-0.11754798144102097,
-0.05853193253278732,
-0.04715031385421753,
0.10618656873703003,
-0.34911325573921204,
0.16848869621753693,
-0.42326927185058594,
-0.3773188889026642,
0.17209337651729584,
0.15513363480567932,
-0.01082286611199379,
0.23844115436077118,
-0.20474110543727875,
0.21943674981594086,
-0.2740277051925659,
0.055500876158475876,
-0.21892870962619781,
0.16128991544246674,
-0.05588398873806,
-0.04242202267050743,
-0.009479247033596039,
0.30879634618759155,
0.03833160549402237,
-0.017996493726968765,
-0.3062889277935028,
0.28603029251098633,
-0.12548455595970154,
0.08035629242658615,
-0.03226495534181595,
-0.14337028563022614,
0.06880630552768707,
-0.07154297828674316,
-0.17518453299999237,
0.20819191634655,
0.33195099234580994,
-0.18012642860412598,
-0.04314299672842026,
0.11287609487771988,
0.1272123008966446,
0.0814221054315567,
0.09886433184146881,
0.16397228837013245,
0.14399199187755585,
-0.06582621484994888,
0.1012795940041542,
0.07743129134178162,
0.23370946943759918,
-0.09498715400695801,
0.20471079647541046,
-0.15645107626914978,
-0.1671449989080429,
-0.11880645900964737,
0.3131202161312103,
0.17005868256092072,
0.16741719841957092,
0.08148638904094696,
-0.2752525210380554,
-0.09487432986497879,
0.07855785638093948,
0.14604909718036652,
0.40096497535705566,
-0.0518328957259655,
-0.10834059119224548,
-0.05257079750299454,
-0.4165968596935272,
0.07112551480531693,
0.17070795595645905,
0.03662925213575363,
0.20912905037403107,
0.30185645818710327,
0.04131554812192917,
0.0873207226395607,
-0.2952670454978943,
-0.35701698064804077,
0.2824336886405945,
0.4405299723148346,
-0.22848191857337952,
0.20788007974624634,
-0.03053159825503826,
-0.0025112517178058624,
-0.06784830242395401,
-0.33363378047943115,
-0.18862853944301605,
-0.342993825674057,
-0.12133617699146271,
0.433775395154953,
0.024119451642036438,
0.181004598736763,
-0.3977614641189575,
-0.022051095962524414,
0.19475087523460388,
-0.11478548496961594,
-0.03137951344251633,
-0.3157978653907776,
-0.2693289816379547,
0.04594217613339424,
0.3818606734275818,
0.09107664972543716,
0.3510980010032654,
-0.06677059084177017,
-0.0925356075167656,
-0.007035041227936745,
-0.05841507762670517,
-0.07556726038455963,
-0.18372085690498352,
0.2440476268529892,
0.009521827101707458,
0.2855835258960724,
-0.17702968418598175,
-0.5220333337783813,
0.5017467737197876,
-0.25570181012153625,
-0.057785287499427795,
0.31510666012763977,
0.27111297845840454,
-0.24919047951698303,
-0.07947683334350586,
-0.37468862533569336,
-0.12645035982131958,
-0.28060582280158997,
-0.05946876108646393,
0.07482925057411194,
0.062020909041166306,
0.39746737480163574,
0.07085651159286499,
0.21601088345050812,
-0.0025735688395798206,
0.1134379655122757,
-0.04826278239488602,
-0.09006398171186447,
0.1859847605228424,
-0.31003400683403015,
-0.31731829047203064,
-0.12134282290935516,
0.00993594154715538,
0.3347616195678711,
0.11073551326990128,
-0.3489593267440796,
-0.21413181722164154,
-0.10495822131633759,
0.08531276881694794,
-0.2213253676891327,
-0.04006670415401459,
0.18286007642745972,
0.07230357825756073,
-0.06572244316339493,
-0.08664388954639435,
0.03598948195576668,
0.07124010473489761,
0.15234598517417908,
0.13496194779872894,
-0.006304748356342316,
0.08922688663005829,
-0.08488400280475616,
0.6008991599082947,
0.21869370341300964,
-0.21437688171863556,
0.30028587579727173,
-0.10327673703432083,
0.005144510418176651,
-0.208683580160141,
-0.4398045539855957,
0.26416414976119995,
-0.11523276567459106,
0.18292897939682007,
0.17231473326683044,
-0.07949357479810715,
-0.2247839719057083,
-0.1925591230392456,
0.06885170936584473,
-0.17844745516777039,
-0.27277958393096924,
0.14616836607456207,
-0.21739450097084045,
0.2787109315395355,
-0.06886422634124756,
0.22253704071044922,
-0.20522335171699524,
-0.16798070073127747,
0.06985078752040863,
0.16693411767482758,
-0.09054567664861679,
0.07967513799667358,
-0.24400167167186737,
-0.27610862255096436,
-0.4799582362174988,
-0.02783966064453125,
0.24103179574012756,
0.643750011920929,
-0.08638451993465424,
0.03718879818916321,
0.08072253316640854,
0.08174140751361847,
0.13737376034259796,
-0.2301362007856369,
0.1822635680437088,
0.2891308069229126,
0.03182467073202133,
-0.31974661350250244,
-0.06433149427175522,
-0.14011231064796448,
0.35801658034324646,
0.0766519159078598,
-0.054431721568107605,
-0.03723123297095299,
-0.1676540970802307,
0.1398320496082306,
0.2599392831325531,
-0.1872951090335846,
-0.044113077223300934,
-0.09173431247472763,
-0.08981046825647354,
-0.30776458978652954,
-0.006154969334602356,
-0.009947758167982101,
0.33566054701805115,
0.12296926230192184,
0.26572471857070923,
-0.5462992191314697,
0.11665705591440201,
0.09016524255275726,
0.17458684742450714,
0.09595315158367157,
0.057944219559431076,
0.18724678456783295,
-0.16663400828838348,
0.18321000039577484,
-0.14590442180633545,
0.5633803606033325,
0.14737597107887268,
-0.3307987451553345,
-0.31952953338623047,
0.02166324108839035,
0.16743338108062744,
0.18398034572601318,
-0.01858552172780037,
-0.14112097024917603,
-0.2769453525543213,
-0.06146351993083954,
-0.008708748035132885,
0.3045704662799835,
0.5610411167144775,
0.0026276633143424988,
-0.3271808922290802,
-0.2585407495498657,
0.4828394949436188,
-0.2850031852722168,
0.11732904613018036,
0.3215572237968445,
0.05337715521454811,
-0.3131922781467438,
0.08413887023925781,
0.07783256471157074,
0.6767752766609192,
0.16953882575035095,
0.3111467659473419,
0.3826707899570465,
0.18392826616764069,
0.4142706096172333,
-0.043089497834444046,
0.2847142815589905,
-0.3927357494831085,
-0.13342586159706116,
-0.08068586140871048,
-0.06546270102262497,
0.10708172619342804,
-0.008873388171195984,
-0.02543865703046322,
0.150621235370636,
0.15688925981521606,
-0.0041420795023441315,
0.05714789777994156,
0.4492526650428772,
-0.03878391534090042,
-0.1968192607164383,
-0.3470253050327301,
0.15601636469364166,
-0.21799974143505096,
0.2975102663040161,
-0.09073382616043091,
-0.06648421287536621,
0.05520467087626457,
-0.06735203415155411,
-0.25555843114852905,
0.2574385404586792,
-0.29947492480278015,
0.4594579339027405,
0.05782182514667511,
-0.4756813049316406,
0.1984151303768158,
0.20709790289402008,
0.1756638139486313,
0.0056989602744579315,
-0.29959404468536377,
0.23877887427806854,
-0.2900899052619934,
-0.22186626493930817,
-0.06728766113519669,
0.11194741725921631,
0.4200734496116638,
-0.17255154252052307,
-0.14637798070907593,
0.14794065058231354,
-0.12065417319536209,
-0.24150244891643524,
0.1039588451385498,
0.036866605281829834,
0.3524894714355469,
-0.3925756514072418,
-0.5152195692062378,
-0.0024207234382629395,
-0.18207629024982452,
-0.17491021752357483,
0.17450003325939178,
0.02345065027475357,
-0.18903149664402008,
0.15189561247825623,
0.14982710778713226,
-0.19898000359535217,
0.11640655994415283,
0.24804237484931946,
-0.2495403289794922,
0.14628303050994873,
0.7637573480606079,
0.03394555673003197,
0.01280517503619194,
-0.3138304352760315,
-0.05428845435380936,
0.12508459389209747,
-0.48199987411499023,
-0.1171272024512291,
0.12550412118434906,
0.16912586987018585,
-0.1442466676235199,
0.49836599826812744,
0.06302111595869064,
-0.01884474605321884,
0.24718548357486725,
-0.5424140095710754,
-0.10621928423643112,
-0.043021634221076965,
0.017753619700670242,
0.23777522146701813,
-0.0026239529252052307,
0.11488902568817139,
0.13550958037376404,
0.1033887192606926,
-0.2726374566555023,
0.014254427514970303,
-0.15762582421302795,
0.1379965841770172,
0.21783430874347687,
-0.1565312147140503,
0.22328168153762817,
-0.07694721221923828,
0.15638616681098938,
-0.09584659337997437,
-0.12303443253040314,
-0.24829328060150146,
-0.25483784079551697,
0.10011143982410431,
0.24556711316108704,
-0.1645212471485138,
-0.030679188668727875,
-0.10233347862958908,
0.02367764711380005,
-0.23110505938529968,
-0.00846264511346817,
-0.11772798001766205,
-0.2933427095413208,
0.38943231105804443,
0.04389800876379013,
0.27836859226226807,
-0.11169030517339706,
0.12635567784309387,
-0.30075740814208984,
0.14912036061286926,
-0.01849590800702572,
-0.07522959262132645,
0.27581319212913513,
0.09365326166152954,
-0.4658869206905365,
0.0054205358028411865,
-0.40260517597198486,
0.03714786097407341,
0.3698212504386902,
-0.4551103711128235,
0.15995843708515167,
-0.1316281408071518,
0.09546546638011932,
0.4656829833984375,
-0.27140846848487854,
-0.0036669299006462097,
0.3496653139591217,
0.23784254491329193,
-0.29741764068603516,
-0.1892606019973755,
0.2399907410144806,
0.061345674097537994,
0.03245936706662178,
0.02723889797925949,
0.04666122421622276,
-0.3037486672401428,
-0.32123446464538574,
0.08927963674068451,
-0.029340408742427826,
-0.2656012773513794,
-0.01140776090323925,
0.33932653069496155,
-0.002364441752433777,
-0.05951501801609993,
-0.0500493124127388,
0.21102115511894226,
0.03539281338453293,
0.38269317150115967,
-0.29260092973709106,
0.2069980353116989,
0.05926353484392166,
0.04391039162874222,
-0.11114301532506943,
-0.21921727061271667,
0.05030050128698349,
-0.15784099698066711,
0.03383420407772064,
0.2952827513217926,
0.09981479495763779,
0.1530807912349701,
-0.2855033874511719,
-0.12453707307577133,
-0.20802274346351624,
0.22792446613311768,
-0.17904222011566162,
-0.04890655726194382,
-0.24299554526805878,
0.02101702243089676,
-0.02587638422846794,
-0.09469917416572571,
-0.14167022705078125,
-0.0381786972284317,
0.3095560371875763,
0.2532220482826233,
-0.1722705215215683,
-0.45553502440452576,
0.10826653242111206,
0.3432941436767578,
0.18004727363586426,
-0.24588416516780853,
0.3368532359600067,
0.19381549954414368,
-0.06877827644348145,
-0.01412438228726387,
0.3971101641654968,
0.43576839566230774,
0.3383936583995819,
-0.364220529794693,
0.08116793632507324,
-0.20338064432144165,
-0.05682189017534256,
-0.023260291665792465,
0.2695123851299286,
0.10607316344976425,
0.11737622320652008,
0.46242257952690125,
0.12148632109165192,
-0.1247272789478302,
0.04363914206624031,
-0.08805669844150543,
-0.2605326473712921,
-0.26294705271720886,
0.5191487073898315,
0.1857946217060089,
-0.1143883466720581,
-0.32065102458000183,
0.1899377703666687,
-0.27498704195022583,
-0.08091447502374649,
0.06285165250301361,
0.24058954417705536,
0.11315394192934036,
-0.21382759511470795,
0.07050890475511551,
0.00031514279544353485,
0.7061734795570374,
0.48772192001342773,
-0.017719194293022156,
-0.3658052682876587,
-0.11652375012636185,
-0.5989872217178345,
0.21783632040023804,
-0.3639681041240692,
-0.26901817321777344,
0.2833365499973297,
-0.07233157753944397,
-0.288082480430603,
0.24852731823921204,
0.1276196390390396,
0.15819591283798218,
-0.05727645754814148,
0.09834779053926468,
-0.4907650053501129,
-0.14860455691814423,
-0.030650503933429718,
-0.007675016298890114,
-0.08318105340003967,
-0.25705307722091675,
0.14532306790351868,
-0.4349946677684784,
0.11610303074121475,
0.01198504213243723,
0.06934809684753418,
-0.00023945607244968414,
0.09664029628038406,
0.35442453622817993,
0.1653239130973816,
0.5012482404708862,
-0.03556128963828087,
0.0036574434489011765,
-0.1911543905735016,
-0.1566217541694641,
-0.2289923131465912,
0.13182267546653748,
0.08762918412685394,
0.5133118629455566,
-0.02610740251839161,
-0.06854520738124847,
-0.26402729749679565,
0.40316787362098694,
-0.08100667595863342,
0.08831582963466644,
-0.1350807249546051,
0.0773145779967308,
-0.0703495442867279,
0.2275840938091278,
0.2643648684024811,
0.42454031109809875,
-0.1783217340707779,
0.2022092193365097,
-0.2722919285297394,
-0.46024608612060547,
0.32893532514572144,
-0.661480724811554,
-0.517790675163269,
0.0751224160194397,
0.1161930188536644,
-0.1423342525959015,
0.05819430202245712,
-0.6006339192390442,
0.07056698948144913,
0.24261271953582764,
-0.1114056184887886,
-0.317119836807251,
0.21794511377811432,
0.016542082652449608,
0.08000141382217407,
0.04357365146279335,
0.4483563303947449,
-0.14847293496131897,
-0.15976761281490326,
-0.0049346014857292175,
-0.163252055644989
] |
https://github.com/huggingface/datasets/issues/166 | Add a method to shuffle a dataset | +1 for the naming convention
About the `shuffle` method, from my understanding it should be done in `Dataloader` (better separation between dataset processing - usage) | Could maybe be a `dataset.shuffle(generator=None, seed=None)` signature method.
Also, we could maybe have a clear indication of which method modify in-place and which methods return/cache a modified dataset. I kinda like torch conversion of having an underscore suffix for all the methods which modify a dataset in-place. What do you think? | 25 | Add a method to shuffle a dataset
Could maybe be a `dataset.shuffle(generator=None, seed=None)` signature method.
Also, we could maybe have a clear indication of which method modify in-place and which methods return/cache a modified dataset. I kinda like torch conversion of having an underscore suffix for all the methods which modify a dataset in-place. What do you think?
+1 for the naming convention
About the `shuffle` method, from my understanding it should be done in `Dataloader` (better separation between dataset processing - usage) | [
0.15341989696025848,
-0.037310101091861725,
-0.06269726157188416,
-0.12907017767429352,
0.17716169357299805,
0.08376287668943405,
0.2535592317581177,
0.2304861843585968,
-0.21282333135604858,
0.33027225732803345,
-0.07075794786214828,
0.7361391186714172,
-0.22251440584659576,
-0.2018119841814041,
0.023780349642038345,
-0.08247566223144531,
0.2442183494567871,
-0.21178573369979858,
-0.1650036722421646,
0.027072928845882416,
-0.11413007974624634,
-0.38973113894462585,
0.023244716227054596,
-0.14219342172145844,
-0.19263318181037903,
-0.0498332604765892,
-0.13309884071350098,
0.04740720987319946,
-0.24616168439388275,
-0.25444748997688293,
-0.46736636757850647,
0.7014355659484863,
-0.15274126827716827,
0.449937105178833,
-0.00011275450378889218,
-0.2929297387599945,
0.3552502989768982,
0.032352328300476074,
-0.3119528293609619,
0.07475161552429199,
-0.1722264140844345,
-0.07203903049230576,
0.06607111543416977,
-0.20177561044692993,
0.21404674649238586,
0.05777452886104584,
0.056991904973983765,
-0.1298425793647766,
0.16466911137104034,
-0.0894339457154274,
0.17472481727600098,
-0.09979449957609177,
-0.30139559507369995,
-0.01625042036175728,
0.5358918905258179,
0.5136167407035828,
-0.15510791540145874,
0.11450314521789551,
0.5382506251335144,
0.3613971173763275,
-0.1880669891834259,
0.156181201338768,
-0.09367482364177704,
-0.07671932876110077,
0.48861464858055115,
-0.29398173093795776,
-0.5896617770195007,
0.04415927454829216,
0.12085763365030289,
0.1790134310722351,
0.6000992059707642,
-0.20126229524612427,
-0.41691845655441284,
-0.24042877554893494,
0.26787981390953064,
-0.13337336480617523,
0.05386372655630112,
-0.19137075543403625,
-0.012277732603251934,
-0.1094486266374588,
-0.13056577742099762,
-0.15746831893920898,
-0.005668371915817261,
-0.05863003432750702,
0.4977310597896576,
0.529700517654419,
0.12314771115779877,
-0.019478455185890198,
0.1149400919675827,
0.004155231639742851,
0.5591570734977722,
-0.10236585140228271,
0.014495473355054855,
0.2615671157836914,
-0.11023664474487305,
-0.10021746903657913,
-0.007673762738704681,
0.2563236355781555,
0.2494794726371765,
0.11320117115974426,
0.3054129481315613,
0.2701375186443329,
-0.06867581605911255,
0.07461673766374588,
-0.06943447887897491,
-0.07609111070632935,
0.0326872393488884,
-0.04483646899461746,
0.2888600826263428,
-0.3153234124183655,
0.179962158203125,
-0.11023575812578201,
-0.15132713317871094,
-0.05018090084195137,
0.03848663344979286,
0.12834730744361877,
-0.3014702796936035,
-0.10199998319149017,
0.19806785881519318,
-0.5291101932525635,
0.06318304687738419,
-0.4272432327270508,
0.07826334983110428,
0.11914832144975662,
0.29036223888397217,
0.11539510637521744,
-0.15124547481536865,
0.049449652433395386,
0.29246804118156433,
-0.1264243870973587,
-0.06676331162452698,
0.0325259193778038,
-0.474370539188385,
0.2319803237915039,
0.1612490564584732,
-0.2171570211648941,
0.10984321683645248,
0.08951105922460556,
0.15006762742996216,
0.22949722409248352,
0.16365483403205872,
0.2171189785003662,
0.32886338233947754,
-0.1775379329919815,
-0.44875964522361755,
-0.06935002654790878,
-0.09622713923454285,
0.29492223262786865,
-0.2965107858181,
0.2620725631713867,
-0.27368491888046265,
-0.2621244490146637,
-0.06397712230682373,
0.12658850848674774,
-0.025156602263450623,
-0.10126557946205139,
-0.2362121343612671,
0.20045337080955505,
0.11881725490093231,
-0.3033382296562195,
0.3808515965938568,
0.1356823444366455,
0.18717367947101593,
-0.10355515033006668,
-0.030979741364717484,
0.259865403175354,
-0.09520679712295532,
-0.020418502390384674,
-0.3389224112033844,
-0.10294423997402191,
0.18109747767448425,
0.11230626702308655,
-0.16153833270072937,
0.023971259593963623,
-0.12279897183179855,
-0.1310102790594101,
0.48198848962783813,
0.21702727675437927,
-0.17160694301128387,
-0.03480614349246025,
-0.15349331498146057,
-0.16826380789279938,
0.5057481527328491,
0.32181769609451294,
-0.07960885018110275,
-0.2573795020580292,
0.28341472148895264,
-0.09259987622499466,
-0.4131712019443512,
0.037119559943675995,
-0.23320911824703217,
-0.13467749953269958,
0.38062286376953125,
0.2380649596452713,
-0.0918971449136734,
0.001127682626247406,
0.0451047383248806,
-0.4092564880847931,
0.18580007553100586,
-0.1324031800031662,
-0.12164705246686935,
-0.252774715423584,
-0.029326658695936203,
0.3391715884208679,
-0.08386562019586563,
-0.09441967308521271,
-0.03489300608634949,
-0.15264181792736053,
0.2866232097148895,
-0.10843174159526825,
0.028408020734786987,
-0.29122602939605713,
0.038068488240242004,
-0.3927571177482605,
-0.004562634974718094,
-0.12355299293994904,
0.03388376533985138,
0.24871128797531128,
-0.24041326344013214,
-0.23405371606349945,
-0.2861441969871521,
-0.19298109412193298,
-0.1690485179424286,
-0.1284978985786438,
-0.22818197309970856,
-0.05662815272808075,
-0.04576103389263153,
-0.046052467077970505,
-0.27629995346069336,
0.20862233638763428,
-0.030198633670806885,
-0.08184047043323517,
-0.17129185795783997,
0.26135411858558655,
0.08897054195404053,
-0.13293933868408203,
0.43658536672592163,
0.345750629901886,
-0.0626278668642044,
0.09248360991477966,
0.1802336722612381,
-0.056374941021203995,
-0.01670355722308159,
-0.09874457120895386,
-0.2994474768638611,
0.2603796124458313,
-0.2665768563747406,
0.09091302007436752,
-0.2621859610080719,
-0.318847119808197,
-0.047044798731803894,
0.37200817465782166,
-0.26494839787483215,
0.1697956919670105,
0.1168682873249054,
0.2092730849981308,
0.35136839747428894,
0.16266946494579315,
-0.3234311044216156,
-0.139518141746521,
0.26496991515159607,
-0.159983828663826,
-0.02203412353992462,
0.34199294447898865,
0.20328062772750854,
-0.24940231442451477,
0.14528779685497284,
0.06851378083229065,
0.37311041355133057,
0.3408048152923584,
0.012890361249446869,
0.07192341238260269,
0.279762327671051,
-0.1501164585351944,
-0.04826968163251877,
0.16651786863803864,
-0.28262168169021606,
-0.01117776334285736,
0.17486003041267395,
0.12027426064014435,
-0.1523294895887375,
-0.38304707407951355,
0.07604926824569702,
0.032207027077674866,
-0.03617866337299347,
-0.07769874483346939,
-0.018525294959545135,
-0.07378381490707397,
-0.2008935809135437,
-0.1971311718225479,
-0.3390846252441406,
-0.2624276578426361,
0.26744744181632996,
0.05849086120724678,
-0.29521071910858154,
0.38806024193763733,
0.18326818943023682,
0.5487815737724304,
-0.2152482271194458,
-0.10795969516038895,
-0.35612156987190247,
-0.4411761164665222,
0.12635695934295654,
0.040955934673547745,
0.22586002945899963,
-0.1359720677137375,
0.7025216817855835,
-0.051004648208618164,
-0.07998791337013245,
-0.382279634475708,
-0.4698299467563629,
-0.08981539309024811,
-0.0074404142796993256,
-0.25710999965667725,
0.382809042930603,
-0.32705962657928467,
0.08849550783634186,
-0.47281864285469055,
-0.06896976381540298,
-0.2552247941493988,
-0.010260610841214657,
0.007352788001298904,
-0.010249239392578602,
0.009276734665036201,
-0.18420101702213287,
-0.29757723212242126,
-0.13124610483646393,
-0.40497976541519165,
0.074064239859581,
-0.6318063735961914,
-0.0500297024846077,
0.012037180364131927,
-0.28683409094810486,
-0.1324150413274765,
-0.22056880593299866,
0.16137036681175232,
-0.13669763505458832,
-0.7596741318702698,
0.19291149079799652,
-0.20223425328731537,
0.057574350386857986,
-0.1422053724527359,
-0.06971137225627899,
0.028892938047647476,
0.6446990370750427,
0.2754821181297302,
-0.16692981123924255,
0.14853470027446747,
0.20165473222732544,
-0.0016144923865795135,
0.15614524483680725,
0.3470441699028015,
0.28477585315704346,
-0.12292183190584183,
0.06234151870012283,
-0.23541176319122314,
-0.11293720453977585,
-0.1072697564959526,
0.31545379757881165,
0.10719215124845505,
0.3211008310317993,
0.01664702221751213,
0.6867965459823608,
-0.6602864861488342,
-0.09058082103729248,
0.01934916153550148,
0.20021802186965942,
0.13724634051322937,
-0.06796775013208389,
-0.09096982330083847,
0.5424612760543823,
0.24561837315559387,
-0.3071576952934265,
0.19216035306453705,
-0.04839305579662323,
-0.16012327373027802,
0.037762805819511414,
0.1311073750257492,
-0.14749892055988312,
-0.14253079891204834,
0.34279873967170715,
-0.32730862498283386,
0.08625137805938721,
-0.04006420075893402,
0.17369800806045532,
-0.29519936442375183,
0.004260499030351639,
0.14684420824050903,
0.20264247059822083,
0.32880860567092896,
-0.27043113112449646,
-0.43609973788261414,
-0.021180186420679092,
-0.12659403681755066,
0.29588377475738525,
0.2474624216556549,
0.12883858382701874,
-0.013604741543531418,
-0.18180373311042786,
0.122365303337574,
0.2576231360435486,
0.4825328588485718,
-0.24698953330516815,
-0.28336113691329956,
-0.005569253116846085,
-0.016896996647119522,
-0.11249476671218872,
0.015213456004858017,
-0.075557641685009,
0.14184683561325073,
0.07289402186870575,
0.09383468329906464,
-0.22726130485534668,
-0.17683012783527374,
0.11363396048545837,
0.19612252712249756,
0.16109314560890198,
-0.33927249908447266,
-0.08296407759189606,
-0.16535870730876923,
-0.15990211069583893,
0.19259142875671387,
-0.023795748129487038,
-0.30083730816841125,
-0.055608510971069336,
0.05883060023188591,
-0.03348209708929062,
0.3097732365131378,
0.026684239506721497,
0.12922780215740204,
0.03208727389574051,
0.1218257024884224,
0.04497941955924034,
0.01223859004676342,
0.37701907753944397,
0.42766568064689636,
-0.20563459396362305,
-0.48697629570961,
-0.170944482088089,
0.01451437920331955,
-0.5441601276397705,
0.24406981468200684,
0.23828548192977905,
0.2514321208000183,
0.29675230383872986,
-0.14040754735469818,
0.1760656088590622,
-0.218506321310997,
0.07353851944208145,
0.05243784189224243,
0.007404102012515068,
-0.5293942093849182,
-0.9117103815078735,
0.5416220426559448,
0.37718644738197327,
-0.32241392135620117,
0.5554148554801941,
0.0005213767290115356,
-0.2684897184371948,
0.4150931239128113,
0.2951989471912384,
1.2055474519729614,
-0.08146865665912628,
0.18745803833007812,
-0.0292167030274868,
-0.3767351508140564,
0.27660760283470154,
-0.18090739846229553,
0.14939947426319122,
-0.1293390691280365,
-0.39364707469940186,
0.05398126691579819,
-0.08897186815738678,
0.07474078983068466,
0.3279804587364197,
-0.12489880621433258,
0.34531208872795105,
-0.3932633399963379,
0.17307855188846588,
0.1445833146572113,
0.12142482399940491,
-0.24394631385803223,
-0.29141977429389954,
-0.08227938413619995,
0.07282465696334839,
-0.09159129858016968,
-0.21026615798473358,
-0.033486489206552505,
-0.005069621838629246,
-0.06700876355171204,
0.14088626205921173,
-0.14437377452850342,
-0.3057858645915985,
0.15224632620811462,
-0.0800418108701706,
-0.2814944088459015,
-0.17594867944717407,
0.4433322846889496,
0.10858981311321259,
0.2535843253135681,
0.07985029369592667,
0.16678963601589203,
0.2920089066028595,
0.08756481856107712,
0.40555620193481445,
-0.0955696776509285,
-0.08928123861551285,
0.10746953636407852,
0.08212121576070786,
-0.048722848296165466,
0.030048537999391556,
0.11088299751281738,
-0.42860132455825806,
-0.5298833847045898,
-0.08485546708106995,
0.5617538690567017,
-0.1269344538450241,
0.09261015057563782,
0.0187520831823349,
-0.10598739981651306,
-0.01749984733760357,
0.13704358041286469,
0.278785765171051,
-0.2586563229560852,
0.36239713430404663,
-0.21821726858615875,
0.019990622997283936,
-0.1200646460056305,
0.10490235686302185,
-0.2883315980434418,
-0.12774547934532166,
0.21792252361774445,
-0.2194971889257431,
-0.19734559953212738,
-0.16577619314193726,
0.11748946458101273,
0.233148455619812,
-0.004312954843044281,
0.0334511324763298,
-0.13740471005439758,
-0.27819085121154785,
-0.1548794060945511,
-0.15670913457870483,
0.21951740980148315,
0.3490118682384491,
-0.03535391390323639,
0.11037425696849823,
-0.4601903259754181,
0.07673440128564835,
0.1705334335565567,
0.3398687541484833,
-0.16756445169448853,
-0.04664931073784828,
-0.11511196941137314,
-0.019233787432312965,
-0.3286210894584656,
-0.1494593471288681,
0.2203085720539093,
0.27189552783966064,
0.009397382847964764,
0.22101452946662903,
-0.2014082372188568,
-0.24054953455924988,
0.06552565842866898,
0.06110464408993721,
-0.018643217161297798,
-0.14807040989398956,
-0.13654419779777527,
0.11171083897352219,
-0.07000520825386047,
0.2294294387102127,
0.20375722646713257,
-0.0818171575665474,
-0.002820374444127083,
-0.25039294362068176,
0.02648245543241501,
0.29474928975105286,
0.005087465047836304,
0.4968271255493164,
0.6184066534042358,
0.0818525031208992,
-0.21739962697029114,
0.20662236213684082,
-0.025502480566501617,
0.031439997255802155,
0.12063337862491608,
0.14772596955299377,
-0.026562681421637535,
-0.020382672548294067,
0.11907152831554413,
0.3216317892074585,
0.18479996919631958,
0.06783601641654968,
-0.09052736312150955,
0.2885022461414337,
0.193085715174675,
0.45367830991744995,
0.09952227026224136,
0.4589996635913849,
0.0012196345487609506,
-0.35758090019226074,
0.43149542808532715,
0.2065579891204834,
-0.019028961658477783,
-0.07362893968820572,
-0.2535402774810791,
-0.005758973769843578,
0.0805494636297226,
-0.005397506058216095,
-0.22965003550052643,
0.015039943158626556,
-0.3449506163597107,
-0.07759958505630493,
0.14512397348880768,
-0.478800892829895,
0.3961937129497528,
0.3324783146381378,
-0.12170538306236267,
-0.02795560285449028,
0.3708794414997101,
0.009444952011108398,
-0.26959097385406494,
0.13245993852615356,
0.4628448486328125,
0.9553411602973938,
0.3267765939235687,
0.16063372790813446,
0.13742747902870178,
0.14922748506069183,
0.16059593856334686,
0.6927061676979065,
0.341178834438324,
0.0890379548072815,
0.3850887715816498,
0.22731852531433105,
0.14771747589111328,
-0.3402741849422455,
0.2771570682525635,
0.07764579355716705,
0.25607356429100037,
0.030500028282403946,
-0.06635604798793793,
-0.19421157240867615,
-0.2519179582595825,
-0.08347742259502411,
0.012616932392120361,
0.051535092294216156,
0.5799620151519775,
0.2349970042705536,
0.25914323329925537,
-0.3528333902359009,
0.126642644405365,
0.2718268632888794,
0.4411761164665222,
-0.15010902285575867,
-0.40551549196243286,
0.14202538132667542,
-0.17151226103305817,
0.745175838470459,
-0.01977100782096386,
-0.001275382936000824,
0.2458317130804062,
0.029737230390310287,
0.1183306872844696,
-0.3746950328350067,
-0.03710135072469711,
-0.01562034897506237,
0.12326828390359879,
0.14358177781105042,
-0.17993007600307465,
-0.012090180069208145,
0.17657999694347382,
-0.14344370365142822,
0.07518965005874634,
-0.07518407702445984,
-0.04627443477511406,
-0.1835743933916092,
0.344208300113678,
0.49961671233177185,
-0.30887603759765625,
0.1062355786561966,
-0.08491865545511246,
-0.1956767439842224,
-0.15276408195495605,
0.04055929183959961,
0.16102313995361328,
-0.20532777905464172,
0.09134699404239655,
0.05906745046377182,
0.2930762767791748,
0.28379178047180176,
0.2766534090042114,
-0.007268339395523071,
-0.14981020987033844,
-0.39398545026779175,
-0.3894713819026947,
-0.1301598846912384,
0.4760110080242157,
0.0036115478724241257,
-0.03547752648591995,
-0.1831997185945511,
0.03684106469154358,
-0.06707943230867386,
0.14567506313323975,
-0.1224084123969078,
0.05333206057548523,
0.19794237613677979,
-0.357058048248291,
-0.1212211549282074,
-0.13139519095420837,
-0.022572332993149757,
0.1836550533771515,
-0.061004143208265305,
-0.30679693818092346,
0.41008299589157104,
0.04413165897130966,
-0.3097118139266968,
0.1448230892419815,
0.06988412141799927,
0.11397361755371094,
0.21174103021621704,
-0.019559109583497047,
0.388078898191452,
-0.0024604089558124542,
-0.1821300983428955,
0.026386026293039322,
-0.14211679995059967,
-0.5724015831947327,
0.12119083851575851,
0.007544107735157013,
-0.011270652525126934,
-0.03836609795689583,
-0.20877541601657867,
-0.44213399291038513,
0.548570454120636,
-0.35532158613204956,
0.08550754934549332,
-0.7277730703353882,
0.15805087983608246,
0.24726364016532898,
0.08188671618700027,
-0.04858000949025154,
0.11439962685108185,
0.05100638046860695,
0.27076050639152527,
-0.22954663634300232,
0.19431617856025696,
0.5219244956970215,
0.16950620710849762,
-0.24273917078971863,
-0.32140734791755676,
0.21311473846435547,
-0.08961277455091476,
0.029533321037888527,
-0.31957271695137024,
-0.08377373218536377,
0.23225055634975433,
0.003435719758272171,
0.07984821498394012,
0.38395240902900696,
0.1284504383802414,
-0.0466567799448967,
-0.22277195751667023,
-0.001449093222618103,
-0.1201058104634285,
-0.030343756079673767,
-0.11485505104064941,
-0.2884330153465271
] |
https://github.com/huggingface/datasets/issues/166 | Add a method to shuffle a dataset | +1 for shuffle in `Dataloader`.
Some `Dataloader` just store idxs of dataset and just shuffle those idxs, which might(?) be faster than do shuffle in dataset, especially when doing shuffle every epoch.
Also +1 for the naming convention. | Could maybe be a `dataset.shuffle(generator=None, seed=None)` signature method.
Also, we could maybe have a clear indication of which method modify in-place and which methods return/cache a modified dataset. I kinda like torch conversion of having an underscore suffix for all the methods which modify a dataset in-place. What do you think? | 38 | Add a method to shuffle a dataset
Could maybe be a `dataset.shuffle(generator=None, seed=None)` signature method.
Also, we could maybe have a clear indication of which method modify in-place and which methods return/cache a modified dataset. I kinda like torch conversion of having an underscore suffix for all the methods which modify a dataset in-place. What do you think?
+1 for shuffle in `Dataloader`.
Some `Dataloader` just store idxs of dataset and just shuffle those idxs, which might(?) be faster than do shuffle in dataset, especially when doing shuffle every epoch.
Also +1 for the naming convention. | [
0.07046830654144287,
0.016060546040534973,
-0.081076979637146,
-0.13309326767921448,
0.18675069510936737,
-0.018765434622764587,
0.3612537086009979,
0.2494378238916397,
-0.1316787302494049,
0.39812397956848145,
-0.11517098546028137,
0.745942234992981,
-0.32974594831466675,
-0.21496982872486115,
-0.04452400282025337,
-0.07981567084789276,
0.2653793692588806,
-0.1031481921672821,
-0.2052428424358368,
0.0562237948179245,
-0.12470757961273193,
-0.34814876317977905,
0.02367430180311203,
-0.14052945375442505,
-0.08968804776668549,
0.01218579150736332,
-0.11303740739822388,
0.0714677944779396,
-0.2733202874660492,
-0.218613401055336,
-0.4450688660144806,
0.7157349586486816,
-0.1049821525812149,
0.566881000995636,
-0.00010911502613453194,
-0.25887179374694824,
0.341471791267395,
0.032926589250564575,
-0.35604017972946167,
0.1413135975599289,
-0.13315832614898682,
-0.07831971347332001,
0.038680098950862885,
-0.272943913936615,
0.22207000851631165,
-0.03439842164516449,
0.11589889973402023,
-0.11278656870126724,
0.11099021136760712,
-0.1473732888698578,
0.1819334626197815,
-0.09936526417732239,
-0.3846816420555115,
0.002091312548145652,
0.5785199999809265,
0.46103423833847046,
-0.2091200351715088,
0.18245258927345276,
0.5745741724967957,
0.3853928744792938,
-0.33382806181907654,
0.1915493905544281,
-0.13094337284564972,
-0.1019473671913147,
0.5779687762260437,
-0.30015552043914795,
-0.539605975151062,
0.06476444005966187,
-0.03939133137464523,
0.20368918776512146,
0.6476193070411682,
-0.19023606181144714,
-0.4480341076850891,
-0.1510586142539978,
0.18167032301425934,
-0.04967717081308365,
0.03078971803188324,
-0.24211889505386353,
-0.01957586407661438,
-0.08532571792602539,
-0.03737848252058029,
-0.11297060549259186,
-0.002562493085861206,
-0.13636167347431183,
0.4217982590198517,
0.5597809553146362,
0.15498246252536774,
-0.0286143496632576,
0.23609453439712524,
-0.022240005433559418,
0.5372042655944824,
-0.06967476010322571,
0.07333254814147949,
0.23729828000068665,
-0.21732141077518463,
-0.18081368505954742,
-0.015533536672592163,
0.211710125207901,
0.18797332048416138,
0.10574356466531754,
0.30266353487968445,
0.2721402049064636,
0.013140109367668629,
0.1095646321773529,
-0.11448945105075836,
-0.03855254873633385,
0.033464789390563965,
-0.10943488031625748,
0.37629491090774536,
-0.2285958230495453,
0.15266044437885284,
-0.08162569999694824,
-0.26237422227859497,
-0.01783922128379345,
0.10215289890766144,
0.14140647649765015,
-0.413308322429657,
0.056872230023145676,
0.17915107309818268,
-0.491369366645813,
0.15620630979537964,
-0.42619937658309937,
0.10317113250494003,
0.18962308764457703,
0.18701566755771637,
0.13203954696655273,
-0.15503767132759094,
-0.0127902552485466,
0.21155117452144623,
-0.18474049866199493,
-0.10223613679409027,
0.04918678104877472,
-0.507145345211029,
0.2194851040840149,
0.10138165950775146,
-0.2031901627779007,
0.11597613245248795,
0.03873898833990097,
0.13651734590530396,
0.3439450263977051,
0.1533035933971405,
0.20069317519664764,
0.19247902929782867,
-0.2556219696998596,
-0.4391716718673706,
-0.12956403195858002,
-0.14438550174236298,
0.3152363896369934,
-0.2803958058357239,
0.24230843782424927,
-0.2930678427219391,
-0.23662276566028595,
-0.11380833387374878,
0.17173609137535095,
-0.001863684505224228,
-0.06199924647808075,
-0.2293267548084259,
0.2463952898979187,
0.07400448620319366,
-0.30563846230506897,
0.4155254364013672,
0.07851982861757278,
0.17123425006866455,
-0.12333601713180542,
-0.07254890352487564,
0.2618194818496704,
-0.11126986145973206,
-0.018436145037412643,
-0.23025205731391907,
-0.16228759288787842,
0.2056494504213333,
0.11422605812549591,
-0.19200213253498077,
0.00789506733417511,
-0.1419527530670166,
-0.14744582772254944,
0.4907086193561554,
0.18126294016838074,
-0.15881508588790894,
-0.012354780919849873,
-0.11443603038787842,
-0.10257536917924881,
0.6056382656097412,
0.3467119634151459,
0.05649430304765701,
-0.33416399359703064,
0.2879277765750885,
-0.06120084226131439,
-0.3102132976055145,
0.09815352410078049,
-0.22475816309452057,
-0.11841296404600143,
0.38146328926086426,
0.26114925742149353,
-0.12281814217567444,
-0.009176865220069885,
0.0056611523032188416,
-0.3373616337776184,
0.19471287727355957,
-0.17169393599033356,
-0.07312556356191635,
-0.23634667694568634,
-0.08199551701545715,
0.30896878242492676,
-0.015054728835821152,
-0.06498883664608002,
-0.06311679631471634,
-0.1157575398683548,
0.29175838828086853,
0.0176498144865036,
0.18580931425094604,
-0.281282901763916,
0.029021091759204865,
-0.2989603579044342,
-0.01543935015797615,
-0.17469657957553864,
0.061628445982933044,
0.26166319847106934,
-0.22212836146354675,
-0.2475365847349167,
-0.2646145820617676,
-0.1795038878917694,
-0.27028512954711914,
-0.16231746971607208,
-0.25778427720069885,
-0.10035745054483414,
-0.04210995137691498,
0.027301959693431854,
-0.2138468325138092,
0.2204703390598297,
-0.13025018572807312,
-0.07318171113729477,
-0.15486472845077515,
0.24804913997650146,
0.11062881350517273,
0.0012296810746192932,
0.30390554666519165,
0.3766377568244934,
-0.023014439269900322,
0.07872435450553894,
0.30762720108032227,
-0.08393964171409607,
0.012866853736341,
-0.11360392719507217,
-0.27618739008903503,
0.2542322874069214,
-0.23281978070735931,
0.08788233995437622,
-0.2713022232055664,
-0.3496970534324646,
-0.008261360228061676,
0.35968276858329773,
-0.33686205744743347,
0.23720219731330872,
0.12871089577674866,
0.27883729338645935,
0.4074001610279083,
0.2508475184440613,
-0.3290272057056427,
-0.13281577825546265,
0.3740355968475342,
-0.12329480051994324,
-0.07980761677026749,
0.3697061836719513,
0.12849664688110352,
-0.2949621081352234,
0.11040480434894562,
0.08891589939594269,
0.3699168860912323,
0.34708428382873535,
0.07254628837108612,
-0.033813491463661194,
0.331180214881897,
-0.13317978382110596,
-0.010054424405097961,
0.09691943973302841,
-0.13696503639221191,
-0.02087973803281784,
0.10166246443986893,
0.058118030428886414,
-0.1998406946659088,
-0.5052339434623718,
0.033564887940883636,
0.09178837388753891,
0.03976184502243996,
-0.07727980613708496,
0.05568966269493103,
-0.05265963077545166,
-0.14146248996257782,
-0.17583584785461426,
-0.2801251709461212,
-0.27149176597595215,
0.2531289756298065,
0.10748499631881714,
-0.3382929563522339,
0.33368679881095886,
0.18314342200756073,
0.5316723585128784,
-0.15840722620487213,
-0.05841858685016632,
-0.37355005741119385,
-0.447194367647171,
0.15386386215686798,
0.07673262059688568,
0.2285132259130478,
-0.1827123463153839,
0.6215428113937378,
-0.035527683794498444,
-0.06387980282306671,
-0.3513753414154053,
-0.3830469250679016,
-0.06246766448020935,
-0.004240013659000397,
-0.2293926179409027,
0.3913438320159912,
-0.22182045876979828,
0.11684173345565796,
-0.4907088279724121,
-0.005510867573320866,
-0.3185173571109772,
-0.10767782479524612,
0.027148324996232986,
0.025267956778407097,
0.013321095146238804,
-0.16682873666286469,
-0.24212759733200073,
-0.17180229723453522,
-0.4843711853027344,
0.03587126359343529,
-0.5416005253791809,
-0.002558000385761261,
0.01305378321558237,
-0.2118820697069168,
-0.10356827825307846,
-0.11099404841661453,
0.15742120146751404,
-0.15449339151382446,
-0.816232442855835,
0.22808286547660828,
-0.18251317739486694,
0.07005289196968079,
-0.22892799973487854,
-0.11542637646198273,
0.08359460532665253,
0.6077487468719482,
0.22179462015628815,
-0.06396794319152832,
0.13452968001365662,
0.13789765536785126,
0.03936556726694107,
0.16842582821846008,
0.26220953464508057,
0.30263376235961914,
-0.1816999614238739,
0.0207793191075325,
-0.2253594547510147,
-0.08990485221147537,
-0.12235292047262192,
0.22594287991523743,
0.17040753364562988,
0.36077162623405457,
-0.015084872022271156,
0.7392673492431641,
-0.6775937080383301,
-0.053755078464746475,
-0.02820456027984619,
0.16907565295696259,
0.13554586470127106,
-0.03121870756149292,
-0.14977528154850006,
0.559766411781311,
0.21935686469078064,
-0.3056308627128601,
0.23087020218372345,
-0.087122343480587,
-0.24886958301067352,
-0.011342715471982956,
0.06998847424983978,
-0.041594069451093674,
-0.057806506752967834,
0.3630118668079376,
-0.30870136618614197,
0.01324857771396637,
-0.06105046346783638,
0.12251811474561691,
-0.32691770792007446,
0.009557018056511879,
0.15242917835712433,
0.22981412708759308,
0.265505313873291,
-0.24354392290115356,
-0.4098946452140808,
0.044229451566934586,
-0.2146960198879242,
0.16246865689754486,
0.2266128957271576,
0.0795103907585144,
0.09746839106082916,
-0.2776513695716858,
0.06662573665380478,
0.2089672088623047,
0.5011021494865417,
-0.12202250212430954,
-0.2938186526298523,
-0.01813543401658535,
-0.03504668548703194,
-0.08999653160572052,
-0.0249855387955904,
-0.11665748059749603,
0.1255786269903183,
0.02066122367978096,
0.09768398106098175,
-0.2659021317958832,
-0.16656813025474548,
0.07446404546499252,
0.13256365060806274,
0.07663963735103607,
-0.335916668176651,
-0.1441165655851364,
-0.0007815398275852203,
-0.1548815667629242,
0.17788606882095337,
-0.09627924859523773,
-0.28561320900917053,
-0.06143783777952194,
-0.021943816915154457,
0.036408379673957825,
0.29397955536842346,
0.07353497296571732,
0.2143486738204956,
0.057643432170152664,
0.07084514200687408,
0.04822836443781853,
-0.06505827605724335,
0.2817290723323822,
0.43656712770462036,
-0.1428242325782776,
-0.46511268615722656,
-0.10632561147212982,
0.13579952716827393,
-0.48085305094718933,
0.24971437454223633,
0.11656621098518372,
0.21496297419071198,
0.19017577171325684,
-0.14731937646865845,
0.21787649393081665,
-0.2683399021625519,
-0.01057024858891964,
0.061114661395549774,
0.028212152421474457,
-0.4887728691101074,
-0.9323238730430603,
0.5213586091995239,
0.36476394534111023,
-0.258247971534729,
0.574323296546936,
0.004262492060661316,
-0.2041110247373581,
0.41235750913619995,
0.3018031418323517,
1.1519230604171753,
-0.09614545106887817,
0.218508780002594,
0.10118705779314041,
-0.21098646521568298,
0.29550737142562866,
-0.2298135906457901,
0.15573906898498535,
-0.15916036069393158,
-0.3745524287223816,
0.06611093133687973,
-0.13276295363903046,
0.04989742860198021,
0.2634168267250061,
-0.25604724884033203,
0.25369787216186523,
-0.3084162473678589,
0.23445823788642883,
0.020436149090528488,
0.19144318997859955,
-0.28746283054351807,
-0.3286157548427582,
-0.05082404613494873,
0.0998365730047226,
-0.05817987769842148,
-0.30008700489997864,
-0.047375887632369995,
-0.05468501150608063,
-0.09370657801628113,
0.2028755247592926,
-0.10154703259468079,
-0.2596939504146576,
0.1305818408727646,
-0.05969154089689255,
-0.2657773494720459,
-0.09929939359426498,
0.36674004793167114,
0.03436394780874252,
0.1254948526620865,
-0.014877259731292725,
0.15132880210876465,
0.24826131761074066,
0.03901910036802292,
0.46660685539245605,
-0.045037683099508286,
-0.13180314004421234,
0.24407753348350525,
0.06336642801761627,
0.005415201187133789,
0.04518643021583557,
0.11685143411159515,
-0.48749643564224243,
-0.42851921916007996,
-0.04317504167556763,
0.5997399091720581,
-0.15401963889598846,
0.11646611988544464,
0.04915709048509598,
-0.19502615928649902,
-0.048161327838897705,
0.1584094613790512,
0.2610589563846588,
-0.23258623480796814,
0.2867871820926666,
-0.1204795241355896,
0.04268600046634674,
-0.1251039355993271,
0.08967898786067963,
-0.1612808108329773,
-0.11361165344715118,
0.19274240732192993,
-0.23611801862716675,
-0.280558705329895,
-0.19184023141860962,
0.15163633227348328,
0.21312810480594635,
-0.02919405698776245,
0.1103457510471344,
-0.23565185070037842,
-0.3742779493331909,
-0.07946967333555222,
-0.19264337420463562,
0.23270660638809204,
0.3861812353134155,
-0.07074115425348282,
0.12319789826869965,
-0.4934324026107788,
0.08805854618549347,
0.09681490063667297,
0.3548377752304077,
-0.24070832133293152,
-0.09278306365013123,
-0.10960809886455536,
-0.01845471002161503,
-0.3788088262081146,
-0.2516290843486786,
0.15548188984394073,
0.1993105262517929,
0.00818982720375061,
0.11616284400224686,
-0.22874048352241516,
-0.10670122504234314,
0.09685687720775604,
0.08086872100830078,
-0.07961455732584,
-0.17176371812820435,
-0.17849420011043549,
0.09644432365894318,
-0.09953518956899643,
0.21651527285575867,
0.21649432182312012,
-0.06108008697628975,
-0.0931975394487381,
-0.24933061003684998,
0.051228735595941544,
0.2615835964679718,
-0.059606075286865234,
0.4868055284023285,
0.6710013747215271,
0.0972437933087349,
-0.20602212846279144,
0.16008427739143372,
0.07366210967302322,
0.05982646346092224,
0.08756186813116074,
0.12772925198078156,
-0.036417748779058456,
-0.09296658635139465,
0.10473387688398361,
0.4397200345993042,
0.15501439571380615,
0.13724616169929504,
-0.002952631562948227,
0.28087615966796875,
0.19764989614486694,
0.3586438000202179,
0.18620380759239197,
0.43419361114501953,
0.041121114045381546,
-0.39689844846725464,
0.412551611661911,
0.23424574732780457,
-0.0356530100107193,
-0.13068056106567383,
-0.2073366641998291,
-0.11624658852815628,
0.13849030435085297,
0.010381326079368591,
-0.14836148917675018,
0.006765358150005341,
-0.21708612143993378,
-0.13100191950798035,
0.09854527562856674,
-0.4322226047515869,
0.36990851163864136,
0.24644212424755096,
-0.1015394926071167,
-0.07392777502536774,
0.442527174949646,
0.01766747608780861,
-0.18382644653320312,
0.16107571125030518,
0.3885459899902344,
0.8879134654998779,
0.3873404860496521,
0.14933861792087555,
0.09435451030731201,
0.17374691367149353,
0.14424824714660645,
0.7236194610595703,
0.23297666013240814,
0.11240538954734802,
0.3068799376487732,
0.2533043622970581,
0.10200060158967972,
-0.2223387360572815,
0.27811363339424133,
0.14876356720924377,
0.13228145241737366,
0.011391542851924896,
-0.03571192920207977,
-0.22587159276008606,
-0.3367294669151306,
-0.09032933413982391,
-0.013227701187133789,
0.0849902480840683,
0.5246771574020386,
0.19994014501571655,
0.29892781376838684,
-0.2885637581348419,
0.14000903069972992,
0.20761984586715698,
0.4345974624156952,
-0.21771685779094696,
-0.42913076281547546,
0.1927124559879303,
-0.11657305061817169,
0.6738446950912476,
0.05358833074569702,
-0.03115168586373329,
0.2896183431148529,
0.054473698139190674,
0.07489553838968277,
-0.3837040662765503,
-0.03711394593119621,
-0.06795172393321991,
0.10829363018274307,
0.10009673237800598,
-0.23522530496120453,
0.04172064736485481,
0.17708905041217804,
-0.199933260679245,
0.016714664176106453,
0.03517799824476242,
-0.14711062610149384,
-0.1254277229309082,
0.23322010040283203,
0.5211758613586426,
-0.23741364479064941,
0.10508299618959427,
-0.02069588005542755,
-0.31418731808662415,
-0.1590208113193512,
-0.029609132558107376,
0.07011150568723679,
-0.1647290587425232,
0.047691188752651215,
0.08573614805936813,
0.24409614503383636,
0.3486331105232239,
0.2794223725795746,
0.009575147181749344,
-0.1195920929312706,
-0.41816824674606323,
-0.40806230902671814,
-0.13012906908988953,
0.44738849997520447,
0.02127697505056858,
-0.02329091727733612,
-0.036524027585983276,
0.03883352875709534,
-0.03901775926351547,
0.16553083062171936,
-0.13707776367664337,
0.01628265157341957,
0.11755913496017456,
-0.36923402547836304,
-0.10993663966655731,
-0.09451670944690704,
-0.05248396843671799,
0.18723328411579132,
-0.12909914553165436,
-0.2749139070510864,
0.31997203826904297,
0.1062961295247078,
-0.24907808005809784,
0.0901089459657669,
0.15677806735038757,
0.1838327795267105,
0.2313612699508667,
-0.10574929416179657,
0.22225704789161682,
-0.013972029089927673,
-0.18763671815395355,
0.06642089039087296,
-0.08607544004917145,
-0.48912352323532104,
0.009830731898546219,
0.09424670040607452,
0.0846363976597786,
-0.02032383903861046,
-0.22575189173221588,
-0.45795518159866333,
0.5146231651306152,
-0.30500298738479614,
0.08379412442445755,
-0.7182446718215942,
0.21887990832328796,
0.23858317732810974,
0.051791317760944366,
-0.15571333467960358,
0.12745359539985657,
0.10186199843883514,
0.2214876413345337,
-0.30647704005241394,
0.16515307128429413,
0.4485177993774414,
0.10767001658678055,
-0.23511822521686554,
-0.28615713119506836,
0.1609083116054535,
-0.043487586081027985,
0.17592792212963104,
-0.3066343665122986,
0.00241696834564209,
0.21606038510799408,
0.011468365788459778,
0.10717856884002686,
0.41457149386405945,
0.05682273954153061,
0.005426015704870224,
-0.20953309535980225,
0.02015519142150879,
-0.14458653330802917,
-0.0305701345205307,
-0.11404657363891602,
-0.28600752353668213
] |
https://github.com/huggingface/datasets/issues/166 | Add a method to shuffle a dataset | As you might already know the issue of dataset shuffling came up in the nlp code [walkthrough](https://youtu.be/G3pOvrKkFuk?t=3204) by Yannic Kilcher
| Could maybe be a `dataset.shuffle(generator=None, seed=None)` signature method.
Also, we could maybe have a clear indication of which method modify in-place and which methods return/cache a modified dataset. I kinda like torch conversion of having an underscore suffix for all the methods which modify a dataset in-place. What do you think? | 20 | Add a method to shuffle a dataset
Could maybe be a `dataset.shuffle(generator=None, seed=None)` signature method.
Also, we could maybe have a clear indication of which method modify in-place and which methods return/cache a modified dataset. I kinda like torch conversion of having an underscore suffix for all the methods which modify a dataset in-place. What do you think?
As you might already know the issue of dataset shuffling came up in the nlp code [walkthrough](https://youtu.be/G3pOvrKkFuk?t=3204) by Yannic Kilcher
| [
0.11682143807411194,
0.047994956374168396,
-0.008072571828961372,
-0.2174365073442459,
0.12888166308403015,
0.028689570724964142,
0.1363588273525238,
0.360643208026886,
-0.2647383213043213,
0.2979813814163208,
0.011635839007794857,
0.851158618927002,
-0.35360410809516907,
-0.2320978194475174,
0.20139333605766296,
-0.07050041109323502,
0.15841257572174072,
-0.10356594622135162,
-0.24149152636528015,
0.0523638054728508,
-0.13913841545581818,
-0.38281068205833435,
-0.07822690159082413,
-0.2000361829996109,
-0.13133971393108368,
-0.09400457888841629,
-0.08385643362998962,
0.13230089843273163,
-0.18401826918125153,
-0.29359671473503113,
-0.4079645276069641,
0.6355051398277283,
-0.10218510776758194,
0.14192354679107666,
-0.00010813646076712757,
-0.27224457263946533,
0.3262631893157959,
0.13107790052890778,
-0.43213951587677,
0.044686466455459595,
-0.08185350894927979,
-0.0996280163526535,
0.00863670278340578,
-0.15263867378234863,
0.06552892178297043,
0.13389600813388824,
0.16543443500995636,
-0.1464117467403412,
0.24235886335372925,
0.050310708582401276,
0.20914514362812042,
-0.03290870040655136,
-0.19009999930858612,
0.15847425162792206,
0.5000157952308655,
0.40686893463134766,
-0.10122678428888321,
0.028628256171941757,
0.43952375650405884,
0.22933261096477509,
-0.2657989263534546,
0.2744673192501068,
-0.06643892079591751,
-0.18149206042289734,
0.3078671991825104,
-0.28791874647140503,
-0.568967878818512,
0.07428516447544098,
0.0025422051548957825,
0.17878586053848267,
0.5037114024162292,
-0.28533515334129333,
-0.3903697729110718,
-0.35262978076934814,
0.3302518129348755,
-0.18850016593933105,
0.01999017596244812,
-0.09641744941473007,
-0.05681595578789711,
-0.06574320793151855,
-0.24524720013141632,
-0.15989506244659424,
0.03680569678544998,
-0.021753549575805664,
0.5161433219909668,
0.6055986881256104,
0.20056715607643127,
-0.003385476768016815,
0.24499811232089996,
0.08339643478393555,
0.5854985117912292,
-0.009341668337583542,
0.03303344547748566,
0.2996443808078766,
-0.14720936119556427,
-0.20837321877479553,
0.055003777146339417,
0.29483646154403687,
0.2364351451396942,
0.14461249113082886,
0.32707205414772034,
0.2851001024246216,
-0.04130205139517784,
0.03735366836190224,
0.005551239475607872,
0.03812050819396973,
-0.05310115963220596,
0.05495560169219971,
0.2810693383216858,
-0.3015080690383911,
0.23124808073043823,
0.003970738500356674,
-0.04903753101825714,
-0.08059713989496231,
-0.010975509881973267,
0.13244429230690002,
-0.19454528391361237,
-0.06849871575832367,
0.03613021969795227,
-0.5815836787223816,
-0.04963257908821106,
-0.32450762391090393,
0.14889642596244812,
0.10779420286417007,
0.27703583240509033,
0.1407214254140854,
-0.10792308300733566,
-0.048173874616622925,
0.18350951373577118,
-0.23938734829425812,
-0.10505374521017075,
0.025838693603873253,
-0.4939265847206116,
0.17078769207000732,
0.17374013364315033,
-0.07522200047969818,
0.1390148103237152,
0.1129436269402504,
0.06702779978513718,
0.23749428987503052,
0.07884752750396729,
0.2658466696739197,
0.4057009220123291,
-0.20365069806575775,
-0.4380703270435333,
-0.13343045115470886,
-0.10840372741222382,
0.2805593013763428,
-0.3744527995586395,
0.2528225779533386,
-0.2730662226676941,
-0.2303438037633896,
-0.0922333374619484,
0.1565236747264862,
-0.09696942567825317,
-0.2698223888874054,
-0.17591553926467896,
0.3530561923980713,
0.06264600157737732,
-0.4234463572502136,
0.35462215542793274,
0.07788464426994324,
0.062279801815748215,
-0.0040478818118572235,
0.013162774965167046,
0.317663311958313,
0.04695447161793709,
0.020499326288700104,
-0.24038124084472656,
0.0018358547240495682,
0.23789846897125244,
0.2391386330127716,
-0.19989801943302155,
-0.02130229026079178,
-0.16164132952690125,
-0.061269547790288925,
0.5229777097702026,
0.1896456927061081,
-0.20807000994682312,
0.013185974210500717,
-0.20950418710708618,
-0.09727853536605835,
0.40916791558265686,
0.3883783519268036,
-0.12241677939891815,
-0.33623144030570984,
0.20757310092449188,
0.11739514768123627,
-0.41046637296676636,
0.1484217792749405,
-0.3570765256881714,
-0.07999233901500702,
0.4687560200691223,
0.31442922353744507,
-0.24346338212490082,
0.000865645706653595,
0.07365517318248749,
-0.1594797521829605,
0.2940753102302551,
-0.1337454915046692,
-0.1370370090007782,
-0.23566274344921112,
-0.06926561892032623,
0.128549724817276,
-0.17178975045681,
-0.1168624758720398,
-0.10402866452932358,
-0.23739498853683472,
0.22362768650054932,
-0.05178038030862808,
0.11644144356250763,
-0.2859424948692322,
0.08745760470628738,
-0.3385698199272156,
0.07401012629270554,
-0.16828955709934235,
0.09142883121967316,
0.11526472866535187,
-0.10391446948051453,
-0.16962818801403046,
-0.22857993841171265,
-0.0651368796825409,
-0.14694315195083618,
-0.1881207376718521,
-0.3230237066745758,
0.029987024143338203,
-0.11075789481401443,
-0.05123117193579674,
-0.07592548429965973,
0.46679234504699707,
-0.08376158028841019,
-0.062399785965681076,
-0.0960649847984314,
0.29552963376045227,
-0.00012784404680132866,
-0.2677119970321655,
0.37398555874824524,
0.2960720658302307,
0.033665966242551804,
0.035146210342645645,
0.09655119478702545,
0.033621616661548615,
-0.05559798330068588,
-0.002862803637981415,
-0.3500950336456299,
0.31631022691726685,
-0.1683957725763321,
0.02897990494966507,
-0.18219545483589172,
-0.25976240634918213,
0.06748025119304657,
0.2224581241607666,
-0.3342282772064209,
0.1662607342004776,
0.21991662681102753,
0.21182863414287567,
0.2813102900981903,
0.22115714848041534,
-0.475361168384552,
0.067124143242836,
0.49271923303604126,
-0.05404485762119293,
0.018465764820575714,
0.34422391653060913,
0.25495633482933044,
-0.332937628030777,
0.12259738892316818,
0.12657177448272705,
0.2766236960887909,
0.4469537138938904,
0.05266153812408447,
0.14309260249137878,
0.09512905031442642,
-0.1651533991098404,
-0.044339440762996674,
-0.06922054290771484,
-0.17121653258800507,
-0.02813558280467987,
0.2366146445274353,
0.14595496654510498,
-0.28768274188041687,
-0.32734712958335876,
-0.04693536460399628,
0.18919777870178223,
-0.1102178692817688,
-0.05883181840181351,
-0.13308194279670715,
-0.30620077252388,
-0.3187927007675171,
-0.09166985750198364,
-0.3395278751850128,
-0.3069959878921509,
0.3917925953865051,
0.010386575013399124,
-0.32073935866355896,
0.40423503518104553,
0.14643113315105438,
0.5348381996154785,
-0.27478501200675964,
-0.011294098570942879,
-0.2897605895996094,
-0.43033847212791443,
-0.08097264170646667,
0.07382319867610931,
0.28863680362701416,
-0.047781944274902344,
0.712497353553772,
0.07893392443656921,
-0.13275235891342163,
-0.30444157123565674,
-0.5318078994750977,
-0.1408616453409195,
0.03139061853289604,
-0.2137415111064911,
0.3421265482902527,
-0.39242321252822876,
0.09010970592498779,
-0.38826945424079895,
-0.18767426908016205,
-0.34289199113845825,
-0.08024118840694427,
0.12296096980571747,
0.0008933634962886572,
0.02239943854510784,
-0.29992955923080444,
-0.34487882256507874,
-0.07238560169935226,
-0.4497673213481903,
0.07709676027297974,
-0.6393797993659973,
0.07205920666456223,
0.05661386623978615,
-0.2364700734615326,
-0.16641592979431152,
-0.37279024720191956,
0.007765317335724831,
-0.12797074019908905,
-0.5969664454460144,
0.16613708436489105,
-0.11037240922451019,
-0.061282236129045486,
-0.2556629180908203,
-0.05603986978530884,
0.01381276547908783,
0.6228564977645874,
0.19484542310237885,
-0.13971500098705292,
0.10687891393899918,
0.07648119330406189,
-0.08116407692432404,
0.15028256177902222,
0.43438106775283813,
0.16205082833766937,
-0.12345730513334274,
0.11876928061246872,
-0.18264272809028625,
0.042115334421396255,
-0.015398278832435608,
0.32869142293930054,
0.034825649112463,
0.2597433030605316,
0.13255898654460907,
0.5310877561569214,
-0.5287259817123413,
-0.08033180236816406,
0.05685708671808243,
0.17602059245109558,
0.25830376148223877,
-0.09530036896467209,
0.0022557098418474197,
0.5387944579124451,
0.29065459966659546,
-0.253852516412735,
0.25488215684890747,
-0.0269765667617321,
-0.30920788645744324,
0.12093102931976318,
0.11350800096988678,
-0.0975208729505539,
-0.1581999510526657,
0.4676395356655121,
-0.33594322204589844,
0.02855132520198822,
0.05402672663331032,
0.12251193076372147,
-0.2675395905971527,
-0.1677858531475067,
0.007246201857924461,
0.04410355165600777,
0.3468672037124634,
-0.13314172625541687,
-0.4249151349067688,
-0.045601293444633484,
-0.29521673917770386,
0.19519026577472687,
0.26279452443122864,
0.27447035908699036,
-0.015354800969362259,
-0.17939487099647522,
0.1379479169845581,
0.1270141303539276,
0.3991087079048157,
-0.1852073073387146,
-0.1568528115749359,
-0.08336517214775085,
0.1259494572877884,
-0.1888723522424698,
0.053663674741983414,
-0.11359268426895142,
0.10668960958719254,
0.16241836547851562,
0.05929304659366608,
-0.26366710662841797,
-0.19537679851055145,
0.13751189410686493,
0.08628317713737488,
0.1633119285106659,
-0.3234401047229767,
-0.07841929793357849,
-0.19659286737442017,
-0.1358698308467865,
0.2577889859676361,
-0.006182191893458366,
-0.2898067533969879,
-0.03264281153678894,
0.08358713984489441,
-0.05086030066013336,
0.22913530468940735,
-0.008727006614208221,
0.17341579496860504,
0.05967771261930466,
0.21080222725868225,
-0.02444550395011902,
-0.008577316999435425,
0.3802028000354767,
0.201516255736351,
-0.17109259963035583,
-0.35532546043395996,
0.0014370828866958618,
-0.080220527946949,
-0.3615971505641937,
0.2507231831550598,
0.21086831390857697,
0.21007803082466125,
0.2614561915397644,
-0.14829213917255402,
0.15075713396072388,
-0.2337452471256256,
-0.030188381671905518,
-0.06791020929813385,
0.007533682510256767,
-0.5339679718017578,
-0.8507195711135864,
0.5450387597084045,
0.3243734836578369,
-0.3054797649383545,
0.4437330663204193,
-0.024501033127307892,
-0.35627874732017517,
0.3782590627670288,
0.32997459173202515,
1.0034143924713135,
-0.07321757078170776,
0.2827591300010681,
0.16532638669013977,
-0.3735780119895935,
0.42987287044525146,
-0.18536461889743805,
0.2949046492576599,
-0.19988366961479187,
-0.26987776160240173,
0.10410730540752411,
-0.0036480799317359924,
-0.028021305799484253,
0.28348779678344727,
-0.23576804995536804,
0.31240272521972656,
-0.16876855492591858,
0.0294245183467865,
0.12953603267669678,
0.2141418755054474,
-0.26988521218299866,
-0.22724027931690216,
-0.24185234308242798,
0.13649655878543854,
-0.22734926640987396,
-0.21245168149471283,
0.02145717665553093,
-0.15386484563350677,
0.007626291364431381,
0.06421861052513123,
-0.1773071587085724,
-0.11582428216934204,
0.11999904364347458,
-0.13377799093723297,
-0.19474442303180695,
-0.06841358542442322,
0.5051286816596985,
0.015424598008394241,
0.2500437796115875,
0.07930870354175568,
0.14135032892227173,
0.23059959709644318,
0.07139067351818085,
0.34186220169067383,
-0.04602603241801262,
-0.03625039383769035,
0.1730341613292694,
0.02574169635772705,
0.0010225772857666016,
-0.059546031057834625,
0.13033847510814667,
-0.6264157891273499,
-0.47416695952415466,
-0.008948206901550293,
0.320462703704834,
-0.025614703074097633,
0.1331462562084198,
0.23690786957740784,
-0.07707677036523819,
-0.08411955088376999,
0.15529413521289825,
0.23977577686309814,
-0.2477659285068512,
0.3586961030960083,
-0.11311745643615723,
-0.03689306974411011,
-0.07945579290390015,
0.15876634418964386,
-0.23023149371147156,
0.015225932002067566,
0.3005438446998596,
-0.23293356597423553,
-0.13038402795791626,
-0.23513087630271912,
-0.019167520105838776,
0.23810626566410065,
-0.06477047502994537,
0.1519562005996704,
-0.13655030727386475,
-0.22427085041999817,
-0.06621584296226501,
-0.13610884547233582,
0.05216206982731819,
0.2807183265686035,
-0.05464257299900055,
0.013736039400100708,
-0.39536499977111816,
0.020800083875656128,
0.09897324442863464,
0.3021586835384369,
-0.1149682030081749,
0.14674429595470428,
-0.15087030827999115,
0.0054872483015060425,
-0.37829846143722534,
-0.24021054804325104,
0.11466757208108902,
0.319722443819046,
0.07316653430461884,
0.15754017233848572,
-0.2105623334646225,
-0.21844366192817688,
0.06116180866956711,
0.043341051787137985,
-0.049846943467855453,
-0.2375105619430542,
-0.13929516077041626,
0.06823790818452835,
-0.003146030008792877,
0.2037644386291504,
0.15675580501556396,
-0.12760591506958008,
-0.03967002406716347,
-0.20938272774219513,
-0.11454802751541138,
0.17652040719985962,
-0.01926197111606598,
0.5665624737739563,
0.5050373673439026,
0.10235260426998138,
0.009776581078767776,
0.18582399189472198,
-0.1405273675918579,
-0.11232700943946838,
0.01957671530544758,
0.2767694592475891,
-0.013695345260202885,
0.051071107387542725,
0.024323076009750366,
0.2786233723163605,
0.14185400307178497,
0.08936851471662521,
-0.08146516233682632,
0.19317325949668884,
0.10954712331295013,
0.46652019023895264,
0.061829812824726105,
0.3582407236099243,
0.08235479146242142,
-0.4855670928955078,
0.43374964594841003,
0.2181694358587265,
-0.16130027174949646,
-0.002209446160122752,
-0.17344042658805847,
0.07349109649658203,
0.16542167961597443,
-0.003153584897518158,
-0.10503259301185608,
-0.06873240321874619,
-0.28761184215545654,
-0.07359515130519867,
0.14936880767345428,
-0.5486273765563965,
0.28238940238952637,
0.2594435214996338,
-0.12507213652133942,
-0.1608252227306366,
0.21707992255687714,
-0.09827996790409088,
-0.1600293517112732,
0.16166973114013672,
0.36011219024658203,
1.0041594505310059,
0.3350103497505188,
0.21191102266311646,
0.024365626275539398,
0.14911051094532013,
0.09338098764419556,
0.643322229385376,
0.3787447214126587,
0.1495162546634674,
0.429431289434433,
0.23128503561019897,
0.18977764248847961,
-0.30213499069213867,
0.260072261095047,
0.1661073863506317,
0.165843665599823,
0.06580869853496552,
-0.1154681071639061,
-0.1193484514951706,
-0.26598140597343445,
-0.007739661261439323,
-0.053818006068468094,
0.10528263449668884,
0.530920684337616,
0.18618106842041016,
0.16036461293697357,
-0.41128939390182495,
0.20345550775527954,
0.2584473192691803,
0.4700574576854706,
-0.18684901297092438,
-0.24186114966869354,
0.025070182979106903,
-0.21610897779464722,
0.7542920112609863,
0.04195919260382652,
0.02450689859688282,
0.28092706203460693,
0.04929617419838905,
0.03278752788901329,
-0.4148055911064148,
0.009417077526450157,
-0.15027835965156555,
0.17937560379505157,
0.2596067786216736,
-0.12145720422267914,
0.021811317652463913,
0.13871459662914276,
-0.11151222139596939,
0.20139601826667786,
-0.04670361056923866,
-0.07099401950836182,
-0.08586189150810242,
0.3180975019931793,
0.5659241676330566,
-0.2598892152309418,
0.04079608991742134,
0.029231250286102295,
-0.13603153824806213,
-0.06514067947864532,
0.00668475404381752,
0.14587558805942535,
-0.17006808519363403,
-0.056863535195589066,
0.09269674867391586,
0.35246074199676514,
0.4031998813152313,
0.2684458792209625,
-0.10742684453725815,
-0.11384580284357071,
-0.36881470680236816,
-0.5009536743164062,
-0.1890978217124939,
0.3571246266365051,
-0.051589444279670715,
-0.028194501996040344,
-0.022273287177085876,
-0.01885136216878891,
-0.018899455666542053,
-0.04477250576019287,
0.035463664680719376,
0.013845345936715603,
0.07077226042747498,
-0.3659396767616272,
-0.013891540467739105,
-0.20218102633953094,
-0.07325318455696106,
0.14310477674007416,
-0.1260942816734314,
-0.2787930965423584,
0.314702570438385,
0.04463823139667511,
-0.22550278902053833,
0.25094741582870483,
-0.08069898188114166,
0.14602085947990417,
0.03393852710723877,
0.13528819382190704,
0.18925467133522034,
0.049447715282440186,
-0.11370118707418442,
-0.15378084778785706,
-0.10955610871315002,
-0.6963850855827332,
0.00513111799955368,
0.05858930945396423,
0.05486719310283661,
-0.06912816315889359,
-0.1053767055273056,
-0.41169583797454834,
0.5068252682685852,
-0.26187863945961,
0.0811077430844307,
-0.5822639465332031,
0.17405733466148376,
0.19211417436599731,
0.1904579997062683,
-0.14750538766384125,
0.21940958499908447,
0.09773136675357819,
0.18745581805706024,
-0.2305743247270584,
0.10078959912061691,
0.46335476636886597,
0.0216558575630188,
-0.1791427880525589,
-0.21649959683418274,
0.2422758936882019,
0.01254146546125412,
-0.14014916121959686,
-0.36441338062286377,
-0.1711253821849823,
0.17598265409469604,
-0.04166674613952637,
0.2560969293117523,
0.46521297097206116,
0.04604590684175491,
-0.04631691426038742,
-0.18348293006420135,
0.0035772770643234253,
-0.06137688457965851,
-0.045355893671512604,
0.005076345056295395,
-0.4476947784423828
] |
https://github.com/huggingface/datasets/issues/163 | [Feature request] Add cos-e v1.0 | Sounds good, @mariamabarham do you want to give a look?
I think we should have two configurations so we can allow either version of the dataset to be loaded with the `1.0` version being the default maybe.
Cc some authors of the great cos-e: @nazneenrajani @bmccann | I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf). | 46 | [Feature request] Add cos-e v1.0
I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf).
Sounds good, @mariamabarham do you want to give a look?
I think we should have two configurations so we can allow either version of the dataset to be loaded with the `1.0` version being the default maybe.
Cc some authors of the great cos-e: @nazneenrajani @bmccann | [
-0.2522469758987427,
-0.2662777900695801,
-0.12816189229488373,
-0.382615327835083,
-0.41568905115127563,
-0.10087786614894867,
0.019268110394477844,
0.2192726880311966,
-0.08714987337589264,
0.38095980882644653,
0.057025887072086334,
0.376335471868515,
-0.01554610300809145,
0.38528168201446533,
-0.07647743076086044,
0.14052680134773254,
0.08472877740859985,
0.36588799953460693,
-0.08661046624183655,
-0.1383289098739624,
-0.20194710791110992,
0.11041399836540222,
-0.06942584365606308,
-0.0544472336769104,
0.14053839445114136,
0.17084470391273499,
-0.1972423642873764,
-0.07244310528039932,
-0.2242700457572937,
-0.2077137976884842,
0.35505497455596924,
0.4555104672908783,
0.22513926029205322,
0.06983283162117004,
-0.00010584223491605371,
-0.2381841242313385,
0.40260040760040283,
-0.07296501845121384,
-0.33391594886779785,
-0.23844747245311737,
-0.41790148615837097,
-0.37712976336479187,
0.06569432467222214,
-0.0959780290722847,
0.06359253823757172,
0.09290831536054611,
0.1650215983390808,
-0.1966177076101303,
0.0641363337635994,
0.011999520473182201,
0.3026267886161804,
0.17412491142749786,
-0.0875844731926918,
-0.34514904022216797,
0.33494824171066284,
0.44910669326782227,
-0.35373738408088684,
-0.17945295572280884,
0.3167716860771179,
0.013063503429293633,
-0.0673423781991005,
0.41108134388923645,
0.22772830724716187,
-0.1817956268787384,
-0.02522088587284088,
-0.06428276002407074,
0.18126511573791504,
0.007419601082801819,
0.14173555374145508,
0.1168770045042038,
0.5061972737312317,
0.12980133295059204,
-0.4155387878417969,
0.28998398780822754,
0.0042793480679392815,
-0.4935304820537567,
0.2665930390357971,
-0.10623874515295029,
-0.029614266008138657,
0.06423866003751755,
0.18722155690193176,
-0.33883601427078247,
-0.49577194452285767,
0.20651434361934662,
-0.07795708626508713,
0.09057144075632095,
-0.15790341794490814,
-0.15367048978805542,
0.12449894845485687,
0.10767865180969238,
-0.043482277542352676,
0.041367921978235245,
-0.1763661652803421,
0.204386368393898,
-0.24313990771770477,
-0.259062796831131,
0.2833954691886902,
0.0010785162448883057,
0.4588758945465088,
0.08281131088733673,
0.15400458872318268,
0.04369566962122917,
-0.07180526852607727,
0.10415858030319214,
0.15376776456832886,
0.20157016813755035,
0.46074309945106506,
-0.059857212007045746,
0.3992583155632019,
0.2871793508529663,
0.4768282175064087,
0.042006347328424454,
0.15518613159656525,
0.03422975912690163,
-0.06027243658900261,
-0.03193368390202522,
0.07255344837903976,
-0.581581711769104,
-0.0960402861237526,
0.050024598836898804,
-0.01638912409543991,
0.01660105027258396,
-0.03814193233847618,
0.09351342171430588,
0.2691534161567688,
0.22098153829574585,
0.2916286587715149,
-0.06439065933227539,
-0.035680435597896576,
-0.4872015416622162,
-0.2953397035598755,
-0.07494331896305084,
-0.2445649951696396,
0.2993691563606262,
0.32775935530662537,
-0.42228981852531433,
0.13820597529411316,
-0.31309938430786133,
0.2833760380744934,
0.04933442175388336,
-0.18007932603359222,
0.33908727765083313,
-0.22517728805541992,
0.12475208938121796,
0.057131920009851456,
0.08531032502651215,
-0.27858254313468933,
0.5125010013580322,
-0.1971522718667984,
0.1246589794754982,
-0.33828338980674744,
-0.4485531151294708,
-0.386896550655365,
0.2870852053165436,
-0.07405190914869308,
-0.15551364421844482,
-0.15182101726531982,
0.3666447699069977,
-0.23981431126594543,
-0.16440415382385254,
-0.08050500601530075,
0.3010808229446411,
-0.27182331681251526,
-0.12088780105113983,
0.027140622958540916,
0.14325252175331116,
-0.12814584374427795,
-0.04009613022208214,
-0.5082143545150757,
-0.0936475545167923,
-0.14256691932678223,
-0.029935766011476517,
-0.12085288017988205,
-0.27354881167411804,
-0.1699310541152954,
-0.17351999878883362,
0.39941591024398804,
-0.3332187235355377,
-0.14639170467853546,
0.23286615312099457,
-0.02869914099574089,
-0.24974213540554047,
0.14834274351596832,
-0.15650637447834015,
0.046719059348106384,
-0.2703949213027954,
-0.22819778323173523,
0.04900597780942917,
-0.14814750850200653,
-0.10404182225465775,
-0.14730152487754822,
-0.44127345085144043,
-0.18274010717868805,
0.26036566495895386,
0.24740354716777802,
0.033463962376117706,
0.22792422771453857,
-0.39961373805999756,
0.09001308679580688,
-0.16994045674800873,
0.17561841011047363,
-0.019764039665460587,
0.7601090669631958,
0.032792869955301285,
0.1584606170654297,
0.06392212212085724,
-0.39667025208473206,
0.07201751321554184,
0.09055445343255997,
0.1692185401916504,
0.22833292186260223,
-0.37668633460998535,
-0.03511722758412361,
-0.049209270626306534,
0.0924886167049408,
-0.0949603021144867,
0.20418097078800201,
0.12047629058361053,
-0.13210266828536987,
-0.015266526490449905,
-0.028222447261214256,
0.25926682353019714,
-0.24022437632083893,
-0.15056917071342468,
-0.07579462230205536,
0.16699109971523285,
-0.18648108839988708,
0.039145804941654205,
-0.1825120449066162,
0.12863759696483612,
-0.0777057483792305,
-0.06598882377147675,
-0.12712767720222473,
0.39034274220466614,
-0.09755895286798477,
0.23098550736904144,
0.055191829800605774,
0.32341456413269043,
0.14523333311080933,
-0.17544777691364288,
0.07596822828054428,
-0.1623838245868683,
-0.10134578496217728,
0.18791499733924866,
-0.22592774033546448,
0.38410699367523193,
0.06922245770692825,
-0.15123489499092102,
0.009792573750019073,
-0.00877450779080391,
0.06245529651641846,
-0.09672942012548447,
-0.3642008900642395,
-0.11718857288360596,
0.18756024539470673,
0.11140085756778717,
-0.44378751516342163,
-0.2857009470462799,
-0.30886125564575195,
-0.08802192658185959,
0.032737839967012405,
-0.06471402943134308,
0.11028396338224411,
0.20297113060951233,
-0.0012311190366744995,
-0.23741555213928223,
0.3081510365009308,
-0.10598641633987427,
0.27346473932266235,
0.3854374587535858,
-0.1669514775276184,
-0.021352270618081093,
-0.20481492578983307,
0.11400623619556427,
0.1383962631225586,
0.28159111738204956,
0.04978880286216736,
0.10224251449108124,
0.3348848521709442,
0.09427326172590256,
-0.35023343563079834,
-0.30894413590431213,
-0.04541849344968796,
0.05769772082567215,
-0.15502676367759705,
-0.19572332501411438,
-0.033697210252285004,
0.07117685675621033,
0.0014656614512205124,
0.14784641563892365,
0.16372083127498627,
-0.1914488673210144,
0.40738844871520996,
0.2692486047744751,
-0.22280721366405487,
0.3243142068386078,
0.03676152601838112,
0.8047561049461365,
-0.12738491594791412,
0.18538598716259003,
-0.24488967657089233,
0.05357445776462555,
-0.3132985532283783,
0.25463640689849854,
-0.22676576673984528,
-0.22785374522209167,
0.46085360646247864,
-0.10080918669700623,
0.24583815038204193,
-0.1181473508477211,
-0.7101554870605469,
0.09934358298778534,
-0.10333864390850067,
-0.09342781454324722,
0.030385147780179977,
-0.2146865874528885,
-0.07387551665306091,
0.019448693841695786,
0.05901806429028511,
-0.4485960006713867,
-0.48253872990608215,
-0.10999599099159241,
-0.2480621039867401,
0.13051103055477142,
-0.3649929463863373,
-0.48683181405067444,
0.14573653042316437,
-0.26064589619636536,
-0.20767129957675934,
-0.05296815186738968,
0.1615414321422577,
0.26981139183044434,
0.12356339395046234,
-0.0581197552382946,
0.06886543333530426,
0.05131299048662186,
-0.38603103160858154,
0.04582185670733452,
0.34243717789649963,
-0.3188911974430084,
-0.41584312915802,
0.1217738538980484,
0.011761464178562164,
0.15939754247665405,
0.17577895522117615,
-0.3779391646385193,
-0.39495590329170227,
0.27527758479118347,
0.12953297793865204,
-0.1465403437614441,
0.06901110708713531,
0.5344862341880798,
0.06983810663223267,
-0.21253933012485504,
-0.07770728319883347,
-0.4181554615497589,
0.18073105812072754,
0.4679791033267975,
0.1432115137577057,
-0.294879287481308,
0.2655492424964905,
0.19312970340251923,
0.3202052414417267,
0.1647084504365921,
-0.07552215456962585,
0.12141621112823486,
0.13372129201889038,
0.21813711524009705,
-0.20591655373573303,
0.010713692754507065,
0.016583044081926346,
0.052660830318927765,
0.17323461174964905,
0.5349007844924927,
0.19639050960540771,
-0.407214492559433,
-0.372956246137619,
-0.22823132574558258,
0.09779674559831619,
0.0007368624210357666,
-0.1938171535730362,
0.1649022400379181,
0.44048231840133667,
-0.06908129155635834,
-0.15247789025306702,
-0.3290403187274933,
-0.10789782553911209,
0.09796702861785889,
0.34180572628974915,
0.15771353244781494,
-0.08698377013206482,
0.09859806299209595,
0.17732566595077515,
-0.2839728891849518,
0.3561050295829773,
0.14722788333892822,
-0.0044860271736979485,
0.005454372614622116,
-0.10187941044569016,
0.15186414122581482,
0.01983906701207161,
0.18591216206550598,
-0.21365287899971008,
-0.16913338005542755,
-0.14002712070941925,
-0.0866285115480423,
0.08970752358436584,
-0.061822038143873215,
-0.11171072721481323,
-0.280530720949173,
-0.09050488471984863,
0.05194654315710068,
0.027261562645435333,
-0.14532747864723206,
0.6831696033477783,
-0.17081420123577118,
0.010883715003728867,
-0.2852770984172821,
0.05051552131772041,
-0.2335626184940338,
-0.0009023305028676987,
-0.017939038574695587,
-0.1901804506778717,
0.0005650762468576431,
-0.10173087567090988,
-0.15057452023029327,
0.2393195480108261,
0.013858072459697723,
-0.006709679961204529,
0.14193856716156006,
-0.14012393355369568,
0.011414280161261559,
0.11479316651821136,
0.08129552006721497,
0.04784281179308891,
0.3729478418827057,
0.12629103660583496,
0.22759857773780823,
-0.26654544472694397,
0.1760542392730713,
-0.19377730786800385,
0.06537304818630219,
0.2491941899061203,
0.030140243470668793,
-0.06442669779062271,
-0.2971714735031128,
-0.22939170897006989,
-0.123458631336689,
-0.20089203119277954,
0.26194342970848083,
0.04154439643025398,
-0.372658371925354,
0.0283846165984869,
0.3245108425617218,
0.02175328880548477,
-0.2729002833366394,
0.2598053216934204,
0.21533317863941193,
-0.24798910319805145,
0.3315582871437073,
0.0006595999002456665,
0.7347702383995056,
0.24774335324764252,
-0.06344842910766602,
0.23774367570877075,
-0.0478474497795105,
0.49948808550834656,
-0.1533694863319397,
0.01370753813534975,
0.07889296114444733,
-0.13275238871574402,
-0.09385041147470474,
0.29843810200691223,
0.3770507276058197,
-0.09206093847751617,
-0.30580034852027893,
0.17827288806438446,
0.36761474609375,
0.24887485802173615,
0.08150078356266022,
0.18558502197265625,
0.3359355628490448,
-0.3099146783351898,
0.1831713169813156,
0.188380628824234,
0.007580742239952087,
0.1698165386915207,
0.000819103792309761,
-0.036344677209854126,
0.014058288186788559,
-0.32612311840057373,
-0.22565679252147675,
-0.14075130224227905,
0.3442858159542084,
-0.00929962657392025,
-0.035762470215559006,
-0.07222989201545715,
0.4353812336921692,
-0.37264421582221985,
0.20798258483409882,
0.19100767374038696,
-0.2896561026573181,
0.12577463686466217,
0.16576635837554932,
0.053724415600299835,
-0.06959030777215958,
-0.09448534995317459,
0.07702066004276276,
-0.16798225045204163,
-0.09140501171350479,
0.18939551711082458,
0.2116372287273407,
-0.15778538584709167,
-0.08024898171424866,
-0.1400250792503357,
-0.032127514481544495,
0.048933904618024826,
0.3648069202899933,
0.5734384059906006,
0.19827184081077576,
-0.28032034635543823,
0.24688145518302917,
0.2291853427886963,
-0.11168717592954636,
-0.07789973169565201,
0.15205621719360352,
-0.10007680952548981,
-0.20936422049999237,
0.41510429978370667,
0.4110593795776367,
-0.40592584013938904,
-0.04722730815410614,
-0.08289749920368195,
-0.08956558257341385,
-0.27430734038352966,
-0.04644796997308731,
0.12019743025302887,
-0.5605071783065796,
-0.19973480701446533,
0.06941761821508408,
-0.20039404928684235,
0.18112991750240326,
0.7872427701950073,
0.1409822404384613,
0.17524513602256775,
-0.05200928449630737,
-0.018956638872623444,
-0.18221917748451233,
0.06492462754249573,
-0.4313209652900696,
0.302185595035553,
-0.026819203048944473,
-0.1548498421907425,
-0.11379803717136383,
0.0398104190826416,
-0.4568730294704437,
-0.19220370054244995,
0.2623075544834137,
-0.13239438831806183,
0.37219303846359253,
0.31053996086120605,
0.26454198360443115,
0.0035354867577552795,
0.2119165062904358,
-0.1414116472005844,
-0.3338809013366699,
-0.20281726121902466,
0.06465190649032593,
0.09212342649698257,
0.06677166372537613,
0.1733732521533966,
-0.038244180381298065,
-0.1149311438202858,
-0.2642989158630371,
0.032552070915699005,
0.26225921511650085,
-0.029773134738206863,
-0.15817293524742126,
0.18510571122169495,
-0.24483980238437653,
-0.07198566943407059,
0.15404579043388367,
0.3823603689670563,
0.18938875198364258,
0.08267536759376526,
-0.06526093930006027,
0.42594367265701294,
-0.007294267416000366,
-0.11266477406024933,
0.046603307127952576,
0.3781132400035858,
-0.27740901708602905,
0.3002438545227051,
0.018674682825803757,
-0.02458496391773224,
-0.08572185039520264,
-0.03785388171672821,
0.13398222625255585,
-0.4113802909851074,
-0.07079374045133591,
0.028906991705298424,
0.03366852179169655,
0.3719574809074402,
-0.2801135182380676,
0.052501458674669266,
-0.05817509815096855,
-0.055172398686409,
0.21768569946289062,
0.19678078591823578,
0.34751248359680176,
0.015417419373989105,
0.7643715143203735,
0.032585494220256805,
0.01245035044848919,
-0.053611353039741516,
0.4525500535964966,
0.1095074936747551,
0.0451970212161541,
0.09280000627040863,
0.08463910967111588,
0.06753060221672058,
0.1761351376771927,
-0.06873731315135956,
0.11972801387310028,
-0.08243213593959808,
0.4220132529735565,
0.5082911849021912,
0.009178526699543,
-0.3382551372051239,
0.07828802615404129,
0.28291958570480347,
0.08967144042253494,
0.03318367153406143,
0.3009582757949829,
-0.16590338945388794,
0.011286738328635693,
0.07916280627250671,
-0.7445873618125916,
-0.1521623581647873,
0.020007815212011337,
-0.1553732007741928,
-0.15849386155605316,
-0.13477876782417297,
-0.40616241097450256,
-0.06609366834163666,
0.16439232230186462,
0.00754677876830101,
0.15479014813899994,
-0.1995062679052353,
0.015690237283706665,
-0.10653702914714813,
-0.00798344612121582,
0.11110593378543854,
0.2240457534790039,
0.026626918464899063,
0.36857226490974426,
-0.4948239326477051,
-0.27720123529434204,
0.3008655607700348,
0.32901614904403687,
-0.016461435705423355,
-0.07080584019422531,
0.38324445486068726,
0.12766481935977936,
0.08333250880241394,
-0.10145267099142075,
0.04092054069042206,
0.08495280891656876,
0.09764710813760757,
0.1466628611087799,
0.209085613489151,
0.20400598645210266,
-0.13698942959308624,
0.24193733930587769,
-0.07487781345844269,
-0.13943180441856384,
-0.28207170963287354,
0.11750312149524689,
0.1690332144498825,
0.09013193100690842,
0.030282072722911835,
0.16643111407756805,
0.041157566010951996,
-0.37090572714805603,
-0.0729445219039917,
-0.05760568007826805,
-0.12956909835338593,
-0.16902801394462585,
0.13554269075393677,
-0.1693432331085205,
-0.04853004589676857,
0.22995777428150177,
0.007201503962278366,
-0.013600717298686504,
-0.40249717235565186,
0.053143538534641266,
0.3580959439277649,
0.1434372365474701,
-0.07688236981630325,
0.06701886653900146,
0.2265019416809082,
0.2597028613090515,
-0.1298811286687851,
0.1573919802904129,
-0.2579093873500824,
0.36999547481536865,
0.09451119601726532,
-0.3097192943096161,
0.16183717548847198,
0.45948630571365356,
-0.02836923860013485,
-0.1124441921710968,
-0.1568191647529602,
-0.10699570178985596,
0.04783381521701813,
0.0735948458313942,
-0.24181495606899261,
0.07018890976905823,
0.13543979823589325,
-0.001816488802433014,
0.5354022979736328,
0.02570386789739132,
0.17436665296554565,
-0.2132638692855835,
-0.04778806120157242,
-0.44986969232559204,
-0.20575019717216492,
-0.08338751643896103,
0.028016671538352966,
0.08583544939756393,
0.08767642825841904,
-0.004705161787569523,
0.05368794873356819,
-0.03178022801876068,
0.27985110878944397,
-0.014120722189545631,
0.0002252983395010233,
-0.2494332194328308,
0.4703889787197113,
-0.37131360173225403,
-0.27084335684776306,
-0.049185097217559814,
-0.15531057119369507,
0.11308008432388306,
-0.1719784140586853,
-0.10465776920318604,
-0.176669180393219,
0.2870733141899109,
-0.07113653421401978,
0.05178259685635567,
-0.18545502424240112,
0.3238450884819031,
0.3122841715812683,
-0.00006301887333393097,
-0.33270472288131714,
0.06873547285795212,
0.1956883668899536,
0.179451584815979,
-0.13641557097434998,
0.26792481541633606,
-0.07479532063007355,
0.023500200361013412,
-0.18617749214172363,
-0.01118343323469162,
-0.19011551141738892,
-0.06747450679540634,
0.03285990282893181,
-0.3748263120651245
] |
https://github.com/huggingface/datasets/issues/163 | [Feature request] Add cos-e v1.0 | cos_e v1.0 is related to CQA v1.0 but only CQA v1.11 dataset is available on their website. Indeed their is lots of ids in cos_e v1, which are not in CQA v1.11 or the other way around.
@sarahwie, @thomwolf, @nazneenrajani, @bmccann do you know where I can find CQA v1.0
| I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf). | 50 | [Feature request] Add cos-e v1.0
I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf).
cos_e v1.0 is related to CQA v1.0 but only CQA v1.11 dataset is available on their website. Indeed their is lots of ids in cos_e v1, which are not in CQA v1.11 or the other way around.
@sarahwie, @thomwolf, @nazneenrajani, @bmccann do you know where I can find CQA v1.0
| [
-0.02323286421597004,
-0.186763197183609,
-0.17846335470676422,
-0.3313103914260864,
-0.5435771942138672,
0.06571724265813828,
-0.17831747233867645,
0.12594062089920044,
-0.3440611958503723,
0.46897250413894653,
0.23541782796382904,
0.1240529790520668,
0.07490070164203644,
0.4212980270385742,
0.01564176194369793,
0.08941159397363663,
0.11703037470579147,
0.40649154782295227,
0.1564115434885025,
-0.07623115926980972,
-0.046965986490249634,
0.3286643326282501,
-0.26885986328125,
-0.012009188532829285,
0.16894929111003876,
0.11247776448726654,
-0.3255740702152252,
-0.2680037021636963,
-0.14709439873695374,
-0.16988055408000946,
0.43014833331108093,
0.2873970866203308,
0.35420387983322144,
-0.008296296000480652,
-0.00011804488894995302,
-0.24944938719272614,
0.26780998706817627,
-0.0638856366276741,
-0.22480155527591705,
-0.2884771227836609,
-0.3987266421318054,
-0.3756754398345947,
-0.1216316670179367,
-0.01598048210144043,
0.13137945532798767,
0.05806165933609009,
0.2008039802312851,
0.015675485134124756,
-0.12592141330242157,
0.10718555003404617,
0.1894945651292801,
0.1807601898908615,
0.14113670587539673,
-0.3795875906944275,
0.1705751121044159,
0.3191806375980377,
-0.2734740078449249,
-0.22853103280067444,
0.26993754506111145,
0.025856537744402885,
0.3077666461467743,
0.4816244840621948,
0.28743380308151245,
-0.3409464359283447,
-0.1720893383026123,
-0.013270949013531208,
0.116734579205513,
-0.1250803917646408,
0.27835139632225037,
-0.04526615887880325,
0.5306007862091064,
0.17983481287956238,
-0.38571879267692566,
0.41310515999794006,
0.04533282667398453,
-0.4731230139732361,
0.2673749029636383,
-0.013816200196743011,
0.06820408999919891,
0.11895711719989777,
0.23744802176952362,
-0.3053065538406372,
-0.43842706084251404,
0.16605892777442932,
-0.16326305270195007,
0.005223505198955536,
-0.11229757964611053,
-0.18681848049163818,
0.06563088297843933,
0.04510565102100372,
-0.048754796385765076,
0.18406324088573456,
-0.25097814202308655,
0.260393887758255,
-0.22966523468494415,
-0.3830537497997284,
0.28179800510406494,
0.021808292716741562,
0.32971617579460144,
-0.03462202101945877,
0.15862037241458893,
-0.21944329142570496,
-0.24751384556293488,
0.0007928647100925446,
0.12062594294548035,
0.32286378741264343,
0.35899585485458374,
0.052947867661714554,
0.14591898024082184,
0.2353777140378952,
0.44060006737709045,
-0.04040244221687317,
0.0712786614894867,
0.012920827604830265,
-0.16717565059661865,
0.056895043700933456,
0.06021244078874588,
-0.6049146056175232,
-0.19651488959789276,
-0.004578499123454094,
-0.23373374342918396,
0.06281173974275589,
-0.14380230009555817,
0.03192576393485069,
0.41804495453834534,
0.21806281805038452,
0.2200229912996292,
-0.19355091452598572,
-0.009806827642023563,
-0.6159113645553589,
-0.2765553593635559,
-0.014677830040454865,
-0.06726313382387161,
0.3063664436340332,
0.2101641148328781,
-0.3618153929710388,
0.2205507904291153,
-0.3328656852245331,
0.22424012422561646,
0.055308446288108826,
-0.15858860313892365,
0.4364677369594574,
-0.22660881280899048,
0.18580719828605652,
-0.02298659458756447,
0.060771942138671875,
-0.28177493810653687,
0.4902442693710327,
-0.21706965565681458,
0.18422415852546692,
-0.38244685530662537,
-0.4308209717273712,
-0.5014219284057617,
0.14038515090942383,
0.05071000009775162,
-0.19810694456100464,
0.036736004054546356,
0.24654097855091095,
-0.2765113115310669,
-0.1712322235107422,
0.02272365242242813,
0.2964550852775574,
-0.17472504079341888,
-0.13263116776943207,
-0.00553295761346817,
0.17904698848724365,
-0.2631228268146515,
-0.062196988612413406,
-0.39297613501548767,
0.07705947011709213,
-0.11440915614366531,
0.05869714170694351,
-0.06112319231033325,
-0.3164398968219757,
-0.14322927594184875,
-0.25975000858306885,
0.3386319577693939,
-0.6128677725791931,
-0.5238038897514343,
0.14918261766433716,
-0.031318195164203644,
-0.2901611328125,
0.2189878523349762,
0.005281124729663134,
0.00720395939424634,
-0.16219674050807953,
-0.20951777696609497,
-0.0362691693007946,
-0.2873406410217285,
-0.33313676714897156,
0.021973613649606705,
-0.4311455488204956,
-0.07969623804092407,
0.10742993652820587,
0.09247314929962158,
0.09353873133659363,
0.23239237070083618,
-0.6215121150016785,
0.1444459855556488,
-0.01956053450703621,
0.010354232043027878,
0.06936415284872055,
0.6898937821388245,
0.07786283642053604,
0.2611396312713623,
0.05161260813474655,
-0.3183964788913727,
0.056200072169303894,
-0.21524792909622192,
0.06954513490200043,
0.26794856786727905,
-0.37729018926620483,
-0.11547413468360901,
0.0034696999937295914,
0.1692008376121521,
-0.28243619203567505,
0.0478886142373085,
0.04885255545377731,
0.10802213847637177,
0.0012774355709552765,
0.013500649482011795,
0.33671051263809204,
-0.15173646807670593,
-0.17996656894683838,
-0.10303992033004761,
0.17719830572605133,
-0.1950802206993103,
0.0085162203758955,
0.016285471618175507,
0.22205933928489685,
0.10666133463382721,
0.019013242796063423,
-0.08943860977888107,
0.1999126672744751,
-0.16442206501960754,
0.25171518325805664,
0.25995245575904846,
0.4301052987575531,
0.22773393988609314,
-0.22602127492427826,
0.0658654049038887,
-0.09690937399864197,
-0.19786733388900757,
0.35074323415756226,
-0.010787330567836761,
0.2520740032196045,
0.14984852075576782,
-0.07521001249551773,
-0.007431790232658386,
0.20284217596054077,
0.03159359097480774,
0.041656870394945145,
-0.20685186982154846,
-0.11898766458034515,
0.2147410809993744,
0.10000599920749664,
-0.34825098514556885,
-0.3811192810535431,
-0.20631006360054016,
0.16081619262695312,
0.13865166902542114,
-0.11609688401222229,
-0.000791594386100769,
0.11394792050123215,
-0.020683571696281433,
-0.0809202790260315,
0.34602686762809753,
-0.10363257676362991,
0.0956856980919838,
0.2869535982608795,
-0.24085912108421326,
-0.1860807090997696,
-0.009621341712772846,
0.16023385524749756,
0.15206804871559143,
0.27990031242370605,
-0.24120919406414032,
-0.17410489916801453,
0.37920939922332764,
0.17880699038505554,
-0.12696203589439392,
-0.23240919411182404,
-0.014871317893266678,
0.05603492259979248,
0.028574872761964798,
-0.09625128656625748,
-0.13883979618549347,
0.005258549004793167,
-0.06992299109697342,
-0.05941121652722359,
0.18317663669586182,
-0.19776906073093414,
0.2772122323513031,
0.1787654161453247,
0.07255779206752777,
0.2747689485549927,
-0.0002000369131565094,
0.7763862013816833,
-0.22260740399360657,
0.3033178150653839,
-0.07584991306066513,
0.13949936628341675,
-0.4241236746311188,
0.13569271564483643,
-0.2917243540287018,
-0.17309853434562683,
0.41069963574409485,
-0.09878095984458923,
0.3334307074546814,
-0.08852609992027283,
-0.8045454621315002,
-0.0008278489112854004,
-0.10774485766887665,
-0.10973872244358063,
0.11922863125801086,
-0.31333667039871216,
-0.09177760779857635,
0.024535104632377625,
-0.02578258328139782,
-0.2734338939189911,
-0.48534756898880005,
-0.16465319693088531,
-0.39834660291671753,
0.08785322308540344,
-0.17175862193107605,
-0.38223913311958313,
-0.04387309402227402,
-0.07672463357448578,
-0.12428030371665955,
-0.12437795102596283,
0.2652050256729126,
0.1253896802663803,
-0.00854033138602972,
-0.07314734160900116,
0.17700539529323578,
-0.04666546732187271,
-0.1972220242023468,
0.20906862616539001,
0.33739566802978516,
-0.3322140574455261,
-0.3296048939228058,
0.3415127098560333,
-0.02170230634510517,
0.2813384532928467,
0.01147801335901022,
-0.4279921054840088,
-0.15206898748874664,
0.06688883900642395,
0.13095764815807343,
0.051632437855005264,
-0.03655090928077698,
0.7915472984313965,
-0.11600484699010849,
-0.07611781358718872,
-0.02755453810095787,
-0.5734846591949463,
0.10225138068199158,
0.5704912543296814,
0.24227428436279297,
-0.11164764314889908,
0.317426860332489,
0.15854166448116302,
0.5127480030059814,
0.35929909348487854,
0.010425470769405365,
0.02273433655500412,
0.1787559986114502,
0.041327670216560364,
-0.12431816011667252,
-0.2332146018743515,
0.030882054939866066,
0.08355062454938889,
0.0810873880982399,
0.3579851984977722,
0.17127439379692078,
-0.2575511932373047,
-0.2342398315668106,
-0.43134695291519165,
-0.048631127923727036,
0.1353089064359665,
-0.34676092863082886,
0.0899704247713089,
0.666692852973938,
-0.057271551340818405,
-0.1794433891773224,
-0.4841732084751129,
-0.05204256996512413,
0.19989363849163055,
0.44825083017349243,
0.31226590275764465,
-0.002331764902919531,
0.159017875790596,
-0.06324783712625504,
-0.2990369498729706,
0.3822367787361145,
0.09644601494073868,
0.0762844979763031,
-0.02362120896577835,
0.0570530891418457,
0.1606551706790924,
0.0039883749559521675,
0.207462877035141,
-0.11883360892534256,
-0.20663686096668243,
-0.08955511450767517,
-0.04198877513408661,
0.32143867015838623,
-0.03235849738121033,
0.03982267901301384,
-0.2484743446111679,
-0.10593543946743011,
-0.18759527802467346,
0.1950107216835022,
-0.03170004114508629,
0.661746621131897,
-0.27993783354759216,
-0.1786489635705948,
-0.11406160891056061,
-0.05655476450920105,
-0.07455011457204819,
0.04568089544773102,
-0.05885583907365799,
-0.261006236076355,
-0.01762521266937256,
-0.03928036987781525,
-0.17231272161006927,
0.21923214197158813,
-0.20522719621658325,
0.00713571161031723,
0.048595529049634933,
-0.06891921907663345,
-0.01868925616145134,
0.08036014437675476,
0.10861791670322418,
-0.028513826429843903,
0.23418131470680237,
0.003001254051923752,
0.39899730682373047,
-0.31781503558158875,
0.17326241731643677,
-0.04418456554412842,
0.22356343269348145,
0.15306678414344788,
-0.031643930822610855,
0.0737861692905426,
-0.17802104353904724,
-0.3110802173614502,
-0.2239454686641693,
-0.4165325164794922,
0.3540852665901184,
0.09462454915046692,
-0.2084658443927765,
0.08699817955493927,
0.2448115050792694,
0.09113173186779022,
-0.2714416980743408,
0.33740535378456116,
0.39424216747283936,
-0.013790847733616829,
0.17862308025360107,
-0.040981538593769073,
0.7828719615936279,
0.3878049850463867,
-0.11633850634098053,
0.08909569680690765,
-0.1653100848197937,
0.30338600277900696,
0.027321740984916687,
0.10152038931846619,
0.1656833291053772,
-0.1250874102115631,
-0.13380074501037598,
0.1904686540365219,
0.3938691318035126,
-0.19231148064136505,
-0.2761598825454712,
0.3090684413909912,
0.2963230013847351,
0.37913772463798523,
0.18517258763313293,
0.04660651832818985,
0.308780699968338,
-0.012174827978014946,
0.22883759438991547,
0.0856974646449089,
0.1700183004140854,
0.44463080167770386,
-0.015017283149063587,
-0.1496933251619339,
-0.07364707440137863,
-0.24480487406253815,
-0.31907719373703003,
-0.24239102005958557,
0.10532356798648834,
-0.12534353137016296,
0.06371273100376129,
-0.13501372933387756,
0.47955790162086487,
-0.18675996363162994,
0.4332156777381897,
0.019766826182603836,
-0.3183548152446747,
0.11428603529930115,
0.2496323585510254,
-0.24592366814613342,
0.05072131007909775,
-0.03206104040145874,
-0.2735680043697357,
-0.19744345545768738,
-0.12815316021442413,
0.4675574004650116,
0.26430127024650574,
-0.18208615481853485,
-0.29033780097961426,
-0.17927472293376923,
-0.009771496057510376,
0.16735342144966125,
0.3781090974807739,
0.4931943714618683,
0.21740108728408813,
-0.23251913487911224,
0.13885162770748138,
0.14542095363140106,
-0.12462020665407181,
-0.33353573083877563,
-0.10845135152339935,
0.12606149911880493,
-0.15928465127944946,
0.20721027255058289,
0.42981356382369995,
-0.3224424123764038,
0.07744616270065308,
-0.12384441494941711,
0.035477541387081146,
-0.13220752775669098,
-0.2717389464378357,
0.030616700649261475,
-0.4341999888420105,
-0.1563023030757904,
0.03174485266208649,
-0.17103588581085205,
0.19185855984687805,
0.9666599631309509,
0.061495013535022736,
0.20077848434448242,
-0.18781906366348267,
-0.015118543058633804,
-0.2095966637134552,
0.1748201549053192,
-0.5250986814498901,
0.21809221804141998,
-0.17597243189811707,
-0.07979463040828705,
-0.16315673291683197,
0.26689305901527405,
-0.2849743366241455,
-0.228902205824852,
0.17995263636112213,
-0.15777570009231567,
0.33274638652801514,
0.28982308506965637,
0.17223277688026428,
0.11206085979938507,
0.043336525559425354,
-0.13135674595832825,
-0.1408834010362625,
-0.047134608030319214,
0.10009497404098511,
0.12241396307945251,
0.08467115461826324,
0.33936193585395813,
-0.037495218217372894,
-0.1875881552696228,
-0.19110731780529022,
0.19971676170825958,
0.24985697865486145,
-0.09309854358434677,
0.0867888331413269,
0.24760381877422333,
-0.2960225045681,
-0.1283235251903534,
-0.08523381501436234,
0.5458859205245972,
0.24163523316383362,
0.13734978437423706,
0.15754488110542297,
0.37560027837753296,
-0.09079910069704056,
-0.03890293836593628,
-0.07435857504606247,
0.4465688467025757,
-0.3893502950668335,
0.2567908465862274,
0.03685351461172104,
0.09243886917829514,
-0.13186967372894287,
0.038229480385780334,
-0.26250752806663513,
-0.5318465828895569,
-0.012972288765013218,
0.19005686044692993,
-0.057240135967731476,
0.20679312944412231,
-0.36436301469802856,
0.022032814100384712,
-0.2610281705856323,
-0.09930095076560974,
-0.0296506155282259,
0.21123558282852173,
0.37755751609802246,
0.0707448273897171,
0.8590601682662964,
0.1181165799498558,
-0.11029167473316193,
-0.07216499000787735,
0.4866432845592499,
0.22771112620830536,
0.3900809586048126,
0.13891121745109558,
0.09025733917951584,
0.0017621535807847977,
0.10719466954469681,
-0.16587089002132416,
-0.07671058923006058,
-0.13972161710262299,
0.4415704011917114,
0.45498254895210266,
0.3275451958179474,
-0.20021550357341766,
-0.20803408324718475,
0.24367785453796387,
0.18482714891433716,
0.014333982020616531,
0.23309193551540375,
-0.08115050941705704,
0.1278199702501297,
0.094309963285923,
-0.7621111273765564,
-0.09891968965530396,
0.07419556379318237,
-0.16120028495788574,
-0.1580151915550232,
-0.12280513346195221,
-0.26581406593322754,
-0.11310794949531555,
0.36796367168426514,
0.0979597419500351,
0.22673699259757996,
-0.27596282958984375,
-0.14950010180473328,
-0.05910411477088928,
-0.20407924056053162,
0.2876177430152893,
0.2594887912273407,
0.06134823337197304,
0.48437702655792236,
-0.564453661441803,
-0.3007173240184784,
0.4297741949558258,
0.21083779633045197,
0.01913793385028839,
-0.2560524642467499,
0.2916184365749359,
0.055539846420288086,
-0.02176825702190399,
-0.26670563220977783,
0.23909780383110046,
0.18271811306476593,
-0.14026705920696259,
0.11083655059337616,
-0.014656071551144123,
0.062215305864810944,
0.04342533275485039,
-0.05880115553736687,
0.012008767575025558,
-0.08062687516212463,
-0.4757099151611328,
0.13423489034175873,
-0.20503276586532593,
0.16521883010864258,
-0.12193162739276886,
0.44938090443611145,
0.08370696753263474,
-0.38023364543914795,
-0.2866361141204834,
-0.044458650052547455,
-0.2227209210395813,
0.014352894388139248,
0.055022262036800385,
-0.4033523499965668,
-0.16033096611499786,
0.3848738968372345,
0.19997671246528625,
-0.12101326137781143,
-0.6013121604919434,
0.06163422018289566,
0.25735101103782654,
0.1335514634847641,
-0.13102898001670837,
0.11507102102041245,
0.2602618336677551,
0.14775578677654266,
-0.2571094036102295,
0.2359616607427597,
-0.014066595584154129,
0.2910211682319641,
0.09884433448314667,
-0.16290105879306793,
0.08296118676662445,
0.3361518383026123,
0.003927494399249554,
-0.24153657257556915,
-0.013702761381864548,
-0.12546321749687195,
0.2838474214076996,
-0.12509283423423767,
-0.148213192820549,
-0.029125213623046875,
0.0956340879201889,
0.12166111171245575,
0.46083852648735046,
0.0902075469493866,
0.021488837897777557,
-0.06572086364030838,
-0.14753443002700806,
-0.40121519565582275,
-0.060062553733587265,
0.03288842365145683,
-0.1326179802417755,
0.014206446707248688,
0.05187322199344635,
-0.135909304022789,
0.3132942318916321,
-0.009249239228665829,
0.4369445741176605,
0.1265651136636734,
-0.024377649649977684,
-0.14826227724552155,
0.4578133225440979,
-0.46626439690589905,
-0.16879814863204956,
0.2816956639289856,
-0.1104644164443016,
0.0842432975769043,
-0.11323767900466919,
-0.10509461909532547,
-0.0178554505109787,
0.17952176928520203,
-0.15866148471832275,
0.2223753184080124,
-0.20011001825332642,
0.40533655881881714,
0.2907789945602417,
-0.031212368980050087,
-0.3527666926383972,
-0.07439643144607544,
0.18313199281692505,
0.27748650312423706,
-0.017893413081765175,
0.38302019238471985,
0.1775818169116974,
0.05988417938351631,
-0.12405893206596375,
0.2663041651248932,
-0.18348199129104614,
-0.0043844785541296005,
0.04803791269659996,
-0.2990565299987793
] |
https://github.com/huggingface/datasets/issues/163 | [Feature request] Add cos-e v1.0 | @mariamabarham I'm also not sure where to find CQA 1.0. Perhaps it's not possible to include this version of the dataset. I'll close the issue if that's the case. | I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf). | 29 | [Feature request] Add cos-e v1.0
I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf).
@mariamabarham I'm also not sure where to find CQA 1.0. Perhaps it's not possible to include this version of the dataset. I'll close the issue if that's the case. | [
-0.24925146996974945,
-0.10364571958780289,
-0.13912147283554077,
-0.42108476161956787,
-0.5307990312576294,
-0.0687481164932251,
-0.07875014841556549,
0.07906541228294373,
-0.21976329386234283,
0.4390559196472168,
0.1513829380273819,
0.29369914531707764,
0.06534174829721451,
0.43753260374069214,
0.006778089329600334,
0.2519569396972656,
0.15442757308483124,
0.3981415927410126,
-0.035902880132198334,
-0.08111092448234558,
-0.098997563123703,
0.30109986662864685,
-0.22698141634464264,
-0.05949544906616211,
0.06923174858093262,
-0.020368127152323723,
-0.27286192774772644,
-0.1656876504421234,
-0.15396252274513245,
-0.15395793318748474,
0.41139307618141174,
0.3626805543899536,
0.20779532194137573,
0.004311591386795044,
-0.0001105137198464945,
-0.21097853779792786,
0.28249117732048035,
-0.1277121603488922,
-0.23003864288330078,
-0.12380580604076385,
-0.33321240544319153,
-0.32515519857406616,
0.008640028536319733,
0.0028272345662117004,
0.0867995023727417,
0.1362747699022293,
0.12899629771709442,
-0.10482463240623474,
0.0015904083847999573,
0.17070774734020233,
0.26446282863616943,
0.2665337324142456,
-0.0055653005838394165,
-0.39218854904174805,
0.16724231839179993,
0.27682894468307495,
-0.3164585828781128,
-0.14915382862091064,
0.3068573474884033,
-0.017131198197603226,
0.08296903967857361,
0.5250522494316101,
0.26207688450813293,
-0.17759650945663452,
-0.1293550431728363,
-0.053835153579711914,
0.12355461716651917,
-0.11475835740566254,
0.32602939009666443,
0.05549313873052597,
0.5153299570083618,
0.14862272143363953,
-0.4204435646533966,
0.3833313286304474,
-0.0019985903054475784,
-0.389568567276001,
0.257610023021698,
-0.05857372283935547,
0.006152037531137466,
0.05968878045678139,
0.14559219777584076,
-0.15127874910831451,
-0.3991320729255676,
0.1424819976091385,
-0.1709086298942566,
0.031247396022081375,
-0.13222801685333252,
-0.21965506672859192,
0.08026755601167679,
0.09614323079586029,
-0.10330730676651001,
0.20984381437301636,
-0.2582564651966095,
0.18841113150119781,
-0.2771468758583069,
-0.28245383501052856,
0.3214116394519806,
0.0659700259566307,
0.4131602942943573,
-0.06235169619321823,
0.151973158121109,
-0.0995105728507042,
-0.11116892844438553,
0.14640206098556519,
0.05179961770772934,
0.25040289759635925,
0.23542797565460205,
-0.053371794521808624,
0.32314854860305786,
0.2254091054201126,
0.48004674911499023,
-0.03999726474285126,
0.16129684448242188,
0.0416819304227829,
-0.21857786178588867,
0.012427378445863724,
-0.026502275839447975,
-0.6751197576522827,
-0.2794654965400696,
0.002901901490986347,
-0.07580031454563141,
0.05903176963329315,
-0.07884785532951355,
0.14038969576358795,
0.38729918003082275,
0.1108703687787056,
0.2383928745985031,
-0.03799448907375336,
-0.06861913204193115,
-0.5039106607437134,
-0.3114447295665741,
0.049900367856025696,
-0.08856596797704697,
0.2114315629005432,
0.29866084456443787,
-0.2297256886959076,
0.3060239255428314,
-0.3308388292789459,
0.3673429489135742,
0.11446791887283325,
-0.20475706458091736,
0.3666544258594513,
-0.19268497824668884,
0.2855261564254761,
0.0603473000228405,
0.042868368327617645,
-0.22038297355175018,
0.3571574091911316,
-0.22282853722572327,
0.09572034329175949,
-0.2677157521247864,
-0.42350250482559204,
-0.47084885835647583,
0.19991570711135864,
0.05588305741548538,
-0.22937512397766113,
0.049219515174627304,
0.32721760869026184,
-0.20584681630134583,
-0.17716988921165466,
-0.02569682151079178,
0.33732426166534424,
-0.10757425427436829,
-0.12294257432222366,
0.11131118983030319,
0.18788516521453857,
-0.2905878722667694,
-0.009798012673854828,
-0.3686021864414215,
0.044304005801677704,
-0.04414796084165573,
0.04356708377599716,
-0.10054714977741241,
-0.22311890125274658,
-0.11662528663873672,
-0.23496821522712708,
0.3060913681983948,
-0.3721950054168701,
-0.41131892800331116,
0.13090969622135162,
0.058612048625946045,
-0.34151044487953186,
0.128153458237648,
-0.153347447514534,
0.019392352551221848,
-0.19477085769176483,
-0.17797908186912537,
0.1028158888220787,
-0.18041346967220306,
-0.16533173620700836,
-0.023646719753742218,
-0.4142703711986542,
-0.12499180436134338,
0.2005959451198578,
0.12091828882694244,
0.06461642682552338,
0.27017322182655334,
-0.6116054058074951,
0.05576079338788986,
-0.1391737461090088,
0.11108908802270889,
0.08375389873981476,
0.7464858889579773,
-0.04615722596645355,
0.1895795315504074,
0.14584100246429443,
-0.3134401738643646,
0.02355070412158966,
-0.26641911268234253,
0.14026635885238647,
0.11664465069770813,
-0.34082651138305664,
-0.0927940085530281,
0.002391614019870758,
0.06440754979848862,
-0.33980435132980347,
0.13861142098903656,
0.09465945512056351,
0.0508364774286747,
0.09796687960624695,
0.1258644461631775,
0.3094979524612427,
-0.19311818480491638,
-0.22526568174362183,
0.001833360642194748,
0.1426396667957306,
-0.2699939012527466,
-0.10479746758937836,
0.14433252811431885,
0.2866573929786682,
0.025029432028532028,
-0.04019121825695038,
-0.1668752133846283,
0.26575028896331787,
-0.16327416896820068,
0.27370142936706543,
0.09590202569961548,
0.38307997584342957,
0.14369438588619232,
-0.14276359975337982,
0.07344484329223633,
-0.1170787364244461,
-0.1200573518872261,
0.3190228044986725,
-0.11595211178064346,
0.34866467118263245,
0.08622618764638901,
-0.08114559203386307,
-0.035293981432914734,
0.18887203931808472,
0.18004760146141052,
-0.03710181266069412,
-0.21818643808364868,
-0.10062845051288605,
0.19473564624786377,
0.09217852354049683,
-0.3050864040851593,
-0.3667620122432709,
-0.24421106278896332,
0.05284672975540161,
0.18153175711631775,
-0.008825916796922684,
0.09464175999164581,
0.16038444638252258,
-0.038517698645591736,
-0.16388607025146484,
0.4497125446796417,
-0.09222950041294098,
0.10848797857761383,
0.3049633204936981,
-0.20059725642204285,
-0.15271013975143433,
-0.14874960482120514,
0.047722503542900085,
0.12991148233413696,
0.2641792893409729,
-0.0851147249341011,
-0.04902441054582596,
0.33934900164604187,
0.14000369608402252,
-0.3533046245574951,
-0.22798293828964233,
-0.05839638411998749,
0.02828158251941204,
0.0008941106498241425,
-0.0952368900179863,
-0.13379213213920593,
0.0065200552344322205,
0.030234232544898987,
0.0011708508245646954,
0.13668008148670197,
-0.23664966225624084,
0.36741703748703003,
0.1476510912179947,
-0.11774073541164398,
0.3822777271270752,
-0.007208691909909248,
0.7500996589660645,
-0.11174765974283218,
0.3082488477230072,
-0.18575958907604218,
0.12192968279123306,
-0.4235031306743622,
0.2297055423259735,
-0.2892768681049347,
-0.1285896599292755,
0.4955853521823883,
-0.09794572740793228,
0.47120773792266846,
-0.10985422879457474,
-0.7647414207458496,
0.06731861084699631,
-0.12290874123573303,
-0.015936559066176414,
0.014705538749694824,
-0.2569577693939209,
-0.1591472029685974,
-0.01935558393597603,
-0.04918188229203224,
-0.33155807852745056,
-0.43553027510643005,
-0.05172509700059891,
-0.48017874360084534,
-0.005570529028773308,
-0.3519701659679413,
-0.4595109522342682,
-0.021146250888705254,
-0.21627861261367798,
-0.1986929327249527,
-0.21795067191123962,
0.17308765649795532,
0.25137925148010254,
0.025441572070121765,
0.05033515766263008,
-0.015435701236128807,
0.007242961786687374,
-0.2543773651123047,
0.1297796219587326,
0.49869659543037415,
-0.3865443766117096,
-0.5030509829521179,
0.29115578532218933,
-0.04333081841468811,
0.3502500355243683,
-0.006292922422289848,
-0.3598858118057251,
-0.2641659080982208,
0.000894526019692421,
0.14793285727500916,
-0.009467877447605133,
0.03826868161559105,
0.7621444463729858,
-0.11581352353096008,
-0.19106866419315338,
-0.11626658588647842,
-0.5392231941223145,
0.19554352760314941,
0.4982726275920868,
0.24280890822410583,
-0.27890506386756897,
0.3810690641403198,
0.20991508662700653,
0.31938087940216064,
0.351168692111969,
-0.056519005447626114,
0.12163647264242172,
0.16339358687400818,
0.14771616458892822,
-0.19633936882019043,
-0.016693828627467155,
0.14289188385009766,
0.07544223964214325,
0.14860877394676208,
0.5334334373474121,
0.12728244066238403,
-0.3797418475151062,
-0.25314009189605713,
-0.27874472737312317,
-0.05657918006181717,
0.052457865327596664,
-0.2920558452606201,
0.015738388523459435,
0.5925155282020569,
-0.02757169120013714,
-0.16437718272209167,
-0.29470545053482056,
-0.024257853627204895,
0.18267162144184113,
0.4032709002494812,
0.22562989592552185,
-0.011568616144359112,
0.08430549502372742,
-0.07599983364343643,
-0.36049914360046387,
0.38195037841796875,
0.05675133317708969,
0.10147261619567871,
-0.12819619476795197,
0.061539679765701294,
0.1697923243045807,
0.010395808145403862,
0.23315387964248657,
-0.19572284817695618,
-0.270768940448761,
-0.09753899276256561,
-0.03323427587747574,
0.20889689028263092,
-0.07565906643867493,
-0.060405682772397995,
-0.17605644464492798,
-0.05845494195818901,
-0.17866334319114685,
0.0345807746052742,
-0.09470606595277786,
0.5656789541244507,
-0.28112345933914185,
-0.04575753211975098,
-0.0969703420996666,
-0.017560925334692,
-0.2522439956665039,
-0.0532970055937767,
0.018999725580215454,
-0.1461751013994217,
-0.029696844518184662,
-0.06324397027492523,
-0.2030780166387558,
0.3560207188129425,
-0.13447648286819458,
0.005193449556827545,
0.20223788917064667,
0.013026426546275616,
0.053487882018089294,
0.06713122129440308,
0.03821226954460144,
0.03194700554013252,
0.20771418511867523,
0.02288118191063404,
0.3638218939304352,
-0.14250923693180084,
0.26192307472229004,
-0.2598850131034851,
0.25790271162986755,
0.17956404387950897,
-0.053154557943344116,
0.04724732041358948,
-0.2090412825345993,
-0.2319692224264145,
-0.11197467148303986,
-0.2654051184654236,
0.28373512625694275,
0.03603268787264824,
-0.14099259674549103,
0.12018948793411255,
0.24428707361221313,
0.026496976613998413,
-0.2426859587430954,
0.23383943736553192,
0.3414636254310608,
-0.10660884529352188,
0.3187498450279236,
0.014410741627216339,
0.7144322991371155,
0.2847661077976227,
-0.1513303518295288,
0.1777021288871765,
-0.09784714877605438,
0.2846790850162506,
-0.08520574867725372,
0.03084205836057663,
0.14362411201000214,
-0.029414750635623932,
-0.10803273320198059,
0.22408488392829895,
0.47330978512763977,
-0.1807129979133606,
-0.4074785113334656,
0.23934654891490936,
0.37372463941574097,
0.25265413522720337,
0.17917318642139435,
0.02582484483718872,
0.2792445719242096,
-0.1941184550523758,
0.22286474704742432,
0.16126205027103424,
0.11865907907485962,
0.24784404039382935,
-0.007930041290819645,
-0.12176413834095001,
-0.10707306861877441,
-0.33475154638290405,
-0.2222701907157898,
-0.15550276637077332,
0.17588695883750916,
-0.1371014267206192,
0.12958724796772003,
-0.13968020677566528,
0.5002411603927612,
-0.21630284190177917,
0.3512284755706787,
0.07694332301616669,
-0.393901526927948,
0.19849856197834015,
0.12374664098024368,
-0.09371845424175262,
-0.04847056418657303,
0.011539828963577747,
-0.09307029098272324,
-0.31500595808029175,
-0.040459439158439636,
0.27459079027175903,
0.13504843413829803,
-0.2294904589653015,
-0.150488018989563,
-0.15534141659736633,
-0.05174735188484192,
0.19557903707027435,
0.3932056725025177,
0.4967649281024933,
0.20558060705661774,
-0.2776392698287964,
0.21186195313930511,
0.19321778416633606,
-0.09961581975221634,
-0.09029289335012436,
0.001679297536611557,
0.052381500601768494,
-0.209777370095253,
0.20240315794944763,
0.3447622060775757,
-0.2052677422761917,
0.11227018386125565,
-0.06963338702917099,
-0.0756426453590393,
-0.23330840468406677,
-0.3203873336315155,
-0.013944464735686779,
-0.5064802765846252,
-0.21499544382095337,
0.04626106098294258,
-0.2646346688270569,
0.16258925199508667,
0.9665590524673462,
0.01933588832616806,
0.08566275238990784,
-0.15413010120391846,
-0.12778069078922272,
-0.27205634117126465,
0.09145689755678177,
-0.6348620653152466,
0.3025992214679718,
-0.09700276702642441,
-0.010685129091143608,
-0.05887637287378311,
0.2275681495666504,
-0.40056437253952026,
-0.23105879127979279,
0.08580842614173889,
-0.07548955082893372,
0.17271468043327332,
0.18505537509918213,
0.3002164363861084,
0.20005735754966736,
0.10802093148231506,
-0.03642883151769638,
-0.2978534996509552,
-0.14092481136322021,
0.06706100702285767,
0.09022772312164307,
0.08517469465732574,
0.265106201171875,
0.015573612414300442,
-0.09612858295440674,
-0.3636767566204071,
0.14022549986839294,
0.31589752435684204,
-0.25541505217552185,
-0.08340774476528168,
0.21389128267765045,
-0.2956829071044922,
-0.15318617224693298,
0.0740920901298523,
0.268174946308136,
0.20325908064842224,
0.00018320977687835693,
0.022653240710496902,
0.40176713466644287,
-0.07402580231428146,
-0.12795908749103546,
0.06694352626800537,
0.39901527762413025,
-0.3243759274482727,
0.23266419768333435,
0.05787014216184616,
0.021776720881462097,
-0.07467720657587051,
-0.027419010177254677,
-0.11537861078977585,
-0.5985841155052185,
-0.05257910490036011,
0.08984836935997009,
0.027268800884485245,
0.2741132080554962,
-0.4083036780357361,
0.10977049171924591,
-0.23368915915489197,
-0.06540708988904953,
0.17333264648914337,
0.1268070489168167,
0.538725733757019,
-0.04353984817862511,
0.9180060625076294,
0.10789883881807327,
-0.07989365607500076,
-0.07315390557050705,
0.35224682092666626,
0.09844856709241867,
0.19314135611057281,
0.2026144564151764,
0.1697167009115219,
0.017392292618751526,
0.08312458544969559,
-0.06407191604375839,
0.010316044092178345,
-0.09518469870090485,
0.3211269974708557,
0.4013398587703705,
0.15263217687606812,
-0.31373360753059387,
0.03715774789452553,
0.16140078008174896,
0.1964500993490219,
0.016423720866441727,
0.21400709450244904,
-0.09558103233575821,
0.12567318975925446,
0.11404748260974884,
-0.8520107865333557,
-0.14799919724464417,
-0.0002811327576637268,
-0.15192794799804688,
-0.15474072098731995,
-0.12153647094964981,
-0.26129478216171265,
-0.10409194231033325,
0.2915908098220825,
0.1082492545247078,
0.29016727209091187,
-0.29568856954574585,
-0.08855624496936798,
-0.07152862101793289,
-0.08061780780553818,
0.14213575422763824,
0.14287446439266205,
0.08947965502738953,
0.5019301772117615,
-0.4905027747154236,
-0.25601014494895935,
0.30503740906715393,
0.3041679263114929,
0.16102735698223114,
-0.20795701444149017,
0.2815849184989929,
0.18219362199306488,
0.019643504172563553,
-0.26642152667045593,
0.16778211295604706,
0.26305466890335083,
-0.0011916086077690125,
0.12151727080345154,
0.1015295535326004,
0.11109834909439087,
-0.06895503401756287,
0.01900523342192173,
-0.11042600870132446,
-0.004637842997908592,
-0.2969089448451996,
0.14319083094596863,
-0.07266214489936829,
0.12516340613365173,
-0.08303329348564148,
0.24224305152893066,
0.0606016144156456,
-0.3382854759693146,
-0.2355436086654663,
-0.14563843607902527,
-0.2185368537902832,
-0.14484553039073944,
0.11242605745792389,
-0.2741743326187134,
0.02028036117553711,
0.24042868614196777,
0.2540437579154968,
-0.02682773396372795,
-0.5908101201057434,
0.002972930669784546,
0.27418720722198486,
0.13339383900165558,
0.03358721733093262,
0.08341849595308304,
0.25750401616096497,
0.208232581615448,
-0.2613700032234192,
0.29738879203796387,
-0.1402307003736496,
0.3001266121864319,
-0.008812136948108673,
-0.35600730776786804,
0.06686928868293762,
0.26842188835144043,
-0.008375920355319977,
-0.18063223361968994,
-0.04371894896030426,
-0.11608526110649109,
0.2443636953830719,
0.0062119849026203156,
-0.2181481271982193,
0.014315061271190643,
0.08671729266643524,
0.04670063406229019,
0.47451052069664,
0.2091076374053955,
0.1296912431716919,
-0.1403009593486786,
-0.13859014213085175,
-0.41770774126052856,
-0.09693159908056259,
0.04019985720515251,
-0.1644831895828247,
0.07427644729614258,
0.22511287033557892,
-0.0425955131649971,
0.13968177139759064,
-0.0036886464804410934,
0.4698243737220764,
0.07916218787431717,
-0.0848124772310257,
-0.12159688770771027,
0.5496423840522766,
-0.4163467586040497,
-0.17564962804317474,
0.12344086170196533,
-0.134454607963562,
0.16413360834121704,
-0.1847333312034607,
-0.1444331854581833,
-0.10510910302400589,
0.27850863337516785,
-0.22749774158000946,
0.09104298055171967,
-0.0843522921204567,
0.31331199407577515,
0.11957132071256638,
-0.010894568637013435,
-0.33837202191352844,
0.04173070937395096,
0.11309703439474106,
0.23142507672309875,
-0.08588773012161255,
0.44417470693588257,
0.10862861573696136,
0.011421862989664078,
-0.14661401510238647,
0.3638548254966736,
-0.15389755368232727,
-0.040989309549331665,
0.04374947026371956,
-0.3198181390762329
] |
https://github.com/huggingface/datasets/issues/163 | [Feature request] Add cos-e v1.0 | You can now do
```python
from nlp import load_dataset
cos_e = load_dataset("cos_e", "v1.0")
```
Thanks @mariamabarham ! | I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf). | 17 | [Feature request] Add cos-e v1.0
I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf).
You can now do
```python
from nlp import load_dataset
cos_e = load_dataset("cos_e", "v1.0")
```
Thanks @mariamabarham ! | [
-0.25247395038604736,
-0.2647853493690491,
-0.1142226904630661,
-0.4864540696144104,
-0.37947577238082886,
-0.20802780985832214,
0.08028712868690491,
0.1892700344324112,
0.11779683828353882,
0.3005794882774353,
-0.155775249004364,
0.5226978063583374,
-0.1476927548646927,
0.4125770926475525,
0.1462078094482422,
0.10172688215970993,
0.03274606913328171,
0.36265653371810913,
-0.14609387516975403,
-0.20175470411777496,
-0.24998591840267181,
0.22434023022651672,
-0.17047974467277527,
-0.0546533465385437,
0.2192804217338562,
0.07695111632347107,
-0.29594311118125916,
0.0793561264872551,
-0.06169799715280533,
-0.19533966481685638,
0.32915693521499634,
0.329232782125473,
0.18306970596313477,
0.06467734277248383,
-0.0001042149233398959,
-0.23515938222408295,
0.257485032081604,
-0.12841549515724182,
-0.28690019249916077,
-0.18150989711284637,
-0.1894627809524536,
-0.4737764894962311,
0.2212621569633484,
-0.21766060590744019,
0.10919704288244247,
0.12459304183721542,
0.20315438508987427,
-0.1243731826543808,
0.1270555704832077,
0.2281511127948761,
0.3232874870300293,
0.4082866907119751,
-0.03426554799079895,
-0.18497490882873535,
0.20779341459274292,
0.2706398069858551,
-0.20863227546215057,
-0.012949122115969658,
0.15916483104228973,
-0.275456041097641,
-0.1968260407447815,
0.40579548478126526,
0.14011336863040924,
-0.09584838151931763,
-0.1321592926979065,
-0.06573273986577988,
0.16082273423671722,
0.021586338058114052,
0.010288204997777939,
0.03543519228696823,
0.23504433035850525,
-0.049714528024196625,
-0.3959871828556061,
0.14017510414123535,
0.028912823647260666,
-0.5668572783470154,
0.09331750869750977,
-0.08714375644922256,
-0.12451334297657013,
-0.14305618405342102,
0.207477867603302,
-0.162346750497818,
-0.4726060926914215,
0.2572448253631592,
0.00482989102602005,
0.29475849866867065,
-0.06364817917346954,
-0.2017003893852234,
0.22664369642734528,
0.04250162094831467,
-0.07998193055391312,
0.15150271356105804,
-0.032829832285642624,
0.3442155718803406,
-0.532577395439148,
-0.2802596092224121,
0.34057557582855225,
0.09036564081907272,
0.2678717374801636,
0.042602624744176865,
0.2928159832954407,
0.14166155457496643,
-0.003866479266434908,
0.19317743182182312,
0.030217591673135757,
0.24012567102909088,
0.292665034532547,
-0.04129859805107117,
0.42817866802215576,
0.2653530538082123,
0.3137470483779907,
0.05636422336101532,
0.0704406276345253,
-0.10898222774267197,
-0.14499956369400024,
-0.06849263608455658,
0.008154410868883133,
-0.4685887098312378,
-0.2638154923915863,
-0.05357527732849121,
-0.055846989154815674,
0.14551283419132233,
-0.013918506912887096,
0.2732974886894226,
0.1701270341873169,
0.24480241537094116,
0.43004345893859863,
0.009215237572789192,
-0.22485925257205963,
-0.3951990306377411,
-0.29168108105659485,
0.09738127887248993,
-0.3190457224845886,
0.08400389552116394,
0.373189777135849,
-0.20060120522975922,
0.27423256635665894,
-0.43340110778808594,
0.25433433055877686,
0.071140818297863,
-0.1991911232471466,
0.23665927350521088,
-0.11447153240442276,
0.06143748760223389,
0.2251134216785431,
-0.04297841712832451,
-0.23835982382297516,
0.20623402297496796,
-0.20838817954063416,
-0.08082080632448196,
-0.3151925504207611,
-0.382951557636261,
-0.40688368678092957,
0.27562108635902405,
-0.055168330669403076,
-0.314896821975708,
-0.13434967398643494,
0.3234364986419678,
-0.17393061518669128,
-0.1865476667881012,
-0.03619306534528732,
0.13921815156936646,
-0.25417569279670715,
-0.12859782576560974,
0.09105675667524338,
0.11252589523792267,
0.054606158286333084,
-0.1368643343448639,
-0.5214046835899353,
0.0013879556208848953,
-0.010001927614212036,
0.049277059733867645,
0.02189880609512329,
-0.12459664791822433,
-0.1309000849723816,
-0.1309100091457367,
0.5791587233543396,
-0.36789417266845703,
-0.06391140818595886,
0.1252528727054596,
0.05375072360038757,
-0.28811267018318176,
0.09406547248363495,
-0.17142541706562042,
-0.14280207455158234,
-0.10669790208339691,
-0.1012190580368042,
0.3418888449668884,
-0.07049553096294403,
0.09957312792539597,
-0.11652086675167084,
-0.30355843901634216,
-0.012261595577001572,
0.3013630211353302,
0.29123976826667786,
-0.08109045773744583,
0.23300936818122864,
-0.15536600351333618,
0.20717063546180725,
-0.2782922685146332,
0.034141480922698975,
0.0545126348733902,
0.5859828591346741,
0.04629027843475342,
0.09907401353120804,
-0.05174317955970764,
-0.3171609342098236,
0.01667911931872368,
-0.11427298933267593,
0.29519736766815186,
0.11283303797245026,
-0.29259783029556274,
-0.03223046660423279,
0.05407194048166275,
0.11803597211837769,
-0.11149375140666962,
0.2614137828350067,
0.11125195026397705,
0.023204389959573746,
0.07920382916927338,
0.07408304512500763,
0.3704969882965088,
-0.14236298203468323,
-0.13941875100135803,
-0.25196874141693115,
0.19473262131214142,
-0.21140211820602417,
-0.09095360338687897,
0.09032346308231354,
0.30762791633605957,
-0.014147154986858368,
-0.016491485759615898,
-0.09004611521959305,
0.3420785963535309,
-0.19772456586360931,
0.3473963141441345,
0.06613952666521072,
0.11991210281848907,
0.03165199235081673,
-0.18702729046344757,
0.10462108999490738,
0.020478149875998497,
0.10501891374588013,
0.19834381341934204,
-0.1874205470085144,
0.4752040505409241,
0.09016667306423187,
-0.0594591423869133,
0.09390716254711151,
0.03295445442199707,
0.1509227156639099,
-0.23204569518566132,
-0.30256161093711853,
0.012772440910339355,
0.38707464933395386,
0.1158938854932785,
-0.3680190443992615,
-0.373274028301239,
-0.37219515442848206,
-0.06634137779474258,
0.1566101759672165,
0.005696229636669159,
0.21773910522460938,
0.1688700020313263,
-0.022963881492614746,
-0.2444078028202057,
0.2332589030265808,
-0.0959550216794014,
0.3129541873931885,
0.33390384912490845,
-0.0884549617767334,
0.03661441057920456,
-0.34952226281166077,
0.038188837468624115,
0.1847696602344513,
0.21045924723148346,
-0.003719043917953968,
0.1817546784877777,
0.4397560656070709,
-0.03354679420590401,
-0.4896514415740967,
-0.41225647926330566,
-0.2240450382232666,
0.048277124762535095,
-0.24939961731433868,
-0.012751483358442783,
-0.06169266998767853,
-0.14514479041099548,
-0.055051274597644806,
0.09441997855901718,
0.0958615392446518,
-0.36516016721725464,
0.28364133834838867,
0.3310319483280182,
-0.25196075439453125,
0.19968518614768982,
-0.011269407346844673,
0.6269261240959167,
-0.040750518441200256,
0.12832379341125488,
-0.2383573055267334,
-0.05031697824597359,
-0.2411792278289795,
0.26183512806892395,
-0.24112819135189056,
0.031092854216694832,
0.4830784201622009,
-0.18815001845359802,
0.26334232091903687,
0.051257871091365814,
-0.6950429081916809,
0.019227750599384308,
-0.12177248299121857,
-0.06724271178245544,
0.10748785734176636,
-0.31135642528533936,
-0.10114424675703049,
-0.0694996640086174,
0.04360108822584152,
-0.6364909410476685,
-0.34482109546661377,
-0.013514799065887928,
-0.23367322981357574,
0.16604368388652802,
-0.4094182252883911,
-0.43483468890190125,
-0.104634590446949,
-0.37184298038482666,
-0.12796847522258759,
0.09901575744152069,
0.18223023414611816,
0.3901268243789673,
-0.0058502196334302425,
0.17498679459095,
0.061040233820676804,
0.05882640928030014,
-0.31342655420303345,
0.17934037744998932,
0.42067214846611023,
-0.40306001901626587,
-0.5246384143829346,
0.008748900145292282,
-0.09246602654457092,
0.3225846290588379,
0.09169071912765503,
-0.11638527363538742,
-0.39315280318260193,
0.17101828753948212,
0.03368833288550377,
-0.13248781859874725,
0.2708769142627716,
0.4044116139411926,
-0.03216135874390602,
-0.21041570603847504,
-0.1765938401222229,
-0.2458331286907196,
0.15085195004940033,
0.4518738090991974,
0.13134139776229858,
-0.24895256757736206,
0.27934443950653076,
0.08622346818447113,
0.11332763731479645,
0.10454657673835754,
-0.16755010187625885,
0.2823275327682495,
-0.027697758749127388,
0.20288461446762085,
-0.001618117094039917,
-0.00043096207082271576,
0.07328081876039505,
0.07297275215387344,
0.2253543883562088,
0.5441485047340393,
0.14013338088989258,
-0.4167070686817169,
-0.35925528407096863,
-0.30449584126472473,
-0.03829622268676758,
-0.08819417655467987,
-0.057566821575164795,
0.2055095136165619,
0.3595203757286072,
-0.028068874031305313,
-0.19928357005119324,
-0.41280996799468994,
-0.20246300101280212,
-0.012766246683895588,
0.2373708039522171,
0.004086844623088837,
-0.06508514285087585,
0.09634464979171753,
0.038656361401081085,
-0.4979262948036194,
0.38196176290512085,
0.11513083428144455,
0.0731695294380188,
0.03802059218287468,
-0.08453947305679321,
0.0638473629951477,
-0.10432162880897522,
0.18705996870994568,
-0.11142290383577347,
0.0054567791521549225,
-0.05644497647881508,
-0.10295884311199188,
-0.1770627200603485,
0.05641874298453331,
-0.378465473651886,
-0.19693318009376526,
0.07580872625112534,
-0.009619325399398804,
-0.0009151995182037354,
-0.17845577001571655,
0.660025954246521,
-0.08007253706455231,
-0.05716114491224289,
-0.19711533188819885,
-0.012537848204374313,
-0.4126783013343811,
-0.0750909373164177,
-0.003672763705253601,
-0.1563308835029602,
0.2179161012172699,
-0.12022322416305542,
-0.08209224045276642,
0.17336639761924744,
-0.017646897584199905,
0.11866284906864166,
0.28284525871276855,
-0.07113154232501984,
0.1216844990849495,
-0.01521703228354454,
-0.025802522897720337,
0.07832600176334381,
0.1132291704416275,
0.11903879046440125,
0.18738582730293274,
-0.06267866492271423,
0.05007655546069145,
-0.05787062644958496,
0.29155233502388,
0.18741901218891144,
0.09294836223125458,
0.022943638265132904,
-0.3587072491645813,
-0.09099902212619781,
-0.08881594985723495,
-0.0064687058329582214,
0.28515785932540894,
0.23027527332305908,
-0.2992844581604004,
0.018360627815127373,
0.4084852337837219,
0.11278808116912842,
-0.2255142480134964,
0.13825823366641998,
0.03543659299612045,
-0.43261680006980896,
0.5216683149337769,
-0.047607384622097015,
0.6814639568328857,
0.2664852738380432,
0.06667885184288025,
0.4089907109737396,
0.01980314403772354,
0.6191628575325012,
-0.12821854650974274,
0.0904495045542717,
0.008613530546426773,
-0.07493537664413452,
-0.02831854857504368,
0.2580915689468384,
0.28022441267967224,
-0.14534053206443787,
-0.3026861846446991,
0.35803529620170593,
0.4741479754447937,
-0.028228703886270523,
0.0660800188779831,
0.1906587779521942,
0.2675008475780487,
-0.35727664828300476,
-0.17591629922389984,
0.19538575410842896,
-0.05740012973546982,
0.1983063966035843,
-0.009514261037111282,
-0.07632473856210709,
-0.03352481126785278,
-0.34462064504623413,
-0.09483597427606583,
-0.0046200137585401535,
0.40876203775405884,
0.06272788345813751,
-0.013134617358446121,
0.00018253177404403687,
0.35457631945610046,
-0.25106653571128845,
0.20681530237197876,
0.1270361840724945,
-0.23320049047470093,
0.13416142761707306,
0.030415289103984833,
0.033475086092948914,
-0.057564765214920044,
0.06580778956413269,
0.17728278040885925,
-0.21683084964752197,
-0.09247618913650513,
0.13309326767921448,
0.2801990211009979,
-0.2276497483253479,
0.07511956989765167,
-0.05992458760738373,
-0.09679773449897766,
0.09913437068462372,
0.2709742784500122,
0.5199607014656067,
0.04232681170105934,
-0.2932434380054474,
0.24941076338291168,
0.21730060875415802,
-0.2473541647195816,
0.1259586215019226,
0.1490776687860489,
-0.14991825819015503,
-0.126140296459198,
0.4295508861541748,
0.3287908434867859,
-0.17596818506717682,
0.1623610258102417,
0.028476331382989883,
-0.06598136574029922,
-0.2654573321342468,
-0.24508410692214966,
-0.0956837460398674,
-0.575057327747345,
-0.0652821883559227,
0.11142811924219131,
-0.1890368014574051,
0.20219171047210693,
0.7269651293754578,
-0.03920883685350418,
0.20746362209320068,
-0.10957221686840057,
-0.2568226456642151,
-0.27607429027557373,
0.05067761242389679,
-0.4521557688713074,
0.2244728058576584,
0.14675357937812805,
0.05748944357037544,
-0.057873405516147614,
0.08658529818058014,
-0.4668600857257843,
-0.22374434769153595,
0.07354412227869034,
-0.011187952011823654,
0.3666561245918274,
0.08408299833536148,
0.33175262808799744,
0.07002590596675873,
0.2591492533683777,
0.01709246262907982,
-0.18132854998111725,
-0.27145418524742126,
-0.12523697316646576,
0.07885979861021042,
0.021880485117435455,
0.17113512754440308,
0.09806933254003525,
-0.056750908493995667,
-0.2730424106121063,
-0.0597003772854805,
0.1882500797510147,
-0.08539941161870956,
-0.1864279955625534,
0.37596821784973145,
-0.20979566872119904,
-0.13131308555603027,
0.37401872873306274,
0.29977643489837646,
0.20191779732704163,
0.013176128268241882,
-0.10522716492414474,
0.4919646680355072,
-0.06271235644817352,
-0.10722265392541885,
0.04128659516572952,
0.1994611769914627,
-0.21136488020420074,
0.10680319368839264,
0.08347342163324356,
0.0005004703998565674,
-0.25967687368392944,
-0.20306336879730225,
0.2125796377658844,
-0.29589134454727173,
0.015859704464673996,
0.06989350914955139,
0.0752127394080162,
0.3328959047794342,
-0.43360841274261475,
0.15516597032546997,
-0.06994199752807617,
-0.15005750954151154,
0.3807324469089508,
0.1659955382347107,
0.2593381404876709,
-0.1449124664068222,
0.6386486291885376,
-0.011185507290065289,
-0.019398774951696396,
0.06352224200963974,
0.2700665295124054,
0.007332455366849899,
0.08318677544593811,
0.0074922144412994385,
0.06729623675346375,
0.002586677670478821,
0.26146405935287476,
-0.024469688534736633,
0.043507687747478485,
-0.026396160945296288,
0.1955518126487732,
0.39803504943847656,
-0.004165023565292358,
-0.21858030557632446,
-0.04063562676310539,
0.2692480981349945,
0.1335301250219345,
0.22033315896987915,
0.12551990151405334,
0.013996191322803497,
-0.0264744870364666,
0.0733947902917862,
-0.6518140435218811,
0.10224491357803345,
0.046333711594343185,
-0.2674894332885742,
-0.19240398705005646,
-0.060146886855363846,
-0.5283677577972412,
-0.03477142006158829,
0.1602238118648529,
-0.09570488333702087,
0.11657209694385529,
-0.05166510492563248,
0.07509457319974899,
-0.17832216620445251,
-0.06448644399642944,
0.1521918773651123,
0.2097455859184265,
-0.07242782413959503,
0.26005953550338745,
-0.3143095374107361,
-0.13356737792491913,
0.11316905915737152,
0.33179306983947754,
0.25361499190330505,
-0.07983915507793427,
0.25138118863105774,
0.18931564688682556,
0.07819020748138428,
-0.06341112405061722,
0.015542060136795044,
0.1274963617324829,
0.1751863658428192,
0.15679259598255157,
0.34565529227256775,
0.19967436790466309,
-0.23538140952587128,
0.10904023051261902,
0.018087133765220642,
-0.1851758062839508,
-0.18787136673927307,
0.2947615683078766,
0.2506910562515259,
0.12793797254562378,
-0.15492777526378632,
0.056655243039131165,
-0.22269272804260254,
-0.31515467166900635,
-0.05655486509203911,
-0.04162641614675522,
-0.06579113751649857,
-0.269204705953598,
0.1421038955450058,
-0.10145178437232971,
0.24289833009243011,
0.20207802951335907,
0.3052961528301239,
0.07524070888757706,
-0.4313358664512634,
-0.16718514263629913,
0.21204820275306702,
0.18553729355335236,
-0.23350785672664642,
-0.04269712418317795,
0.16694118082523346,
0.14643627405166626,
-0.2412625402212143,
0.10201048851013184,
-0.1333187371492386,
0.42490410804748535,
-0.0015241876244544983,
-0.39028072357177734,
0.1590537130832672,
0.14354091882705688,
-0.0917150229215622,
-0.03733240067958832,
-0.259224534034729,
-0.3049335777759552,
-0.1383424997329712,
0.13726061582565308,
-0.2919718027114868,
0.09674203395843506,
0.006600707769393921,
0.13372191786766052,
0.419193297624588,
0.029713384807109833,
0.2779366374015808,
-0.33394160866737366,
-0.006887739524245262,
-0.3844677209854126,
-0.25012096762657166,
-0.06227702647447586,
0.046573176980018616,
0.096226766705513,
0.17797496914863586,
0.020027371123433113,
0.1866796761751175,
0.04949438199400902,
0.39270493388175964,
0.03392908722162247,
-0.23147547245025635,
-0.04233120381832123,
0.5437836647033691,
-0.3518795371055603,
-0.20718622207641602,
-0.07825567573308945,
-0.00487276166677475,
0.039167795330286026,
-0.13390235602855682,
-0.05519881844520569,
-0.30653655529022217,
0.3257245421409607,
-0.3351879119873047,
-0.058628469705581665,
-0.07195790857076645,
0.3476722240447998,
0.1555512547492981,
-0.006516776978969574,
-0.3395659625530243,
0.16316473484039307,
0.14248691499233246,
0.16235291957855225,
-0.03403221070766449,
0.39861780405044556,
-0.1481122374534607,
-0.012054719030857086,
-0.21766544878482819,
-0.16810856759548187,
-0.06432831287384033,
-0.08481381088495255,
0.13156446814537048,
-0.43430906534194946
] |
https://github.com/huggingface/datasets/issues/163 | [Feature request] Add cos-e v1.0 | @mariamabarham Just wanted to note that default behavior `cos_e = load_dataset("cos_e")` now loads `v1.0`. Not sure if this is intentional (but the flag specification does work as intended). | I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf). | 28 | [Feature request] Add cos-e v1.0
I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf).
@mariamabarham Just wanted to note that default behavior `cos_e = load_dataset("cos_e")` now loads `v1.0`. Not sure if this is intentional (but the flag specification does work as intended). | [
-0.22634360194206238,
-0.2859199047088623,
-0.11841721832752228,
-0.4919188618659973,
-0.45303940773010254,
-0.25085964798927307,
0.21630574762821198,
0.22147011756896973,
-0.035638511180877686,
0.3164646625518799,
0.07013271749019623,
0.4571438431739807,
0.032457053661346436,
0.353317528963089,
-0.16244831681251526,
0.4214378893375397,
0.11718563735485077,
0.2206689417362213,
-0.030111968517303467,
-0.25561654567718506,
-0.22714577615261078,
0.1309107542037964,
-0.16859979927539825,
-0.1252732276916504,
0.16298648715019226,
0.2887749671936035,
-0.2544236481189728,
-0.09574774652719498,
-0.04146188497543335,
-0.18337297439575195,
0.4028764069080353,
0.34786319732666016,
0.17024505138397217,
0.06462868303060532,
-0.00011004399857483804,
-0.13638831675052643,
0.4567965865135193,
-0.06395504623651505,
-0.2753702700138092,
-0.1536128669977188,
-0.35569217801094055,
-0.3650529980659485,
0.07075216621160507,
-0.07159383594989777,
0.21727675199508667,
0.16272687911987305,
0.14945903420448303,
-0.031100904569029808,
0.04020855575799942,
0.16627220809459686,
0.269146591424942,
0.2860799729824066,
-0.03167672082781792,
-0.33285099267959595,
0.21256232261657715,
0.47362667322158813,
-0.3600451350212097,
-0.07488913834095001,
0.043695442378520966,
-0.09709266573190689,
-0.14182782173156738,
0.3820023536682129,
0.22545596957206726,
-0.17204217612743378,
-0.2601481080055237,
-0.030674681067466736,
0.21465083956718445,
0.1305542290210724,
0.2605668902397156,
0.0569026842713356,
0.35295259952545166,
0.1386500895023346,
-0.26492398977279663,
0.2500227987766266,
-0.05883818492293358,
-0.42920055985450745,
0.2250400185585022,
-0.16231562197208405,
0.021105274558067322,
0.004746139049530029,
0.35412001609802246,
-0.18666288256645203,
-0.5334497690200806,
0.15618228912353516,
-0.21667085587978363,
0.17143064737319946,
-0.2124955803155899,
-0.14087381958961487,
0.09422009438276291,
0.10761164128780365,
-0.09298375993967056,
0.11195191740989685,
-0.20708155632019043,
0.18042734265327454,
-0.34744328260421753,
-0.10264956206083298,
0.30851954221725464,
-0.06392960995435715,
0.42677047848701477,
0.15892182290554047,
0.19507107138633728,
0.19056737422943115,
-0.01569845899939537,
0.15070189535617828,
0.01156392227858305,
0.36866244673728943,
0.5664448142051697,
0.0640154629945755,
0.4030507206916809,
0.14254896342754364,
0.40475839376449585,
0.016548022627830505,
0.0781300961971283,
0.02118225395679474,
-0.002247307449579239,
-0.16156670451164246,
0.11037556827068329,
-0.5184801816940308,
-0.18017205595970154,
-0.03196031600236893,
-0.10153421759605408,
0.09271793812513351,
0.004587896168231964,
0.2791184186935425,
0.2888188064098358,
0.1953786313533783,
0.32147789001464844,
-0.02211962640285492,
0.016755154356360435,
-0.2821887135505676,
-0.2884853184223175,
-0.08126683533191681,
-0.2485470026731491,
0.2028690129518509,
0.19906418025493622,
-0.3987305164337158,
0.2090894877910614,
-0.364455908536911,
0.4094005823135376,
-0.06413433700799942,
-0.22893166542053223,
0.3046197295188904,
-0.035716377198696136,
0.26344993710517883,
0.038811665028333664,
-0.017299553379416466,
-0.09945590794086456,
0.3986690044403076,
-0.16598179936408997,
0.11357759684324265,
-0.21756243705749512,
-0.48887720704078674,
-0.2699550688266754,
0.26509127020835876,
-0.1804889291524887,
-0.2526893615722656,
-0.24294298887252808,
0.41736164689064026,
-0.2470448613166809,
-0.007607344537973404,
0.01368434727191925,
0.1410551220178604,
-0.32141146063804626,
-0.20329102873802185,
-0.08240259438753128,
0.19734466075897217,
-0.04359922558069229,
-0.08860630542039871,
-0.6579610705375671,
-0.09929913282394409,
0.015475288033485413,
-0.18410447239875793,
-0.018393991515040398,
-0.30888569355010986,
-0.24293749034404755,
-0.09758506715297699,
0.4091992974281311,
-0.540909469127655,
-0.08889669179916382,
0.30070286989212036,
-0.05289766564965248,
-0.21085941791534424,
0.1997181475162506,
-0.30009984970092773,
-0.15993160009384155,
-0.2848050892353058,
-0.3112843334674835,
0.05204365402460098,
-0.03445470333099365,
-0.05105540156364441,
-0.0711141973733902,
-0.34644249081611633,
-0.34897786378860474,
0.2585710883140564,
0.36376211047172546,
0.03293449059128761,
0.3567889630794525,
-0.41883379220962524,
0.15049877762794495,
-0.05560467764735222,
0.13320334255695343,
-0.025527622550725937,
0.6704121828079224,
0.10371123254299164,
0.19556771218776703,
0.13810691237449646,
-0.3721381425857544,
0.09697645157575607,
0.18270781636238098,
0.1522466391324997,
0.20965853333473206,
-0.36246728897094727,
-0.15044835209846497,
0.14429157972335815,
-0.006205279380083084,
-0.19019728899002075,
0.18903614580631256,
0.16746029257774353,
-0.06673913449048996,
-0.03944755345582962,
-0.04032126069068909,
0.4120458960533142,
-0.333312064409256,
-0.08935071527957916,
0.16916675865650177,
0.06708654761314392,
-0.05909055471420288,
-0.007216337136924267,
-0.052231565117836,
0.09110017120838165,
-0.003276742994785309,
0.008714205585420132,
-0.1518043875694275,
0.3978510797023773,
-0.014699926599860191,
0.137334942817688,
0.07569354772567749,
0.20276620984077454,
0.12991942465305328,
-0.11296959221363068,
0.015640564262866974,
0.031186847016215324,
-0.0605439729988575,
0.10886550694704056,
-0.21376872062683105,
0.36783480644226074,
-0.04400141164660454,
0.07868464291095734,
-0.003053363412618637,
-0.08954405039548874,
0.026837507262825966,
-0.0728670060634613,
-0.5226487517356873,
-0.21800456941127777,
0.24215564131736755,
0.10695752501487732,
-0.42331528663635254,
-0.23976372182369232,
-0.22046196460723877,
-0.08050710707902908,
0.1762455701828003,
-0.10011544823646545,
0.15004447102546692,
0.3162190020084381,
0.10816863924264908,
-0.1911516785621643,
0.27675729990005493,
-0.1665319800376892,
0.406342089176178,
0.31514111161231995,
-0.1061272919178009,
-0.048021040856838226,
-0.30542588233947754,
-0.05322825536131859,
0.13648022711277008,
0.2142147272825241,
0.12367867678403854,
0.1257350742816925,
0.41697460412979126,
-0.14952263236045837,
-0.5176544189453125,
-0.4135934114456177,
-0.06272319704294205,
-0.16659285128116608,
-0.19666188955307007,
-0.16656161844730377,
-0.06399566680192947,
0.09422243386507034,
-0.10740857571363449,
0.038636185228824615,
0.08334244787693024,
-0.23619933426380157,
0.2636566162109375,
0.22466324269771576,
-0.061354316771030426,
0.23576238751411438,
0.025401555001735687,
0.6541306972503662,
-0.02252654731273651,
0.13648198544979095,
-0.15872688591480255,
0.06660034507513046,
-0.420367956161499,
0.19410818815231323,
-0.5060151219367981,
-0.22600547969341278,
0.4339211881160736,
-0.007591546513140202,
0.3097063899040222,
-0.06009943038225174,
-0.6933549642562866,
0.07365789264440536,
-0.19269134104251862,
-0.1378568857908249,
0.06659695506095886,
-0.28835171461105347,
-0.11153594404459,
0.04072219133377075,
0.08749237656593323,
-0.39441999793052673,
-0.3563591539859772,
-0.08151979744434357,
-0.23026928305625916,
0.27909958362579346,
-0.34588751196861267,
-0.4851737320423126,
0.23486736416816711,
-0.33899614214897156,
-0.11091116070747375,
-0.08392272144556046,
0.12878653407096863,
0.5446902513504028,
0.13814018666744232,
0.08742569386959076,
0.1251380741596222,
-0.014643311500549316,
-0.41065657138824463,
0.23893660306930542,
0.340101957321167,
-0.3349621295928955,
-0.40006378293037415,
0.10895256698131561,
0.09359128773212433,
0.1544482409954071,
0.20974069833755493,
-0.186634361743927,
-0.5588259696960449,
0.18018372356891632,
0.15571671724319458,
-0.2045297622680664,
0.15855006873607635,
0.38408079743385315,
-0.01926819048821926,
-0.19568870961666107,
-0.18685048818588257,
-0.3143167197704315,
0.2257436215877533,
0.3081617057323456,
0.1298706978559494,
-0.16425472497940063,
0.2678801119327545,
0.16116443276405334,
0.1489793360233307,
0.08203333616256714,
0.019120145589113235,
0.0505388081073761,
0.11084745079278946,
0.35109445452690125,
-0.025693602859973907,
0.05527877062559128,
0.13333112001419067,
0.08192263543605804,
0.2069118618965149,
0.46736425161361694,
0.1389227658510208,
-0.2309902012348175,
-0.2874261736869812,
-0.2523173689842224,
0.16300898790359497,
0.03166082873940468,
-0.16662462055683136,
0.18828527629375458,
0.43356117606163025,
-0.12905935943126678,
-0.09658840298652649,
-0.32698288559913635,
0.03286070004105568,
0.061074819415807724,
0.42140090465545654,
0.09682787209749222,
-0.17435342073440552,
-0.004774656146764755,
0.14035241305828094,
-0.32818493247032166,
0.3598346710205078,
0.10829274356365204,
0.051345594227313995,
-0.003542773425579071,
-0.20926478505134583,
0.21159037947654724,
-0.029142964631319046,
0.43104124069213867,
-0.180899515748024,
0.013701669871807098,
-0.11118042469024658,
-0.07789909094572067,
-0.0930248275399208,
-0.16937604546546936,
-0.117866650223732,
-0.30604276061058044,
-0.03530868515372276,
-0.0355609655380249,
-0.0528147891163826,
-0.02926049381494522,
0.5762631893157959,
-0.2663783133029938,
0.07449094951152802,
-0.2874302566051483,
-0.2082001268863678,
-0.4295231103897095,
-0.10088328272104263,
0.004545547068119049,
-0.05962265282869339,
-0.09537079930305481,
-0.22082705795764923,
-0.13561594486236572,
0.2697882056236267,
-0.22745123505592346,
-0.14196427166461945,
0.12684498727321625,
-0.2542559802532196,
-0.0007774727419018745,
-0.03305472806096077,
0.10001487284898758,
-0.11615099012851715,
0.3154967725276947,
0.016632303595542908,
0.28698280453681946,
-0.3732559382915497,
0.10811797529459,
-0.1803286075592041,
0.21710634231567383,
0.2719831168651581,
0.0013405452482402325,
0.14543338119983673,
-0.44116175174713135,
-0.23803676664829254,
-0.013946308754384518,
-0.08445215970277786,
0.21031159162521362,
-0.004942900966852903,
-0.20481325685977936,
-0.046241022646427155,
0.3996998369693756,
0.05420348420739174,
-0.2666933834552765,
0.2724321484565735,
0.14732803404331207,
-0.2883746027946472,
0.44838619232177734,
0.011259645223617554,
0.6613934636116028,
0.2898107171058655,
-0.2178923785686493,
0.29652997851371765,
-0.21648341417312622,
0.567108690738678,
-0.18582533299922943,
0.13965463638305664,
0.09834583103656769,
-0.14164145290851593,
0.02411883883178234,
0.26291313767433167,
0.36447304487228394,
-0.04198654741048813,
-0.32919690012931824,
0.24835877120494843,
0.21675215661525726,
0.30089035630226135,
0.21273399889469147,
0.11631877720355988,
0.0853671133518219,
-0.3070460855960846,
0.0013402141630649567,
0.18750104308128357,
0.08409202843904495,
0.27029120922088623,
-0.04117569699883461,
0.09877137094736099,
0.028510134667158127,
-0.3716997504234314,
-0.22798886895179749,
0.03163043409585953,
0.4609610438346863,
0.11891809105873108,
0.01270783506333828,
0.06544384360313416,
0.23905551433563232,
-0.32361117005348206,
0.2711412012577057,
0.1031317487359047,
-0.0883096233010292,
0.2994316518306732,
0.31932589411735535,
0.01049517560750246,
-0.17676059901714325,
-0.1510268598794937,
0.024320952594280243,
-0.15881362557411194,
-0.2019999623298645,
0.22722762823104858,
0.17419648170471191,
-0.23866330087184906,
-0.20172880589962006,
0.033909138292074203,
-0.05447171628475189,
0.14230918884277344,
0.5334226489067078,
0.43454355001449585,
0.10620944201946259,
-0.1701265126466751,
0.20466430485248566,
0.126929372549057,
-0.11475132405757904,
0.0031180456280708313,
0.15291021764278412,
-0.19069086015224457,
-0.18325138092041016,
0.5322153568267822,
0.2791718542575836,
-0.13204531371593475,
-0.06292682886123657,
-0.11571274697780609,
0.01629609242081642,
-0.21505886316299438,
-0.1890406608581543,
0.14092497527599335,
-0.3937106430530548,
-0.12774957716464996,
0.1681395024061203,
-0.28275278210639954,
0.24938490986824036,
0.8095275163650513,
0.07201125472784042,
0.20189455151557922,
-0.22826357185840607,
-0.12816625833511353,
-0.0254083052277565,
-0.07955542206764221,
-0.47719642519950867,
0.1812090128660202,
-0.020505765452980995,
-0.05071515217423439,
-0.08789937943220139,
-0.012811316177248955,
-0.3956336975097656,
-0.24205580353736877,
0.19528831541538239,
-0.09695497155189514,
0.4021480083465576,
0.21221643686294556,
0.4604622423648834,
0.18588757514953613,
0.21235516667366028,
0.015105679631233215,
-0.2088434398174286,
-0.1787453293800354,
-0.013656483963131905,
0.10726441442966461,
0.08703909069299698,
0.2987450957298279,
-0.1990329772233963,
-0.182963564991951,
-0.29235193133354187,
0.022287528961896896,
0.3350929617881775,
0.10991951078176498,
-0.19674436748027802,
0.08827021718025208,
-0.45101431012153625,
0.010249175131320953,
0.3422631025314331,
0.18725672364234924,
0.17638683319091797,
0.0917046070098877,
-0.06608221679925919,
0.3762291669845581,
-0.12612779438495636,
-0.026595328003168106,
0.12284565716981888,
0.3449653685092926,
-0.25990837812423706,
0.1292843222618103,
0.008576061576604843,
0.08216619491577148,
-0.19888152182102203,
-0.17354610562324524,
0.01640097051858902,
-0.3018588125705719,
0.006897013634443283,
-0.05663786828517914,
-0.16726350784301758,
0.30348318815231323,
-0.23948132991790771,
0.06966474652290344,
-0.2762695550918579,
-0.16598938405513763,
0.2079390287399292,
0.2772292494773865,
0.25617948174476624,
-0.09345092624425888,
0.7590211629867554,
0.10688691586256027,
0.14143744111061096,
-0.07472974807024002,
0.22079774737358093,
0.16938209533691406,
0.04263456538319588,
0.16868597269058228,
0.275814026594162,
-0.08789417147636414,
0.3604969382286072,
-0.07755021750926971,
0.3008502721786499,
0.03680393472313881,
0.2739916145801544,
0.5524515509605408,
0.05506028234958649,
-0.31329697370529175,
0.10778632014989853,
0.46236613392829895,
0.05116477236151695,
0.058433495461940765,
0.18636423349380493,
-0.22566846013069153,
-0.02091851457953453,
0.18213818967342377,
-0.7633129954338074,
-0.1767711490392685,
0.08755525201559067,
-0.2771150469779968,
-0.19742590188980103,
-0.10568825155496597,
-0.47327953577041626,
-0.0067762937396764755,
0.2994886040687561,
0.05078279227018356,
-0.01612088829278946,
-0.20815585553646088,
0.00819290429353714,
-0.060377806425094604,
-0.27781009674072266,
0.07377645373344421,
0.25696396827697754,
0.0064140744507312775,
0.2032153308391571,
-0.41788995265960693,
-0.13610747456550598,
0.37700480222702026,
0.13934074342250824,
0.13725166022777557,
-0.08849247545003891,
0.5053783059120178,
0.11966408789157867,
0.10259053111076355,
-0.09160061180591583,
-0.009294308722019196,
0.18863511085510254,
0.12328091263771057,
0.10457594692707062,
0.18037049472332,
0.1920611411333084,
-0.18656572699546814,
0.15649476647377014,
-0.03523563966155052,
-0.24298474192619324,
-0.2443149983882904,
0.18434317409992218,
0.10635501146316528,
0.15036237239837646,
-0.08765771985054016,
0.22046926617622375,
0.0323292538523674,
-0.3462274670600891,
-0.06211291626095772,
0.020574815571308136,
-0.127640962600708,
-0.14604659378528595,
0.11986339092254639,
-0.06510604918003082,
-0.12488344311714172,
0.1699475198984146,
-0.1149890199303627,
0.06258704513311386,
-0.37308019399642944,
-0.004313208162784576,
0.3659430742263794,
0.18773038685321808,
0.07066258043050766,
0.054785750806331635,
0.14213617146015167,
0.14274626970291138,
-0.2538003921508789,
0.12222763895988464,
-0.4326280951499939,
0.5907477140426636,
-0.08773459494113922,
-0.182802215218544,
0.14077596366405487,
0.4150146245956421,
-0.11227633059024811,
-0.12778548896312714,
-0.29606902599334717,
-0.2116578370332718,
0.06730365008115768,
0.10888493806123734,
-0.33292514085769653,
-0.1272968351840973,
0.18393906950950623,
0.03788965940475464,
0.4441293179988861,
0.04809124022722244,
0.21306069195270538,
-0.12853814661502838,
-0.07115915417671204,
-0.5014457702636719,
-0.13466623425483704,
-0.02391596883535385,
0.09259101003408432,
-0.1338445246219635,
-0.02983829379081726,
0.04316052049398422,
0.1195140928030014,
0.02203383296728134,
0.3425883650779724,
0.04612986743450165,
-0.0907575711607933,
-0.09505608677864075,
0.4244759976863861,
-0.5147942304611206,
-0.3080165684223175,
-0.106026791036129,
-0.10277212411165237,
0.06682396680116653,
-0.12948061525821686,
-0.04089657962322235,
-0.2425185889005661,
0.3495897054672241,
-0.22609196603298187,
-0.08503811061382294,
-0.08611143380403519,
0.434344083070755,
0.20386970043182373,
0.08677305281162262,
-0.22049090266227722,
0.09851088374853134,
0.2275274693965912,
0.19771936535835266,
-0.2760642170906067,
0.15084731578826904,
-0.04482172802090645,
0.017772745341062546,
-0.2207435965538025,
0.023583587259054184,
-0.1709718108177185,
0.01504305936396122,
0.1533428579568863,
-0.3238043785095215
] |
https://github.com/huggingface/datasets/issues/163 | [Feature request] Add cos-e v1.0 | > @mariamabarham Just wanted to note that default behavior `cos_e = load_dataset("cos_e")` now loads `v1.0`. Not sure if this is intentional (but the flag specification does work as intended).
In the new version of `nlp`, if you try `cos_e = load_dataset("cos_e")` it throws this error:
```
ValueError: Config name is missing.
Please pick one among the available configs: ['v1.0', 'v1.11']
Example of usage:
`load_dataset('cos_e', 'v1.0')`
```
For datasets with at least two configurations, we now force the user to pick one (no default) | I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf). | 83 | [Feature request] Add cos-e v1.0
I noticed the second release of cos-e (v1.11) is included in this repo. I wanted to request inclusion of v1.0, since this is the version on which results are reported on in [the paper](https://www.aclweb.org/anthology/P19-1487/), and v1.11 has noted [annotation](https://github.com/salesforce/cos-e/issues/2) [issues](https://arxiv.org/pdf/2004.14546.pdf).
> @mariamabarham Just wanted to note that default behavior `cos_e = load_dataset("cos_e")` now loads `v1.0`. Not sure if this is intentional (but the flag specification does work as intended).
In the new version of `nlp`, if you try `cos_e = load_dataset("cos_e")` it throws this error:
```
ValueError: Config name is missing.
Please pick one among the available configs: ['v1.0', 'v1.11']
Example of usage:
`load_dataset('cos_e', 'v1.0')`
```
For datasets with at least two configurations, we now force the user to pick one (no default) | [
-0.16037391126155853,
-0.1905597746372223,
-0.04093010723590851,
-0.5251523852348328,
-0.5301496982574463,
-0.20913472771644592,
0.07916980981826782,
0.30271077156066895,
-0.08486784994602203,
0.299315482378006,
0.09133685380220413,
0.5883416533470154,
-0.1273888498544693,
0.3007548153400421,
0.14482657611370087,
0.19229458272457123,
0.04938075318932533,
0.35735592246055603,
0.016091279685497284,
-0.14633303880691528,
-0.2847519516944885,
0.2668963074684143,
-0.15900404751300812,
0.022066358476877213,
0.1762133240699768,
0.1823170781135559,
-0.3217965066432953,
-0.026325665414333344,
-0.06103866547346115,
-0.2656816840171814,
0.43385595083236694,
0.29688435792922974,
0.24196362495422363,
-0.15443021059036255,
-0.00011306988017167896,
-0.24875320494174957,
0.5088641047477722,
-0.06220303475856781,
-0.4297455847263336,
-0.30758827924728394,
-0.33396410942077637,
-0.518495500087738,
0.1690250188112259,
-0.09877884387969971,
0.18584349751472473,
0.15064656734466553,
0.36876288056373596,
-0.03254234418272972,
-0.0012722685933113098,
0.10815970599651337,
0.22739464044570923,
0.28239163756370544,
-0.08409285545349121,
-0.2982408404350281,
0.11302663385868073,
0.3750301003456116,
-0.3086332678794861,
-0.16344043612480164,
-0.04228101670742035,
-0.2713524103164673,
-0.052446700632572174,
0.3673299252986908,
0.20168179273605347,
-0.22526933252811432,
-0.1958562433719635,
-0.047848042100667953,
0.14524710178375244,
0.04428553581237793,
0.07859809696674347,
0.09422263503074646,
0.34997427463531494,
0.046612564474344254,
-0.26323071122169495,
0.04236665368080139,
0.07684116065502167,
-0.5963772535324097,
0.2815065383911133,
-0.06955289095640182,
-0.17123259603977203,
-0.07540741562843323,
0.265972375869751,
-0.27415749430656433,
-0.42526862025260925,
0.38042956590652466,
-0.06080397218465805,
0.26074498891830444,
-0.06658745557069778,
-0.06787668913602829,
0.23503394424915314,
0.08089528977870941,
-0.10468436777591705,
0.02762921340763569,
-0.14414864778518677,
0.2545181214809418,
-0.41611653566360474,
-0.14212238788604736,
0.4012792706489563,
0.04141942784190178,
0.2769642770290375,
0.14983642101287842,
0.27908506989479065,
0.012850144878029823,
-0.05144141614437103,
0.18539756536483765,
0.08551662415266037,
0.31466540694236755,
0.6022413372993469,
0.0287075936794281,
0.2610603868961334,
0.09194577485322952,
0.5128618478775024,
0.10024430602788925,
0.0753757506608963,
0.02059401199221611,
-0.16388960182666779,
-0.12788313627243042,
0.11135821044445038,
-0.3812928795814514,
-0.1226559653878212,
-0.09454679489135742,
-0.09384286403656006,
0.06300080567598343,
0.02480902150273323,
0.19082999229431152,
0.2591687738895416,
0.2565681040287018,
0.3442854881286621,
-0.07276070863008499,
-0.1324227899312973,
-0.38469749689102173,
-0.24910198152065277,
-0.05333347246050835,
-0.39312514662742615,
0.27025628089904785,
0.3587169647216797,
-0.23135316371917725,
0.28058433532714844,
-0.4026279151439667,
0.19323456287384033,
0.01676630973815918,
-0.21883098781108856,
0.31003624200820923,
-0.16564753651618958,
0.07989118993282318,
0.04688231274485588,
0.013723818585276604,
-0.30024245381355286,
0.2614317536354065,
-0.25514549016952515,
0.09527446329593658,
-0.2514302134513855,
-0.5217938423156738,
-0.2898748219013214,
0.2131016105413437,
-0.21021588146686554,
-0.3397212326526642,
-0.16480210423469543,
0.48887547850608826,
-0.22434589266777039,
-0.2618383467197418,
-0.01977597177028656,
0.07405805587768555,
-0.37112361192703247,
-0.1326882541179657,
-0.08441707491874695,
0.1536417007446289,
0.032275158911943436,
-0.23951095342636108,
-0.6589329242706299,
0.023701321333646774,
0.05040479078888893,
-0.10603713989257812,
-0.10561701655387878,
-0.2657807171344757,
-0.14965106546878815,
-0.059897467494010925,
0.7229763269424438,
-0.4373762905597687,
-0.11550042033195496,
0.2689363956451416,
-0.06760762631893158,
-0.20526154339313507,
0.1048460379242897,
-0.13712191581726074,
-0.23001375794410706,
-0.15859819948673248,
-0.17310106754302979,
0.2563074827194214,
-0.05131041258573532,
-0.10487190634012222,
-0.08494409918785095,
-0.3723757565021515,
-0.08402266353368759,
0.2475232034921646,
0.2598855793476105,
0.010238341987133026,
0.26540127396583557,
-0.17162618041038513,
0.20318901538848877,
-0.0694110244512558,
0.14847148954868317,
0.03821396082639694,
0.4409765899181366,
0.04296783357858658,
0.09988922625780106,
0.1025068536400795,
-0.5050915479660034,
0.07856355607509613,
-0.04806385189294815,
0.2747189998626709,
0.32303059101104736,
-0.21497683227062225,
-0.0498177707195282,
-0.05138123407959938,
0.06278397887945175,
-0.242958664894104,
0.12956157326698303,
0.2916696071624756,
-0.0453818254172802,
-0.027404244989156723,
-0.08810260891914368,
0.4771674871444702,
-0.2147001028060913,
-0.17016050219535828,
-0.22500795125961304,
0.0794714018702507,
-0.1317957043647766,
-0.03842912241816521,
0.0011595971882343292,
0.30664271116256714,
-0.005750447511672974,
0.0314609594643116,
-0.08589667081832886,
0.3410400450229645,
-0.170721635222435,
0.2327120304107666,
0.0020121224224567413,
0.051782846450805664,
0.15532881021499634,
-0.17103667557239532,
0.07149931788444519,
-0.03874899446964264,
-0.05914821848273277,
0.1741674244403839,
-0.23587444424629211,
0.40878480672836304,
0.055551592260599136,
-0.004943102598190308,
0.015664152801036835,
-0.025185253471136093,
0.024581311270594597,
-0.2130439132452011,
-0.5066878795623779,
-0.1608453392982483,
0.3907111585140228,
0.09037633240222931,
-0.4192774295806885,
-0.21827377378940582,
-0.4219490885734558,
-0.053912483155727386,
0.2659192383289337,
0.010921310633420944,
0.06860508769750595,
0.34612029790878296,
0.19898223876953125,
-0.2583036720752716,
0.28767603635787964,
-0.03375620394945145,
0.5213517546653748,
0.3559092879295349,
-0.14374244213104248,
0.055378712713718414,
-0.497071772813797,
-0.03433407098054886,
0.19374391436576843,
0.22271722555160522,
0.16498364508152008,
0.034512847661972046,
0.47993749380111694,
0.02471921592950821,
-0.4151760935783386,
-0.4975740611553192,
0.03008299507200718,
-0.066778264939785,
-0.1709928810596466,
-0.07678590714931488,
-0.23566105961799622,
-0.24855297803878784,
-0.13437846302986145,
0.15273742377758026,
-0.0066424161195755005,
-0.282269686460495,
0.25305429100990295,
0.2228183001279831,
-0.09684845805168152,
0.27046480774879456,
-0.08819729089736938,
0.7165156006813049,
-0.1732388734817505,
0.13250194489955902,
-0.21116551756858826,
-0.019733045250177383,
-0.43862247467041016,
0.1435931771993637,
-0.36732134222984314,
-0.12818720936775208,
0.43063753843307495,
0.03370526432991028,
0.2416907399892807,
0.10172414034605026,
-0.6566219925880432,
0.07370659708976746,
-0.16742011904716492,
-0.08497529476881027,
0.07531517744064331,
-0.3813067674636841,
-0.17965354025363922,
-0.09716552495956421,
0.09173286706209183,
-0.34687790274620056,
-0.3567788600921631,
-0.06084062159061432,
-0.17782963812351227,
0.19364377856254578,
-0.38614848256111145,
-0.5043299794197083,
-0.0028921980410814285,
-0.3854024410247803,
-0.06033317744731903,
-0.03287291154265404,
0.26456350088119507,
0.7287460565567017,
-0.02927185222506523,
0.06091072037816048,
-0.018814094364643097,
0.05397900193929672,
-0.32225850224494934,
0.41111987829208374,
0.2417624145746231,
-0.36633071303367615,
-0.32564133405685425,
-0.09408034384250641,
-0.00901089422404766,
0.27595460414886475,
0.1377246379852295,
-0.20072084665298462,
-0.3760529160499573,
0.17288640141487122,
0.09563268721103668,
-0.18954989314079285,
0.16957513988018036,
0.49473267793655396,
0.03568524867296219,
-0.14348937571048737,
-0.1199135035276413,
-0.3978126049041748,
0.2254878580570221,
0.5513763427734375,
0.3134695291519165,
-0.09973718971014023,
0.23797953128814697,
0.12890547513961792,
0.05465463176369667,
0.18605999648571014,
-0.03154749795794487,
0.21331404149532318,
0.07510698586702347,
0.30275553464889526,
-0.06819289177656174,
-0.04883962124586105,
0.1862042099237442,
0.11914383620023727,
0.32899224758148193,
0.4975132346153259,
0.10180947184562683,
-0.49265363812446594,
-0.3609597980976105,
-0.24205844104290009,
0.12460757046937943,
0.003417808562517166,
-0.06890664994716644,
0.060732077807188034,
0.4087863266468048,
0.02603987231850624,
-0.26158949732780457,
-0.413523405790329,
-0.17632880806922913,
-0.10904942452907562,
0.438190221786499,
0.032993145287036896,
0.01286526769399643,
-0.08266288042068481,
0.026466118171811104,
-0.42439061403274536,
0.2321767956018448,
0.06501637399196625,
0.2848566770553589,
-0.05420083925127983,
-0.13267439603805542,
0.11208420991897583,
0.08531028777360916,
0.2600693106651306,
-0.23703260719776154,
-0.12139749526977539,
-0.011055062524974346,
0.12416991591453552,
-0.19625326991081238,
-0.06323409080505371,
-0.16072770953178406,
-0.17356686294078827,
0.07299992442131042,
0.016527269035577774,
0.012415766716003418,
-0.18408209085464478,
0.5894104242324829,
-0.1919885128736496,
0.02772824838757515,
-0.3377680480480194,
-0.15445546805858612,
-0.2920680642127991,
-0.09544730186462402,
-0.088752381503582,
-0.1869194507598877,
0.1422540843486786,
-0.20191369950771332,
-0.005332905799150467,
0.22868721187114716,
-0.0948631688952446,
-0.005437694489955902,
0.22884415090084076,
-0.24832817912101746,
0.13451328873634338,
-0.0950876772403717,
0.0174885131418705,
0.09789498895406723,
0.039771780371665955,
-0.045927368104457855,
0.23973794281482697,
-0.09043021500110626,
0.1836397647857666,
0.04171430692076683,
0.34280651807785034,
0.29112493991851807,
0.07612721621990204,
0.15024366974830627,
-0.38553011417388916,
-0.25055748224258423,
-0.04244660586118698,
-0.08079680800437927,
0.24254879355430603,
-0.06657206267118454,
-0.33067649602890015,
-0.09095704555511475,
0.4912468492984772,
0.06609167158603668,
-0.3306334912776947,
0.32408303022384644,
0.08614321053028107,
-0.3378436267375946,
0.4092395305633545,
-0.128919780254364,
0.7491973638534546,
0.39504677057266235,
0.03774014860391617,
0.32539910078048706,
-0.03980815410614014,
0.8740342855453491,
-0.03195716440677643,
0.276810884475708,
0.07144159078598022,
0.05260826647281647,
0.03373285382986069,
0.2498621940612793,
0.3760501444339752,
-0.015048772096633911,
-0.3114895820617676,
0.37499985098838806,
0.5791000127792358,
0.0683809369802475,
0.19329120218753815,
0.35138118267059326,
0.1492745578289032,
-0.4552721381187439,
-0.16807512938976288,
0.12077014148235321,
-0.10806265473365784,
0.38529083132743835,
-0.01413146685808897,
-0.006577968597412109,
0.01694067195057869,
-0.3202211260795593,
-0.21057552099227905,
0.04029100388288498,
0.39293041825294495,
0.05890291929244995,
0.07368309795856476,
0.028256915509700775,
0.4237452745437622,
-0.23016300797462463,
0.18266725540161133,
0.1609453707933426,
-0.2040279060602188,
0.16447216272354126,
0.13954228162765503,
-0.01857990026473999,
-0.07313825190067291,
-0.14397455751895905,
0.08395542949438095,
-0.17628920078277588,
-0.2379300743341446,
0.10621485114097595,
0.19553440809249878,
-0.20474018156528473,
-0.11868377774953842,
-0.0075542256236076355,
-0.038433343172073364,
0.245245561003685,
0.29218775033950806,
0.5004429817199707,
0.10781100392341614,
-0.23766829073429108,
0.17232924699783325,
0.09804810583591461,
-0.10802941769361496,
0.02397996559739113,
0.20026244223117828,
-0.15120664238929749,
-0.11280268430709839,
0.5301057696342468,
0.21330490708351135,
-0.18939775228500366,
0.10306406766176224,
-0.14518506824970245,
0.07328271120786667,
-0.19599440693855286,
-0.15487869083881378,
-0.03298511356115341,
-0.5144609212875366,
-0.19930748641490936,
0.1846107691526413,
-0.2377409040927887,
0.3092068135738373,
0.7213867902755737,
0.01655513234436512,
0.24946650862693787,
-0.1088578999042511,
-0.18847283720970154,
-0.05346190929412842,
0.02773410826921463,
-0.5827196836471558,
0.16098614037036896,
0.13868549466133118,
0.05973051115870476,
-0.03966548293828964,
0.07866834104061127,
-0.36422815918922424,
-0.2929225564002991,
0.12223701924085617,
0.04758665710687637,
0.5287963151931763,
0.1722342073917389,
0.22847604751586914,
0.08470907807350159,
0.13575135171413422,
-0.1003018170595169,
-0.18807870149612427,
-0.15801215171813965,
-0.13643504679203033,
0.11905047297477722,
0.17177554965019226,
0.17103181779384613,
-0.17962628602981567,
-0.19826346635818481,
-0.20716488361358643,
-0.024118181318044662,
0.1777467578649521,
-0.0709180161356926,
-0.19365088641643524,
0.3347185254096985,
-0.46812567114830017,
-0.045132651925086975,
0.3891853094100952,
0.3572053015232086,
0.16981005668640137,
0.04913054406642914,
-0.02882903628051281,
0.5353574752807617,
-0.036852143704891205,
-0.05114138126373291,
-0.08615133166313171,
0.24315854907035828,
-0.32708412408828735,
0.24757322669029236,
-0.09059052914381027,
-0.007488466799259186,
-0.22181108593940735,
-0.22819679975509644,
-0.030339930206537247,
-0.3078686594963074,
0.035737134516239166,
-0.04483149200677872,
0.06395252794027328,
0.23791752755641937,
-0.3148873746395111,
0.05522292107343674,
-0.035948533564805984,
-0.02913190796971321,
0.18411898612976074,
0.21877333521842957,
0.321713924407959,
-0.11545760929584503,
0.6415478587150574,
-0.04418723285198212,
0.014910969883203506,
-0.18163026869297028,
0.2836940884590149,
0.19051030278205872,
0.168939471244812,
0.08880265802145004,
0.18636415898799896,
0.008465366438031197,
0.333029180765152,
-0.06245899945497513,
0.22023767232894897,
-0.048584818840026855,
0.3439480662345886,
0.5547138452529907,
0.07117709517478943,
-0.35833030939102173,
-0.0543023981153965,
0.38938528299331665,
0.14579077064990997,
0.12391214072704315,
0.13414651155471802,
0.007062092423439026,
-0.07100224494934082,
0.18138790130615234,
-0.6420041918754578,
0.05338055640459061,
0.031960733234882355,
-0.35199853777885437,
-0.3825598955154419,
-0.09260974079370499,
-0.5104484558105469,
-0.062152255326509476,
0.14173433184623718,
-0.007492981851100922,
0.0329425185918808,
-0.07868874073028564,
0.023906812071800232,
-0.20594541728496552,
-0.05458962172269821,
0.22706550359725952,
0.1682695746421814,
-0.023408660665154457,
0.3689236640930176,
-0.5310978293418884,
-0.21128693222999573,
0.1906963288784027,
0.24770760536193848,
0.20929521322250366,
-0.03900149464607239,
0.4058581292629242,
0.11202459782361984,
0.14556202292442322,
-0.070763498544693,
-0.05981936678290367,
0.16103318333625793,
0.3544895052909851,
0.04199705272912979,
0.261322021484375,
0.09808698296546936,
-0.09979218989610672,
0.14007270336151123,
0.04343094676733017,
-0.29908275604248047,
-0.21188074350357056,
0.3249717056751251,
0.1753530353307724,
0.18041372299194336,
-0.02329987660050392,
0.375754714012146,
-0.13017168641090393,
-0.23831558227539062,
0.08112317323684692,
0.10263880342245102,
-0.10894875228404999,
-0.24176271259784698,
0.09944389015436172,
-0.07116594910621643,
0.007066130638122559,
0.18419763445854187,
-0.03055773675441742,
0.021134626120328903,
-0.41406774520874023,
-0.12865155935287476,
0.2505955696105957,
0.11373455822467804,
-0.12676304578781128,
0.09774207323789597,
0.1597735583782196,
0.04668580740690231,
-0.28360629081726074,
-0.12935732305049896,
-0.0501638762652874,
0.5626107454299927,
-0.019448615610599518,
-0.2112591415643692,
0.15099968016147614,
0.3584880828857422,
-0.02639116160571575,
-0.12816977500915527,
-0.18867045640945435,
-0.28754135966300964,
0.043898917734622955,
-0.008159462362527847,
-0.3241661787033081,
0.011525779962539673,
0.04369834437966347,
0.23319722712039948,
0.3404276669025421,
0.10100193321704865,
0.2775700092315674,
-0.15534351766109467,
-0.08501657843589783,
-0.5489779710769653,
-0.18481047451496124,
-0.05637962371110916,
0.06647180765867233,
-0.0956384539604187,
0.052344925701618195,
-0.03479737415909767,
0.3438432514667511,
-0.01012194063514471,
0.31706640124320984,
-0.02081414684653282,
-0.09819796681404114,
-0.032694943249225616,
0.4011123776435852,
-0.47488024830818176,
-0.1552659571170807,
-0.021511338651180267,
-0.017494864761829376,
0.0346456840634346,
-0.06058492511510849,
-0.0785987451672554,
-0.23899737000465393,
0.35251232981681824,
-0.1608169674873352,
-0.04476703703403473,
-0.020304527133703232,
0.4243362843990326,
0.25574547052383423,
0.07693658024072647,
-0.259465754032135,
-0.01638060063123703,
0.21026991307735443,
0.1324426829814911,
-0.1359894573688507,
0.2562759220600128,
-0.15202341973781586,
-0.025489356368780136,
-0.2026941031217575,
-0.10972937941551208,
-0.11596860736608505,
-0.15834075212478638,
0.11542041599750519,
-0.34984612464904785
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | usually you can replace `download` in your dataset script with `download_and_prepare()` - could you share the code for your dataset here? :-) | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 22 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
usually you can replace `download` in your dataset script with `download_and_prepare()` - could you share the code for your dataset here? :-) | [
-0.29844120144844055,
0.2715889811515808,
-0.02540157362818718,
-0.1736123263835907,
0.11133774369955063,
-0.032490555197000504,
0.3496929109096527,
0.3046949505805969,
0.09639129042625427,
0.13277660310268402,
0.1502353847026825,
0.18139126896858215,
-0.29633480310440063,
0.05446108430624008,
0.16967593133449554,
0.030123520642518997,
-0.0018446296453475952,
0.23788097500801086,
-0.10852649807929993,
0.26449400186538696,
-0.1570073366165161,
0.02594122849404812,
-0.08346939086914062,
0.034720588475465775,
-0.007924170233309269,
0.14469146728515625,
-0.15397818386554718,
0.01550845056772232,
-0.37364181876182556,
-0.9120110869407654,
0.4226647913455963,
0.08653847128152847,
0.18527039885520935,
0.4016510844230652,
-0.00012305592827033252,
-0.07805018872022629,
0.5848661065101624,
-0.08126456290483475,
-0.6614242792129517,
-0.24752645194530487,
0.17996779084205627,
-0.44016483426094055,
0.33093389868736267,
-0.030891790986061096,
0.05642986297607422,
-0.1428367644548416,
0.22567245364189148,
0.036392658948898315,
0.06255191564559937,
0.3939168453216553,
0.14157582819461823,
0.278430312871933,
0.1039668470621109,
-0.22894807159900665,
-0.11398161202669144,
0.06613485515117645,
-0.13955555856227875,
0.5098291039466858,
0.33754754066467285,
0.08086451143026352,
-0.02614521235227585,
-0.1172662228345871,
0.07583940029144287,
0.48263734579086304,
0.1798248291015625,
-0.02010524645447731,
0.45073410868644714,
-0.026417814195156097,
-0.19099846482276917,
0.000986546277999878,
0.8557760715484619,
-0.557236909866333,
-0.28589072823524475,
0.020645715296268463,
0.09727933257818222,
-0.1694420576095581,
0.2176305055618286,
-0.20579713582992554,
-0.3246438503265381,
0.017004769295454025,
-0.19486898183822632,
-0.33706381916999817,
-0.0902523398399353,
0.31063973903656006,
-0.21952788531780243,
0.18331260979175568,
0.06803271919488907,
0.21227160096168518,
0.055997855961322784,
-0.09097349643707275,
0.23839086294174194,
-0.02267947793006897,
-0.0061225928366184235,
0.25748273730278015,
-0.08425585925579071,
-0.24596454203128815,
-0.31582510471343994,
-0.20292413234710693,
0.1599837839603424,
0.05829679220914841,
-0.4827140271663666,
-0.1835443377494812,
0.04289053753018379,
0.21460548043251038,
0.11195938289165497,
0.31773316860198975,
0.34393370151519775,
0.284592866897583,
0.19506846368312836,
0.17445611953735352,
0.2424221932888031,
0.15372461080551147,
-0.07111602276563644,
-0.39698195457458496,
0.106655552983284,
0.08801091462373734,
0.24009372293949127,
-0.28065356612205505,
-0.1707746535539627,
-0.26196417212486267,
-0.3381372094154358,
0.009782221168279648,
-0.07732273638248444,
0.2922813296318054,
-0.09014897793531418,
-0.23386314511299133,
0.049078308045864105,
0.44676899909973145,
-0.19828662276268005,
-0.1562919318675995,
-0.027289625257253647,
0.10530099272727966,
-0.21463525295257568,
0.049913570284843445,
0.3252117931842804,
0.014612821862101555,
0.4042748212814331,
-0.24093686044216156,
-0.1593516618013382,
-0.046743668615818024,
0.10865804553031921,
0.05923198536038399,
-0.2635221779346466,
0.30100688338279724,
-0.07218009978532791,
0.0834098532795906,
0.048662979155778885,
-0.27629342675209045,
-0.21490874886512756,
0.2309892475605011,
0.06791456043720245,
-0.495361328125,
-0.023342696949839592,
0.11333990842103958,
-0.5093955397605896,
-0.059858813881874084,
-0.06913221627473831,
-0.16433435678482056,
0.10568083077669144,
-0.39293548464775085,
-0.03081464022397995,
-0.43483680486679077,
-0.37226438522338867,
-0.11169140040874481,
-0.03351198881864548,
0.29697728157043457,
-0.3369503319263458,
-0.2700841724872589,
-0.4456767737865448,
-0.38237226009368896,
0.21316760778427124,
-0.2579703629016876,
-0.07269936800003052,
0.20810380578041077,
-0.41918885707855225,
-0.02921367436647415,
0.5602774620056152,
-0.5683714151382446,
-0.3613015115261078,
0.4470440149307251,
-0.41898679733276367,
-0.25901299715042114,
0.18650424480438232,
-0.0008598624845035374,
0.06650566309690475,
-0.3295419216156006,
-0.1430531144142151,
0.06461173295974731,
0.042373839765787125,
-0.13622698187828064,
-0.11024289578199387,
-0.2676573097705841,
0.19914427399635315,
0.2632276713848114,
-0.09678244590759277,
0.13125520944595337,
0.14763687551021576,
0.10275794565677643,
0.32669585943222046,
0.14259028434753418,
0.1718102991580963,
-0.08835853636264801,
0.23017264902591705,
-0.2256695181131363,
-0.1406850665807724,
-0.10932890325784683,
-0.6099806427955627,
0.23831871151924133,
-0.06623587012290955,
0.20779454708099365,
-0.14170894026756287,
0.023358382284641266,
-0.6258837580680847,
0.01587006263434887,
-0.059171970933675766,
-0.22863852977752686,
0.006851989775896072,
0.1909550577402115,
0.11202706396579742,
0.018214717507362366,
0.03710780665278435,
0.0626564770936966,
-0.2197256088256836,
0.1759641319513321,
0.010265050455927849,
-0.0012474823743104935,
-0.1033817008137703,
0.03828231245279312,
0.23613706231117249,
0.22019842267036438,
0.08650315552949905,
-0.3108551800251007,
-0.0424867607653141,
0.28622928261756897,
0.2748509347438812,
0.2039646953344345,
0.1929638385772705,
-0.07467357814311981,
0.13896968960762024,
0.153835266828537,
0.17406843602657318,
0.21679812669754028,
0.0869944840669632,
-0.2102239429950714,
0.08055438101291656,
0.11069171875715256,
0.19249221682548523,
-0.02169358730316162,
-0.17491629719734192,
0.026053832843899727,
0.4049431383609772,
0.12913748621940613,
-0.02623719535768032,
-0.38228338956832886,
0.100460484623909,
0.29537445306777954,
0.6366948485374451,
-0.047104500234127045,
0.36636239290237427,
-0.10841915756464005,
-0.19691750407218933,
-0.34861764311790466,
0.008201133459806442,
0.1602071225643158,
-0.15804868936538696,
-0.09225586801767349,
-0.005740595981478691,
0.2688911557197571,
0.8805612921714783,
-0.02649056911468506,
0.17164528369903564,
0.14539217948913574,
-0.11143910884857178,
-0.2071063071489334,
0.18835212290287018,
0.07700619101524353,
0.0482562780380249,
0.14204102754592896,
-0.014179175719618797,
-0.38311082124710083,
-0.08877219259738922,
-0.053082115948200226,
0.45894408226013184,
0.4843933582305908,
-0.3677518665790558,
-0.19629822671413422,
-0.24734243750572205,
-0.3671186566352844,
-0.41309159994125366,
-0.32595205307006836,
-0.15261602401733398,
-0.3070302903652191,
-0.12076395750045776,
0.276625394821167,
0.13867108523845673,
0.22709307074546814,
-0.2515861988067627,
0.18580688536167145,
-0.2386370152235031,
-0.31146034598350525,
0.09593987464904785,
-0.17135804891586304,
-0.34025344252586365,
0.030635088682174683,
0.2242274135351181,
0.031321022659540176,
0.41515225172042847,
-0.14686699211597443,
-0.2182319313287735,
-0.25129908323287964,
-0.24454772472381592,
0.12566012144088745,
0.08897501230239868,
0.5211694836616516,
0.45991751551628113,
-0.027609139680862427,
0.45716768503189087,
0.11719471216201782,
0.03460448607802391,
-0.2661333382129669,
-0.46694308519363403,
-0.1576690822839737,
-0.01980411261320114,
0.08315401524305344,
-0.03829817846417427,
-0.4752780497074127,
-0.5595124959945679,
-0.07798320055007935,
0.017075933516025543,
0.10753892362117767,
0.02640506625175476,
0.044131919741630554,
-0.09966827183961868,
0.2051914483308792,
0.02571728453040123,
-0.11663936078548431,
-0.14416952431201935,
0.0730145275592804,
0.020061299204826355,
-0.1757686883211136,
-0.17963053286075592,
0.11319698393344879,
-0.06287625432014465,
0.08196168392896652,
-0.15483397245407104,
-0.4178168773651123,
-0.3486687242984772,
0.07465767115354538,
0.18385706841945648,
0.28053760528564453,
-0.2723371088504791,
0.2895950376987457,
0.24983292818069458,
0.14815521240234375,
-0.12449968606233597,
-0.3925282061100006,
0.1562221199274063,
0.019437197595834732,
0.25050416588783264,
0.14687776565551758,
0.48256438970565796,
-0.19213886559009552,
0.750655472278595,
0.11803838610649109,
-0.16311019659042358,
0.02059563621878624,
-0.2556125521659851,
0.04147198796272278,
-0.053950242698192596,
-0.12413864582777023,
0.31781071424484253,
-0.13975435495376587,
-0.24665479362010956,
0.195745587348938,
-0.22311368584632874,
-0.05246236175298691,
-0.09552216529846191,
0.22133150696754456,
-0.06543809175491333,
-0.025436192750930786,
-0.053477056324481964,
-0.20936018228530884,
0.05761290341615677,
0.037889156490564346,
-0.07096286118030548,
-0.194407656788826,
-0.21401989459991455,
0.004863161593675613,
0.3135368824005127,
0.004929304122924805,
0.1602725237607956,
-0.300514817237854,
0.01857445202767849,
-0.44620150327682495,
0.30397462844848633,
0.2712736427783966,
0.5984058380126953,
0.08295075595378876,
0.07675129175186157,
0.12854966521263123,
0.10277162492275238,
0.21404898166656494,
-0.028820769861340523,
0.12243359535932541,
0.2516896724700928,
-0.13396108150482178,
-0.08915548026561737,
-0.24068519473075867,
-0.06588228046894073,
0.212519109249115,
-0.029730867594480515,
0.09589413553476334,
-0.3500882387161255,
-0.08926252275705338,
0.26529330015182495,
0.14095553755760193,
-0.08590082079172134,
-0.3551112711429596,
-0.12330791354179382,
-0.0726567730307579,
-0.15032236278057098,
-0.2127329707145691,
-0.17580492794513702,
0.10044097900390625,
-0.12927871942520142,
0.28205567598342896,
0.0149540388956666,
-0.09018874168395996,
-0.08661633729934692,
0.11567696928977966,
0.14001023769378662,
-0.1844521313905716,
0.3376268446445465,
0.17730818688869476,
0.04688061773777008,
0.4023391008377075,
0.3133348226547241,
-0.10161547362804413,
-0.2746429443359375,
0.026888955384492874,
-0.006902131251990795,
0.3866167962551117,
0.12779274582862854,
0.1136166974902153,
0.0418584905564785,
-0.2697530686855316,
-0.14895150065422058,
-0.298460453748703,
0.1984386295080185,
0.38250574469566345,
-0.09436509013175964,
-0.05138221010565758,
-0.3670404255390167,
0.6012394428253174,
0.2057901918888092,
-0.15702910721302032,
0.4772726893424988,
-0.25194334983825684,
-0.2803328335285187,
-0.055179085582494736,
0.07219109684228897,
0.8358827233314514,
0.12051726132631302,
0.16542378067970276,
0.37753602862358093,
-0.26247894763946533,
0.3626871705055237,
0.0903792679309845,
0.16148532927036285,
-0.5544987916946411,
-0.08480050414800644,
0.024787774309515953,
-0.23059780895709991,
0.24379867315292358,
-0.1052333265542984,
-0.23620760440826416,
0.37085607647895813,
0.04794023931026459,
0.2831416130065918,
0.2545764744281769,
0.3559746742248535,
-0.11178473383188248,
-0.0445249006152153,
-0.10924947261810303,
0.10165834426879883,
-0.16587114334106445,
0.40507522225379944,
-0.2347889542579651,
0.08953969180583954,
-0.0864686518907547,
-0.012371841818094254,
-0.2658649981021881,
-0.11775972694158554,
-0.14358939230442047,
0.06133344769477844,
0.07406353950500488,
-0.1460016369819641,
0.10794614255428314,
0.19950461387634277,
0.1334606111049652,
-0.16214729845523834,
-0.16512370109558105,
0.15120500326156616,
-0.15446165204048157,
0.10339847207069397,
0.33099159598350525,
0.05736219137907028,
0.23977355659008026,
-0.3374669849872589,
-0.1727195680141449,
0.13349249958992004,
-0.23813071846961975,
-0.1332811564207077,
-0.09552429616451263,
-0.1865772157907486,
0.10564965009689331,
-0.3507993221282959,
-0.32004013657569885,
-0.14020805060863495,
0.0729285180568695,
-0.1441505253314972,
0.0400049202144146,
0.27288639545440674,
-0.3790874183177948,
-0.006065584719181061,
-0.12708011269569397,
-0.30062317848205566,
0.01657910645008087,
0.4735439121723175,
-0.061930589377880096,
-0.1693362593650818,
0.7641564607620239,
-0.17778785526752472,
0.06867421418428421,
-0.1367506980895996,
0.06282451003789902,
0.0116067910566926,
-0.13863560557365417,
0.0257415808737278,
-0.04889092221856117,
-0.18072542548179626,
0.10184190422296524,
0.5352264642715454,
0.33291196823120117,
0.00482177734375,
0.00259973481297493,
-0.4617112874984741,
-0.44225797057151794,
-0.09019428491592407,
-0.1543557196855545,
0.1846054494380951,
-0.07652467489242554,
0.13444074988365173,
0.2172488421201706,
0.10431493073701859,
-0.20098242163658142,
-0.17669543623924255,
0.0075926464051008224,
0.24287089705467224,
-0.1265757530927658,
0.0439223013818264,
-0.02672361396253109,
0.0873129814863205,
0.031429849565029144,
-0.027036983519792557,
-0.3348514139652252,
-0.07218397408723831,
-0.06499525904655457,
0.2020931839942932,
0.09678614139556885,
-0.028630653396248817,
0.07220377027988434,
-0.15105386078357697,
-0.02545313909649849,
0.1781972348690033,
-0.026853755116462708,
0.08564923703670502,
-0.09723049402236938,
0.15172505378723145,
0.32388049364089966,
-0.07167687267065048,
-0.05003277212381363,
0.21732322871685028,
0.05624870955944061,
0.1620158553123474,
-0.06300629675388336,
0.2864287495613098,
-0.13696002960205078,
0.0546017587184906,
0.20251110196113586,
0.10919035971164703,
0.00827055424451828,
0.25383976101875305,
0.11799740791320801,
-0.1682087481021881,
0.14139583706855774,
-0.04990189149975777,
0.355796217918396,
0.7263289093971252,
-0.2195245325565338,
-0.12481633573770523,
0.4329032003879547,
0.05636553466320038,
-0.25470447540283203,
-0.04399612173438072,
0.30986154079437256,
0.13776184618473053,
0.0462355799973011,
0.21163588762283325,
0.0015202611684799194,
-0.03864777460694313,
0.16678792238235474,
0.13611534237861633,
0.1286683976650238,
-0.2262921780347824,
-0.059038933366537094,
0.4483218193054199,
-0.2203175276517868,
0.16248925030231476,
0.3900028169155121,
0.06479001045227051,
0.21330344676971436,
0.2186937928199768,
0.03703268989920616,
0.6142652630805969,
0.05644655600190163,
0.01788436621427536,
0.08402562141418457,
-0.04976402968168259,
-0.0006030946969985962,
0.27663666009902954,
-0.030039355158805847,
-0.08608447760343552,
0.32754379510879517,
0.554908037185669,
-0.35028696060180664,
-0.15907345712184906,
-0.26408180594444275,
-0.08660198748111725,
0.031998004764318466,
-0.1442386656999588,
-0.285094678401947,
0.08155801147222519,
-0.21613916754722595,
-0.13049781322479248,
-0.118877112865448,
-0.309390127658844,
0.16270625591278076,
0.017042867839336395,
-0.3983369469642639,
-0.24440379440784454,
-0.2909781038761139,
0.1936606466770172,
-0.10940318554639816,
-0.269906222820282,
0.22087472677230835,
-0.013040043413639069,
0.0328560397028923,
0.29115331172943115,
0.32487064599990845,
0.46994632482528687,
0.1625407487154007,
-0.31814834475517273,
-0.2325119972229004,
-0.1214059591293335,
0.09721105545759201,
0.0350799523293972,
0.3806981146335602,
-0.04988767206668854,
-0.10703162848949432,
0.46314841508865356,
0.0726584866642952,
0.03713392838835716,
0.21864308416843414,
0.43211278319358826,
-0.4861971139907837,
-0.17150580883026123,
0.7934107780456543,
-0.07552888989448547,
-0.14116674661636353,
-0.12957748770713806,
0.25525903701782227,
-0.26042264699935913,
0.1343466192483902,
0.09955894947052002,
-0.07344657927751541,
0.1301887035369873,
0.025473061949014664,
0.03947754204273224,
-0.1064056009054184,
0.3546757698059082,
0.31101417541503906,
-0.04381667822599411,
-0.3694727420806885,
-0.2513991594314575,
-0.7986485362052917,
0.22746261954307556,
-0.11356881260871887,
-0.3236978054046631,
-0.06485424935817719,
-0.2603072226047516,
0.1893695592880249,
0.04811112582683563,
-0.14149154722690582,
0.19518303871154785,
0.054870352149009705,
0.13517674803733826,
-0.1899448037147522,
-0.31790873408317566,
-0.2887229323387146,
-0.023948533460497856,
-0.10388312488794327,
-0.38692671060562134,
0.11374451965093613,
-0.33049675822257996,
-0.07958605885505676,
0.11841166019439697,
-0.00978144258260727,
0.4779796600341797,
-0.005791578441858292,
0.3654896914958954,
-0.11248210072517395,
0.7752768993377686,
0.18795090913772583,
0.06328277289867401,
-0.1649438440799713,
0.12217646837234497,
-0.1206473559141159,
0.13483703136444092,
-0.0703357458114624,
0.10441069304943085,
-0.11896272748708725,
0.5212554335594177,
-0.44372111558914185,
0.4605461657047272,
-0.028103414922952652,
0.07408122718334198,
-0.3021467626094818,
0.045647986233234406,
-0.25546106696128845,
0.12183534353971481,
0.3444596230983734,
0.14114543795585632,
-0.09161031246185303,
0.3550700843334198,
-0.21494290232658386,
-0.19039209187030792,
0.3962547779083252,
-0.10348934680223465,
-0.0939866304397583,
0.021515648812055588,
0.26462745666503906,
-0.05172332376241684,
-0.14009112119674683,
-0.4393866956233978,
0.19632798433303833,
0.2907601296901703,
-0.09371230006217957,
0.11838948726654053,
0.2602345049381256,
0.2837517559528351,
0.13402226567268372,
0.01832754909992218,
0.9827132225036621,
-0.05974341928958893,
0.17604415118694305,
-0.10538431257009506,
-0.2278595268726349
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | I have an initial version here: https://github.com/EntilZha/nlp/tree/master/datasets/qanta Thats pretty close to what I'll do as a PR, but still want to do some more sanity checks/tests (just got tests passing).
I figured out how to get all tests passing by adding a download command and some finagling with the data zip https://github.com/EntilZha/nlp/blob/master/tests/utils.py#L127
| Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 52 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
I have an initial version here: https://github.com/EntilZha/nlp/tree/master/datasets/qanta Thats pretty close to what I'll do as a PR, but still want to do some more sanity checks/tests (just got tests passing).
I figured out how to get all tests passing by adding a download command and some finagling with the data zip https://github.com/EntilZha/nlp/blob/master/tests/utils.py#L127
| [
-0.19621720910072327,
0.4000372290611267,
-0.031468600034713745,
-0.16441306471824646,
0.04428334906697273,
-0.13329291343688965,
0.27948498725891113,
0.37617409229278564,
0.009489316493272781,
0.08292682468891144,
0.2064318209886551,
0.15806886553764343,
-0.300568163394928,
0.06804143637418747,
0.13692401349544525,
0.001200944185256958,
-0.056462906301021576,
0.16989606618881226,
-0.09795263409614563,
0.21250595152378082,
-0.12722066044807434,
0.07482471317052841,
0.02045775204896927,
0.10806221514940262,
-0.027999823912978172,
0.08875592052936554,
-0.21589478850364685,
0.03439011424779892,
-0.38094663619995117,
-0.785807728767395,
0.38182637095451355,
0.07057259231805801,
0.18520070612430573,
0.3587058484554291,
-0.00012268955470062792,
-0.08625639975070953,
0.5880786776542664,
-0.056077003479003906,
-0.7038208842277527,
-0.2316201776266098,
0.24540674686431885,
-0.4804558753967285,
0.3018532991409302,
-0.021508552134037018,
0.1885167360305786,
-0.13163866102695465,
0.244207963347435,
0.10435053706169128,
0.16175124049186707,
0.32244858145713806,
0.11873665452003479,
0.2776326537132263,
0.05146857723593712,
-0.17972375452518463,
-0.10094422847032547,
0.08600423485040665,
-0.089267797768116,
0.5028809905052185,
0.36486244201660156,
0.031120793893933296,
-0.11236346513032913,
-0.13111886382102966,
0.09226366877555847,
0.49313563108444214,
0.1250217854976654,
-0.022293921560049057,
0.5011737942695618,
0.019112227484583855,
-0.21289393305778503,
0.041048698127269745,
0.7716661095619202,
-0.5064082145690918,
-0.37548553943634033,
-0.07860944420099258,
0.0564955398440361,
-0.13751456141471863,
0.2607557475566864,
-0.1600874811410904,
-0.3946448266506195,
0.019819922745227814,
-0.1663755178451538,
-0.28037229180336,
-0.06712237000465393,
0.29351305961608887,
-0.2830924987792969,
0.2682918310165405,
0.07774843275547028,
0.17557892203330994,
0.0895024761557579,
-0.1008504182100296,
0.25734415650367737,
-0.061836645007133484,
0.024405064061284065,
0.23488165438175201,
-0.030216123908758163,
-0.2238750010728836,
-0.26101967692375183,
-0.22214099764823914,
0.19221365451812744,
0.08718404173851013,
-0.4626269042491913,
-0.1906760036945343,
-0.031207039952278137,
0.14959892630577087,
0.1416134089231491,
0.4171294867992401,
0.33842408657073975,
0.2389010190963745,
0.24328817427158356,
0.16279183328151703,
0.2434389591217041,
0.2634248733520508,
-0.059813324362039566,
-0.3704584240913391,
-0.032496556639671326,
0.09223347902297974,
0.14825278520584106,
-0.32870444655418396,
-0.15333986282348633,
-0.2270713895559311,
-0.38531753420829773,
-0.046314116567373276,
-0.05492560938000679,
0.23764824867248535,
-0.10888989269733429,
-0.14659425616264343,
0.04901201277971268,
0.41204380989074707,
-0.20630092918872833,
-0.15113496780395508,
-0.02948884107172489,
0.0445263497531414,
-0.19153976440429688,
-0.012614157050848007,
0.30864521861076355,
0.055757902562618256,
0.37803590297698975,
-0.36712178587913513,
-0.1176607757806778,
-0.03431224077939987,
0.11314693093299866,
0.1852354258298874,
-0.26896554231643677,
0.2899591028690338,
-0.15554548799991608,
0.05203224718570709,
0.07850468158721924,
-0.2927016317844391,
-0.22106757760047913,
0.16356539726257324,
0.12039398401975632,
-0.45691055059432983,
0.03789440914988518,
0.0930616483092308,
-0.6060149073600769,
-0.0646645650267601,
0.012726657092571259,
-0.11572961509227753,
0.09138727188110352,
-0.3326219618320465,
0.026575684547424316,
-0.39136946201324463,
-0.2052660435438156,
-0.06727050244808197,
-0.0997258797287941,
0.2391044795513153,
-0.2667432725429535,
-0.33723169565200806,
-0.44814231991767883,
-0.32592347264289856,
0.12920187413692474,
-0.22480536997318268,
-0.07712345570325851,
0.21498161554336548,
-0.37946203351020813,
-0.00851573795080185,
0.5497831702232361,
-0.521664023399353,
-0.3586077094078064,
0.4454956650733948,
-0.42921698093414307,
-0.2467309534549713,
0.234197199344635,
-0.048981454223394394,
-0.002735354006290436,
-0.36214715242385864,
-0.08949658274650574,
0.08227436989545822,
0.04962074011564255,
-0.17818878591060638,
-0.18848390877246857,
-0.34391722083091736,
0.11360957473516464,
0.22009776532649994,
-0.03988174721598625,
0.08876357972621918,
0.09676428884267807,
0.05409690737724304,
0.35139429569244385,
0.11439789831638336,
0.1550447791814804,
-0.14401833713054657,
0.17716747522354126,
-0.23787619173526764,
-0.17119497060775757,
-0.0517728291451931,
-0.5992653965950012,
0.2523059844970703,
-0.11843126267194748,
0.21302318572998047,
-0.046452537178993225,
-0.011181812733411789,
-0.5071437358856201,
0.0033057983964681625,
0.019839856773614883,
-0.2721046805381775,
0.002070598304271698,
0.2044222056865692,
0.12961789965629578,
-0.04795825853943825,
-0.010605555027723312,
0.03222370520234108,
-0.21072933077812195,
0.19253289699554443,
-0.009809723123908043,
-0.020285815000534058,
-0.046190306544303894,
0.06240805611014366,
0.24959459900856018,
0.2555881440639496,
0.05471888929605484,
-0.3409825265407562,
0.007953019812703133,
0.2820030152797699,
0.20832470059394836,
0.18946516513824463,
0.18919211626052856,
-0.07011069357395172,
0.17034898698329926,
0.26392462849617004,
0.16457989811897278,
0.2629548907279968,
-0.015182099305093288,
-0.2123050093650818,
-0.08616406470537186,
0.24468600749969482,
0.1680406779050827,
0.04419178515672684,
-0.1283629685640335,
0.06571394205093384,
0.3238115608692169,
0.11381283402442932,
-0.13485538959503174,
-0.22805827856063843,
0.19604414701461792,
0.28523752093315125,
0.6019864678382874,
-0.050456494092941284,
0.3259407579898834,
-0.04792296141386032,
-0.2781184911727905,
-0.3706555962562561,
0.0179365836083889,
0.11389971524477005,
-0.09621275216341019,
-0.05627509206533432,
0.09414380043745041,
0.36090919375419617,
0.8490374088287354,
-0.0392586886882782,
0.270916223526001,
0.08667962998151779,
-0.18442897498607635,
-0.231657937169075,
0.15094077587127686,
0.11443627625703812,
-0.026465723291039467,
0.15560941398143768,
0.0009208349511027336,
-0.401189923286438,
-0.08902250230312347,
-0.00013074278831481934,
0.4331216812133789,
0.39993196725845337,
-0.3471737802028656,
-0.10980457067489624,
-0.3021012246608734,
-0.44454970955848694,
-0.39858970046043396,
-0.36305147409439087,
-0.2080814093351364,
-0.3813641369342804,
-0.061455756425857544,
0.22124451398849487,
-0.00008041411638259888,
0.23552905023097992,
-0.19494938850402832,
0.28329282999038696,
-0.30940207839012146,
-0.3343961834907532,
0.1164737343788147,
-0.2011948674917221,
-0.40045812726020813,
0.03807687386870384,
0.28132164478302,
0.0704876109957695,
0.4426933228969574,
-0.1078203022480011,
-0.29736101627349854,
-0.21326030790805817,
-0.31885039806365967,
0.13285496830940247,
0.06095752865076065,
0.5699266791343689,
0.4761795103549957,
-0.014883913099765778,
0.4204102158546448,
0.07882925122976303,
0.042044125497341156,
-0.2335488647222519,
-0.4335296154022217,
-0.2341788411140442,
0.09182915836572647,
0.0969143807888031,
-0.13966424763202667,
-0.39729323983192444,
-0.52669358253479,
-0.08559001982212067,
0.1703435778617859,
0.12703530490398407,
0.07320810854434967,
0.0939830020070076,
-0.11142731457948685,
0.2511827349662781,
0.08683265745639801,
-0.18744917213916779,
-0.11685249209403992,
0.07108868658542633,
-0.009083796292543411,
-0.1429181545972824,
-0.1871635913848877,
0.0666741281747818,
-0.11608918011188507,
0.08681826293468475,
-0.1572064608335495,
-0.48865634202957153,
-0.44232651591300964,
0.1542486846446991,
0.23099470138549805,
0.39259210228919983,
-0.20678259432315826,
0.2817327082157135,
0.201801598072052,
0.12314780056476593,
-0.10951663553714752,
-0.34012529253959656,
0.1602247953414917,
0.09377153217792511,
0.3110189139842987,
0.13703428208827972,
0.34237098693847656,
-0.11723089218139648,
0.7626632452011108,
0.11879229545593262,
-0.0941152274608612,
-0.03337521851062775,
-0.1344081610441208,
0.015389334410429,
-0.017840825021266937,
-0.04059571772813797,
0.33505961298942566,
-0.20015400648117065,
-0.3104262351989746,
0.20721706748008728,
-0.11684448271989822,
-0.03705424815416336,
-0.13537587225437164,
0.2891801595687866,
-0.017412874847650528,
-0.06730526685714722,
0.0038466546684503555,
-0.21916741132736206,
0.008076868951320648,
0.09175167977809906,
-0.02824871614575386,
-0.19920854270458221,
-0.15857353806495667,
0.031044337898492813,
0.3056078553199768,
0.009298950433731079,
0.17336422204971313,
-0.25022339820861816,
0.006671939045190811,
-0.3804589807987213,
0.32095175981521606,
0.3083265721797943,
0.4791111648082733,
0.08994166553020477,
0.04050246626138687,
0.128177210688591,
0.023768838495016098,
0.2255096435546875,
0.07952557504177094,
0.1641315370798111,
0.25303009152412415,
-0.13103324174880981,
-0.04519321769475937,
-0.24799959361553192,
-0.06108873710036278,
0.0637972354888916,
0.004301479086279869,
0.09554530680179596,
-0.40971314907073975,
-0.09873314946889877,
0.1882554143667221,
0.08911511301994324,
-0.07824192941188812,
-0.23516100645065308,
-0.0749972015619278,
-0.08631077408790588,
-0.11132027953863144,
-0.21148717403411865,
-0.22183217108249664,
0.01701824925839901,
-0.21502210199832916,
0.4063695967197418,
-0.0038536395877599716,
-0.08811713010072708,
-0.06015479564666748,
0.09694615006446838,
0.08987809717655182,
-0.28205639123916626,
0.29240572452545166,
0.2651258111000061,
0.07484520971775055,
0.3037792146205902,
0.31530141830444336,
-0.09081141650676727,
-0.2188895046710968,
0.025368649512529373,
0.055203232914209366,
0.4211719334125519,
0.35064882040023804,
0.10434022545814514,
-0.05036770552396774,
-0.23994183540344238,
-0.20737259089946747,
-0.23432552814483643,
0.19697564840316772,
0.2857738137245178,
-0.030911825597286224,
0.0785093754529953,
-0.31849727034568787,
0.7194925546646118,
0.22033126652240753,
-0.2501452565193176,
0.4313562512397766,
-0.2180648297071457,
-0.26280924677848816,
-0.06578311324119568,
0.12758301198482513,
0.9033367037773132,
0.14794975519180298,
0.23772436380386353,
0.4199579656124115,
-0.26912355422973633,
0.4643268585205078,
0.07282888889312744,
0.15510977804660797,
-0.49473056197166443,
-0.00016525853425264359,
0.01968093402683735,
-0.1823749989271164,
0.20952045917510986,
-0.09575746953487396,
-0.2247014343738556,
0.3749465048313141,
0.1465231329202652,
0.28106725215911865,
0.3701074421405792,
0.3088003396987915,
-0.2517704367637634,
-0.0336604006588459,
-0.1858089119195938,
0.09027861803770065,
-0.1498020440340042,
0.40192827582359314,
-0.28164350986480713,
-0.00031447969377040863,
-0.14423677325248718,
-0.044248081743717194,
-0.2529454231262207,
-0.11223725229501724,
-0.173439621925354,
0.06214238703250885,
0.15585285425186157,
-0.13206005096435547,
-0.06616057455539703,
0.18333186209201813,
0.08269128203392029,
-0.21432547271251678,
-0.14978264272212982,
0.1254417449235916,
-0.14331692457199097,
0.16847188770771027,
0.3818264901638031,
0.04532884433865547,
0.3266820013523102,
-0.3169657289981842,
-0.05816731974482536,
0.06710837036371231,
-0.2803245484828949,
-0.12472721934318542,
-0.13294482231140137,
-0.17246964573860168,
0.14165642857551575,
-0.29994386434555054,
-0.1425621658563614,
-0.10251238942146301,
-0.009897671639919281,
-0.115902841091156,
0.02239544875919819,
0.28106242418289185,
-0.3552970886230469,
-0.061010830104351044,
-0.11896087229251862,
-0.22990930080413818,
0.009612835943698883,
0.4747704863548279,
-0.06723793596029282,
-0.1376439929008484,
0.6765257120132446,
-0.2103765457868576,
0.06588243693113327,
-0.12991788983345032,
0.062012724578380585,
-0.10107389092445374,
-0.11184273660182953,
0.07678307592868805,
-0.16967424750328064,
-0.3008666932582855,
0.04371436685323715,
0.5850268006324768,
0.4418943524360657,
0.012407097965478897,
-0.07040699571371078,
-0.46289244294166565,
-0.41166603565216064,
-0.0003568902611732483,
-0.14149731397628784,
0.20699253678321838,
-0.2121647298336029,
0.22073912620544434,
0.16328157484531403,
0.046032145619392395,
-0.18724983930587769,
-0.2017056792974472,
0.049464620649814606,
0.20594938099384308,
-0.1384763866662979,
0.04342859610915184,
-0.015562606044113636,
0.14493200182914734,
-0.03392532095313072,
0.06349072605371475,
-0.36153310537338257,
-0.07694461941719055,
-0.10113637149333954,
0.2054293155670166,
0.11184283345937729,
-0.03894909471273422,
0.15560282766819,
-0.11734654009342194,
0.03972204774618149,
0.2143976390361786,
-0.06621687114238739,
-0.048358578234910965,
-0.09268885850906372,
0.1126721203327179,
0.34582823514938354,
0.09795041382312775,
-0.006950933486223221,
0.30149030685424805,
0.10003826022148132,
0.17635124921798706,
-0.11613377183675766,
0.2669965922832489,
-0.2339322417974472,
0.08855469524860382,
0.20248861610889435,
0.12920896708965302,
-0.019432008266448975,
0.2600127160549164,
0.13960126042366028,
-0.1141728013753891,
0.08041916787624359,
-0.1625291109085083,
0.3586396276950836,
0.8415080308914185,
-0.17826029658317566,
-0.13109177350997925,
0.4703673720359802,
0.03272813931107521,
-0.19339068233966827,
0.027116749435663223,
0.22767898440361023,
0.20254075527191162,
0.039652761071920395,
0.26613757014274597,
0.010690603405237198,
-0.13747431337833405,
0.19611197710037231,
0.1407437026500702,
0.09474238008260727,
-0.17869940400123596,
-0.07266853749752045,
0.5383134484291077,
-0.2553038001060486,
0.16207416355609894,
0.3502659797668457,
0.00047488510608673096,
0.21568593382835388,
0.08506079018115997,
0.025451581925153732,
0.5338096022605896,
-0.012156344950199127,
0.058235470205545425,
0.11353041231632233,
0.019126318395137787,
-0.04424290731549263,
0.2593919038772583,
0.05144317448139191,
-0.011776052415370941,
0.3216552138328552,
0.6301924586296082,
-0.43068036437034607,
-0.17472785711288452,
-0.27786174416542053,
-0.0494084469974041,
0.08228203654289246,
-0.14998453855514526,
-0.3964492380619049,
0.0435982421040535,
-0.2213098108768463,
-0.07336217910051346,
-0.14795054495334625,
-0.3185235857963562,
0.2299106866121292,
0.00329657644033432,
-0.35559141635894775,
-0.3461935818195343,
-0.39676228165626526,
0.1408468633890152,
-0.03580810874700546,
-0.27528682351112366,
0.2508656084537506,
0.029407210648059845,
0.018531780689954758,
0.2829647660255432,
0.28391745686531067,
0.4441567063331604,
0.08628561347723007,
-0.43873557448387146,
-0.2540844678878784,
-0.19133098423480988,
0.13583232462406158,
-0.07762150466442108,
0.399572491645813,
-0.059817150235176086,
-0.16802312433719635,
0.49920526146888733,
0.05886781960725784,
0.043532341718673706,
0.26643142104148865,
0.3724864423274994,
-0.5206148624420166,
-0.16898134350776672,
0.82081538438797,
-0.06794869899749756,
-0.16675175726413727,
-0.027103736996650696,
0.17767956852912903,
-0.23198482394218445,
0.08259600400924683,
-0.03570432588458061,
-0.04749995470046997,
0.18776077032089233,
0.11940518021583557,
0.04107680171728134,
-0.1780635267496109,
0.3992721140384674,
0.33888137340545654,
-0.07150008529424667,
-0.3425288796424866,
-0.21393299102783203,
-0.8131759166717529,
0.08850471675395966,
-0.10057628154754639,
-0.3737140893936157,
-0.06355031579732895,
-0.23741291463375092,
0.25356799364089966,
0.10478387773036957,
-0.257435142993927,
0.17715543508529663,
-0.0015824269503355026,
0.1259436309337616,
-0.2627962529659271,
-0.36598822474479675,
-0.2140856832265854,
-0.025764482095837593,
-0.02974064275622368,
-0.402548223733902,
0.07842466235160828,
-0.3133713901042938,
-0.09926487505435944,
0.22371746599674225,
-0.03939526528120041,
0.49409544467926025,
0.0730830579996109,
0.25377756357192993,
-0.012197377160191536,
0.6868562698364258,
0.24270299077033997,
-0.03130260854959488,
-0.24734267592430115,
0.17876696586608887,
-0.13330836594104767,
0.1253570318222046,
-0.10701526701450348,
0.13508643209934235,
-0.17025792598724365,
0.6143170595169067,
-0.414183109998703,
0.4506014883518219,
0.0749511867761612,
0.0781891867518425,
-0.2869768440723419,
0.047970786690711975,
-0.3413870632648468,
0.14387987554073334,
0.3280654847621918,
0.30497345328330994,
-0.11956609785556793,
0.34439802169799805,
-0.26570069789886475,
-0.15193809568881989,
0.4117482304573059,
-0.24894636869430542,
-0.05838599056005478,
0.05723504349589348,
0.21902164816856384,
0.0009547099471092224,
-0.15867112576961517,
-0.44349995255470276,
0.12104444950819016,
0.2671409547328949,
-0.13255095481872559,
0.0848160833120346,
0.1458553820848465,
0.2846495807170868,
0.026441995054483414,
-0.035740792751312256,
0.9360103607177734,
-0.07236693054437637,
0.15447020530700684,
-0.018570510670542717,
-0.24318110942840576
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | I'm quite positive that you can just replace the `dl_manager.download()` statements here: https://github.com/EntilZha/nlp/blob/4d46443b65f1f756921db8275594e6af008a1de7/datasets/qanta/qanta.py#L194 with `dl_manager.download_and_extract()` even though you don't extract anything. I would prefer to avoid adding more functions to the MockDataLoadManager and keep it as simple as possible (It's already to complex now IMO).
Could you check if you can replace the `download()` function? | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 55 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
I'm quite positive that you can just replace the `dl_manager.download()` statements here: https://github.com/EntilZha/nlp/blob/4d46443b65f1f756921db8275594e6af008a1de7/datasets/qanta/qanta.py#L194 with `dl_manager.download_and_extract()` even though you don't extract anything. I would prefer to avoid adding more functions to the MockDataLoadManager and keep it as simple as possible (It's already to complex now IMO).
Could you check if you can replace the `download()` function? | [
-0.10087041556835175,
0.5024332404136658,
-0.039797212928533554,
-0.08978384733200073,
0.0968024805188179,
-0.12240689992904663,
0.2872871160507202,
0.31355321407318115,
-0.054385315626859665,
0.11574174463748932,
0.04618164151906967,
0.16493384540081024,
-0.2744549512863159,
-0.005963634699583054,
0.165956512093544,
-0.0370168462395668,
-0.07802139967679977,
0.25511327385902405,
-0.09114491939544678,
0.2149970978498459,
-0.23069195449352264,
0.12446141242980957,
-0.0709371566772461,
0.07457991689443588,
0.1365300565958023,
0.19969812035560608,
-0.16580642759799957,
0.05431877821683884,
-0.31603482365608215,
-0.8764681220054626,
0.3479219675064087,
0.18099507689476013,
0.24238255620002747,
0.23878884315490723,
-0.00012480560690164566,
-0.153802752494812,
0.5954884886741638,
-0.12650670111179352,
-0.6724078059196472,
-0.1728314608335495,
0.24162229895591736,
-0.4436880946159363,
0.2643413245677948,
-0.0716199055314064,
0.2790188491344452,
-0.16837634146213531,
0.18214735388755798,
0.11028318107128143,
0.07405327260494232,
0.38633590936660767,
0.11946217715740204,
0.24075785279273987,
0.08585745096206665,
-0.12019345164299011,
-0.05844981223344803,
0.024083450436592102,
-0.0008228309452533722,
0.6254268884658813,
0.40664759278297424,
0.021436626091599464,
0.021082788705825806,
-0.010083932429552078,
-0.06172134727239609,
0.45013153553009033,
0.24951234459877014,
-0.04781989008188248,
0.49971404671669006,
-0.07006866484880447,
-0.1631966531276703,
-0.013614587485790253,
0.6971592307090759,
-0.5866325497627258,
-0.36203816533088684,
-0.05475027114152908,
0.15433429181575775,
-0.20426039397716522,
0.1349426805973053,
-0.28096291422843933,
-0.43949681520462036,
0.058052726089954376,
-0.10192982852458954,
-0.5488121509552002,
0.017848558723926544,
0.2542361915111542,
-0.3011972904205322,
0.28678974509239197,
0.11398311704397202,
0.1454489380121231,
0.24242769181728363,
-0.05278812348842621,
0.21367669105529785,
-0.022138364613056183,
-0.08245567977428436,
0.16982369124889374,
0.0019519105553627014,
-0.304499089717865,
-0.31498029828071594,
-0.21552741527557373,
0.09691528230905533,
0.13492155075073242,
-0.37371471524238586,
-0.14380395412445068,
-0.05633974075317383,
0.1341736614704132,
0.09189127385616302,
0.41653361916542053,
0.3381829857826233,
0.22063644230365753,
0.10820474475622177,
0.2282303422689438,
0.23546725511550903,
0.12068722397089005,
0.03867356479167938,
-0.3611081838607788,
0.019834887236356735,
0.1914500594139099,
0.1347879022359848,
-0.19446946680545807,
-0.08906851708889008,
-0.24023905396461487,
-0.4562418460845947,
-0.057777341455221176,
-0.17793463170528412,
0.20956367254257202,
-0.08753730356693268,
-0.08982730656862259,
0.10732926428318024,
0.40889471769332886,
-0.12385638058185577,
-0.2714741826057434,
0.003222732339054346,
0.19675253331661224,
-0.098024383187294,
0.1111707016825676,
0.21871055662631989,
0.02494201436638832,
0.33839648962020874,
-0.37400129437446594,
-0.034397415816783905,
-0.0379936546087265,
0.10087799280881882,
-0.0139267323538661,
-0.17526453733444214,
0.2979564368724823,
-0.13329315185546875,
0.03545448184013367,
0.020310809835791588,
-0.35186827182769775,
-0.2085862159729004,
0.24709346890449524,
0.22873249650001526,
-0.4571879804134369,
-0.09473897516727448,
0.05991044268012047,
-0.5005056262016296,
-0.02239135652780533,
-0.05310019105672836,
-0.07679609954357147,
-0.07516729086637497,
-0.5091546773910522,
0.15669900178909302,
-0.36302250623703003,
-0.28936347365379333,
-0.05024613067507744,
-0.059419915080070496,
0.37651246786117554,
-0.2985680401325226,
-0.2998124957084656,
-0.540572464466095,
-0.3079770803451538,
0.1497212052345276,
-0.24499936401844025,
-0.16400101780891418,
0.2662373483181,
-0.34657225012779236,
0.04316511005163193,
0.667220413684845,
-0.6826150417327881,
-0.38173288106918335,
0.3879488408565521,
-0.29687464237213135,
-0.2016325145959854,
0.13723118603229523,
-0.08174246549606323,
0.07141735404729843,
-0.3140597343444824,
-0.20285391807556152,
-0.005927072837948799,
0.0915985181927681,
-0.21299782395362854,
-0.13809290528297424,
-0.4739532172679901,
0.13925617933273315,
0.22118902206420898,
0.0007849894464015961,
0.24563631415367126,
0.03358955681324005,
0.14707604050636292,
0.3634043335914612,
0.1003376767039299,
0.13167636096477509,
-0.15881599485874176,
0.249946728348732,
-0.18818019330501556,
-0.1837327778339386,
-0.08811596035957336,
-0.5891331434249878,
0.21658015251159668,
-0.1606370508670807,
0.22971299290657043,
-0.07063737511634827,
-0.0018130950629711151,
-0.4160648286342621,
-0.03989424556493759,
0.09383711963891983,
-0.2353096604347229,
-0.025886792689561844,
0.1969701051712036,
0.19552312791347504,
0.004466298967599869,
-0.0157301127910614,
0.06437630206346512,
-0.16206413507461548,
0.2334323674440384,
0.07400716841220856,
-0.05165005475282669,
-0.022029435262084007,
0.14289583265781403,
0.20402976870536804,
0.2436189353466034,
0.030902357771992683,
-0.25026312470436096,
-0.03667755797505379,
0.3134893476963043,
0.14573079347610474,
0.27442294359207153,
0.10608696937561035,
-0.04028916358947754,
0.1848420351743698,
0.2803106904029846,
0.16047827899456024,
0.2589093744754791,
0.11254415661096573,
-0.12400823831558228,
0.08150599151849747,
0.11401208490133286,
0.3063763678073883,
0.036905985325574875,
-0.10141032934188843,
0.048838041722774506,
0.2526004910469055,
0.06619587540626526,
-0.12181852757930756,
-0.3277985155582428,
-0.02463017776608467,
0.26366302371025085,
0.6258196830749512,
-0.09830470383167267,
0.30670344829559326,
-0.10810399800539017,
-0.27656808495521545,
-0.3729349374771118,
0.02712627872824669,
0.1354561299085617,
-0.24313884973526,
-0.05934799462556839,
0.0059099141508340836,
0.4128139019012451,
0.889143168926239,
-0.08765040338039398,
0.21271073818206787,
0.2576933801174164,
0.09946372359991074,
-0.14763511717319489,
0.3102174699306488,
0.27317506074905396,
0.03670463711023331,
0.15607155859470367,
0.017295630648732185,
-0.2442476898431778,
-0.032427191734313965,
-0.09209543466567993,
0.33091625571250916,
0.35919851064682007,
-0.30033421516418457,
-0.10634095221757889,
-0.30636581778526306,
-0.5244472622871399,
-0.36918240785598755,
-0.3438991606235504,
-0.20262132585048676,
-0.3367350101470947,
-0.16702450811862946,
0.2561098039150238,
-0.016800876706838608,
0.2510792315006256,
-0.1769595891237259,
0.23437507450580597,
-0.35818105936050415,
-0.261892169713974,
0.01408899575471878,
-0.06981229037046432,
-0.28657788038253784,
0.005503062158823013,
0.23285901546478271,
0.16187742352485657,
0.24962705373764038,
-0.2545627951622009,
-0.21234312653541565,
-0.34649068117141724,
-0.18361705541610718,
0.19877390563488007,
0.24772752821445465,
0.4137888252735138,
0.5279136896133423,
-0.07021409273147583,
0.35673272609710693,
0.059449680149555206,
-0.0660829097032547,
-0.1920318752527237,
-0.37169942259788513,
-0.30342361330986023,
-0.0005277288728393614,
0.27848020195961,
-0.08362515270709991,
-0.3137316405773163,
-0.6029024720191956,
-0.14122089743614197,
0.03423180431127548,
0.07534775137901306,
0.12522128224372864,
0.0305909626185894,
-0.241026371717453,
0.22648760676383972,
-0.0675986036658287,
-0.23341895639896393,
-0.20004770159721375,
0.15993042290210724,
-0.009144742041826248,
-0.16310185194015503,
-0.0454622246325016,
0.07400737702846527,
-0.10867740213871002,
0.0565042719244957,
-0.23117852210998535,
-0.4390268325805664,
-0.4993737041950226,
0.2032100111246109,
-0.011472251266241074,
0.14936907589435577,
-0.18084731698036194,
0.22669407725334167,
0.24462680518627167,
0.1441558301448822,
0.007774624973535538,
-0.40508028864860535,
0.12961594760417938,
0.1733417510986328,
0.2596013844013214,
0.2025211751461029,
0.4707232415676117,
-0.18957823514938354,
0.6809959411621094,
0.08019046485424042,
-0.06540736556053162,
-0.006915055215358734,
-0.19380617141723633,
0.12983432412147522,
0.09109852463006973,
-0.07360170036554337,
0.21883246302604675,
-0.19008871912956238,
-0.27239489555358887,
0.26072990894317627,
-0.36413365602493286,
-0.09074007719755173,
-0.15291041135787964,
0.21480898559093475,
-0.1826370358467102,
-0.1637749969959259,
0.07783818989992142,
-0.20450931787490845,
0.0020859837532043457,
0.1484215408563614,
0.00008292868733406067,
-0.21906617283821106,
-0.05846768245100975,
0.10795803368091583,
0.2922644317150116,
0.0909213125705719,
0.11736852675676346,
-0.2829023003578186,
-0.0073561519384384155,
-0.4521166682243347,
0.357546865940094,
0.3472751975059509,
0.4865119755268097,
0.21581445634365082,
0.03920448571443558,
0.008247800171375275,
0.040773775428533554,
0.21377846598625183,
-0.029948057606816292,
0.01300492137670517,
0.25568151473999023,
-0.1364879012107849,
0.061477094888687134,
-0.22550590336322784,
-0.09265458583831787,
0.07190170884132385,
0.0817243754863739,
-0.0707302838563919,
-0.3118754029273987,
-0.15123586356639862,
0.33285269141197205,
0.15579362213611603,
-0.11175557971000671,
-0.24236750602722168,
0.008510123938322067,
-0.15314172208309174,
-0.19700324535369873,
-0.19007036089897156,
-0.24555917084217072,
0.1381574273109436,
-0.12386288493871689,
0.44703003764152527,
0.013527256436645985,
-0.09884018450975418,
0.08706212043762207,
0.024769417941570282,
0.1871049702167511,
-0.15448376536369324,
0.13126252591609955,
0.17856888473033905,
0.002818576991558075,
0.30415141582489014,
0.28680574893951416,
-0.02494533360004425,
-0.2621816098690033,
0.02490977756679058,
0.11324077099561691,
0.3784663677215576,
0.3422499895095825,
0.19741113483905792,
0.06382715702056885,
-0.2843545079231262,
-0.1820514053106308,
-0.14466552436351776,
0.1674746423959732,
0.3507557511329651,
-0.10339272767305374,
0.05127161368727684,
-0.2381136119365692,
0.6501338481903076,
0.1520877480506897,
-0.21758562326431274,
0.2924673557281494,
-0.1957998424768448,
-0.251296728849411,
-0.12040594965219498,
0.14373937249183655,
0.9772177934646606,
0.1787053644657135,
0.1921570748090744,
0.3799651563167572,
-0.27018001675605774,
0.5282027125358582,
0.12167224287986755,
0.11431455612182617,
-0.49746766686439514,
-0.036809418350458145,
0.012771746143698692,
-0.21958325803279877,
0.22603967785835266,
-0.15513795614242554,
-0.23718351125717163,
0.3542986512184143,
-0.010540299117565155,
0.28239768743515015,
0.3365882933139801,
0.3203301429748535,
-0.22276359796524048,
-0.026248697191476822,
-0.1613606959581375,
0.04255671054124832,
-0.049717940390110016,
0.41778963804244995,
-0.29927900433540344,
0.009875815361738205,
-0.0863073468208313,
-0.04552706331014633,
-0.3256157636642456,
-0.20060059428215027,
-0.29272350668907166,
0.017192630097270012,
0.0827985405921936,
-0.13996833562850952,
-0.010616284795105457,
0.17796529829502106,
0.08981610089540482,
-0.21600724756717682,
-0.09981639683246613,
0.0924350768327713,
-0.14039334654808044,
0.2634114623069763,
0.3869931399822235,
0.09648358076810837,
0.2686980366706848,
-0.34610795974731445,
-0.09964456409215927,
0.30464762449264526,
-0.23491992056369781,
-0.2469954490661621,
-0.04180097579956055,
-0.20667655766010284,
0.13844750821590424,
-0.19164037704467773,
-0.32677707076072693,
-0.025653012096881866,
0.00028639286756515503,
-0.1344083845615387,
-0.003131527453660965,
0.16473454236984253,
-0.36389032006263733,
-0.008035466074943542,
-0.20352201163768768,
-0.2534613609313965,
0.049440596252679825,
0.4804389774799347,
-0.02904576063156128,
-0.22069184482097626,
0.665513277053833,
-0.26307475566864014,
0.117669478058815,
-0.1220516636967659,
-0.0074471160769462585,
-0.0930064469575882,
-0.10929860174655914,
0.07604210078716278,
-0.17611928284168243,
-0.17633569240570068,
-0.010683082975447178,
0.5820418000221252,
0.3484700322151184,
0.08524657785892487,
-0.15745815634727478,
-0.4427753686904907,
-0.4029707908630371,
0.017590399831533432,
-0.06714573502540588,
0.1379370242357254,
-0.18047964572906494,
0.18105773627758026,
0.1291486918926239,
0.08300850540399551,
-0.17618054151535034,
-0.10881167650222778,
0.02771732024848461,
0.1015767902135849,
-0.1334146112203598,
0.17750445008277893,
0.005330667831003666,
0.14194746315479279,
-0.062301814556121826,
0.17821498215198517,
-0.29202935099601746,
-0.052992284297943115,
-0.1140306144952774,
0.22683238983154297,
0.023889118805527687,
0.06089300662279129,
0.1892106533050537,
-0.047966498881578445,
0.015474952757358551,
0.24556544423103333,
-0.10414773225784302,
-0.03355497866868973,
-0.05473878234624863,
0.21973399817943573,
0.3419259786605835,
0.04210352897644043,
-0.1363525092601776,
0.2392880618572235,
0.2469775229692459,
0.21957457065582275,
-0.1397828459739685,
0.3792558014392853,
-0.11718574166297913,
0.06506052613258362,
0.28737008571624756,
0.04528255760669708,
-0.07998436689376831,
0.26757439970970154,
0.09384791553020477,
0.03071209415793419,
0.11529344320297241,
-0.07018141448497772,
0.2299191802740097,
0.8423088192939758,
-0.24265402555465698,
-0.116752989590168,
0.40150654315948486,
0.009781595319509506,
-0.233236163854599,
-0.08031406253576279,
0.21382126212120056,
0.06446291506290436,
0.009682219475507736,
0.29438072443008423,
0.04901884123682976,
-0.017301306128501892,
0.3186420798301697,
0.09393900632858276,
0.08764500916004181,
-0.14573413133621216,
-0.07335054874420166,
0.5390334725379944,
-0.26027172803878784,
0.21228526532649994,
0.3923051059246063,
0.13994263112545013,
0.38456282019615173,
0.15995630621910095,
-0.06687822192907333,
0.564166247844696,
-0.06525686383247375,
0.007685359567403793,
0.20442351698875427,
-0.08264769613742828,
-0.08976000547409058,
0.3919522166252136,
0.028775639832019806,
0.022416558116674423,
0.3010081648826599,
0.3995402157306671,
-0.3488949239253998,
-0.1671561896800995,
-0.20334208011627197,
0.03066154569387436,
0.12445712834596634,
-0.11075709760189056,
-0.23745091259479523,
0.005827784538269043,
-0.2603166699409485,
-0.05811135843396187,
-0.18110890686511993,
-0.3672564625740051,
0.25372642278671265,
-0.05136583000421524,
-0.3961370587348938,
-0.1772400140762329,
-0.5898517370223999,
0.02973219007253647,
-0.10691618174314499,
-0.26929712295532227,
0.05167829245328903,
0.03170248121023178,
0.07564826309680939,
0.22591061890125275,
0.4408133029937744,
0.3618394434452057,
0.10118646174669266,
-0.32470765709877014,
-0.3104070723056793,
-0.20572011172771454,
0.16892816126346588,
-0.0008588489145040512,
0.26479315757751465,
0.06462579220533371,
-0.18335506319999695,
0.40197765827178955,
0.034111350774765015,
0.05196739733219147,
0.18164271116256714,
0.41097551584243774,
-0.4785667359828949,
-0.2713505029678345,
0.9588333368301392,
0.018587686121463776,
-0.0753745585680008,
-0.10514387488365173,
0.20924463868141174,
-0.24594122171401978,
0.15358968079090118,
-0.05407014861702919,
-0.025078708305954933,
0.16526871919631958,
0.20228441059589386,
0.01158355176448822,
-0.04843902215361595,
0.2834644913673401,
0.2929685711860657,
-0.0652443915605545,
-0.2998434901237488,
-0.32373642921447754,
-0.8680163621902466,
0.1610240489244461,
0.09295070171356201,
-0.2784692049026489,
-0.019421810284256935,
-0.2899569869041443,
0.17587065696716309,
0.18767693638801575,
-0.2499033361673355,
0.25636425614356995,
-0.007288940716534853,
-0.03545430302619934,
-0.28572243452072144,
-0.2891830801963806,
-0.24124287068843842,
-0.023864595219492912,
-0.022986827418208122,
-0.39517971873283386,
0.19543111324310303,
-0.43772879242897034,
-0.1360103338956833,
0.16049259901046753,
-0.051106780767440796,
0.4187009334564209,
0.07762956619262695,
0.4448578953742981,
-0.03417609632015228,
0.505246639251709,
0.15348967909812927,
-0.05015362799167633,
-0.047820840030908585,
0.25087106227874756,
-0.14112074673175812,
0.1136057898402214,
-0.07329361140727997,
0.09428730607032776,
-0.17538873851299286,
0.6784104108810425,
-0.41788214445114136,
0.40138810873031616,
0.01165064051747322,
0.12361008673906326,
-0.4917759299278259,
-0.002498175948858261,
-0.1737731397151947,
0.14623795449733734,
0.37973955273628235,
0.25357934832572937,
-0.17763745784759521,
0.36763089895248413,
-0.4226214289665222,
0.02618400938808918,
0.504698634147644,
-0.16471484303474426,
-0.07719218730926514,
-0.0422571636736393,
0.31683629751205444,
-0.046242401003837585,
-0.2065516859292984,
-0.5365791916847229,
0.06525742262601852,
0.24328738451004028,
-0.06352643668651581,
0.14099594950675964,
0.20620779693126678,
0.17869821190834045,
0.0790720134973526,
-0.038183897733688354,
0.8223003149032593,
-0.002348240464925766,
0.11937950551509857,
-0.19420163333415985,
-0.2611883580684662
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | I might be doing something wrong, but swapping those two gives this error:
```
> with open(path) as f:
E IsADirectoryError: [Errno 21] Is a directory: 'datasets/qanta/dummy/mode=first,char_skip=25/2018.4.18/dummy_data-zip-extracted/dummy_data'
src/nlp/datasets/qanta/3d965403133687b819905ead4b69af7bcee365865279b2f797c79f809b4490c3/qanta.py:280: IsADirectoryError
During handling of the above exception, another exception occurred:
```
So it seems like the directory name is getting passed. Is this not functioning as expected, or is there some caching happening maybe? I deleted the dummy files and re-ran the import script with no changes. I'm digging a bit in with a debugger, but no clear reason yet | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 88 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
I might be doing something wrong, but swapping those two gives this error:
```
> with open(path) as f:
E IsADirectoryError: [Errno 21] Is a directory: 'datasets/qanta/dummy/mode=first,char_skip=25/2018.4.18/dummy_data-zip-extracted/dummy_data'
src/nlp/datasets/qanta/3d965403133687b819905ead4b69af7bcee365865279b2f797c79f809b4490c3/qanta.py:280: IsADirectoryError
During handling of the above exception, another exception occurred:
```
So it seems like the directory name is getting passed. Is this not functioning as expected, or is there some caching happening maybe? I deleted the dummy files and re-ran the import script with no changes. I'm digging a bit in with a debugger, but no clear reason yet | [
0.0540458969771862,
0.07422429323196411,
0.009660083800554276,
0.17164751887321472,
0.018456868827342987,
-0.1827668398618698,
0.40755602717399597,
0.1807367354631424,
0.031773824244737625,
0.24988536536693573,
0.038060203194618225,
0.06830566376447678,
-0.06527296453714371,
-0.2527969479560852,
0.016633106395602226,
0.15957820415496826,
0.1347910314798355,
0.04466550052165985,
-0.2199346125125885,
-0.0055113062262535095,
-0.35158419609069824,
0.20710384845733643,
-0.18735049664974213,
0.1459728181362152,
-0.09561737626791,
0.2706403136253357,
-0.22023658454418182,
0.253609836101532,
-0.19941851496696472,
-0.5675516128540039,
0.14673244953155518,
0.0295448936522007,
0.16571646928787231,
0.574688732624054,
-0.00013265380403026938,
-0.07714223116636276,
0.5401036143302917,
-0.12277983129024506,
-0.6687530875205994,
-0.23048795759677887,
0.2879287898540497,
-0.15296036005020142,
0.2021130472421646,
-0.08125125616788864,
0.27061575651168823,
-0.17419052124023438,
0.20436622202396393,
-0.06535617262125015,
0.12489980459213257,
0.352989137172699,
0.019502006471157074,
0.1126968264579773,
-0.010982226580381393,
0.07280859351158142,
0.09343883395195007,
0.2516893744468689,
-0.09757190942764282,
0.46646958589553833,
0.21144595742225647,
0.0007744794711470604,
-0.04591620713472366,
-0.015806565061211586,
0.019108260050415993,
0.46090826392173767,
0.3064592480659485,
0.18696486949920654,
0.4650615453720093,
0.10373464971780777,
-0.012513544410467148,
-0.037865325808525085,
0.6569064259529114,
-0.483895868062973,
-0.4344106912612915,
-0.0811818316578865,
-0.12728391587734222,
-0.20948468148708344,
0.38311195373535156,
-0.10318616777658463,
-0.3200289011001587,
0.09504377841949463,
0.014491195790469646,
-0.2616751194000244,
-0.03538689389824867,
0.21442347764968872,
-0.3736017048358917,
0.39959248900413513,
0.03471030667424202,
0.19331267476081848,
0.0728292390704155,
-0.049595415592193604,
0.30319857597351074,
-0.34249186515808105,
0.04692394286394119,
0.16503408551216125,
0.09963254630565643,
-0.0047329626977443695,
-0.16642418503761292,
-0.06243463605642319,
-0.14533305168151855,
0.03446204215288162,
-0.4331532418727875,
-0.13929203152656555,
-0.18535861372947693,
0.2131970226764679,
0.18500934541225433,
0.44877105951309204,
0.25296205282211304,
0.49305203557014465,
0.17895863950252533,
0.13217853009700775,
0.13476116955280304,
0.1885266900062561,
-0.007200427819043398,
-0.4462215304374695,
-0.00336444191634655,
0.10703611373901367,
0.2182113230228424,
-0.2600003182888031,
-0.26317456364631653,
-0.2860173285007477,
-0.46615487337112427,
-0.036148957908153534,
-0.057705942541360855,
0.2854338586330414,
-0.21941198408603668,
-0.11122133582830429,
0.06850851327180862,
0.38588768243789673,
-0.19950073957443237,
0.058217186480760574,
0.0005526789464056492,
0.039048463106155396,
-0.2579006552696228,
0.03631364181637764,
0.09758567810058594,
0.1127357929944992,
0.21362905204296112,
-0.3273884952068329,
0.1367974430322647,
-0.14557063579559326,
0.07292064279317856,
-0.0004481300711631775,
0.11817510426044464,
0.35788652300834656,
-0.14977261424064636,
0.1903308928012848,
0.10121174156665802,
-0.45273327827453613,
-0.25621846318244934,
0.29938071966171265,
-0.10430816560983658,
-0.4040021300315857,
0.09910072386264801,
-0.005106193944811821,
-0.4261919856071472,
0.060874685645103455,
0.07882974296808243,
-0.3964563310146332,
0.19351822137832642,
-0.5260316729545593,
0.06719474494457245,
-0.27525579929351807,
-0.2804780900478363,
-0.12022753059864044,
-0.09893935173749924,
0.48066312074661255,
-0.34747314453125,
-0.2877002954483032,
-0.3806164562702179,
-0.043282147496938705,
0.1235184296965599,
-0.0717243105173111,
-0.12091965973377228,
0.043958328664302826,
-0.5625421404838562,
0.018757790327072144,
0.43581622838974,
-0.5859134197235107,
-0.3239840567111969,
0.3623734712600708,
-0.5026475191116333,
-0.19662752747535706,
0.4976199269294739,
-0.11810924112796783,
-0.019310494884848595,
-0.4362892508506775,
0.00029174238443374634,
0.04905955493450165,
0.06989674270153046,
-0.04112561047077179,
-0.17711324989795685,
-0.2051975578069687,
-0.02500303089618683,
0.08768302202224731,
-0.17620697617530823,
0.10934769362211227,
0.04550113528966904,
-0.10576526820659637,
0.4786716401576996,
0.0737261027097702,
0.09647504985332489,
-0.04458694905042648,
0.20204539597034454,
0.050491005182266235,
-0.04118292033672333,
0.25568586587905884,
-0.5695757269859314,
0.14952585101127625,
-0.15539118647575378,
0.12621267139911652,
-0.2437577098608017,
-0.08564536273479462,
-0.3687710762023926,
0.06484142690896988,
-0.14587223529815674,
-0.15639926493167877,
-0.10608261823654175,
0.5268374681472778,
-0.0165015310049057,
-0.06277436017990112,
0.04309337958693504,
0.08777257055044174,
-0.1442553848028183,
0.24223849177360535,
-0.11042909324169159,
0.0053618308156728745,
-0.051639944314956665,
0.08585318177938461,
-0.07348939776420593,
0.030897952616214752,
0.22429129481315613,
-0.40818122029304504,
0.03320857882499695,
0.3498995900154114,
0.27478379011154175,
0.46276575326919556,
-0.022554911673069,
-0.1348695009946823,
0.1559963971376419,
0.24798241257667542,
0.30912429094314575,
0.34455084800720215,
0.08198750764131546,
-0.28991881012916565,
-0.01919369399547577,
0.27006644010543823,
0.1689300537109375,
0.31897249817848206,
-0.031788356602191925,
-0.049406748265028,
0.04129443317651749,
0.13392701745033264,
-0.06262287497520447,
-0.2984601855278015,
0.18931813538074493,
0.16936108469963074,
0.5996588468551636,
0.0712875947356224,
0.32798266410827637,
0.02567467838525772,
-0.17272032797336578,
-0.27904778718948364,
-0.08578654378652573,
-0.00003851577639579773,
-0.18876498937606812,
-0.08370187878608704,
0.09133266657590866,
0.40567946434020996,
0.9681351780891418,
-0.09375648945569992,
0.33288437128067017,
0.03304961323738098,
-0.10807809978723526,
-0.2747822701931,
0.28881046175956726,
0.22763341665267944,
-0.07494223117828369,
0.17336967587471008,
-0.031398676335811615,
-0.318402498960495,
-0.0401051789522171,
-0.050305068492889404,
0.5000061988830566,
0.14260096848011017,
-0.5107771754264832,
0.22430628538131714,
-0.25457626581192017,
-0.3097939193248749,
-0.6035181283950806,
-0.31199488043785095,
-0.06053781881928444,
-0.5021187663078308,
-0.09551560878753662,
0.3961228132247925,
-0.030482858419418335,
0.20940709114074707,
-0.07476457953453064,
0.08459112048149109,
-0.44329190254211426,
-0.44742313027381897,
-0.014093589037656784,
0.008263982832431793,
-0.48457759618759155,
-0.1461125612258911,
0.3326222896575928,
-0.08755472302436829,
0.22779244184494019,
-0.23387663066387177,
-0.20161934196949005,
-0.23572483658790588,
-0.29723623394966125,
0.12632709741592407,
0.15794748067855835,
0.4473174214363098,
0.23237921297550201,
0.00020796805620193481,
0.46073251962661743,
0.00311282929033041,
0.12738218903541565,
-0.20606091618537903,
-0.3891749083995819,
-0.1575377732515335,
0.12728087604045868,
0.13422878086566925,
-0.1593405157327652,
-0.39147821068763733,
-0.4792371988296509,
-0.03614705055952072,
-0.09529043734073639,
0.05918179824948311,
0.12565350532531738,
0.2484217882156372,
-0.1625194549560547,
0.14527693390846252,
0.06382455676794052,
-0.09572599828243256,
-0.03304025158286095,
0.0895199328660965,
0.038432203233242035,
-0.23889976739883423,
-0.0015531666576862335,
0.044273559004068375,
0.00772886723279953,
0.056634943932294846,
-0.09045366942882538,
-0.4622616171836853,
-0.47036102414131165,
0.19328805804252625,
0.055600088089704514,
0.18048320710659027,
-0.10260474681854248,
0.45524048805236816,
0.2974397540092468,
0.13758741319179535,
-0.09040047228336334,
-0.3450206518173218,
0.024569302797317505,
0.08051788806915283,
0.3078870177268982,
0.1523379385471344,
0.3881366550922394,
-0.19256743788719177,
0.8443016409873962,
0.12629902362823486,
0.035268448293209076,
0.08385501801967621,
-0.15377211570739746,
0.1894451081752777,
-0.08218657225370407,
-0.031549304723739624,
0.15041430294513702,
-0.08360810577869415,
-0.5522128939628601,
0.36745840311050415,
-0.05712199956178665,
-0.23132175207138062,
-0.06647630035877228,
0.2273532748222351,
-0.14406490325927734,
-0.15885165333747864,
0.0742008164525032,
-0.19066937267780304,
-0.01243416965007782,
0.16560128331184387,
0.002517789602279663,
-0.2638314366340637,
-0.2158578336238861,
0.01242510974407196,
0.3022843599319458,
0.02733498066663742,
0.0839228555560112,
-0.330544114112854,
-0.1284155398607254,
-0.14755147695541382,
0.3084336519241333,
0.3300758898258209,
0.4101949632167816,
-0.01594208925962448,
-0.1134246289730072,
0.28132885694503784,
0.007648559287190437,
0.3506704568862915,
0.0673462450504303,
0.21243363618850708,
0.19533106684684753,
-0.0024002231657505035,
-0.11793342232704163,
-0.18610519170761108,
-0.07736092805862427,
0.14718542993068695,
0.10939393937587738,
0.18208011984825134,
-0.23847326636314392,
-0.26433059573173523,
0.20997938513755798,
0.19632458686828613,
-0.15524880588054657,
-0.2132083773612976,
-0.2094298154115677,
-0.12904754281044006,
-0.1241973415017128,
-0.3455800712108612,
-0.13917407393455505,
-0.06293387711048126,
-0.09446351230144501,
0.3878284990787506,
0.01809648983180523,
-0.18357983231544495,
0.05521734431385994,
0.004763578996062279,
0.30929049849510193,
-0.1802648901939392,
0.15318980813026428,
0.3662013113498688,
0.10744713246822357,
0.406025767326355,
0.38970839977264404,
-0.18061383068561554,
-0.12755854427814484,
0.02575552463531494,
0.09579350054264069,
0.39173397421836853,
0.6246479749679565,
0.046177927404642105,
-0.1896105408668518,
-0.2906065285205841,
-0.2193542867898941,
-0.2398289144039154,
0.09601430594921112,
0.40891286730766296,
0.009106417186558247,
0.10071636736392975,
-0.2854565680027008,
0.5554723739624023,
0.20811237394809723,
-0.35643666982650757,
0.5225512981414795,
-0.003554403781890869,
-0.2918553054332733,
0.11549738794565201,
-0.05118612200021744,
1.1163864135742188,
0.29423439502716064,
0.42396584153175354,
0.36086010932922363,
-0.20886582136154175,
0.09465119987726212,
0.1167902946472168,
0.1752214878797531,
-0.4606742858886719,
-0.021532047539949417,
-0.019033282995224,
-0.33305877447128296,
0.23628032207489014,
-0.03547031432390213,
-0.09988817572593689,
0.4064427316188812,
-0.04007875546813011,
0.3567257523536682,
0.193649023771286,
0.15737178921699524,
-0.2964199185371399,
0.028264716267585754,
0.026144342496991158,
-0.04065537452697754,
0.20728260278701782,
0.45894935727119446,
-0.16293072700500488,
0.03178037330508232,
-0.26329657435417175,
-0.07733353972434998,
-0.030731793493032455,
-0.0730976015329361,
-0.13402125239372253,
0.07461818307638168,
0.022244608029723167,
-0.25191012024879456,
-0.2052023857831955,
0.3793686628341675,
0.19289639592170715,
-0.22925756871700287,
0.022599468007683754,
0.17318694293498993,
-0.17188304662704468,
0.365487277507782,
0.3521057367324829,
-0.04134276881814003,
0.30463165044784546,
-0.13484054803848267,
-0.13243813812732697,
0.10160700976848602,
-0.2835327088832855,
-0.19923004508018494,
-0.2421746850013733,
-0.09257858991622925,
0.22591666877269745,
-0.3246315121650696,
-0.14834462106227875,
-0.14957788586616516,
-0.08646188676357269,
-0.10077975690364838,
-0.05219167098402977,
0.14122480154037476,
-0.28765591979026794,
0.010074004530906677,
-0.2608496844768524,
-0.42889732122421265,
-0.0010194424539804459,
0.5187014937400818,
-0.12068293243646622,
-0.05585869401693344,
0.8927491903305054,
-0.2553896903991699,
0.07004066556692123,
0.03783545643091202,
0.16071438789367676,
-0.22212950885295868,
-0.26517605781555176,
0.06714945286512375,
-0.18132168054580688,
-0.24391548335552216,
0.02168789505958557,
0.56891930103302,
0.32607346773147583,
0.08179120719432831,
-0.3220890760421753,
-0.4693026840686798,
-0.24841606616973877,
0.006860598921775818,
-0.13581523299217224,
0.18076582252979279,
-0.2004815638065338,
0.02838112786412239,
0.18213112652301788,
-0.11743354797363281,
-0.10768835991621017,
-0.019980747252702713,
0.11945166438817978,
0.22964121401309967,
-0.15153944492340088,
0.05161178857088089,
0.06271803379058838,
0.03996072709560394,
-0.08371775597333908,
0.10385216027498245,
-0.2190840244293213,
0.056734517216682434,
-0.0864664763212204,
0.2645622193813324,
0.028700631111860275,
0.004550819750875235,
0.006185074336826801,
-0.32587987184524536,
0.13018319010734558,
0.06811779737472534,
-0.02315872721374035,
0.02889157086610794,
-0.050951115787029266,
0.04266997426748276,
0.30082887411117554,
0.06145787984132767,
0.029404588043689728,
0.3885266184806824,
0.05780847370624542,
0.25832945108413696,
-0.18535099923610687,
0.21913087368011475,
-0.2305954396724701,
0.020766451954841614,
0.040415238589048386,
0.10006482899188995,
-0.018763378262519836,
0.2092517614364624,
0.13397377729415894,
-0.18022271990776062,
0.11828559637069702,
-0.10023938119411469,
0.36394810676574707,
0.9179773926734924,
-0.14689356088638306,
-0.23009686172008514,
0.4129929840564728,
-0.09078706800937653,
-0.057011187076568604,
-0.12697485089302063,
0.07886934280395508,
0.1358589082956314,
-0.058446865528821945,
0.3512890040874481,
-0.052806586027145386,
-0.11743712425231934,
0.34743165969848633,
0.21134522557258606,
0.20100340247154236,
-0.23741672933101654,
-0.10164037346839905,
0.4046119749546051,
-0.30559778213500977,
0.4028899371623993,
0.4748879075050354,
0.0623086653649807,
0.20034976303577423,
0.3251499533653259,
0.08612170815467834,
0.5218544006347656,
-0.14537331461906433,
-0.02890695258975029,
0.12090800702571869,
-0.10828767716884613,
-0.029849331825971603,
0.2552216053009033,
-0.005976662039756775,
0.04436124861240387,
0.35601699352264404,
0.5558950304985046,
-0.47650131583213806,
-0.10528735816478729,
-0.23334404826164246,
-0.13780389726161957,
0.01676420494914055,
-0.2931421101093292,
-0.21884988248348236,
-0.03580223396420479,
-0.1372559666633606,
-0.03259801119565964,
-0.19874674081802368,
-0.19986771047115326,
0.2898292541503906,
0.056157853454351425,
-0.2658582329750061,
-0.2286197692155838,
-0.36382436752319336,
0.019897585734725,
0.039980411529541016,
-0.34758293628692627,
0.25455909967422485,
-0.00025400519371032715,
0.13587933778762817,
0.2975616157054901,
0.13145563006401062,
0.48757925629615784,
0.1934380829334259,
-0.2696226239204407,
-0.2617153227329254,
-0.2879706621170044,
-0.0018292609602212906,
-0.07789882272481918,
0.35549309849739075,
-0.029869720339775085,
-0.09149475395679474,
0.35833123326301575,
-0.01570925861597061,
-0.005666815675795078,
0.22060003876686096,
0.40760788321495056,
-0.2764076292514801,
-0.14980629086494446,
0.809942901134491,
-0.24034637212753296,
-0.2101065218448639,
-0.07573121786117554,
0.033688705414533615,
-0.4592142701148987,
0.12718133628368378,
0.011043690145015717,
-0.14476530253887177,
0.1875208616256714,
0.11137866973876953,
-0.03916380926966667,
-0.09055313467979431,
0.3421502709388733,
0.4022057056427002,
-0.1118353083729744,
-0.33004412055015564,
-0.19953064620494843,
-0.8534044623374939,
0.2650274932384491,
-0.05009061470627785,
-0.14365550875663757,
-0.20968382060527802,
-0.07952213287353516,
0.21403393149375916,
-0.017104536294937134,
-0.11020126938819885,
0.11080672591924667,
0.05849342793226242,
0.183257058262825,
-0.3073982000350952,
-0.3775629997253418,
-0.18099546432495117,
0.03965005278587341,
-0.008477963507175446,
-0.5915560722351074,
0.19940391182899475,
-0.41751718521118164,
-0.15232011675834656,
0.16196760535240173,
-0.07171527296304703,
0.36899691820144653,
0.20901601016521454,
0.36452004313468933,
-0.10860452055931091,
0.6161583662033081,
0.17797735333442688,
-0.14680546522140503,
-0.26281970739364624,
0.057859353721141815,
-0.09725827723741531,
0.018361754715442657,
-0.0892745703458786,
0.17369011044502258,
-0.3242899477481842,
0.4118088483810425,
-0.3782767951488495,
0.22013422846794128,
0.0850958377122879,
-0.003485518041998148,
-0.22224657237529755,
0.18447397649288177,
-0.35888946056365967,
0.17099478840827942,
0.32443973422050476,
0.3272290527820587,
0.04074651747941971,
0.3295930325984955,
-0.30356234312057495,
-0.24247659742832184,
0.6405372619628906,
-0.0990561991930008,
-0.1643480807542801,
0.13678687810897827,
0.2945443391799927,
-0.011159442365169525,
-0.27710604667663574,
-0.5036942958831787,
0.1726938784122467,
0.24136310815811157,
0.06933782994747162,
0.024126015603542328,
0.05193420872092247,
0.2529219090938568,
0.01719309762120247,
-0.06566262990236282,
0.9180787801742554,
0.031080707907676697,
0.07061383873224258,
0.09902819991111755,
-0.20347744226455688
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | From what I can tell here: https://github.com/huggingface/nlp/blob/master/tests/utils.py#L115
1. `data_url` is the correct http link
2. `path_to_dummy_data` is a directory, which is causing the issue
That path comes from `download_dummy_data`, which I think assumes that the data comes from the zip file, but isn't aware of individual files. So it seems like it data manager needs to be aware if the url its getting is for a file or a zip/directory, and pass this information along. This might happen in `download_dummy_data`, but probably better to happen in `download_and_extract`? Maybe a simple check to see if `os.path.basename` returns the dummy data zip filename, if not then join paths with the basename of the url? | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 112 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
From what I can tell here: https://github.com/huggingface/nlp/blob/master/tests/utils.py#L115
1. `data_url` is the correct http link
2. `path_to_dummy_data` is a directory, which is causing the issue
That path comes from `download_dummy_data`, which I think assumes that the data comes from the zip file, but isn't aware of individual files. So it seems like it data manager needs to be aware if the url its getting is for a file or a zip/directory, and pass this information along. This might happen in `download_dummy_data`, but probably better to happen in `download_and_extract`? Maybe a simple check to see if `os.path.basename` returns the dummy data zip filename, if not then join paths with the basename of the url? | [
-0.07890299707651138,
0.2855145335197449,
0.0002486761659383774,
0.052755214273929596,
0.05063414201140404,
-0.260754257440567,
0.21438196301460266,
0.2759755849838257,
-0.05403422564268112,
0.08017334342002869,
0.20722761750221252,
0.22357384860515594,
-0.2214677333831787,
-0.034581124782562256,
0.12442823499441147,
0.05447620525956154,
-0.10658464580774307,
0.0847872644662857,
-0.22504177689552307,
0.15503334999084473,
-0.24932248890399933,
0.175332173705101,
0.0034216642379760742,
0.16723057627677917,
0.015413494780659676,
0.14610643684864044,
-0.22377105057239532,
0.20182129740715027,
-0.4194304645061493,
-0.7930228114128113,
0.3121379017829895,
0.030213307589292526,
0.23527833819389343,
0.3840058743953705,
-0.00012361556582618505,
-0.09185232222080231,
0.5898000001907349,
-0.15598922967910767,
-0.7334057092666626,
-0.42152416706085205,
0.2433733344078064,
-0.5072743892669678,
0.2773005962371826,
-0.1551036238670349,
0.18571290373802185,
-0.06349457055330276,
0.2981802523136139,
0.20960953831672668,
0.18837349116802216,
0.4003972113132477,
0.07241328805685043,
0.30033084750175476,
0.051999133080244064,
-0.1126798614859581,
0.00852164626121521,
0.1745273917913437,
-0.05216128006577492,
0.587381899356842,
0.20252278447151184,
0.07431738078594208,
-0.15627047419548035,
-0.07906942069530487,
0.10531939566135406,
0.5026991367340088,
0.15227723121643066,
0.06298090517520905,
0.39901190996170044,
0.04652874916791916,
-0.26758745312690735,
0.08663026243448257,
0.6675558090209961,
-0.5247460007667542,
-0.35870662331581116,
-0.0709836483001709,
-0.07901205867528915,
-0.057431042194366455,
0.38079071044921875,
-0.1414184868335724,
-0.41265830397605896,
0.09209894388914108,
-0.10644978284835815,
-0.17128974199295044,
-0.03199546039104462,
0.39670461416244507,
-0.2983643412590027,
0.4051721394062042,
-0.01846560835838318,
0.16227881610393524,
0.1562568098306656,
0.05911780148744583,
0.256651908159256,
-0.17506058514118195,
0.17345485091209412,
0.18063046038150787,
0.10605965554714203,
-0.20942501723766327,
-0.2895841598510742,
-0.27422627806663513,
0.1452917456626892,
0.11145221441984177,
-0.30826395750045776,
-0.19240990281105042,
-0.06261324882507324,
0.22528690099716187,
0.23071277141571045,
0.3241159915924072,
0.1796366274356842,
0.2692381739616394,
0.2589324116706848,
0.30539003014564514,
0.2700367271900177,
0.16195189952850342,
0.007208423689007759,
-0.33093106746673584,
-0.121018186211586,
0.15665867924690247,
0.2048185169696808,
-0.21207661926746368,
-0.19729706645011902,
-0.2485964596271515,
-0.4048672914505005,
-0.1265595555305481,
-0.06877486407756805,
0.31161001324653625,
-0.19009706377983093,
-0.10306080430746078,
0.09242895245552063,
0.3832482695579529,
-0.12803812325000763,
-0.07070959359407425,
0.028685245662927628,
0.043144356459379196,
-0.24823197722434998,
0.02863708883523941,
0.2963487207889557,
0.2202124446630478,
0.4854157269001007,
-0.29047438502311707,
-0.16111861169338226,
-0.058454759418964386,
0.12964698672294617,
0.04346011206507683,
-0.04721284657716751,
0.21914930641651154,
-0.07588900625705719,
0.18278975784778595,
0.09156713634729385,
-0.3037327527999878,
-0.2998288571834564,
0.17252540588378906,
-0.07229041308164597,
-0.4023594856262207,
0.10723474621772766,
0.06545607000589371,
-0.5473224520683289,
0.02173425815999508,
0.09589454531669617,
-0.16957339644432068,
-0.05753979831933975,
-0.3571425974369049,
0.04796421900391579,
-0.23688243329524994,
-0.25407958030700684,
-0.1595519483089447,
-0.013156723231077194,
0.3331226110458374,
-0.16873471438884735,
-0.31161749362945557,
-0.4004577696323395,
-0.29786086082458496,
0.2116445004940033,
-0.19554108381271362,
-0.1178334653377533,
0.272870808839798,
-0.4967009425163269,
0.06526096165180206,
0.6163495182991028,
-0.4722350835800171,
-0.29971882700920105,
0.5806673169136047,
-0.45252561569213867,
-0.06820160150527954,
0.263814240694046,
-0.036954089999198914,
-0.22122503817081451,
-0.2977391183376312,
-0.08449353277683258,
0.13490734994411469,
0.026060912758111954,
-0.15002301335334778,
-0.1978701651096344,
-0.3536168336868286,
0.14594607055187225,
0.23883675038814545,
-0.08798076212406158,
0.09268943965435028,
0.05308478698134422,
-0.07039500772953033,
0.45289844274520874,
0.10668683052062988,
0.06376808136701584,
-0.06113768368959427,
0.12078891694545746,
-0.19681991636753082,
-0.10716584324836731,
0.02618805319070816,
-0.5845916271209717,
0.12513163685798645,
-0.31481361389160156,
0.19763019680976868,
-0.1885025054216385,
-0.07421603798866272,
-0.5055443644523621,
-0.018278643488883972,
0.02284902334213257,
-0.2564987242221832,
0.009734272956848145,
0.35500970482826233,
0.09080711007118225,
-0.04917621612548828,
0.03225105628371239,
0.015585926361382008,
-0.20264923572540283,
0.2942972183227539,
-0.010932495817542076,
0.06413185596466064,
-0.08776205778121948,
0.11537980288267136,
0.24681350588798523,
0.2504459619522095,
0.16802050173282623,
-0.40396788716316223,
0.030690042302012444,
0.3176622688770294,
0.19105228781700134,
0.18399843573570251,
0.2012675404548645,
-0.06688788533210754,
0.16839499771595,
0.191099613904953,
0.08350713551044464,
0.46942803263664246,
0.04755901172757149,
-0.12958696484565735,
0.04580263793468475,
0.20797201991081238,
0.15497848391532898,
-0.0021299943327903748,
-0.07428234815597534,
0.07928677648305893,
0.3448399603366852,
0.022174391895532608,
-0.10134498029947281,
-0.2545163631439209,
0.10405221581459045,
0.3349344730377197,
0.6334259510040283,
-0.006708128377795219,
0.2735132575035095,
-0.10974115878343582,
-0.14043673872947693,
-0.3109172284603119,
0.046973202377557755,
0.14044451713562012,
-0.1851264238357544,
-0.10904297232627869,
0.0009038746356964111,
0.375546395778656,
0.8084438443183899,
-0.00867752730846405,
0.337849497795105,
0.09863558411598206,
-0.16344335675239563,
-0.23178473114967346,
0.24697157740592957,
0.1726224720478058,
-0.09168840199708939,
0.125870019197464,
-0.15991605818271637,
-0.3018524646759033,
-0.14503926038742065,
0.0199350044131279,
0.42337411642074585,
0.3181326985359192,
-0.4547545611858368,
-0.0568389967083931,
-0.2974061369895935,
-0.5187103152275085,
-0.5051658749580383,
-0.31656911969184875,
-0.20915921032428741,
-0.35626786947250366,
-0.056083157658576965,
0.28348276019096375,
-0.13092832267284393,
0.166825070977211,
-0.11503647267818451,
0.2502066493034363,
-0.32945573329925537,
-0.3059857487678528,
0.05414070188999176,
-0.09253225475549698,
-0.4306950271129608,
0.0013972930610179901,
0.40533092617988586,
0.09085674583911896,
0.25072017312049866,
-0.23175708949565887,
-0.2034362554550171,
-0.2620789706707001,
-0.27703648805618286,
0.13477784395217896,
0.18046344816684723,
0.5565597414970398,
0.4462127685546875,
-0.0005804598331451416,
0.4154548645019531,
0.023446351289749146,
0.021319406107068062,
-0.17712323367595673,
-0.3594783842563629,
-0.16657453775405884,
0.11461669206619263,
0.11637789756059647,
-0.17482349276542664,
-0.4352656900882721,
-0.5285282731056213,
-0.05853002518415451,
0.02924032136797905,
0.08637484908103943,
0.1540939211845398,
0.09188532829284668,
-0.17155218124389648,
0.18889687955379486,
0.04282163083553314,
-0.14498649537563324,
-0.1551208794116974,
-0.07493049651384354,
0.02633287012577057,
-0.14079639315605164,
-0.1739194393157959,
0.008674915879964828,
-0.2095598429441452,
0.05793796479701996,
-0.16223236918449402,
-0.40622490644454956,
-0.5565923452377319,
0.14096695184707642,
0.18127119541168213,
0.25342342257499695,
-0.15074804425239563,
0.37731078267097473,
0.18244123458862305,
0.09180489927530289,
-0.13267090916633606,
-0.3363349437713623,
0.2459818720817566,
0.10700096935033798,
0.40160325169563293,
0.2060067057609558,
0.2957024872303009,
-0.02632203698158264,
0.7256442308425903,
0.14918823540210724,
-0.07229571044445038,
0.09985023736953735,
-0.1860622614622116,
0.10383379459381104,
0.15628525614738464,
0.00590037927031517,
0.18452025949954987,
-0.15817192196846008,
-0.2670908570289612,
0.3186189830303192,
-0.19768214225769043,
-0.04666414111852646,
-0.11971660703420639,
0.2846112847328186,
-0.25960278511047363,
-0.12736406922340393,
0.12735623121261597,
-0.05860152840614319,
-0.04352828860282898,
0.09806585311889648,
-0.04892734810709953,
-0.16124717891216278,
-0.061358604580163956,
0.12111495435237885,
0.35151779651641846,
0.033287689089775085,
0.14570960402488708,
-0.3123936951160431,
-0.04856228455901146,
-0.33045876026153564,
0.28733155131340027,
0.382264643907547,
0.42916834354400635,
0.05898071452975273,
0.013043813407421112,
0.0952792763710022,
0.0012861217837780714,
0.2868995666503906,
0.019052179530262947,
0.15850667655467987,
0.13101911544799805,
-0.15485472977161407,
0.02473199926316738,
-0.15523315966129303,
-0.09564242511987686,
0.09846919029951096,
0.007519437000155449,
0.15079307556152344,
-0.46832722425460815,
-0.13879436254501343,
0.19019170105457306,
0.1147201880812645,
-0.058022391051054,
-0.22207745909690857,
-0.01593119278550148,
-0.12120790779590607,
-0.047307536005973816,
-0.22213134169578552,
-0.14633366465568542,
-0.009872816503047943,
-0.10142961889505386,
0.29026487469673157,
0.07743420451879501,
-0.1481543332338333,
-0.014838173985481262,
0.08856996893882751,
0.2045021653175354,
-0.3280985951423645,
0.11342334747314453,
0.27185356616973877,
0.19918057322502136,
0.22384952008724213,
0.40062448382377625,
-0.1000058501958847,
-0.21022135019302368,
0.03399192914366722,
0.05974150821566582,
0.3214837610721588,
0.4006612002849579,
0.10434781759977341,
-0.039059631526470184,
-0.2513597905635834,
-0.15662208199501038,
-0.33567067980766296,
0.22357992827892303,
0.4120948612689972,
-0.10309460014104843,
0.1445939540863037,
-0.22911985218524933,
0.6646549701690674,
0.13159412145614624,
-0.2383853942155838,
0.5089074373245239,
-0.28388911485671997,
-0.2806604504585266,
-0.077364481985569,
0.046777043491601944,
1.0281771421432495,
0.24669449031352997,
0.25193649530410767,
0.4927613437175751,
-0.26039767265319824,
0.2928636074066162,
0.06944653391838074,
0.09858127683401108,
-0.43218085169792175,
0.01908116042613983,
-0.06404997408390045,
-0.20193004608154297,
0.25413867831230164,
0.0323689728975296,
-0.23341050744056702,
0.33858874440193176,
0.1327558159828186,
0.38942986726760864,
0.24295952916145325,
0.4002091884613037,
-0.24319452047348022,
-0.02153216302394867,
-0.2314874529838562,
0.04449514299631119,
-0.02915450930595398,
0.357897013425827,
-0.20181342959403992,
-0.08174533396959305,
-0.20169222354888916,
-0.13223759829998016,
-0.0011773854494094849,
-0.08184608072042465,
-0.3922838568687439,
0.028829768300056458,
0.0667119100689888,
-0.10534249246120453,
-0.23339538276195526,
0.2026793509721756,
0.10940498113632202,
-0.2765062749385834,
-0.131254643201828,
0.14214517176151276,
-0.31567680835723877,
0.2580554187297821,
0.32302427291870117,
-0.006119425408542156,
0.24911458790302277,
-0.3315946161746979,
-0.026277735829353333,
0.07291926443576813,
-0.3236357271671295,
-0.19239988923072815,
0.07747150957584381,
-0.21757884323596954,
0.07555195689201355,
-0.3103991746902466,
-0.2757740318775177,
-0.1316889226436615,
-0.08827870339155197,
-0.11784468591213226,
-0.004206649959087372,
0.22242960333824158,
-0.35297122597694397,
-0.07808303087949753,
-0.06195707991719246,
-0.26087620854377747,
-0.005462471395730972,
0.41550642251968384,
-0.2048795223236084,
-0.048417191952466965,
0.6307448148727417,
-0.41792699694633484,
0.09337036311626434,
-0.07985340058803558,
0.13359007239341736,
-0.15759526193141937,
-0.11624114215373993,
0.05989890545606613,
-0.08217970281839371,
-0.31458503007888794,
-0.05027610808610916,
0.5699489712715149,
0.42291873693466187,
0.1599046289920807,
-0.18029290437698364,
-0.4978507161140442,
-0.30219781398773193,
0.04070744663476944,
-0.19161346554756165,
0.1929028332233429,
-0.08632348477840424,
0.21488791704177856,
0.23817583918571472,
0.0008389707654714584,
-0.17753931879997253,
-0.11061951518058777,
-0.044823408126831055,
0.18705295026302338,
-0.17645959556102753,
0.028117746114730835,
0.08777680993080139,
0.11093795299530029,
-0.05144146829843521,
0.07127989083528519,
-0.26637977361679077,
-0.03337724506855011,
-0.10417591035366058,
0.22602683305740356,
0.15439248085021973,
-0.07422837615013123,
0.1739831566810608,
-0.14891168475151062,
0.02848183363676071,
0.15573972463607788,
-0.13240166008472443,
-0.0511799156665802,
-0.030449509620666504,
0.11647063493728638,
0.23405784368515015,
0.0443299263715744,
-0.20257171988487244,
0.2824553847312927,
-0.0093793123960495,
0.15508587658405304,
-0.09460094571113586,
0.20901909470558167,
-0.32232046127319336,
0.03160156309604645,
0.17144279181957245,
0.0984681248664856,
-0.06700043380260468,
0.2769375145435333,
0.13658586144447327,
0.0017016790807247162,
0.0024577639997005463,
-0.04743047058582306,
0.3074738681316376,
0.7473387718200684,
-0.20278300344944,
-0.1288805902004242,
0.46390342712402344,
-0.003537174314260483,
-0.211854487657547,
0.06120787560939789,
0.1913791447877884,
0.004370968788862228,
0.0706610381603241,
0.2556614279747009,
0.045390624552965164,
0.0798020213842392,
0.2536444067955017,
0.05678654462099075,
0.15905046463012695,
-0.06254468113183975,
-0.05567086860537529,
0.5163021683692932,
-0.24758440256118774,
0.34521734714508057,
0.34482505917549133,
-0.026771780103445053,
0.31721267104148865,
0.043735288083553314,
-0.022251777350902557,
0.548308789730072,
-0.005632694810628891,
0.007812529802322388,
0.12488171458244324,
0.007367581129074097,
-0.10260365903377533,
0.20615416765213013,
0.0983358845114708,
0.05027972534298897,
0.25428175926208496,
0.6443103551864624,
-0.5301637053489685,
-0.19425921142101288,
-0.2695655822753906,
-0.09844449162483215,
0.08751742541790009,
-0.11784860491752625,
-0.45354101061820984,
-0.008798956871032715,
-0.325763463973999,
-0.14106620848178864,
-0.13782058656215668,
-0.3443898558616638,
0.25596433877944946,
0.003879956901073456,
-0.3412185311317444,
-0.25168558955192566,
-0.43340232968330383,
0.13744866847991943,
-0.04456020146608353,
-0.3266587257385254,
0.2011287808418274,
0.033438317477703094,
0.031245622783899307,
0.27481305599212646,
0.29906928539276123,
0.4600580930709839,
0.07712925970554352,
-0.2869519293308258,
-0.3478582799434662,
-0.1940525621175766,
0.07553841173648834,
-0.07693585008382797,
0.2965201437473297,
0.006350502371788025,
-0.16871435940265656,
0.5234032273292542,
0.04897032678127289,
0.015593406744301319,
0.2165277898311615,
0.4239833354949951,
-0.4900081157684326,
-0.1489172875881195,
0.7677968740463257,
-0.07951385527849197,
-0.08629504591226578,
-0.05311248451471329,
-0.0124601349234581,
-0.2715527415275574,
0.06507033109664917,
-0.10145239531993866,
-0.13405360281467438,
0.22263294458389282,
0.12485482543706894,
0.026110291481018066,
-0.059313204139471054,
0.29371005296707153,
0.36874908208847046,
-0.12910723686218262,
-0.4022064507007599,
-0.2841159701347351,
-0.9730969667434692,
0.07774315774440765,
0.019219333305954933,
-0.3939654529094696,
-0.07160516828298569,
-0.276656836271286,
0.21714946627616882,
0.11051171272993088,
-0.2178172916173935,
0.2072967290878296,
0.24071791768074036,
0.04598340019583702,
-0.26249340176582336,
-0.3137997090816498,
-0.24278898537158966,
0.03638816624879837,
-0.04189561679959297,
-0.4255923628807068,
0.11773188412189484,
-0.22743497788906097,
-0.14005209505558014,
0.2893140912055969,
-0.04074516519904137,
0.34043124318122864,
0.0762927234172821,
0.28897255659103394,
-0.07201776653528214,
0.6170159578323364,
0.10390684753656387,
0.010898256674408913,
-0.11753702163696289,
0.21040001511573792,
-0.11691687256097794,
0.0672914907336235,
-0.07970216870307922,
0.20908327400684357,
-0.18039096891880035,
0.6635023355484009,
-0.5068444013595581,
0.4374556839466095,
0.04022591561079025,
0.08135279268026352,
-0.26135605573654175,
0.10217372328042984,
-0.3644084334373474,
0.13158951699733734,
0.35818034410476685,
0.28291043639183044,
-0.12177640199661255,
0.30615195631980896,
-0.1378706991672516,
-0.19781450927257538,
0.3982648551464081,
-0.12612102925777435,
-0.041531506925821304,
0.04977952316403389,
0.2727915346622467,
-0.09283065050840378,
-0.061108775436878204,
-0.44523483514785767,
0.05422306805849075,
0.27372869849205017,
0.02921084128320217,
0.11292874813079834,
0.09593437612056732,
0.15679357945919037,
0.11953762173652649,
-0.06224054843187332,
0.8743886947631836,
0.04461134970188141,
0.017599323764443398,
0.0011314190924167633,
-0.24424110352993011
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | I think the dataset script works correctly. Just the dummy data structure seems to be wrong. I will soon add more commands that should make the create of the dummy data easier.
I'd recommend that you won't concentrate too much on the dummy data.
If you manage to load the dataset correctly via:
```python
# use local path to qanta
nlp.load_dataset("./datasets/qanta")
```
then feel free to open a PR and we will look into the dummy data problem together :-)
Also please make sure that the Version is in the format 1.0.0 (three numbers separated by two points) - not a date. | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 102 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
I think the dataset script works correctly. Just the dummy data structure seems to be wrong. I will soon add more commands that should make the create of the dummy data easier.
I'd recommend that you won't concentrate too much on the dummy data.
If you manage to load the dataset correctly via:
```python
# use local path to qanta
nlp.load_dataset("./datasets/qanta")
```
then feel free to open a PR and we will look into the dummy data problem together :-)
Also please make sure that the Version is in the format 1.0.0 (three numbers separated by two points) - not a date. | [
-0.16123457252979279,
0.25518926978111267,
0.016922496259212494,
-0.0688912570476532,
-0.01873302087187767,
-0.07994215935468674,
0.4035909175872803,
0.33871880173683167,
0.07540589570999146,
0.048679523169994354,
0.19280530512332916,
0.1107184961438179,
-0.29939645528793335,
0.10281576961278915,
0.10059244930744171,
-0.11661408841609955,
0.022554785013198853,
0.22912092506885529,
-0.17938730120658875,
0.22091637551784515,
-0.25348174571990967,
0.10033519566059113,
-0.11082915961742401,
0.17837145924568176,
-0.011252150870859623,
0.1582915186882019,
-0.28702640533447266,
0.0593031570315361,
-0.33930763602256775,
-0.7205919027328491,
0.35620036721229553,
0.07208052277565002,
0.2591177821159363,
0.4941641688346863,
-0.00012244142999406904,
-0.07432939857244492,
0.5197003483772278,
-0.1447192281484604,
-0.675597071647644,
-0.23255501687526703,
0.24015584588050842,
-0.35562556982040405,
0.33595699071884155,
0.001460447907447815,
0.05675724148750305,
-0.22579844295978546,
0.24793411791324615,
0.1120186448097229,
0.22972828149795532,
0.36378130316734314,
0.13691160082817078,
0.29282712936401367,
0.05487312749028206,
-0.12325570732355118,
-0.14173871278762817,
-0.011339962482452393,
-0.11851313710212708,
0.544145405292511,
0.34197700023651123,
0.03315939009189606,
0.007737316191196442,
-0.05453301966190338,
0.08724568039178848,
0.39128631353378296,
0.19234415888786316,
0.00016621872782707214,
0.5235511064529419,
-0.04455576092004776,
-0.11648385971784592,
0.0907764807343483,
0.7365921139717102,
-0.5787572264671326,
-0.38571593165397644,
-0.00001623481512069702,
0.051615335047245026,
-0.11142754554748535,
0.17219947278499603,
-0.1005590409040451,
-0.29932621121406555,
0.05937647074460983,
-0.10987194627523422,
-0.22395355999469757,
-0.10024036467075348,
0.2735373079776764,
-0.21386848390102386,
0.23304477334022522,
0.06023814529180527,
0.22848206758499146,
0.0010030008852481842,
-0.10714861750602722,
0.19523392617702484,
-0.130006343126297,
-0.05614924803376198,
0.2684307396411896,
-0.09157226979732513,
-0.18151730298995972,
-0.344387024641037,
-0.1629757583141327,
0.13957548141479492,
-0.1011957973241806,
-0.31825655698776245,
-0.11622599512338638,
0.0414256751537323,
0.18302571773529053,
0.15644404292106628,
0.36657193303108215,
0.2711389660835266,
0.2031317502260208,
0.12128384411334991,
0.1413872390985489,
0.2718666195869446,
0.20314240455627441,
-0.06695925444364548,
-0.3533778488636017,
-0.012509308755397797,
0.09310374408960342,
0.20516282320022583,
-0.279924601316452,
-0.16181987524032593,
-0.21086351573467255,
-0.3621448278427124,
0.011534607037901878,
-0.12015796452760696,
0.3297590911388397,
-0.19222243130207062,
-0.18938562273979187,
0.07900408655405045,
0.5592828989028931,
-0.20093844830989838,
-0.21602337062358856,
-0.01442256011068821,
0.02494082972407341,
-0.21503762900829315,
-0.06536278128623962,
0.2374853938817978,
0.009567760862410069,
0.40282773971557617,
-0.255793035030365,
-0.2903883457183838,
-0.006051894277334213,
0.2314986139535904,
0.020160995423793793,
-0.1914072036743164,
0.2558795213699341,
-0.05008906126022339,
-0.02477305382490158,
0.10018885135650635,
-0.33269721269607544,
-0.22785735130310059,
0.22125381231307983,
0.10084739327430725,
-0.46670836210250854,
-0.2118019014596939,
0.09065298736095428,
-0.4503854513168335,
0.021674536168575287,
0.017006002366542816,
-0.046402547508478165,
0.09855165332555771,
-0.36174729466438293,
-0.08257303386926651,
-0.4229154586791992,
-0.2915908098220825,
-0.11434758454561234,
-0.057407885789871216,
0.32801368832588196,
-0.43154019117355347,
-0.27291274070739746,
-0.40979209542274475,
-0.29973480105400085,
0.10333655774593353,
-0.26148858666419983,
-0.07541268318891525,
0.2706596255302429,
-0.39036864042282104,
-0.10745108127593994,
0.5073695778846741,
-0.5006064176559448,
-0.2522049844264984,
0.44504252076148987,
-0.3928949236869812,
-0.19235235452651978,
0.17964544892311096,
0.03588748350739479,
0.002271756064146757,
-0.2983287572860718,
-0.12099172174930573,
0.07886011153459549,
0.08520586043596268,
-0.13364507257938385,
-0.1600973904132843,
-0.3697941303253174,
0.139165997505188,
0.2701592743396759,
-0.08963312208652496,
0.1255897730588913,
0.021427154541015625,
-0.011060118675231934,
0.33645498752593994,
0.08014397323131561,
0.1863797903060913,
-0.08931335061788559,
0.11018542945384979,
-0.1883334070444107,
-0.09345072507858276,
-0.011489389464259148,
-0.6761329174041748,
0.2105301022529602,
-0.20468048751354218,
0.3002508282661438,
-0.01447094976902008,
0.03403789550065994,
-0.602074146270752,
0.01895187236368656,
-0.08776955306529999,
-0.2432880401611328,
0.04227837175130844,
0.19854815304279327,
0.13480232656002045,
0.05542029067873955,
0.0055914223194122314,
0.13680914044380188,
-0.15025188028812408,
0.25498688220977783,
-0.07851333916187286,
-0.028988558799028397,
-0.11474830657243729,
0.09138835966587067,
0.30210480093955994,
0.28191596269607544,
0.08846971392631531,
-0.3099205493927002,
0.05243707820773125,
0.28284236788749695,
0.2346717268228531,
0.14354732632637024,
0.2016160488128662,
-0.11179046332836151,
0.08561429381370544,
0.22559982538223267,
0.2614986002445221,
0.3159290552139282,
0.10255780816078186,
-0.21182101964950562,
-0.001661062240600586,
0.24940182268619537,
0.2455359399318695,
-0.004479527473449707,
-0.22424300014972687,
0.058573052287101746,
0.29595980048179626,
0.10568228363990784,
-0.10605470091104507,
-0.31116706132888794,
0.09343528002500534,
0.3330496847629547,
0.5936193466186523,
-0.09914626181125641,
0.19831421971321106,
-0.03524620085954666,
-0.26504409313201904,
-0.320637971162796,
0.11222005635499954,
0.11663520336151123,
-0.283305287361145,
-0.10186264663934708,
0.032512299716472626,
0.2716321349143982,
0.8015956282615662,
-0.05509653687477112,
0.05959898978471756,
0.11370687186717987,
-0.153585746884346,
-0.1946409046649933,
0.19420088827610016,
0.10261137783527374,
-0.07959931343793869,
0.11133971810340881,
-0.04581393301486969,
-0.3477388322353363,
-0.03733554854989052,
-0.00987880676984787,
0.41767418384552,
0.40672385692596436,
-0.40734031796455383,
-0.05698326975107193,
-0.15354426205158234,
-0.37526407837867737,
-0.38578373193740845,
-0.3960627317428589,
-0.20939934253692627,
-0.3791486918926239,
-0.06100854277610779,
0.3446577489376068,
0.018216382712125778,
0.25030481815338135,
-0.09401370584964752,
0.26372215151786804,
-0.20558635890483856,
-0.3096761107444763,
0.1600995659828186,
-0.13870495557785034,
-0.4587654173374176,
0.03016543760895729,
0.24290655553340912,
0.16651377081871033,
0.36580029129981995,
-0.26891186833381653,
-0.21224729716777802,
-0.20119880139827728,
-0.31963756680488586,
0.1471567153930664,
-0.010631486773490906,
0.6500743627548218,
0.4507486820220947,
0.05853548273444176,
0.29792624711990356,
0.11121876537799835,
0.003967395052313805,
-0.1363392025232315,
-0.3817053437232971,
-0.08096225559711456,
-0.021139590069651604,
0.06345357745885849,
-0.1135386973619461,
-0.4393893778324127,
-0.5979088544845581,
-0.02806536667048931,
0.07417380809783936,
0.11462894082069397,
0.12124425172805786,
0.13008537888526917,
-0.01536463387310505,
0.18101954460144043,
0.03190884366631508,
-0.19629228115081787,
-0.1938023418188095,
0.05310021713376045,
0.08232904970645905,
-0.17546875774860382,
-0.28174200654029846,
0.16572795808315277,
-0.21765828132629395,
0.08913887292146683,
-0.26760947704315186,
-0.4637167453765869,
-0.46481841802597046,
0.24480928480625153,
0.163632333278656,
0.30453333258628845,
-0.20452965795993805,
0.29216694831848145,
0.251864492893219,
0.17327265441417694,
-0.12148859351873398,
-0.3563101589679718,
0.20366646349430084,
0.015652041882276535,
0.32238906621932983,
0.19924810528755188,
0.39701831340789795,
-0.27665087580680847,
0.7669869661331177,
0.18207097053527832,
-0.08122356235980988,
-0.03907804191112518,
-0.2118774652481079,
0.09913470596075058,
-0.08708595484495163,
-0.05764743685722351,
0.23883286118507385,
-0.1382332444190979,
-0.2020779699087143,
0.3131054639816284,
-0.17024582624435425,
-0.009244050830602646,
-0.12770086526870728,
0.23863375186920166,
-0.11140106618404388,
-0.06311244517564774,
0.059580087661743164,
-0.16654354333877563,
0.03780529275536537,
0.098680779337883,
-0.014956295490264893,
-0.26176801323890686,
-0.19446444511413574,
-0.05254671350121498,
0.3353535830974579,
0.0021536946296691895,
0.11820797622203827,
-0.3188006281852722,
0.01123667974025011,
-0.42654624581336975,
0.27860593795776367,
0.2302422970533371,
0.5973356366157532,
0.12704850733280182,
0.08186542987823486,
0.10294012725353241,
0.10305597633123398,
0.21146516501903534,
-0.007445132359862328,
0.099692702293396,
0.2119990736246109,
-0.0997568815946579,
-0.21547281742095947,
-0.24166740477085114,
-0.08823574334383011,
0.15256533026695251,
-0.04120660200715065,
0.12435625493526459,
-0.4224529266357422,
-0.06276498734951019,
0.23153817653656006,
0.19613614678382874,
-0.18541806936264038,
-0.3014693558216095,
-0.19508326053619385,
-0.013291332870721817,
-0.10634040832519531,
-0.22760498523712158,
-0.2369612753391266,
0.07546576857566833,
-0.19839833676815033,
0.434601366519928,
0.026548190042376518,
-0.0950339064002037,
-0.0094674751162529,
0.22040186822414398,
0.21856418251991272,
-0.22556573152542114,
0.34710660576820374,
0.212654709815979,
0.04422229155898094,
0.1937830001115799,
0.2733420133590698,
0.04669993370771408,
-0.26991817355155945,
0.07171868532896042,
-0.055965546518564224,
0.3882956802845001,
0.2309386134147644,
0.07861830294132233,
-0.00005412846803665161,
-0.2286573350429535,
-0.15552125871181488,
-0.2668573260307312,
0.11353760957717896,
0.36508840322494507,
-0.012089261785149574,
-0.057566914707422256,
-0.3237791657447815,
0.5772803425788879,
0.1279294192790985,
-0.2223547101020813,
0.3620973527431488,
-0.2282121330499649,
-0.2341749221086502,
0.1770775318145752,
0.05815240740776062,
0.8921768665313721,
0.16323108971118927,
0.26067525148391724,
0.4901677072048187,
-0.2221510261297226,
0.35116297006607056,
0.21474815905094147,
0.11311942338943481,
-0.6522517204284668,
-0.002711131237447262,
0.03967949002981186,
-0.14634232223033905,
0.21416574716567993,
-0.14346690475940704,
-0.33664727210998535,
0.3871508240699768,
0.004389531910419464,
0.2776857614517212,
0.28608784079551697,
0.3106580376625061,
-0.178711399435997,
-0.027079682797193527,
-0.11676041781902313,
0.08298251032829285,
-0.08146439492702484,
0.3729132413864136,
-0.23302605748176575,
-0.07518521696329117,
-0.26928502321243286,
-0.062462709844112396,
-0.19180415570735931,
-0.13464801013469696,
-0.16934475302696228,
-0.052009984850883484,
0.11992661654949188,
-0.11077143251895905,
-0.04196767508983612,
0.23126064240932465,
0.24265559017658234,
-0.14473292231559753,
-0.2273571789264679,
0.05623307079076767,
-0.2652631402015686,
0.07546389847993851,
0.32904568314552307,
0.06114065647125244,
0.25031226873397827,
-0.2712119221687317,
-0.1735934019088745,
0.10917004197835922,
-0.24852509796619415,
-0.06863466650247574,
-0.14945855736732483,
-0.20029298961162567,
0.1652698963880539,
-0.3002743422985077,
-0.3457500636577606,
-0.11714127659797668,
-0.049097299575805664,
-0.09219112992286682,
0.02859160676598549,
0.22841797769069672,
-0.34068039059638977,
-0.005799546837806702,
-0.11406514048576355,
-0.2673192024230957,
-0.028432749211788177,
0.4541555643081665,
-0.029472291469573975,
-0.01376478374004364,
0.8067978620529175,
-0.09696400165557861,
0.1509828418493271,
-0.12489811331033707,
0.0640556737780571,
-0.00214083562605083,
-0.20873409509658813,
0.007497620768845081,
-0.07276029884815216,
-0.3054572343826294,
0.06333999335765839,
0.6002620458602905,
0.3502771854400635,
-0.006405100226402283,
-0.015813302248716354,
-0.5503168106079102,
-0.47054189443588257,
-0.01743742823600769,
-0.13372236490249634,
0.10882799327373505,
-0.09000854194164276,
0.1982867568731308,
0.259976327419281,
0.030203042551875114,
-0.20928725600242615,
-0.13878828287124634,
-0.02385549061000347,
0.19493086636066437,
-0.1560315042734146,
0.01562574878334999,
0.04091256856918335,
0.10926033556461334,
-0.015660665929317474,
0.01699753664433956,
-0.39186587929725647,
-0.07138168066740036,
-0.10062699019908905,
0.20227810740470886,
0.11084682494401932,
-0.11428558081388474,
0.06330285221338272,
-0.12285292148590088,
-0.11143916845321655,
0.19947606325149536,
-0.0942072719335556,
0.017175450921058655,
-0.1065148115158081,
0.18531452119350433,
0.3287245035171509,
0.051338911056518555,
-0.09047839790582657,
0.2512051463127136,
0.10262133926153183,
0.189700186252594,
-0.11579453200101852,
0.2186831831932068,
-0.25777652859687805,
0.04440464824438095,
0.12394805252552032,
0.13644638657569885,
-0.06430709362030029,
0.31939175724983215,
0.1831655204296112,
-0.14177630841732025,
0.14575521647930145,
-0.12332576513290405,
0.3411395251750946,
0.7627294659614563,
-0.2596036195755005,
-0.1603023260831833,
0.4350288510322571,
0.04208820313215256,
-0.23856458067893982,
0.005389163736253977,
0.20815473794937134,
0.10267128795385361,
0.05342177674174309,
0.26197218894958496,
0.0547143928706646,
-0.08130946010351181,
0.17981886863708496,
0.1486179530620575,
0.1108655333518982,
-0.19002793729305267,
-0.08867540955543518,
0.504672646522522,
-0.2913787364959717,
0.2332158386707306,
0.37284061312675476,
0.042408380657434464,
0.1642451137304306,
0.16576366126537323,
0.0522635318338871,
0.47337597608566284,
0.055275097489356995,
0.05170278996229172,
0.11520883440971375,
-0.026024559512734413,
-0.004513751715421677,
0.3991509974002838,
-0.009431816637516022,
0.008123233914375305,
0.3110029995441437,
0.5946427583694458,
-0.4088001847267151,
-0.15509100258350372,
-0.3245684802532196,
-0.10484825074672699,
0.035217925906181335,
-0.13292965292930603,
-0.38027244806289673,
0.07117969542741776,
-0.253785103559494,
-0.15523608028888702,
-0.1535770148038864,
-0.32617002725601196,
0.1191234141588211,
0.0025212764739990234,
-0.3347843885421753,
-0.23041340708732605,
-0.46209514141082764,
0.296138197183609,
-0.10243219882249832,
-0.21056632697582245,
0.2456563264131546,
0.06732206046581268,
0.13905887305736542,
0.35602322220802307,
0.38687512278556824,
0.4162227213382721,
0.15023067593574524,
-0.4203754961490631,
-0.17785893380641937,
-0.15420058369636536,
0.10862676799297333,
0.07844686508178711,
0.3482341170310974,
-0.01889950782060623,
-0.18846863508224487,
0.551433801651001,
0.06358034908771515,
0.041565146297216415,
0.2617347538471222,
0.4324660897254944,
-0.4136831760406494,
-0.1912732571363449,
0.7280192375183105,
-0.14776593446731567,
-0.12769809365272522,
-0.11568330228328705,
0.17403200268745422,
-0.3391324281692505,
0.1881857067346573,
0.05504055321216583,
-0.011934895068407059,
0.20172029733657837,
0.004270358011126518,
0.0377386100590229,
-0.1704934686422348,
0.42981845140457153,
0.39635366201400757,
-0.030322395265102386,
-0.4015501141548157,
-0.241623654961586,
-0.8262504935264587,
0.19436654448509216,
-0.09572447836399078,
-0.317832887172699,
-0.037830013781785965,
-0.23111912608146667,
0.19117669761180878,
0.14636509120464325,
-0.2504756450653076,
0.2390633225440979,
-0.015760596841573715,
0.1646002233028412,
-0.351351261138916,
-0.3869234621524811,
-0.2707552909851074,
0.11316990852355957,
-0.08452510088682175,
-0.4501946270465851,
0.1749820113182068,
-0.2466265857219696,
-0.09763594716787338,
0.16377025842666626,
-0.01951543614268303,
0.4524601101875305,
0.10025601834058762,
0.3120701313018799,
-0.04562416672706604,
0.5762510895729065,
0.17790579795837402,
-0.040750354528427124,
-0.23221498727798462,
0.19575996696949005,
-0.1450602412223816,
0.09771563112735748,
0.049104947596788406,
0.15912657976150513,
-0.12989236414432526,
0.5070652365684509,
-0.3636961281299591,
0.4363595247268677,
0.08669717609882355,
0.1201665997505188,
-0.4500044286251068,
0.17375850677490234,
-0.22239556908607483,
0.1384895145893097,
0.24804355204105377,
0.26967653632164,
-0.10547012090682983,
0.4141574501991272,
-0.18960265815258026,
-0.05892527848482132,
0.4289872944355011,
-0.20631742477416992,
-0.10361835360527039,
0.06802307814359665,
0.19691064953804016,
-0.11535202711820602,
-0.17309705913066864,
-0.4120732247829437,
0.2724257707595825,
0.24500282108783722,
-0.06220118701457977,
0.1468648612499237,
0.16532815992832184,
0.261756956577301,
0.09281069040298462,
-0.012294737622141838,
0.8619529008865356,
-0.04305990785360336,
0.12368963658809662,
-0.07380132377147675,
-0.23250676691532135
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | The script loading seems to work fine so I'll work on getting a PR open after a few sanity checks on the data.
On version, we currently have it versioned with YYYY.MM.DD scheme so it would be nice to not change that, but will it cause issues? | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 47 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
The script loading seems to work fine so I'll work on getting a PR open after a few sanity checks on the data.
On version, we currently have it versioned with YYYY.MM.DD scheme so it would be nice to not change that, but will it cause issues? | [
-0.17673911154270172,
0.211175799369812,
-0.009480161592364311,
-0.13179269433021545,
0.07344302535057068,
-0.14275367558002472,
0.4176613688468933,
0.2573600709438324,
0.04997287318110466,
0.11905574053525925,
0.22333268821239471,
0.06963523477315903,
-0.2887466251850128,
0.08405555784702301,
0.09769432246685028,
-0.007682241499423981,
0.06393394619226456,
0.14133603870868683,
-0.10444194078445435,
0.20766906440258026,
-0.25531724095344543,
-0.005777670070528984,
-0.05395089089870453,
0.10496244579553604,
-0.021724596619606018,
0.12302412837743759,
-0.209518700838089,
0.10340224206447601,
-0.43610069155693054,
-0.8527143001556396,
0.3802427053451538,
0.10694992542266846,
0.288836807012558,
0.3949592411518097,
-0.00012843438889831305,
-0.05747811868786812,
0.5988147258758545,
-0.1096535176038742,
-0.6252241134643555,
-0.1496017426252365,
0.27855581045150757,
-0.3912251591682434,
0.3590851426124573,
-0.03522179648280144,
0.1500791609287262,
-0.1874672919511795,
0.21873152256011963,
0.041837818920612335,
0.1443508267402649,
0.2882784307003021,
0.0764792263507843,
0.2813306748867035,
0.06819677352905273,
-0.21769098937511444,
-0.11556913703680038,
0.05953776836395264,
-0.08263536542654037,
0.5680218935012817,
0.4420577883720398,
0.16450203955173492,
-0.04790712147951126,
-0.1347491294145584,
0.09925621747970581,
0.45589518547058105,
0.18909728527069092,
-0.04519214481115341,
0.6421708464622498,
0.01721707358956337,
-0.14175671339035034,
-0.0005506984889507294,
0.9479653239250183,
-0.5009499192237854,
-0.39741554856300354,
0.05029571056365967,
-0.011666812933981419,
-0.121365986764431,
0.23012828826904297,
-0.192775696516037,
-0.29002612829208374,
0.04725087806582451,
-0.17219513654708862,
-0.30624648928642273,
-0.12384654581546783,
0.30030035972595215,
-0.30258822441101074,
0.30529946088790894,
0.10334379225969315,
0.24936047196388245,
0.018844015896320343,
-0.11828610301017761,
0.28435900807380676,
-0.03635101020336151,
-0.014641761779785156,
0.18634501099586487,
0.07852449268102646,
-0.28582820296287537,
-0.3459250032901764,
-0.2041810154914856,
0.11312181502580643,
-0.041234441101551056,
-0.4233127534389496,
-0.18879029154777527,
-0.03495577722787857,
0.17621392011642456,
0.2227984070777893,
0.2793654501438141,
0.32268935441970825,
0.19643908739089966,
0.24403151869773865,
0.07674850523471832,
0.3281916081905365,
0.2670007646083832,
-0.07985208928585052,
-0.4030311107635498,
0.016208577901124954,
0.059761494398117065,
0.21140821278095245,
-0.35215792059898376,
-0.08716558665037155,
-0.26098182797431946,
-0.33429986238479614,
-0.04781266674399376,
-0.1376747190952301,
0.25438007712364197,
-0.11698386818170547,
-0.09509874135255814,
0.030406370759010315,
0.42387014627456665,
-0.15298610925674438,
-0.1591300517320633,
-0.010798684321343899,
0.014280443079769611,
-0.16778892278671265,
-0.01822957955300808,
0.21012519299983978,
0.08893676102161407,
0.3157946467399597,
-0.27740445733070374,
-0.20177383720874786,
0.003569364547729492,
-0.015546571463346481,
0.09739150106906891,
-0.19562101364135742,
0.2981414198875427,
-0.2475421279668808,
-0.021107912063598633,
0.043806929141283035,
-0.29938891530036926,
-0.20705442130565643,
0.2779179811477661,
0.09650816023349762,
-0.45383507013320923,
-0.017878426238894463,
0.04868265241384506,
-0.5866076350212097,
-0.006349720060825348,
-0.018574371933937073,
-0.11635701358318329,
0.11945286393165588,
-0.382311075925827,
0.01369631290435791,
-0.44516515731811523,
-0.3795369267463684,
-0.10745582729578018,
-0.15624310076236725,
0.2226879596710205,
-0.3308177590370178,
-0.2761637568473816,
-0.3116797208786011,
-0.34300097823143005,
0.15970644354820251,
-0.2424597293138504,
-0.09673304855823517,
0.09309795498847961,
-0.35627588629722595,
-0.21318884193897247,
0.51652991771698,
-0.6141237020492554,
-0.31686344742774963,
0.47944414615631104,
-0.3933299779891968,
-0.31927359104156494,
0.24876073002815247,
-0.020787766203284264,
0.09857186675071716,
-0.4370945990085602,
-0.12158043682575226,
-0.015840131789445877,
-0.01884741149842739,
-0.16953249275684357,
-0.21318617463111877,
-0.3432087004184723,
0.15771746635437012,
0.2769617438316345,
-0.06715589761734009,
0.1459978222846985,
0.1615191102027893,
0.1352694183588028,
0.3999654948711395,
0.19973193109035492,
0.15013937652111053,
-0.17016687989234924,
0.24233378469944,
-0.2819077968597412,
-0.03480280563235283,
-0.06494960188865662,
-0.6823077201843262,
0.20384737849235535,
-0.08313953876495361,
0.16828688979148865,
0.0175626203417778,
-0.010356884449720383,
-0.5097718834877014,
-0.004371738061308861,
0.0005457699298858643,
-0.18655158579349518,
-0.07908060401678085,
0.1180780753493309,
0.17097052931785583,
-0.06011899560689926,
-0.029049022123217583,
0.008818209171295166,
-0.2176758199930191,
0.19490456581115723,
0.06572453677654266,
0.021833261474967003,
-0.04672509431838989,
0.05511993542313576,
0.20559047162532806,
0.27329277992248535,
0.057880252599716187,
-0.34605303406715393,
-0.007602706551551819,
0.27380260825157166,
0.37539637088775635,
0.24678641557693481,
0.1457490473985672,
0.03405618667602539,
0.20076186954975128,
0.24317732453346252,
0.27019351720809937,
0.24104556441307068,
0.013897025026381016,
-0.18850594758987427,
0.04307830333709717,
0.19351914525032043,
0.16598354279994965,
-0.03977649658918381,
-0.16236159205436707,
-0.028106730431318283,
0.27386921644210815,
0.16490115225315094,
-0.16081154346466064,
-0.32471802830696106,
0.016357697546482086,
0.3211113512516022,
0.6261170506477356,
0.021359853446483612,
0.22093909978866577,
-0.10340329259634018,
-0.24081888794898987,
-0.36838605999946594,
-0.03585381060838699,
0.1324320137500763,
-0.14667385816574097,
-0.13123926520347595,
0.03457293286919594,
0.2909606397151947,
0.813957154750824,
-0.05824141949415207,
0.14619754254817963,
0.09321149438619614,
-0.0868021696805954,
-0.21096459031105042,
0.13557134568691254,
0.13352090120315552,
0.08008913695812225,
0.13520997762680054,
0.024450553581118584,
-0.33166074752807617,
-0.012322034686803818,
0.05064729228615761,
0.42544808983802795,
0.3760313391685486,
-0.3850039541721344,
-0.14506055414676666,
-0.1898254007101059,
-0.41637134552001953,
-0.46484336256980896,
-0.26002487540245056,
-0.24017611145973206,
-0.32249775528907776,
-0.11344344913959503,
0.32590705156326294,
0.017790652811527252,
0.20503288507461548,
-0.1692851036787033,
0.2984495162963867,
-0.29495880007743835,
-0.2706928849220276,
0.12766197323799133,
-0.20652709901332855,
-0.3765334486961365,
-0.00597800500690937,
0.22037088871002197,
-0.059067513793706894,
0.42291051149368286,
-0.15566517412662506,
-0.30039364099502563,
-0.15991686284542084,
-0.3217743933200836,
0.143232062458992,
0.16493967175483704,
0.5009920597076416,
0.4258585274219513,
-0.019074521958827972,
0.46502506732940674,
0.18073001503944397,
0.029476545751094818,
-0.1994137018918991,
-0.4520101249217987,
-0.2094363123178482,
-0.013931268826127052,
0.09201016277074814,
-0.09755668044090271,
-0.3627033829689026,
-0.6268526315689087,
-0.049434974789619446,
0.09246359020471573,
0.046491969376802444,
0.08684596419334412,
0.07008558511734009,
-0.17430393397808075,
0.1262962818145752,
0.06489109992980957,
-0.14631466567516327,
-0.13924884796142578,
0.12885414063930511,
-0.06379900872707367,
-0.1144397035241127,
-0.25293752551078796,
0.08709757030010223,
-0.09722965955734253,
-0.02210501953959465,
-0.06927597522735596,
-0.41635191440582275,
-0.4980792999267578,
0.18607714772224426,
0.12020492553710938,
0.3934658169746399,
-0.3054565191268921,
0.3518294095993042,
0.22900041937828064,
0.1961493343114853,
-0.07248476892709732,
-0.34929347038269043,
0.21882480382919312,
0.11768500506877899,
0.21085339784622192,
0.3140135109424591,
0.39684075117111206,
-0.17006197571754456,
0.6948559880256653,
0.1315314918756485,
-0.17439702153205872,
-0.08181397616863251,
-0.18463508784770966,
0.026518724858760834,
-0.07165741175413132,
0.025269342586398125,
0.2892470061779022,
-0.12184956669807434,
-0.3842000961303711,
0.23318777978420258,
-0.17590048909187317,
-0.04469316452741623,
-0.18192744255065918,
0.30313539505004883,
0.04550124704837799,
-0.023568280041217804,
-0.017659490928053856,
-0.18742920458316803,
0.062108974903821945,
0.06367619335651398,
-0.038225844502449036,
-0.16917134821414948,
-0.19289445877075195,
0.006161367520689964,
0.3494342565536499,
0.0028035715222358704,
0.20179885625839233,
-0.23703844845294952,
0.06796187162399292,
-0.3249555230140686,
0.3246842324733734,
0.3511451184749603,
0.6161120533943176,
0.12353888154029846,
0.006404511630535126,
0.12947885692119598,
0.045251764357089996,
0.16851752996444702,
0.015866238623857498,
0.20254437625408173,
0.1941901445388794,
-0.15339314937591553,
-0.10331499576568604,
-0.2794736623764038,
-0.05562499165534973,
0.10736370086669922,
-0.014489255845546722,
0.20647253096103668,
-0.37307024002075195,
-0.16325289011001587,
0.21614541113376617,
0.13574643433094025,
-0.10049250721931458,
-0.33303171396255493,
-0.08526661247015,
-0.01718934066593647,
-0.032943207770586014,
-0.28790518641471863,
-0.2201475203037262,
-0.0035184796433895826,
-0.17048873007297516,
0.3609248995780945,
-0.00987154059112072,
-0.15480631589889526,
-0.045074060559272766,
0.12206505239009857,
0.1488848328590393,
-0.28252148628234863,
0.30649590492248535,
0.2818530797958374,
0.10912124812602997,
0.42920392751693726,
0.2410028576850891,
-0.07917197048664093,
-0.2065410017967224,
0.06244774907827377,
-0.008030018769204617,
0.38697096705436707,
0.366956889629364,
0.1010068953037262,
-0.04046178609132767,
-0.19147416949272156,
-0.18607087433338165,
-0.35990071296691895,
0.10493271052837372,
0.3145606517791748,
-0.07839662581682205,
-0.08095967769622803,
-0.37498563528060913,
0.6471115946769714,
0.18893469870090485,
-0.2820153832435608,
0.4349672198295593,
-0.29321223497390747,
-0.24159453809261322,
0.016749652102589607,
0.11472064256668091,
0.9402281045913696,
0.10115319490432739,
0.1793755739927292,
0.4074016213417053,
-0.2569122314453125,
0.2777276933193207,
0.20907984673976898,
0.09308325499296188,
-0.5795201659202576,
0.03690945729613304,
0.006617432460188866,
-0.18128754198551178,
0.22857549786567688,
-0.10842613875865936,
-0.14125262200832367,
0.3231203854084015,
0.06759403645992279,
0.34466981887817383,
0.29964393377304077,
0.3267166018486023,
-0.13545875251293182,
0.038733746856451035,
-0.1763441562652588,
0.014816254377365112,
-0.1632358729839325,
0.3315982520580292,
-0.2451387345790863,
0.02070743218064308,
-0.20245015621185303,
-0.0634014755487442,
-0.26311010122299194,
-0.20407173037528992,
-0.14579352736473083,
0.02936004474759102,
0.05805596709251404,
-0.17235895991325378,
-0.003578571602702141,
0.2685673236846924,
0.18531253933906555,
-0.28354403376579285,
-0.11798523366451263,
0.0657288059592247,
-0.14783445000648499,
0.12417230755090714,
0.3541322350502014,
0.09130000323057175,
0.324359267950058,
-0.3461558222770691,
-0.04170437902212143,
0.07845711708068848,
-0.3147277235984802,
-0.11034661531448364,
-0.1682370901107788,
-0.1697041094303131,
0.17790326476097107,
-0.35208582878112793,
-0.2943044900894165,
-0.14130601286888123,
0.028502169996500015,
-0.052879318594932556,
-0.021204594522714615,
0.2687152326107025,
-0.24451056122779846,
-0.011231012642383575,
-0.13838420808315277,
-0.24387352168560028,
0.014475924894213676,
0.44725728034973145,
0.03498488664627075,
-0.10985312610864639,
0.6268347501754761,
-0.200073704123497,
0.07830161601305008,
-0.08096441626548767,
0.04233304411172867,
-0.03040461242198944,
-0.13849696516990662,
0.07945126295089722,
-0.06528531759977341,
-0.3092535138130188,
0.03099972754716873,
0.6317120790481567,
0.4538189768791199,
-0.022200830280780792,
-0.018440190702676773,
-0.4137721061706543,
-0.4684459865093231,
0.060229018330574036,
-0.13376890122890472,
0.15528979897499084,
-0.14459756016731262,
0.1882135421037674,
0.1062481701374054,
-0.04616036266088486,
-0.1483946144580841,
-0.15582576394081116,
0.17581810057163239,
0.22977690398693085,
-0.18760833144187927,
0.04707951843738556,
-0.02007327973842621,
0.042338963598012924,
-0.06394980102777481,
-0.0045035220682621,
-0.373477041721344,
-0.0004291422665119171,
-0.06305216997861862,
0.2435455471277237,
0.10599242150783539,
-0.10039091110229492,
0.10395446419715881,
-0.19135868549346924,
-0.013094846159219742,
0.2529705762863159,
-0.04260454326868057,
0.09640418738126755,
-0.08035597205162048,
0.1069931611418724,
0.3446801006793976,
0.15482018887996674,
-0.00897163338959217,
0.3556568920612335,
0.08667542040348053,
0.302620530128479,
-0.0783776044845581,
0.318191260099411,
-0.25813016295433044,
0.07906076312065125,
0.18990476429462433,
0.15776759386062622,
-0.01704178750514984,
0.20191439986228943,
0.11414919793605804,
-0.17145690321922302,
0.14508678019046783,
-0.04361787438392639,
0.4042547643184662,
0.8169977068901062,
-0.23315949738025665,
-0.20942068099975586,
0.39549365639686584,
-0.006465056911110878,
-0.20162171125411987,
0.04672809690237045,
0.27429765462875366,
0.16639955341815948,
-0.024561770260334015,
0.31011277437210083,
0.09837274253368378,
-0.016525067389011383,
0.13899202644824982,
0.20030370354652405,
0.1752067506313324,
-0.25456076860427856,
-0.014316165819764137,
0.43618109822273254,
-0.19119298458099365,
0.2348250150680542,
0.3925989866256714,
0.10050824284553528,
0.19480380415916443,
0.09433528780937195,
0.08113208413124084,
0.5245576500892639,
0.12521156668663025,
0.10351605713367462,
0.1761600524187088,
-0.013916222378611565,
0.026047738268971443,
0.40117451548576355,
-0.0035628527402877808,
-0.04608459770679474,
0.40405765175819397,
0.607949435710907,
-0.38512474298477173,
-0.2014325112104416,
-0.2968820035457611,
-0.19066695868968964,
0.051356736570596695,
-0.13128788769245148,
-0.2509273886680603,
-0.02136513963341713,
-0.18068495392799377,
-0.06044846773147583,
-0.24239742755889893,
-0.2871664762496948,
0.23147481679916382,
-0.004475004971027374,
-0.27352219820022583,
-0.281095415353775,
-0.36880767345428467,
0.13310948014259338,
-0.02977117896080017,
-0.24174059927463531,
0.2890284061431885,
-0.010914258658885956,
0.04701438546180725,
0.39378583431243896,
0.2517334520816803,
0.4028513729572296,
0.13960056006908417,
-0.3574991822242737,
-0.28657081723213196,
-0.2061855047941208,
0.05763343721628189,
0.04515703022480011,
0.3485932946205139,
-0.0030630454421043396,
-0.13039466738700867,
0.47411972284317017,
0.029031751677393913,
0.106221504509449,
0.2274838089942932,
0.3550854027271271,
-0.46599534153938293,
-0.10022158920764923,
0.8348633050918579,
-0.08329667896032333,
-0.2012389898300171,
0.04727889969944954,
0.17994128167629242,
-0.201237291097641,
0.04935801029205322,
-0.06658066809177399,
0.008687353692948818,
0.16352641582489014,
0.14323116838932037,
-0.0007180701941251755,
-0.09857748448848724,
0.2886528968811035,
0.3661203682422638,
0.025453779846429825,
-0.2843555212020874,
-0.2156105786561966,
-0.7466064095497131,
0.1942780315876007,
-0.056634511798620224,
-0.3099117577075958,
-0.021589912474155426,
-0.25138479471206665,
0.2322976291179657,
0.061979860067367554,
-0.17731793224811554,
0.18057352304458618,
0.09646039456129074,
0.10784228146076202,
-0.19800600409507751,
-0.27597445249557495,
-0.2155531495809555,
0.022782862186431885,
-0.10384839028120041,
-0.42491912841796875,
0.11890013515949249,
-0.3571050465106964,
-0.15924254059791565,
0.08887829631567001,
0.017661772668361664,
0.4647807478904724,
0.005589578300714493,
0.2521131634712219,
-0.0838739424943924,
0.7441830635070801,
0.2783360183238983,
-0.06739955395460129,
-0.16776920855045319,
0.12654736638069153,
-0.1436951458454132,
0.1740298867225647,
-0.12162190675735474,
0.0844416692852974,
-0.1829201877117157,
0.5333899855613708,
-0.41235408186912537,
0.4977741241455078,
-0.12797129154205322,
0.0690179243683815,
-0.3403317928314209,
0.059882499277591705,
-0.26378893852233887,
0.031390152871608734,
0.30836620926856995,
0.1954003870487213,
-0.03780286759138107,
0.30247578024864197,
-0.22645694017410278,
-0.12371501326560974,
0.4578656256198883,
-0.17120201885700226,
-0.03230812028050423,
0.08505763113498688,
0.2551974654197693,
0.05695349723100662,
-0.14033180475234985,
-0.48256686329841614,
0.1895676553249359,
0.24742929637432098,
-0.09605929255485535,
0.12113316357135773,
0.16393177211284637,
0.2560332119464874,
0.014003757387399673,
-0.023637229576706886,
1.0229697227478027,
-0.111495740711689,
0.08293845504522324,
-0.1492394059896469,
-0.23327721655368805
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | > The script loading seems to work fine so I'll work on getting a PR open after a few sanity checks on the data.
>
> On version, we currently have it versioned with YYYY.MM.DD scheme so it would be nice to not change that, but will it cause issues?
It would cause issues for sure for the tests....not sure if it would also cause issues otherwise.
I would prefer to keep the same version style as we have for other models. You could for example simply add version 1.0.0 and add a comment with the date you currently use for the versioning.
What is your opinion regarding the version here @lhoestq @mariamabarham @thomwolf ? | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 115 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
> The script loading seems to work fine so I'll work on getting a PR open after a few sanity checks on the data.
>
> On version, we currently have it versioned with YYYY.MM.DD scheme so it would be nice to not change that, but will it cause issues?
It would cause issues for sure for the tests....not sure if it would also cause issues otherwise.
I would prefer to keep the same version style as we have for other models. You could for example simply add version 1.0.0 and add a comment with the date you currently use for the versioning.
What is your opinion regarding the version here @lhoestq @mariamabarham @thomwolf ? | [
-0.07840734720230103,
0.21769899129867554,
-0.00799448974430561,
-0.21871642768383026,
-0.016750335693359375,
-0.15013828873634338,
0.45485737919807434,
0.3005519211292267,
0.01723051816225052,
0.06836661696434021,
0.2465081661939621,
0.07947704941034317,
-0.3443646728992462,
0.09023884683847427,
0.06199255958199501,
0.004056885838508606,
0.11398136615753174,
0.08718730509281158,
-0.06385979056358337,
0.15320876240730286,
-0.23857025802135468,
-0.046687252819538116,
0.058539554476737976,
0.18519851565361023,
0.010334712453186512,
0.11389532685279846,
-0.24757279455661774,
0.08724653720855713,
-0.4137381315231323,
-0.8389006853103638,
0.3315029442310333,
0.16535544395446777,
0.38253968954086304,
0.4212987422943115,
-0.0001269610074814409,
-0.09459542483091354,
0.6248884201049805,
-0.02055453322827816,
-0.602401077747345,
-0.16927851736545563,
0.3652231693267822,
-0.3112027049064636,
0.4110460877418518,
0.024779781699180603,
0.16198405623435974,
-0.2027106136083603,
0.1706407368183136,
0.16206806898117065,
0.131315216422081,
0.13344086706638336,
0.06785380095243454,
0.22151798009872437,
0.05243736132979393,
-0.14496354758739471,
-0.19909533858299255,
0.0519704595208168,
-0.06580491364002228,
0.6167840361595154,
0.5382672548294067,
0.177215576171875,
-0.02148120105266571,
-0.002134070498868823,
0.14147163927555084,
0.328044056892395,
0.20711109042167664,
-0.07337615638971329,
0.7348245978355408,
0.06136088818311691,
-0.13098597526550293,
0.00815608724951744,
0.9527407288551331,
-0.4113694429397583,
-0.5182245373725891,
0.055669642984867096,
0.04883920028805733,
-0.1310153603553772,
0.18289068341255188,
-0.16959063708782196,
-0.1973831057548523,
0.10677914321422577,
-0.18128953874111176,
-0.3202578127384186,
-0.22140301764011383,
0.28122878074645996,
-0.2812548875808716,
0.22530825436115265,
0.0833771601319313,
0.24231508374214172,
-0.10925690829753876,
-0.17242580652236938,
0.26023194193840027,
-0.09966812282800674,
-0.018706846982240677,
0.19757528603076935,
0.1821487843990326,
-0.3591311275959015,
-0.3890572488307953,
-0.11086901277303696,
0.14589783549308777,
-0.10912869870662689,
-0.39681699872016907,
-0.2765677273273468,
-0.05124089494347572,
0.09083911031484604,
0.25132492184638977,
0.2249232530593872,
0.41865625977516174,
0.1173015758395195,
0.23796439170837402,
0.028204115107655525,
0.38567882776260376,
0.27554240822792053,
-0.03827491030097008,
-0.3110353946685791,
0.03038856014609337,
0.0722004845738411,
0.18404839932918549,
-0.40609803795814514,
0.04705127328634262,
-0.23230332136154175,
-0.34174269437789917,
-0.13881908357143402,
-0.1190888062119484,
0.18631941080093384,
-0.1159299835562706,
0.0003313906490802765,
-0.007226672023534775,
0.3783921003341675,
-0.12641994655132294,
-0.18677881360054016,
-0.02923940122127533,
-0.057438816875219345,
-0.13046739995479584,
-0.0203388798981905,
0.19088779389858246,
0.03255531191825867,
0.28977516293525696,
-0.2891445755958557,
-0.18417240679264069,
0.020452052354812622,
-0.08764714002609253,
0.12490960955619812,
-0.2652386426925659,
0.26830825209617615,
-0.40122637152671814,
-0.01537303440272808,
-0.07192283868789673,
-0.36129653453826904,
-0.15017588436603546,
0.2882692515850067,
0.07951914519071579,
-0.43441006541252136,
-0.015946442261338234,
0.052783165127038956,
-0.48552602529525757,
-0.012248285114765167,
-0.02927067130804062,
-0.05822480842471123,
0.14872422814369202,
-0.32598841190338135,
0.043539706617593765,
-0.4276154041290283,
-0.32640188932418823,
-0.1250613033771515,
-0.20648102462291718,
0.23732170462608337,
-0.3779642879962921,
-0.24657811224460602,
-0.21628716588020325,
-0.3262249529361725,
0.051763907074928284,
-0.20617172122001648,
-0.09009283035993576,
0.034393928945064545,
-0.14357246458530426,
-0.24087359011173248,
0.525596022605896,
-0.6463609337806702,
-0.2875416874885559,
0.5019087791442871,
-0.2739056348800659,
-0.2755510210990906,
0.252553254365921,
-0.024601487442851067,
0.1583230346441269,
-0.5408313870429993,
-0.15352262556552887,
-0.10466593503952026,
-0.038840390741825104,
-0.17798306047916412,
-0.33155345916748047,
-0.42146816849708557,
0.20058287680149078,
0.3345435857772827,
-0.14667843282222748,
0.10944339632987976,
0.09240778535604477,
0.07713993638753891,
0.5037010312080383,
0.1834126114845276,
0.05109693109989166,
-0.2177705317735672,
0.3656325042247772,
-0.23294924199581146,
-0.07816824316978455,
-0.014533840119838715,
-0.7206133008003235,
0.18981388211250305,
-0.10229069739580154,
0.09577057510614395,
0.13708694279193878,
0.005196623504161835,
-0.43599677085876465,
-0.023731933906674385,
-0.013888668268918991,
-0.2627043128013611,
-0.0815754309296608,
-0.06165136396884918,
0.05206908658146858,
-0.029485389590263367,
-0.010522857308387756,
0.02294955775141716,
-0.20240578055381775,
0.22217687964439392,
0.08579118549823761,
-0.0024010632187128067,
-0.09218499064445496,
0.04781786724925041,
0.15576091408729553,
0.293927937746048,
0.07502377033233643,
-0.30252036452293396,
-0.020342204719781876,
0.3204720914363861,
0.380601704120636,
0.2452130913734436,
0.11209166049957275,
0.10057678818702698,
0.29977232217788696,
0.3446667790412903,
0.324491411447525,
0.1484437733888626,
-0.04383333399891853,
-0.09661421179771423,
-0.002046257257461548,
0.19905754923820496,
0.19929979741573334,
-0.15083476901054382,
-0.24920322000980377,
-0.08458079397678375,
0.18606244027614594,
0.2040824294090271,
-0.22944794595241547,
-0.298494815826416,
-0.02239767089486122,
0.3367256820201874,
0.5842093229293823,
0.010334759950637817,
0.18908604979515076,
-0.035991378128528595,
-0.22549137473106384,
-0.381384015083313,
-0.11914383620023727,
0.1591705083847046,
-0.15317359566688538,
-0.17685851454734802,
0.03739115968346596,
0.2746085524559021,
0.6558879613876343,
-0.05080951005220413,
0.06169295310974121,
0.07968907058238983,
-0.09127530455589294,
-0.15820492804050446,
0.13297709822654724,
0.19518598914146423,
0.07974904775619507,
0.07448263466358185,
0.02701413445174694,
-0.22329097986221313,
0.05465976148843765,
0.0741833746433258,
0.29648903012275696,
0.30123257637023926,
-0.30336418747901917,
-0.1087808758020401,
-0.14369496703147888,
-0.3550179898738861,
-0.44845256209373474,
-0.2716017961502075,
-0.36121875047683716,
-0.2839103639125824,
-0.04440955072641373,
0.3055323660373688,
-0.008049050346016884,
0.16161353886127472,
-0.0884672999382019,
0.35138940811157227,
-0.30625659227371216,
-0.08021794259548187,
0.13091756403446198,
-0.16871540248394012,
-0.4021384119987488,
-0.0075457170605659485,
0.1693287491798401,
-0.1414065659046173,
0.39903172850608826,
-0.07358181476593018,
-0.31047070026397705,
-0.07312048971652985,
-0.4179686903953552,
0.07629488408565521,
0.1368345022201538,
0.5680723786354065,
0.4437888562679291,
-0.015858083963394165,
0.4559708833694458,
0.21411621570587158,
0.02653995342552662,
-0.18789558112621307,
-0.37476012110710144,
-0.2456979751586914,
0.002451459178701043,
0.062213171273469925,
-0.0628884807229042,
-0.34115564823150635,
-0.674794614315033,
0.01595253497362137,
0.14174193143844604,
0.04154038056731224,
0.09176705777645111,
0.09137057512998581,
-0.2075149267911911,
0.009894395247101784,
-0.033491384238004684,
-0.12606926262378693,
-0.09700173139572144,
0.1426059752702713,
-0.11858950555324554,
-0.11486150324344635,
-0.21240977942943573,
0.09414660930633545,
0.05003800243139267,
-0.04971389099955559,
-0.1521892100572586,
-0.38123035430908203,
-0.5387279987335205,
0.27524423599243164,
0.0959395170211792,
0.44321736693382263,
-0.37508341670036316,
0.3168640434741974,
0.25746065378189087,
0.2106017917394638,
-0.030558090656995773,
-0.3124099373817444,
0.22272086143493652,
0.20246106386184692,
0.23872721195220947,
0.3416236340999603,
0.4278688430786133,
-0.17156076431274414,
0.698760449886322,
0.26078981161117554,
-0.21202413737773895,
-0.23117151856422424,
-0.0054813530296087265,
-0.12854982912540436,
-0.0936509296298027,
0.03923318535089493,
0.26029449701309204,
-0.11454686522483826,
-0.36592668294906616,
0.28301018476486206,
-0.07185623794794083,
0.000910244882106781,
-0.17153982818126678,
0.23263579607009888,
0.048266418278217316,
-0.025847740471363068,
-0.01699184440076351,
-0.10419665277004242,
0.09018269926309586,
0.036169275641441345,
-0.061963461339473724,
-0.16355231404304504,
-0.24948880076408386,
0.0705663412809372,
0.45116740465164185,
-0.0071663036942481995,
0.23893849551677704,
-0.1418859213590622,
0.14389027655124664,
-0.3231486976146698,
0.29190781712532043,
0.3646889626979828,
0.5911163091659546,
0.20548398792743683,
-0.06498757004737854,
0.16462990641593933,
0.03949234262108803,
0.16430622339248657,
0.06811744719743729,
0.22538653016090393,
0.08400434255599976,
-0.23833215236663818,
-0.08051209151744843,
-0.3215267062187195,
0.0013930052518844604,
0.043014269322156906,
0.0670982152223587,
0.207816019654274,
-0.3719228506088257,
-0.22546428442001343,
0.1916746348142624,
0.1168142780661583,
-0.1499803066253662,
-0.32392820715904236,
-0.04555001109838486,
0.13843384385108948,
0.07787726074457169,
-0.3222935199737549,
-0.31121325492858887,
-0.0988617017865181,
-0.23056131601333618,
0.3555451035499573,
-0.003292117267847061,
-0.1536957025527954,
-0.06030814349651337,
0.1760215163230896,
0.12314103543758392,
-0.35025733709335327,
0.32314881682395935,
0.30365249514579773,
0.1975913792848587,
0.41991445422172546,
0.11987721174955368,
-0.12025178968906403,
-0.10920153558254242,
-0.038991253823041916,
-0.09179171919822693,
0.33053553104400635,
0.44662657380104065,
0.02940857782959938,
-0.07550718635320663,
-0.15196441113948822,
-0.21442179381847382,
-0.369579017162323,
-0.03050500713288784,
0.28523194789886475,
-0.049796491861343384,
-0.06767596304416656,
-0.34444305300712585,
0.6544525623321533,
0.1329580396413803,
-0.3539952039718628,
0.38949456810951233,
-0.26032763719558716,
-0.20492435991764069,
0.014469064772129059,
0.12303577363491058,
0.9271784424781799,
0.13575266301631927,
0.22614456713199615,
0.35611456632614136,
-0.26288020610809326,
0.19106149673461914,
0.2073080688714981,
-0.021173972636461258,
-0.5951223969459534,
0.07956109941005707,
-0.01045474037528038,
-0.11937639117240906,
0.25975117087364197,
-0.06818681210279465,
-0.0672571063041687,
0.3064366281032562,
0.11517393589019775,
0.3037260174751282,
0.27472925186157227,
0.31663256883621216,
-0.0745704397559166,
0.12467688322067261,
-0.14576467871665955,
-0.002733757719397545,
-0.19871364533901215,
0.22155605256557465,
-0.2173815667629242,
-0.05912107229232788,
-0.13456155359745026,
-0.13533854484558105,
-0.19719448685646057,
-0.27885568141937256,
-0.1417296677827835,
0.002587556838989258,
0.09939530491828918,
-0.2422436624765396,
0.09887169301509857,
0.20783917605876923,
0.21243155002593994,
-0.2769320011138916,
-0.10583136975765228,
-0.006890475749969482,
-0.09415439516305923,
0.19183050096035004,
0.23260439932346344,
0.11455319821834564,
0.4135674238204956,
-0.3656522035598755,
-0.029833689332008362,
-0.0021504461765289307,
-0.30152446031570435,
-0.07882071286439896,
-0.24475958943367004,
-0.22926904261112213,
0.20691938698291779,
-0.34996190667152405,
-0.24335049092769623,
-0.07171539962291718,
0.060952719300985336,
-0.04963530972599983,
-0.016589514911174774,
0.2987672984600067,
-0.16764627397060394,
0.0024614334106445312,
-0.06528228521347046,
-0.14836618304252625,
0.0035221297293901443,
0.4236816167831421,
0.03534163162112236,
-0.1286199986934662,
0.5450732707977295,
-0.17769336700439453,
-0.012218818068504333,
-0.06524503976106644,
0.0422201007604599,
-0.0569339320063591,
-0.2640582025051117,
0.024849386885762215,
-0.08269265294075012,
-0.254199355840683,
0.026647554710507393,
0.6445192098617554,
0.5140349864959717,
-0.08816101402044296,
0.008511319756507874,
-0.3115549087524414,
-0.4337587356567383,
0.11887909471988678,
-0.14966128766536713,
0.1279405653476715,
-0.2016347050666809,
0.19356271624565125,
0.08962829411029816,
-0.08079346269369125,
-0.1644304394721985,
-0.16892458498477936,
0.28728964924812317,
0.16615432500839233,
-0.20746590197086334,
0.05575067922472954,
-0.05666795000433922,
0.00035731587558984756,
-0.07731951028108597,
-0.09144656360149384,
-0.4320649802684784,
-0.009923234581947327,
-0.0681835412979126,
0.22385188937187195,
0.09701959043741226,
-0.0993722602725029,
0.07501251995563507,
-0.1820572167634964,
0.032962217926979065,
0.33374613523483276,
-0.029270030558109283,
0.05774620175361633,
0.040878526866436005,
0.2147265374660492,
0.3124197721481323,
0.2434011697769165,
-0.026759691536426544,
0.41367027163505554,
0.052882254123687744,
0.27785611152648926,
-0.031204234808683395,
0.30528852343559265,
-0.2380792200565338,
0.03763595223426819,
0.07074977457523346,
0.19237913191318512,
-0.1881691962480545,
0.32301491498947144,
0.044290460646152496,
-0.19937767088413239,
0.17659614980220795,
0.008234193548560143,
0.3879280090332031,
0.7847013473510742,
-0.19644686579704285,
-0.300943523645401,
0.45363563299179077,
0.027808213606476784,
-0.12452957779169083,
0.08317085355520248,
0.262359619140625,
0.19259516894817352,
-0.04848910868167877,
0.33698800206184387,
0.14231334626674652,
0.037863247096538544,
0.10244549810886383,
0.23270544409751892,
0.11558371782302856,
-0.3071414828300476,
-0.014103030785918236,
0.4850953221321106,
-0.19111378490924835,
0.25854936242103577,
0.42612993717193604,
0.2196153700351715,
0.042595185339450836,
0.01736105978488922,
0.08998870104551315,
0.40315714478492737,
0.20004752278327942,
0.04172372817993164,
0.21260783076286316,
0.07285183668136597,
-0.05200717970728874,
0.3586235046386719,
0.010092176496982574,
-0.07322878390550613,
0.43289124965667725,
0.6263275742530823,
-0.24576957523822784,
-0.2735118865966797,
-0.265232652425766,
-0.2573288381099701,
0.11760283261537552,
-0.15073952078819275,
-0.3253525197505951,
-0.031386084854602814,
-0.172324538230896,
-0.06642265617847443,
-0.3928256630897522,
-0.23233743011951447,
0.24641136825084686,
0.060927681624889374,
-0.2492004781961441,
-0.35219913721084595,
-0.4377782344818115,
0.042293112725019455,
0.06692017614841461,
-0.14867763221263885,
0.24843816459178925,
0.003967605531215668,
0.09395244717597961,
0.4052654802799225,
0.24692629277706146,
0.24045298993587494,
0.09698637574911118,
-0.39798590540885925,
-0.33229953050613403,
-0.2425733357667923,
0.0760229080915451,
0.16924098134040833,
0.2883455455303192,
0.02029649168252945,
-0.1690838783979416,
0.43928295373916626,
0.004951445385813713,
0.1724262833595276,
0.36718422174453735,
0.30420124530792236,
-0.41586968302726746,
-0.11310699582099915,
0.866989016532898,
-0.01036369800567627,
-0.2329448163509369,
0.14805153012275696,
0.19929929077625275,
-0.20762670040130615,
0.12630227208137512,
-0.041104625910520554,
0.05794176459312439,
0.128401517868042,
0.15669363737106323,
0.012644585222005844,
-0.03198806196451187,
0.18832483887672424,
0.3991011083126068,
-0.01953880488872528,
-0.2369244396686554,
-0.12392812967300415,
-0.5654717087745667,
0.07696305215358734,
0.051341086626052856,
-0.21406476199626923,
-0.018772482872009277,
-0.24497383832931519,
0.20464445650577545,
0.06571180373430252,
-0.11546401679515839,
0.022159021347761154,
-0.05080560967326164,
0.14864704012870789,
-0.17918580770492554,
-0.19621114432811737,
-0.13138964772224426,
0.1199856549501419,
-0.1198875829577446,
-0.30400794744491577,
0.05137854814529419,
-0.3177834749221802,
-0.19125229120254517,
0.018191250041127205,
0.047366246581077576,
0.4646492600440979,
0.03857523575425148,
0.13066107034683228,
-0.06797149032354355,
0.5171793699264526,
0.3847469091415405,
-0.17758965492248535,
-0.1369655728340149,
0.10956788063049316,
-0.12803296744823456,
0.18178817629814148,
-0.13699199259281158,
0.1513938158750534,
-0.122855544090271,
0.4253520369529724,
-0.3331281542778015,
0.41835877299308777,
-0.22756367921829224,
0.0001626563025638461,
-0.4170818626880646,
0.10477407276630402,
-0.11555361747741699,
-0.11772534996271133,
0.2918640971183777,
0.27572381496429443,
-0.07171913981437683,
0.2615319788455963,
-0.2811012268066406,
-0.07436523586511612,
0.4302865266799927,
-0.22998549044132233,
0.04756632819771767,
0.09626506268978119,
0.2981060743331909,
0.11599423736333847,
-0.05385667085647583,
-0.531058132648468,
0.12829163670539856,
0.23650754988193512,
-0.14698582887649536,
0.022672098129987717,
0.2222898006439209,
0.3116585314273834,
-0.06905553489923477,
-0.03913304582238197,
1.0794569253921509,
-0.17351484298706055,
0.11268402636051178,
-0.15644319355487823,
-0.19749954342842102
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | Maybe use the YYYY.MM.DD as the config name ? That's what we are doing for wikipedia | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 16 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
Maybe use the YYYY.MM.DD as the config name ? That's what we are doing for wikipedia | [
-0.14118072390556335,
0.2805648446083069,
-0.010229086503386497,
-0.1734384149312973,
0.09962055087089539,
-0.05622601509094238,
0.3951389193534851,
0.35677868127822876,
0.1325157731771469,
0.1633101850748062,
0.2544320225715637,
0.11689873039722443,
-0.26364362239837646,
-0.032296013087034225,
0.08826718479394913,
-0.022581331431865692,
0.024319849908351898,
0.153996542096138,
-0.06924255192279816,
0.253808856010437,
-0.15772663056850433,
0.02764403447508812,
-0.07621055841445923,
0.0034688711166381836,
-0.03206753730773926,
0.14956483244895935,
-0.12435545027256012,
-0.02923256903886795,
-0.39765340089797974,
-0.8835684061050415,
0.38515710830688477,
0.08030331134796143,
0.15719950199127197,
0.4587191045284271,
-0.0001239301636815071,
-0.09218358993530273,
0.6603642106056213,
-0.09545937180519104,
-0.7126159071922302,
-0.11028550565242767,
0.21409562230110168,
-0.44317543506622314,
0.31489816308021545,
-0.12270475178956985,
0.07477682828903198,
-0.12571555376052856,
0.24232164025306702,
0.0029502809047698975,
0.04234407842159271,
0.2779586613178253,
0.11370958387851715,
0.20985466241836548,
0.14470228552818298,
-0.20508523285388947,
-0.06326273828744888,
0.07268209010362625,
-0.1255190372467041,
0.5561835765838623,
0.29881545901298523,
0.08979629725217819,
-0.011444158852100372,
-0.08872745931148529,
0.08542583882808685,
0.47456541657447815,
0.2024761140346527,
-0.0256972573697567,
0.5517069697380066,
0.010823531076312065,
-0.16354912519454956,
-0.0021503716707229614,
0.9606097936630249,
-0.5900260806083679,
-0.2856663763523102,
0.055983081459999084,
0.06181573495268822,
-0.044158145785331726,
0.22932526469230652,
-0.1933574676513672,
-0.3710883855819702,
0.005593400448560715,
-0.113864466547966,
-0.34605908393859863,
-0.13907605409622192,
0.3863377571105957,
-0.2816322147846222,
0.3920343220233917,
0.12043490260839462,
0.2018035352230072,
0.029666583985090256,
-0.12271088361740112,
0.1766301840543747,
-0.037354256957769394,
0.05294102430343628,
0.2122683823108673,
0.053161948919296265,
-0.29137104749679565,
-0.36121830344200134,
-0.23289954662322998,
0.11769244819879532,
-0.0717003345489502,
-0.5114047527313232,
-0.21405303478240967,
0.060136254876852036,
0.21360686421394348,
0.11943654716014862,
0.2886669933795929,
0.3164389431476593,
0.26326677203178406,
0.2690865695476532,
0.1590999960899353,
0.23070356249809265,
0.22681641578674316,
-0.001236175769008696,
-0.39059746265411377,
0.00787830725312233,
0.043517276644706726,
0.23724471032619476,
-0.27922511100769043,
-0.001813456416130066,
-0.223365917801857,
-0.35482579469680786,
-0.03768952563405037,
-0.15496297180652618,
0.27120161056518555,
-0.21224386990070343,
-0.21906012296676636,
0.03549148142337799,
0.3669431209564209,
-0.19033747911453247,
-0.0829746425151825,
-0.030062638223171234,
0.10269162058830261,
-0.20946572721004486,
0.04133981466293335,
0.2736015319824219,
0.11987332999706268,
0.3815648853778839,
-0.22116583585739136,
-0.17527373135089874,
-0.06266403198242188,
0.04889075458049774,
0.16503886878490448,
-0.2584547996520996,
0.3138117790222168,
-0.17547893524169922,
0.09148240834474564,
0.0757020115852356,
-0.3986794352531433,
-0.2606750428676605,
0.190580815076828,
0.08797687292098999,
-0.39845409989356995,
-0.07537218183279037,
0.09867958724498749,
-0.5322721004486084,
-0.04728294909000397,
0.03677947074174881,
-0.10876646637916565,
0.16949871182441711,
-0.43949902057647705,
0.039980269968509674,
-0.3296203017234802,
-0.32755377888679504,
-0.12069296091794968,
-0.04477449879050255,
0.22451508045196533,
-0.3344626724720001,
-0.3448535203933716,
-0.3996001183986664,
-0.262083500623703,
0.19108641147613525,
-0.2722560465335846,
-0.05161494389176369,
0.1798931062221527,
-0.3446755111217499,
-0.09361154586076736,
0.5451646447181702,
-0.5609612464904785,
-0.3666335344314575,
0.4103245735168457,
-0.39714157581329346,
-0.30935925245285034,
0.2160005271434784,
-0.0019480688497424126,
0.072139672935009,
-0.2954326272010803,
-0.13503113389015198,
0.026698965579271317,
0.05478984862565994,
-0.12957745790481567,
-0.17708122730255127,
-0.3129168748855591,
0.15713399648666382,
0.24047555029392242,
-0.057767730206251144,
0.12762778997421265,
0.17676837742328644,
0.22123213112354279,
0.33956870436668396,
0.12165810167789459,
0.19460859894752502,
-0.08479996770620346,
0.20399177074432373,
-0.17558155953884125,
-0.07350810617208481,
-0.09873545169830322,
-0.6286861896514893,
0.21739527583122253,
-0.040479544550180435,
0.28844982385635376,
-0.07102851569652557,
-0.051276326179504395,
-0.6030595898628235,
-0.028186338022351265,
0.007144272327423096,
-0.254384845495224,
0.0009690672159194946,
0.2109040468931198,
0.12575265765190125,
0.07182292640209198,
0.08742757141590118,
-0.05625335872173309,
-0.20948581397533417,
0.18995748460292816,
-0.039936479181051254,
-0.016076302155852318,
-0.11674629896879196,
0.11367613822221756,
0.12232330441474915,
0.20108270645141602,
0.03238675370812416,
-0.26659008860588074,
-0.011400045827031136,
0.18859511613845825,
0.3017377555370331,
0.26696479320526123,
0.2012650966644287,
-0.028640851378440857,
0.18482038378715515,
0.14330661296844482,
0.23561516404151917,
0.3190940022468567,
0.07314888387918472,
-0.2795489430427551,
0.0007633194327354431,
0.13875505328178406,
0.21099036931991577,
0.0036713331937789917,
-0.22517900168895721,
-0.008010979741811752,
0.3341837525367737,
0.1293625384569168,
-0.1294441968202591,
-0.3318285048007965,
0.09353769570589066,
0.3465370535850525,
0.5930149555206299,
-0.03065631352365017,
0.3187482953071594,
-0.17704996466636658,
-0.1961137056350708,
-0.33191588521003723,
0.010572269558906555,
0.1472766101360321,
-0.1484430730342865,
-0.13274461030960083,
0.004782436415553093,
0.2607828974723816,
0.7473019957542419,
-0.017134200781583786,
0.21024386584758759,
0.08281274884939194,
-0.19435252249240875,
-0.18114571273326874,
0.19616247713565826,
0.14606767892837524,
0.05849679559469223,
0.11732535809278488,
0.008353392593562603,
-0.3501940071582794,
-0.0421718992292881,
-0.01063714548945427,
0.46164852380752563,
0.4212026000022888,
-0.3261987566947937,
-0.1254185289144516,
-0.2086644470691681,
-0.4111090302467346,
-0.4504467248916626,
-0.4019869863986969,
-0.3150010406970978,
-0.3542323410511017,
-0.10665440559387207,
0.2702239751815796,
0.08679600059986115,
0.2829837501049042,
-0.224715918302536,
0.30379197001457214,
-0.25691190361976624,
-0.35868990421295166,
0.07040300965309143,
-0.2922021448612213,
-0.3351595401763916,
0.011352062225341797,
0.233516663312912,
0.0032299216836690903,
0.4592945873737335,
-0.12466802448034286,
-0.3249701261520386,
-0.22680646181106567,
-0.36631810665130615,
0.10803449153900146,
0.06434579193592072,
0.5244491100311279,
0.41656604409217834,
0.04030180349946022,
0.47716838121414185,
0.04909319430589676,
0.034976787865161896,
-0.18719081580638885,
-0.424094557762146,
-0.23610278964042664,
-0.012634423561394215,
0.1769871711730957,
-0.09271982312202454,
-0.37856370210647583,
-0.5373615622520447,
-0.10313151776790619,
0.0880431979894638,
0.06720203161239624,
0.006694704294204712,
0.1528788059949875,
-0.1076124906539917,
0.1514066904783249,
0.10712626576423645,
-0.055705778300762177,
-0.13396570086479187,
0.12558957934379578,
0.02072177082300186,
-0.16886909306049347,
-0.10974130034446716,
0.10617506504058838,
-0.11159314215183258,
0.03736857697367668,
-0.13643242418766022,
-0.45776915550231934,
-0.4050000309944153,
0.10826603323221207,
0.1651182919740677,
0.40959522128105164,
-0.252712219953537,
0.2943410277366638,
0.23262062668800354,
0.14786069095134735,
-0.09710405021905899,
-0.3855840563774109,
0.1825857162475586,
0.03584716096520424,
0.25486335158348083,
0.23821192979812622,
0.42762523889541626,
-0.18805336952209473,
0.8638371825218201,
0.12577833235263824,
-0.0933363139629364,
-0.06046298146247864,
-0.2205599844455719,
0.003717418760061264,
-0.05921005457639694,
-0.044465601444244385,
0.32291167974472046,
-0.11662009358406067,
-0.32144469022750854,
0.27593040466308594,
-0.20463067293167114,
-0.15403355658054352,
-0.13479188084602356,
0.28695449233055115,
-0.006108589470386505,
-0.0675116553902626,
-0.0446653738617897,
-0.14884768426418304,
0.04530714452266693,
0.054063793271780014,
-0.049502961337566376,
-0.22893069684505463,
-0.25206342339515686,
0.04696158319711685,
0.31666630506515503,
-0.15776339173316956,
0.1885860413312912,
-0.24663028120994568,
0.031642619520425797,
-0.44746971130371094,
0.2941854000091553,
0.33318576216697693,
0.5381502509117126,
0.10278929769992828,
-0.015300169587135315,
0.11338121443986893,
0.1049145832657814,
0.20852705836296082,
-0.017759324982762337,
0.1344524323940277,
0.24128973484039307,
-0.09606370329856873,
-0.12461607903242111,
-0.25974878668785095,
-0.008720126003026962,
0.1897033452987671,
-0.004294808954000473,
0.13426710665225983,
-0.4184403419494629,
-0.07045483589172363,
0.2634961009025574,
0.19597165286540985,
-0.09762413799762726,
-0.3244107961654663,
-0.08676270395517349,
-0.028297312557697296,
-0.08013050258159637,
-0.23945486545562744,
-0.16850070655345917,
0.10118240863084793,
-0.07583743333816528,
0.3622826933860779,
0.036848463118076324,
-0.06702408194541931,
-0.0823664516210556,
0.15544454753398895,
0.146712988615036,
-0.20712384581565857,
0.2648325562477112,
0.22875167429447174,
0.027473947033286095,
0.3402649164199829,
0.241371288895607,
-0.11826840043067932,
-0.2586958706378937,
-0.047578878700733185,
0.007216406054794788,
0.35540905594825745,
0.23109319806098938,
0.1883850246667862,
-0.019396789371967316,
-0.1601121723651886,
-0.14804227650165558,
-0.3491378724575043,
0.19839347898960114,
0.32603761553764343,
-0.09454551339149475,
-0.08157745748758316,
-0.3744667172431946,
0.6699296832084656,
0.2106671929359436,
-0.2216612696647644,
0.5757378339767456,
-0.21588154137134552,
-0.361310750246048,
-0.02096259407699108,
0.09729389101266861,
0.9390982389450073,
0.12304747104644775,
0.22184543311595917,
0.3271251916885376,
-0.2036057412624359,
0.40682482719421387,
0.1139771044254303,
0.1631506383419037,
-0.5522783994674683,
0.035590000450611115,
0.041692376136779785,
-0.18077494204044342,
0.18681372702121735,
-0.12864047288894653,
-0.2766346335411072,
0.34582558274269104,
0.09094040095806122,
0.3162321150302887,
0.28049272298812866,
0.3736043870449066,
-0.06282483041286469,
-0.047387201339006424,
-0.16777822375297546,
0.06752441823482513,
-0.17312860488891602,
0.3932380676269531,
-0.250163733959198,
0.09912212193012238,
-0.1918768584728241,
-0.03845309466123581,
-0.31208086013793945,
-0.19377604126930237,
-0.12246156483888626,
0.12016215175390244,
0.05442022532224655,
-0.1686798483133316,
-0.02505229040980339,
0.22702550888061523,
0.12529388070106506,
-0.16949120163917542,
-0.17709821462631226,
0.14197885990142822,
-0.1813591718673706,
0.06414823234081268,
0.30314627289772034,
0.05139261856675148,
0.3021053671836853,
-0.3474116623401642,
-0.09088625013828278,
0.12196370959281921,
-0.2841305136680603,
-0.20523595809936523,
-0.1263769567012787,
-0.1708373725414276,
0.08427345752716064,
-0.3267577886581421,
-0.282860666513443,
-0.13302059471607208,
0.04689626768231392,
-0.14486834406852722,
0.02616175264120102,
0.22552156448364258,
-0.3177244961261749,
0.0012358054518699646,
-0.03404851630330086,
-0.3448730707168579,
0.018304821103811264,
0.44678616523742676,
-0.08538536727428436,
-0.07896117866039276,
0.7237139940261841,
-0.1690613180398941,
0.038177311420440674,
-0.11864368617534637,
0.023047514259815216,
-0.18729455769062042,
-0.15366312861442566,
0.049600694328546524,
-0.05159308761358261,
-0.2729284167289734,
0.01061205193400383,
0.5785098671913147,
0.4408789277076721,
0.04504683241248131,
-0.02072543278336525,
-0.4588911235332489,
-0.41634103655815125,
0.007794685661792755,
-0.18109852075576782,
0.2008616030216217,
-0.08202992379665375,
0.18932278454303741,
0.15709927678108215,
0.01595485582947731,
-0.187468022108078,
-0.16336193680763245,
0.040294744074344635,
0.24360188841819763,
-0.13370975852012634,
0.0225283894687891,
-0.07007408887147903,
0.08745723962783813,
0.0018108636140823364,
-0.0883050337433815,
-0.28574225306510925,
-0.05251786857843399,
-0.13653428852558136,
0.2203616350889206,
0.0687347948551178,
-0.002946962136775255,
0.0809541642665863,
-0.19381718337535858,
-0.005588049069046974,
0.1685536950826645,
-0.05514583736658096,
0.10774029046297073,
-0.09697437286376953,
0.19977815449237823,
0.33400067687034607,
0.048022352159023285,
-0.019415859133005142,
0.2950708270072937,
0.1199374794960022,
0.2520233392715454,
-0.04795244708657265,
0.3378598690032959,
-0.19110234081745148,
0.06257529556751251,
0.17886307835578918,
0.2028523087501526,
-0.0861780047416687,
0.17287001013755798,
0.0845031663775444,
-0.10913452506065369,
0.10387429594993591,
0.04550378397107124,
0.3643854856491089,
0.7686900496482849,
-0.26971736550331116,
-0.1473635882139206,
0.433666467666626,
0.04313832148909569,
-0.2070346474647522,
-0.06151576340198517,
0.3559982180595398,
0.0967506617307663,
0.05956525728106499,
0.24292254447937012,
-0.003486037254333496,
-0.019756466150283813,
0.15557114779949188,
0.16882425546646118,
0.08332838118076324,
-0.22388117015361786,
-0.014182325452566147,
0.38112443685531616,
-0.204329714179039,
0.16130280494689941,
0.3652931749820709,
0.12268346548080444,
0.2558835744857788,
0.11702345311641693,
0.12785866856575012,
0.4928240478038788,
0.06652931869029999,
0.03491068631410599,
0.07122965157032013,
0.07629594206809998,
0.061420440673828125,
0.2696564197540283,
-0.09182748198509216,
-0.021174706518650055,
0.37101098895072937,
0.551271378993988,
-0.3462454676628113,
-0.1316280961036682,
-0.2795216143131256,
-0.14258629083633423,
0.04645552113652229,
-0.18091359734535217,
-0.24025443196296692,
0.013755857944488525,
-0.13747644424438477,
-0.11026807129383087,
-0.15492680668830872,
-0.3587164282798767,
0.24380084872245789,
0.008351609110832214,
-0.36951738595962524,
-0.30901604890823364,
-0.2120947539806366,
0.17734560370445251,
-0.006553530693054199,
-0.3145363926887512,
0.18164990842342377,
-0.06015767157077789,
0.00930163636803627,
0.28603386878967285,
0.296482115983963,
0.45625102519989014,
0.08334749191999435,
-0.4143468141555786,
-0.2541944980621338,
-0.1805916279554367,
0.06383518129587173,
-0.02755061164498329,
0.34688523411750793,
0.037008341401815414,
-0.1990613043308258,
0.4957922399044037,
0.06062592566013336,
0.0358571894466877,
0.13405011594295502,
0.4426795244216919,
-0.5077688694000244,
-0.12595930695533752,
0.6570250988006592,
-0.06691066920757294,
-0.17114922404289246,
-0.014399982988834381,
0.2682860195636749,
-0.31312260031700134,
0.09172575920820236,
-0.0007790941745042801,
-0.04264107346534729,
0.14234831929206848,
0.07496239244937897,
0.025010138750076294,
-0.17087215185165405,
0.40392714738845825,
0.31939420104026794,
0.01959727704524994,
-0.26244738698005676,
-0.259154736995697,
-0.7384799122810364,
0.19107267260551453,
-0.11629621684551239,
-0.34262752532958984,
-0.07228414714336395,
-0.19995804131031036,
0.24219250679016113,
0.04681190848350525,
-0.1436450034379959,
0.10192464292049408,
0.029758833348751068,
0.14397859573364258,
-0.18503157794475555,
-0.3121945559978485,
-0.20069928467273712,
-0.02207382582128048,
-0.06889434158802032,
-0.40647274255752563,
0.11685904860496521,
-0.36691635847091675,
-0.09841718524694443,
0.07443760335445404,
0.0026448816061019897,
0.5323455333709717,
0.07270558178424835,
0.2942667007446289,
-0.10212308168411255,
0.8140294551849365,
0.17402300238609314,
-0.04890239238739014,
-0.17330361902713776,
0.11475576460361481,
-0.10631570219993591,
0.16286811232566833,
-0.12736479938030243,
0.1119912713766098,
-0.20888233184814453,
0.4868563711643219,
-0.38907647132873535,
0.601815402507782,
-0.017861688509583473,
0.08193861693143845,
-0.2825641930103302,
0.011469272896647453,
-0.25492197275161743,
0.08918756246566772,
0.2956137955188751,
0.195259690284729,
-0.07665424048900604,
0.354806125164032,
-0.15306319296360016,
-0.2579878866672516,
0.41756850481033325,
-0.16063252091407776,
-0.11916562914848328,
0.03131815791130066,
0.22145994007587433,
-0.012549281120300293,
-0.09062881022691727,
-0.43135032057762146,
0.1975601315498352,
0.3064979016780853,
-0.06527065485715866,
0.03529031202197075,
0.19647520780563354,
0.22549034655094147,
0.09795331954956055,
-0.005873385816812515,
0.9912326335906982,
-0.10930561274290085,
0.11685295403003693,
-0.1647682934999466,
-0.2565416693687439
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | > Maybe use the YYYY.MM.DD as the config name ? That's what we are doing for wikipedia
I'm not sure if this will work because the name should be unique and it seems that he has multiple config name in his data with the same version.
As @patrickvonplaten suggested, I think you can add a comment about the version in the data description. | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 63 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
> Maybe use the YYYY.MM.DD as the config name ? That's what we are doing for wikipedia
I'm not sure if this will work because the name should be unique and it seems that he has multiple config name in his data with the same version.
As @patrickvonplaten suggested, I think you can add a comment about the version in the data description. | [
-0.0867203027009964,
0.2737462520599365,
0.011248860508203506,
-0.14076009392738342,
0.06271111220121384,
-0.048166945576667786,
0.3938751518726349,
0.3804904520511627,
0.08933477103710175,
0.20729276537895203,
0.2584836483001709,
0.14728564023971558,
-0.23994089663028717,
-0.015442601405084133,
0.04751161113381386,
-0.006765063852071762,
-0.058515287935733795,
0.21216976642608643,
-0.029032625257968903,
0.2738305926322937,
-0.08489841967821121,
-0.011124121025204659,
0.07523150742053986,
0.09017886966466904,
-0.044721562415361404,
0.11217676103115082,
-0.12271841615438461,
-0.06276867538690567,
-0.26378533244132996,
-0.9248581528663635,
0.34500613808631897,
0.12437264621257782,
0.1424262821674347,
0.5053983926773071,
-0.0001223480503540486,
-0.053185708820819855,
0.6260417103767395,
-0.10737155377864838,
-0.6992904543876648,
-0.15020211040973663,
0.230825275182724,
-0.46198561787605286,
0.28589895367622375,
-0.18482646346092224,
0.034542784094810486,
-0.13203290104866028,
0.23104481399059296,
0.05033749341964722,
0.0913199782371521,
0.14613573253154755,
0.10933606326580048,
0.14259855449199677,
0.11538048088550568,
-0.16234828531742096,
-0.10149707645177841,
0.027807284146547318,
-0.09675844758749008,
0.5679475665092468,
0.2544049024581909,
0.13260623812675476,
0.016347140073776245,
-0.010725745931267738,
0.06912654638290405,
0.45414209365844727,
0.13088610768318176,
-0.05509103834629059,
0.5264000296592712,
0.0546017661690712,
-0.12745758891105652,
0.13458862900733948,
0.9771101474761963,
-0.5941919088363647,
-0.34010767936706543,
0.00994681566953659,
0.14042051136493683,
-0.003393854945898056,
0.2467772364616394,
-0.1763128787279129,
-0.36520838737487793,
0.008558828383684158,
-0.09733168035745621,
-0.29024937748908997,
-0.1943594217300415,
0.3475720286369324,
-0.25344792008399963,
0.42434707283973694,
0.13284409046173096,
0.2170562744140625,
-0.050475139170885086,
-0.23413114249706268,
0.14442618191242218,
-0.04758576303720474,
0.06462261080741882,
0.1204758733510971,
0.06505173444747925,
-0.31929999589920044,
-0.4705291986465454,
-0.3281729519367218,
0.11237967759370804,
-0.17740869522094727,
-0.40035638213157654,
-0.24110457301139832,
0.06570759415626526,
0.20268884301185608,
0.12156444787979126,
0.19925321638584137,
0.3851895034313202,
0.22244952619075775,
0.2539423704147339,
0.14471569657325745,
0.17460191249847412,
0.20782190561294556,
0.0239003524184227,
-0.4101085364818573,
0.0025973469018936157,
0.030733253806829453,
0.28490954637527466,
-0.2973403334617615,
0.017245011404156685,
-0.1251339316368103,
-0.3631380498409271,
-0.026332607492804527,
-0.2165975570678711,
0.35842543840408325,
-0.25124818086624146,
-0.2243998944759369,
0.08188818395137787,
0.3014507293701172,
-0.1021781712770462,
-0.07199285924434662,
-0.023294907063245773,
0.02457548677921295,
-0.12462329864501953,
0.11025374382734299,
0.24170337617397308,
0.08670319616794586,
0.4142286777496338,
-0.22951820492744446,
-0.1562180072069168,
-0.1250024139881134,
-0.003739631734788418,
0.21193437278270721,
-0.23602980375289917,
0.31187009811401367,
-0.17207065224647522,
0.09038291126489639,
0.025926532223820686,
-0.4385862946510315,
-0.30044984817504883,
0.19515305757522583,
0.0872914046049118,
-0.34400737285614014,
-0.11515498161315918,
0.09680038690567017,
-0.5595490336418152,
-0.08119669556617737,
0.1679888665676117,
-0.12055999040603638,
0.13395191729068756,
-0.46944481134414673,
0.03654436767101288,
-0.2592833638191223,
-0.30312782526016235,
-0.15861903131008148,
-0.0653032585978508,
0.27007025480270386,
-0.31470486521720886,
-0.35894307494163513,
-0.33123230934143066,
-0.20738773047924042,
0.09957849979400635,
-0.3180846571922302,
-0.036983706057071686,
0.13217496871948242,
-0.23593921959400177,
-0.07427404820919037,
0.5720571875572205,
-0.5332987904548645,
-0.3166050910949707,
0.4164281487464905,
-0.3450377583503723,
-0.24903108179569244,
0.25984981656074524,
0.024157822132110596,
0.16989871859550476,
-0.2648543417453766,
-0.12308821082115173,
-0.050398506224155426,
0.12207365781068802,
-0.10380485653877258,
-0.19102084636688232,
-0.4137361943721771,
0.09981665760278702,
0.2717949151992798,
-0.108523428440094,
0.10879955440759659,
0.12809619307518005,
0.19002844393253326,
0.40333476662635803,
0.08722396194934845,
0.12643882632255554,
-0.08443883806467056,
0.19085730612277985,
-0.09954707324504852,
-0.15517735481262207,
-0.037928398698568344,
-0.650165319442749,
0.2827853560447693,
-0.022536560893058777,
0.22074221074581146,
0.029344789683818817,
-0.11142091453075409,
-0.5947408080101013,
-0.07118986546993256,
-0.014745701104402542,
-0.2298116683959961,
0.038247525691986084,
0.24519820511341095,
0.04038124158978462,
0.028742395341396332,
0.1323024034500122,
-0.0691981315612793,
-0.1727847009897232,
0.15835630893707275,
-0.057500746101140976,
-0.035947319120168686,
-0.10883574932813644,
0.10054506361484528,
0.14131920039653778,
0.19206145405769348,
0.08820653706789017,
-0.20974351465702057,
-0.008258426561951637,
0.19893258810043335,
0.2664552927017212,
0.29947489500045776,
0.17117848992347717,
-0.03975299000740051,
0.11774808168411255,
0.16865256428718567,
0.22219626605510712,
0.280743271112442,
0.0006242794916033745,
-0.26477840542793274,
0.012452129274606705,
0.18017485737800598,
0.2809547483921051,
-0.021284624934196472,
-0.3174169659614563,
-0.028278619050979614,
0.3193451464176178,
0.06371940672397614,
-0.1611047089099884,
-0.28946101665496826,
0.04568493738770485,
0.3787929117679596,
0.5581892728805542,
-0.052863121032714844,
0.1500057578086853,
-0.24770140647888184,
-0.24770912528038025,
-0.3083847463130951,
0.01466410607099533,
0.0906410962343216,
-0.17407086491584778,
-0.025309447199106216,
0.058844588696956635,
0.2664116322994232,
0.6372910737991333,
0.046900514513254166,
0.1413993239402771,
0.08129169046878815,
-0.23515871167182922,
-0.1235392615199089,
0.1703161597251892,
0.18290171027183533,
0.12640784680843353,
0.14134618639945984,
-0.009156955406069756,
-0.28563162684440613,
0.027415350079536438,
-0.033082716166973114,
0.4702059328556061,
0.3248135447502136,
-0.33750948309898376,
-0.10117167234420776,
-0.23019549250602722,
-0.3934479355812073,
-0.5377248525619507,
-0.4357340335845947,
-0.4151223599910736,
-0.30199292302131653,
-0.03800155967473984,
0.29891565442085266,
0.021401599049568176,
0.32440927624702454,
-0.21723322570323944,
0.29080918431282043,
-0.27205806970596313,
-0.4005089998245239,
0.0599130317568779,
-0.2860786020755768,
-0.3161654472351074,
0.008332610130310059,
0.24271626770496368,
-0.040144819766283035,
0.47745466232299805,
-0.0952480286359787,
-0.3994389772415161,
-0.24949181079864502,
-0.3282950818538666,
0.08962157368659973,
0.08339346945285797,
0.5332790017127991,
0.4108935594558716,
0.11481627076864243,
0.5304829478263855,
-0.03753073886036873,
0.017749542370438576,
-0.07441209256649017,
-0.35614117980003357,
-0.2321394830942154,
-0.01416950486600399,
0.21951957046985626,
-0.05585123598575592,
-0.33744117617607117,
-0.5183432102203369,
-0.11137236654758453,
0.08031556010246277,
0.058061737567186356,
0.07833410054445267,
0.2125878483057022,
-0.09202147275209427,
0.10448282212018967,
0.06396199762821198,
0.012659653089940548,
-0.13171161711215973,
0.1249200850725174,
0.04393646866083145,
-0.16999350488185883,
-0.03391966596245766,
0.12768365442752838,
-0.06895244121551514,
0.04899900034070015,
-0.1415833681821823,
-0.4356604814529419,
-0.4000314176082611,
0.16557317972183228,
0.17159394919872284,
0.3695302903652191,
-0.2987920939922333,
0.25390851497650146,
0.21395723521709442,
0.12991255521774292,
-0.10910617560148239,
-0.42785999178886414,
0.22798621654510498,
0.10129096359014511,
0.328249990940094,
0.277874618768692,
0.3687107563018799,
-0.19837872684001923,
0.8586010336875916,
0.20692913234233856,
-0.2106233388185501,
-0.1409544050693512,
-0.24552223086357117,
-0.06579752266407013,
0.03593466803431511,
0.013525234535336494,
0.21882010996341705,
-0.02735571563243866,
-0.31299543380737305,
0.30828821659088135,
-0.23085924983024597,
-0.1324729472398758,
-0.12156108021736145,
0.20832255482673645,
-0.02576594240963459,
-0.11315509676933289,
0.060084156692028046,
-0.14215581119060516,
0.060876816511154175,
0.008019208908081055,
-0.06661482900381088,
-0.242212176322937,
-0.25388821959495544,
0.02873433381319046,
0.3385995626449585,
-0.18707025051116943,
0.199899360537529,
-0.15251682698726654,
0.018473247066140175,
-0.40777039527893066,
0.3384018540382385,
0.3403618633747101,
0.5474084615707397,
0.12012188136577606,
-0.03538349270820618,
0.130252867937088,
0.1420363336801529,
0.2074132114648819,
-0.09370404481887817,
0.14432397484779358,
0.2877647876739502,
-0.07581368833780289,
-0.13675853610038757,
-0.3179689347743988,
0.03660054877400398,
0.18235085904598236,
0.03332754597067833,
0.12281167507171631,
-0.47096461057662964,
-0.09846272319555283,
0.28636598587036133,
0.19446681439876556,
-0.16313233971595764,
-0.3334006369113922,
-0.10241515934467316,
0.04879126697778702,
-0.0787477195262909,
-0.2163064181804657,
-0.24037285149097443,
0.044299788773059845,
-0.038856104016304016,
0.3086199164390564,
0.008862460032105446,
-0.035333748906850815,
-0.061219364404678345,
0.2663484513759613,
0.203140527009964,
-0.20016586780548096,
0.28932374715805054,
0.26163649559020996,
0.08416691422462463,
0.3153352439403534,
0.2017228603363037,
-0.08268649876117706,
-0.2403506636619568,
-0.08250287920236588,
0.01741049438714981,
0.3056638836860657,
0.30834639072418213,
0.24035514891147614,
-0.008557572960853577,
-0.1876189410686493,
-0.14486680924892426,
-0.2892586886882782,
0.16906335949897766,
0.2935923933982849,
-0.1301058530807495,
-0.10033605247735977,
-0.32827988266944885,
0.753041684627533,
0.1722811609506607,
-0.29610389471054077,
0.5668507218360901,
-0.23936660587787628,
-0.4109605550765991,
-0.013560649938881397,
0.10263343155384064,
0.983655571937561,
0.07682211697101593,
0.21855401992797852,
0.22350868582725525,
-0.19695599377155304,
0.39025282859802246,
0.16065627336502075,
0.061364591121673584,
-0.5651345252990723,
0.08804209530353546,
0.02915951795876026,
-0.09895415604114532,
0.24448162317276,
-0.0641174241900444,
-0.3517036437988281,
0.340796560049057,
0.08218178153038025,
0.29725372791290283,
0.251806378364563,
0.37033355236053467,
-0.04620489478111267,
-0.03925669938325882,
-0.24055305123329163,
0.051032960414886475,
-0.22437436878681183,
0.37193751335144043,
-0.2197386622428894,
0.0341653898358345,
-0.18881729245185852,
-0.07785946130752563,
-0.32790809869766235,
-0.23958012461662292,
-0.1501384824514389,
0.0694781243801117,
0.01919705979526043,
-0.18754321336746216,
-0.027795296162366867,
0.23903633654117584,
0.06307213008403778,
-0.12049311399459839,
-0.19020836055278778,
0.11415368318557739,
-0.20278063416481018,
0.08895593881607056,
0.23756279051303864,
-0.017683597281575203,
0.3286873996257782,
-0.344938188791275,
-0.11815755814313889,
0.153084397315979,
-0.18728309869766235,
-0.2327251136302948,
-0.0833955630660057,
-0.19458208978176117,
0.04582098871469498,
-0.3402763903141022,
-0.24017846584320068,
-0.07632221281528473,
0.027845080941915512,
-0.10413603484630585,
0.03824275732040405,
0.1613779217004776,
-0.3257570266723633,
0.017180494964122772,
0.05420565605163574,
-0.3329341411590576,
0.046963922679424286,
0.3687138855457306,
-0.08637317270040512,
-0.0008773207664489746,
0.6735666990280151,
-0.24754710495471954,
0.0873531699180603,
-0.1080072820186615,
0.00033754855394363403,
-0.3327271342277527,
-0.13322949409484863,
-0.041136953979730606,
-0.04393347352743149,
-0.2875954210758209,
-0.06571599096059799,
0.5596664547920227,
0.5117817521095276,
0.10100822895765305,
0.06241864338517189,
-0.38301175832748413,
-0.3422272801399231,
0.07540889829397202,
-0.12961728870868683,
0.26565831899642944,
-0.07393591105937958,
0.2888074219226837,
0.09227896481752396,
0.04482793062925339,
-0.2038612961769104,
-0.14279797673225403,
0.017405079677700996,
0.2378128170967102,
-0.1625673472881317,
0.12307857722043991,
-0.11569193005561829,
0.02843397483229637,
-0.014393167570233345,
-0.10343128442764282,
-0.26048529148101807,
-0.046801865100860596,
-0.1658414751291275,
0.22512242197990417,
0.030804991722106934,
0.08343673497438431,
0.012772510759532452,
-0.18992915749549866,
0.09936897456645966,
0.17254619300365448,
0.004947792738676071,
0.11314799636602402,
-0.06754785776138306,
0.27282944321632385,
0.3285064697265625,
0.11845237016677856,
-0.12467221170663834,
0.27501192688941956,
0.10709872841835022,
0.21082846820354462,
-0.006238457281142473,
0.3608352243900299,
-0.2627809941768646,
0.03662126511335373,
0.18331493437290192,
0.1857268363237381,
-0.20792989432811737,
0.13544869422912598,
0.016381077468395233,
-0.043131835758686066,
0.033261869102716446,
0.14998728036880493,
0.3344946801662445,
0.7781230807304382,
-0.31009289622306824,
-0.17035159468650818,
0.45299553871154785,
0.06668003648519516,
-0.19272948801517487,
-0.05105960741639137,
0.33120492100715637,
0.04032453894615173,
0.07683902978897095,
0.26023223996162415,
0.011644836515188217,
-0.06465494632720947,
0.19975247979164124,
0.1704651117324829,
-0.010798591189086437,
-0.25926119089126587,
0.08984926342964172,
0.3426205813884735,
-0.1821492463350296,
0.1657041758298874,
0.3916597068309784,
0.1482623666524887,
0.27847620844841003,
0.0073833465576171875,
0.1359972506761551,
0.42005884647369385,
0.041430309414863586,
-0.07995542883872986,
0.09235894680023193,
0.11966158449649811,
0.10311749577522278,
0.2714880704879761,
-0.11963316798210144,
0.03871629387140274,
0.40465420484542847,
0.5331206917762756,
-0.2811599373817444,
-0.1410217136144638,
-0.3413615822792053,
-0.15611927211284637,
0.06328190863132477,
-0.2039298415184021,
-0.31007635593414307,
0.02806532382965088,
-0.12455867975950241,
-0.12496000528335571,
-0.17175202071666718,
-0.3785262703895569,
0.26906606554985046,
0.069513238966465,
-0.37244659662246704,
-0.33372125029563904,
-0.2165621817111969,
0.2483433187007904,
0.09707961976528168,
-0.35574105381965637,
0.15877225995063782,
-0.02369759976863861,
-0.032223887741565704,
0.2971591055393219,
0.337347149848938,
0.4456102252006531,
-0.01678197830915451,
-0.3285940885543823,
-0.2467661201953888,
-0.16939690709114075,
0.09490392357110977,
0.032078564167022705,
0.20311376452445984,
0.010795369744300842,
-0.30086663365364075,
0.550868570804596,
0.07143069058656693,
0.05135621130466461,
0.12386082112789154,
0.39140841364860535,
-0.437709778547287,
-0.17570669949054718,
0.5832920670509338,
-0.017454370856285095,
-0.18201804161071777,
0.0052442774176597595,
0.24485048651695251,
-0.32897526025772095,
0.1818324476480484,
0.021824555471539497,
0.04144666716456413,
0.14532455801963806,
0.08675605058670044,
0.021519936621189117,
-0.11364661157131195,
0.41381996870040894,
0.2832196354866028,
-0.067356176674366,
-0.26395896077156067,
-0.22315652668476105,
-0.7593231201171875,
0.18017226457595825,
-0.13770221173763275,
-0.37075382471084595,
0.00038871075958013535,
-0.2127862572669983,
0.24636933207511902,
0.0333915539085865,
-0.1169736236333847,
-0.01768765226006508,
-0.004545869305729866,
0.18568389117717743,
-0.23927201330661774,
-0.3589065968990326,
-0.13322223722934723,
0.01474012155085802,
0.013599071651697159,
-0.3658691942691803,
0.11531181633472443,
-0.28083860874176025,
-0.1155008003115654,
0.061025869101285934,
0.012041762471199036,
0.5453343391418457,
0.053665194660425186,
0.24777232110500336,
-0.16881844401359558,
0.7727642059326172,
0.15961363911628723,
-0.06454945355653763,
-0.1531020998954773,
0.09544989466667175,
-0.13104097545146942,
0.1424974501132965,
-0.08216860890388489,
0.1293344348669052,
-0.16671285033226013,
0.4938800632953644,
-0.36660730838775635,
0.5406874418258667,
-0.09922477602958679,
0.08082855492830276,
-0.22181880474090576,
-0.03709619492292404,
-0.1514166295528412,
0.11986333131790161,
0.22769096493721008,
0.27160707116127014,
-0.10734821856021881,
0.35704654455184937,
-0.23412734270095825,
-0.35361191630363464,
0.4814947545528412,
-0.10037000477313995,
-0.15508422255516052,
0.021687045693397522,
0.3206314742565155,
-0.09507077187299728,
0.07444199919700623,
-0.42972448468208313,
0.2376844584941864,
0.3241073191165924,
-0.04060295969247818,
0.008704844862222672,
0.2114335149526596,
0.22685380280017853,
0.08315175771713257,
0.0017669722437858582,
1.0600345134735107,
-0.1092364564538002,
0.02344811148941517,
-0.2541804015636444,
-0.3114486336708069
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | Actually maybe our versioning format (inherited from tfds) is too strong for what we use it for?
We could allow any string maybe?
I see it more and more like an identifier for the user that we will back with a serious hashing/versioning system.- so we could let the user quite free on it. | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 54 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
Actually maybe our versioning format (inherited from tfds) is too strong for what we use it for?
We could allow any string maybe?
I see it more and more like an identifier for the user that we will back with a serious hashing/versioning system.- so we could let the user quite free on it. | [
-0.15275150537490845,
0.21056944131851196,
0.005356155335903168,
-0.15212193131446838,
0.1695309579372406,
-0.12297330796718597,
0.34444764256477356,
0.3772251605987549,
0.013979699462652206,
0.22968517243862152,
0.1677790880203247,
0.015225032344460487,
-0.334241658449173,
0.031307391822338104,
0.022818464785814285,
-0.1002444326877594,
-0.0594150647521019,
0.197006493806839,
-0.07303541898727417,
0.34329521656036377,
-0.06011242792010307,
-0.07316155731678009,
0.0019713863730430603,
0.1934303343296051,
0.010817679576575756,
0.14580464363098145,
-0.1153508797287941,
-0.018754221498966217,
-0.3885170817375183,
-0.8583570718765259,
0.13438120484352112,
0.09185026586055756,
0.2320997565984726,
0.43688473105430603,
-0.00012612353020813316,
-0.07396548241376877,
0.5866605639457703,
-0.024042073637247086,
-0.7674411535263062,
-0.16982929408550262,
0.34464287757873535,
-0.3756412863731384,
0.25355127453804016,
-0.06578004360198975,
0.11371976882219315,
-0.1838429570198059,
0.18135371804237366,
0.07539583742618561,
0.1361459195613861,
0.245559960603714,
0.09919436275959015,
0.31069257855415344,
0.028131205588579178,
-0.11110033094882965,
-0.05956900864839554,
0.12354503571987152,
-0.14380034804344177,
0.5142217874526978,
0.48955070972442627,
0.24067121744155884,
-0.07860211282968521,
-0.07082480192184448,
0.06261495500802994,
0.4359807074069977,
0.13713976740837097,
-0.0326455682516098,
0.5384781360626221,
0.044237054884433746,
-0.19004222750663757,
0.16044630110263824,
0.8945168852806091,
-0.5086084604263306,
-0.4655519425868988,
-0.06761332601308823,
0.017939716577529907,
-0.10367359966039658,
0.10765813291072845,
-0.19388851523399353,
-0.3774493634700775,
0.20891021192073822,
-0.1669583022594452,
-0.33218520879745483,
-0.09904003143310547,
0.28893008828163147,
-0.17620722949504852,
0.23123739659786224,
0.1270466297864914,
0.25155389308929443,
-0.02958333119750023,
-0.0673801377415657,
0.1549283266067505,
-0.052094221115112305,
0.015269063413143158,
0.1340530812740326,
0.08804330229759216,
-0.3319090008735657,
-0.4149754047393799,
-0.29810580611228943,
0.1995212733745575,
0.025635112076997757,
-0.5338376760482788,
-0.18990269303321838,
-0.06855496019124985,
0.17624177038669586,
0.08776327967643738,
0.2744106650352478,
0.36686965823173523,
0.22054314613342285,
0.311817467212677,
-0.010775187984108925,
0.28586411476135254,
0.21933385729789734,
-0.00553248543292284,
-0.27972203493118286,
-0.002387784421443939,
0.07539418339729309,
0.10619138181209564,
-0.21187756955623627,
-0.02138431742787361,
-0.25974953174591064,
-0.42282959818840027,
-0.0277206152677536,
-0.09297081083059311,
0.23292586207389832,
-0.17843417823314667,
-0.1466093361377716,
-0.01997271366417408,
0.3341640830039978,
-0.10098528116941452,
-0.1949630081653595,
-0.00010901223868131638,
-0.020320232957601547,
-0.24842840433120728,
-0.06086083501577377,
0.22468288242816925,
-0.13178770244121552,
0.3598708212375641,
-0.35544416308403015,
-0.14415745437145233,
-0.03814074397087097,
-0.022520100697875023,
0.03089410811662674,
-0.17065325379371643,
0.28824383020401,
-0.23571887612342834,
0.017072374001145363,
0.05582606792449951,
-0.30029064416885376,
-0.2188141644001007,
0.21825045347213745,
-0.0032299980521202087,
-0.43608370423316956,
-0.13643638789653778,
0.06006927415728569,
-0.5637033581733704,
0.02172400988638401,
0.04728544503450394,
-0.16956348717212677,
0.18883562088012695,
-0.2967650294303894,
0.14172445237636566,
-0.250382661819458,
-0.36074426770210266,
-0.15156853199005127,
-0.1783817857503891,
0.22806385159492493,
-0.31079187989234924,
-0.2898619771003723,
-0.22972798347473145,
-0.38468137383461,
0.07798102498054504,
-0.13051730394363403,
-0.07232106477022171,
0.20862683653831482,
-0.33610525727272034,
-0.035919029265642166,
0.6512778997421265,
-0.5617484450340271,
-0.2883245646953583,
0.6501520872116089,
-0.39960044622421265,
-0.2595352530479431,
0.2737455368041992,
-0.07269967347383499,
0.14991018176078796,
-0.44446316361427307,
-0.1325370967388153,
0.004221666604280472,
-0.04450642317533493,
-0.1131410151720047,
-0.08715605735778809,
-0.42463457584381104,
0.2098807692527771,
0.20373685657978058,
-0.06479039788246155,
0.2234140932559967,
0.1218448057770729,
0.10671255737543106,
0.4471711218357086,
0.03521332889795303,
0.16927526891231537,
-0.21021631360054016,
0.20478932559490204,
-0.1228678822517395,
-0.1074662134051323,
-0.13562634587287903,
-0.5853860378265381,
0.24203673005104065,
-0.04733653366565704,
0.15349692106246948,
-0.006374247372150421,
-0.06405392289161682,
-0.4417177438735962,
0.02850235067307949,
0.10575544834136963,
-0.21586723625659943,
-0.05539102852344513,
0.14584729075431824,
0.025066480040550232,
-0.03469604253768921,
-0.02631925232708454,
-0.00754067488014698,
-0.2913230061531067,
0.16251416504383087,
0.20891226828098297,
-0.14848344027996063,
-0.08332210779190063,
0.09957940131425858,
0.15043026208877563,
0.2522900700569153,
-0.06979330629110336,
-0.3053167164325714,
0.02069862186908722,
0.32338932156562805,
0.25860595703125,
0.14943833649158478,
0.07985370606184006,
0.05053447186946869,
0.18621467053890228,
0.26682206988334656,
0.14637459814548492,
0.20671021938323975,
0.024877086281776428,
-0.2785708010196686,
0.023999277502298355,
0.15529467165470123,
0.15474027395248413,
-0.024672679603099823,
-0.2123958319425583,
-0.042884498834609985,
0.2966698110103607,
0.08589234948158264,
-0.15950703620910645,
-0.28861576318740845,
0.10071870684623718,
0.2132439762353897,
0.6271629333496094,
0.013069907203316689,
0.23440656065940857,
-0.16070425510406494,
-0.19119104743003845,
-0.4197957515716553,
0.047629404813051224,
0.2504350244998932,
-0.08639683574438095,
-0.06156587973237038,
-0.03870204836130142,
0.24559788405895233,
0.8113179206848145,
0.0071622407995164394,
0.2236732691526413,
0.05936606228351593,
-0.06221941113471985,
-0.2031267285346985,
0.21539631485939026,
0.18741638958454132,
-0.019955070689320564,
0.14958512783050537,
-0.009534548968076706,
-0.213071808218956,
0.011151015758514404,
-0.02994939126074314,
0.37450703978538513,
0.3891151249408722,
-0.45985034108161926,
-0.071262426674366,
-0.2434227615594864,
-0.4637845754623413,
-0.35133445262908936,
-0.32140475511550903,
-0.2830204963684082,
-0.28866180777549744,
-0.07606277614831924,
0.32052579522132874,
0.0429517887532711,
0.22180591523647308,
-0.27010664343833923,
0.2553025782108307,
-0.2692341208457947,
-0.2900591194629669,
0.039597876369953156,
-0.13836529850959778,
-0.3783036172389984,
-0.010134518146514893,
0.2034052461385727,
-0.12987132370471954,
0.49237048625946045,
-0.04010806977748871,
-0.2758660316467285,
-0.21922940015792847,
-0.34642720222473145,
0.1785959154367447,
-0.008019987493753433,
0.5385330319404602,
0.5283278822898865,
0.011747114360332489,
0.49219995737075806,
0.04509781673550606,
-0.10305843502283096,
-0.2824671268463135,
-0.44600310921669006,
-0.1996392160654068,
0.04542342200875282,
0.12376132607460022,
-0.22519946098327637,
-0.24200621247291565,
-0.5144346952438354,
-0.10970619320869446,
0.14452898502349854,
-0.03499829024076462,
0.12034574151039124,
0.27052778005599976,
-0.18616634607315063,
0.13806453347206116,
-0.006836146581918001,
-0.06195448338985443,
-0.15893393754959106,
0.07213608920574188,
-0.09341348707675934,
-0.15120358765125275,
-0.1503472477197647,
0.05138719454407692,
0.009144652634859085,
-0.026123594492673874,
-0.03587005287408829,
-0.34018993377685547,
-0.46588650345802307,
0.15529721975326538,
0.13913819193840027,
0.34824758768081665,
-0.22888325154781342,
0.19969868659973145,
0.2338806539773941,
0.1612386405467987,
-0.06107719987630844,
-0.34528347849845886,
0.14796283841133118,
0.04752747714519501,
0.24498242139816284,
0.26928919553756714,
0.4195297360420227,
-0.01958618126809597,
0.7755740284919739,
0.14332546293735504,
-0.0958905965089798,
-0.07831813395023346,
-0.2671540081501007,
0.006282620131969452,
-0.05424752086400986,
-0.005567440763115883,
0.31085702776908875,
-0.10074695944786072,
-0.28282248973846436,
0.3185688853263855,
-0.18947568535804749,
0.05149201303720474,
-0.09044620394706726,
0.2656155824661255,
-0.06809309124946594,
-0.0441906563937664,
0.05007345229387283,
-0.28195029497146606,
0.039340317249298096,
-0.012657798826694489,
-0.03752116113901138,
-0.13320261240005493,
-0.21860477328300476,
0.09952671825885773,
0.3623552918434143,
-0.018679574131965637,
0.29034313559532166,
-0.11583904922008514,
0.15687815845012665,
-0.34239599108695984,
0.2570706009864807,
0.4411430060863495,
0.6185430288314819,
0.08319763839244843,
0.09134873002767563,
0.1832665205001831,
0.12001954764127731,
0.2273235023021698,
-0.03647734224796295,
0.23378071188926697,
0.06326091289520264,
-0.23603403568267822,
-0.017865262925624847,
-0.2264620065689087,
0.00059470534324646,
0.09605272859334946,
-0.07571941614151001,
0.17361825704574585,
-0.4774007499217987,
-0.23207788169384003,
0.21772129833698273,
0.10532347857952118,
-0.07665837556123734,
-0.38931038975715637,
-0.06505332887172699,
0.03828480839729309,
-0.05286567658185959,
-0.31292566657066345,
-0.136131152510643,
-0.0052222381345927715,
-0.08902165293693542,
0.43324971199035645,
-0.10226196050643921,
-0.14556947350502014,
-0.005133286118507385,
0.10432887077331543,
0.044709838926792145,
-0.19614487886428833,
0.20612138509750366,
0.19784824550151825,
0.1746518313884735,
0.21705137193202972,
0.18835315108299255,
-0.0840260237455368,
-0.1561623066663742,
-0.03743549808859825,
-0.05730261281132698,
0.3986186385154724,
0.3663225769996643,
0.10062596201896667,
0.04277164861559868,
-0.2101757824420929,
-0.15302953124046326,
-0.34225931763648987,
0.22055724263191223,
0.28233063220977783,
-0.16399061679840088,
-0.05102991312742233,
-0.28409022092819214,
0.6471732258796692,
0.14356431365013123,
-0.2456749975681305,
0.4512062668800354,
-0.1504860818386078,
-0.30368852615356445,
-0.025458380579948425,
0.12860321998596191,
0.985715925693512,
0.043363362550735474,
0.22869481146335602,
0.38514605164527893,
-0.33894407749176025,
0.42819705605506897,
0.14748515188694,
0.02666272222995758,
-0.5198193192481995,
-0.05517926067113876,
-0.05943042039871216,
-0.165473073720932,
0.274152547121048,
-0.15859314799308777,
-0.20023588836193085,
0.34560856223106384,
0.08795057237148285,
0.3736129701137543,
0.4137502610683441,
0.39923718571662903,
-0.10544490814208984,
-0.05788303539156914,
-0.16087783873081207,
0.02206481248140335,
-0.18493792414665222,
0.28433409333229065,
-0.21571719646453857,
-0.020652487874031067,
-0.18660970032215118,
-0.028540097177028656,
-0.24675114452838898,
-0.23737698793411255,
-0.1255301535129547,
0.017985105514526367,
0.1404607594013214,
-0.10921992361545563,
0.05769843980669975,
0.16871511936187744,
0.1828477382659912,
-0.09496639668941498,
-0.13535992801189423,
0.025371313095092773,
-0.23170378804206848,
0.2188091278076172,
0.3044604957103729,
0.028277065604925156,
0.3999037444591522,
-0.28152593970298767,
-0.07076147198677063,
0.14869144558906555,
-0.2799605131149292,
-0.2452802211046219,
-0.17162904143333435,
-0.21622012555599213,
0.16090381145477295,
-0.35440143942832947,
-0.2652537226676941,
-0.1846257746219635,
-0.020434550940990448,
-0.03614324703812599,
-0.03854873403906822,
0.23290929198265076,
-0.3300037682056427,
-0.01323217898607254,
-0.037422265857458115,
-0.3219470977783203,
0.03071577660739422,
0.48213672637939453,
-0.04637731611728668,
-0.17012344300746918,
0.6307938098907471,
-0.24155570566654205,
0.028976164758205414,
-0.0897454023361206,
0.03222358971834183,
-0.18571768701076508,
-0.1862180531024933,
0.03852279856801033,
-0.07007022202014923,
-0.3210486173629761,
-0.03493773564696312,
0.6218963861465454,
0.5002497434616089,
0.026229266077280045,
-0.07093337178230286,
-0.4239475727081299,
-0.4768606126308441,
-0.019827544689178467,
-0.21596606075763702,
0.14384189248085022,
-0.20705530047416687,
0.3047216832637787,
0.09505714476108551,
0.03632984682917595,
-0.1691185086965561,
-0.2332279086112976,
0.12708936631679535,
0.26113492250442505,
-0.20231159031391144,
0.03588312864303589,
-0.010400895029306412,
0.04883423447608948,
-0.07755549252033234,
0.054522521793842316,
-0.34435224533081055,
-0.022740554064512253,
-0.22121775150299072,
0.2403482049703598,
0.12901584804058075,
0.015883587300777435,
0.1009754091501236,
-0.12922483682632446,
-0.03020528331398964,
0.19713294506072998,
-0.03883189707994461,
0.1435362994670868,
-0.08869205415248871,
0.2655784785747528,
0.31918010115623474,
0.1678486168384552,
-0.0894201248884201,
0.2904230058193207,
0.08135998994112015,
0.2633010745048523,
-0.03736348822712898,
0.3029985725879669,
-0.22787117958068848,
0.036965735256671906,
0.10371330380439758,
0.246509850025177,
-0.018953166902065277,
0.24331048130989075,
0.11851654946804047,
-0.08313368260860443,
0.09952300786972046,
0.0027661691419780254,
0.38336580991744995,
0.7761162519454956,
-0.18420851230621338,
-0.3148205578327179,
0.4969845116138458,
0.017806198447942734,
-0.10703211277723312,
0.006450509186834097,
0.24761880934238434,
0.16800172626972198,
0.02530844137072563,
0.3604945242404938,
0.03009425476193428,
-0.035909440368413925,
0.09229389578104019,
0.1062341257929802,
0.08866747468709946,
-0.26417475938796997,
-0.2379094362258911,
0.5210915207862854,
-0.2259112149477005,
0.24124941229820251,
0.3535771667957306,
0.13580672442913055,
0.29599878191947937,
0.03766085207462311,
0.07566314935684204,
0.5019505620002747,
-0.010013192892074585,
0.04312687739729881,
0.14046424627304077,
0.13297908008098602,
0.014500580728054047,
0.2870316505432129,
0.07500987499952316,
0.013744734227657318,
0.33756130933761597,
0.5905369520187378,
-0.20217715203762054,
-0.1644720584154129,
-0.1727122813463211,
-0.16748780012130737,
0.0769597664475441,
-0.228070467710495,
-0.2735540568828583,
0.1288490891456604,
-0.21248170733451843,
-0.1030297726392746,
-0.23020565509796143,
-0.29267215728759766,
0.21165421605110168,
0.05275091901421547,
-0.33862531185150146,
-0.27144676446914673,
-0.4014511704444885,
0.1491457223892212,
0.05067802220582962,
-0.34592893719673157,
0.12932947278022766,
-0.07099097967147827,
0.11562046408653259,
0.3956110179424286,
0.2540735602378845,
0.3397336006164551,
0.06733053922653198,
-0.3097277283668518,
-0.31341180205345154,
-0.32432109117507935,
0.15070955455303192,
0.008740007877349854,
0.39771607518196106,
0.017714716494083405,
-0.11327928304672241,
0.6163249015808105,
0.004212956875562668,
0.10033030062913895,
0.2640596628189087,
0.36592113971710205,
-0.5369967222213745,
-0.11764606833457947,
0.7859679460525513,
0.07999040186405182,
-0.1935425102710724,
0.07940411567687988,
0.22868478298187256,
-0.19130200147628784,
0.17380353808403015,
0.046440206468105316,
-0.11265183240175247,
0.1843630075454712,
0.11147186905145645,
0.01518373191356659,
-0.05229577049612999,
0.34844377636909485,
0.4192717373371124,
-0.0645558089017868,
-0.2744944393634796,
-0.015578880906105042,
-0.6457434296607971,
0.181339830160141,
-0.05328163132071495,
-0.25216221809387207,
0.0043504745699465275,
-0.242372527718544,
0.17777614295482635,
0.11598408967256546,
-0.2468876987695694,
0.13935711979866028,
-0.08880764245986938,
0.08666262775659561,
-0.1472114473581314,
-0.3679315149784088,
-0.17883417010307312,
0.0805131047964096,
-0.07546988129615784,
-0.4362681806087494,
0.20022113621234894,
-0.4206122159957886,
-0.12240853160619736,
0.07628065347671509,
0.015164688229560852,
0.5335344672203064,
-0.019309580326080322,
0.2926962673664093,
-0.05495215207338333,
0.5333094596862793,
0.19510090351104736,
0.006029875949025154,
-0.18519791960716248,
0.18206799030303955,
-0.1992652863264084,
0.13084818422794342,
-0.04895910248160362,
0.06954202055931091,
-0.14772485196590424,
0.5281546115875244,
-0.4214254915714264,
0.5098816752433777,
-0.05077594146132469,
0.16153916716575623,
-0.32901185750961304,
0.10240151733160019,
-0.24033862352371216,
0.08635570108890533,
0.2888404428958893,
0.21862655878067017,
-0.11910434067249298,
0.3717103898525238,
-0.2540442943572998,
-0.20215848088264465,
0.4779549837112427,
-0.1859750598669052,
-0.10019859671592712,
0.15425102412700653,
0.3032086491584778,
0.19870346784591675,
-0.18652045726776123,
-0.5294916033744812,
0.15762919187545776,
0.3263663649559021,
-0.10436972230672836,
-0.04502715915441513,
0.22184592485427856,
0.20797038078308105,
0.06086595728993416,
0.007538933306932449,
0.9585251808166504,
-0.13304033875465393,
0.08896137028932571,
-0.06882606446743011,
-0.24809643626213074
] |
https://github.com/huggingface/datasets/issues/161 | Discussion on version identifier & MockDataLoaderManager for test data | I'm good with either putting it in description, adding it to the config, or loosening version formatting. I mostly don't have a full conceptual grasp of what each identifier ends up meaning in the datasets code so hard to evaluate the best approach.
For background, the multiple formats is a consequence of:
1. Each example is one multi-sentence trivia question
2. For training, its better to treat each sentence as an example
3. For evaluation, should test on: (1) first sentence, (2) full question, and (3) partial questions (does the model get the question right having seen the first half)
We use the date format for version since: (1) we expect some degree of updates since new questions come in every year and (2) the timestamp itself matches the Wikipedia dump that it is dependent on (so similar to the Wikipedia dataset).
perhaps this is better discussed in https://github.com/huggingface/nlp/pull/169 or update title? | Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done. | 152 | Discussion on version identifier & MockDataLoaderManager for test data
Hi, I'm working on adding a dataset and ran into an error due to `download` not being defined on `MockDataLoaderManager`, but being defined in `nlp/utils/download_manager.py`. The readme step running this: `RUN_SLOW=1 pytest tests/test_dataset_common.py::DatasetTest::test_load_real_dataset_localmydatasetname` triggers the error. If I can get something to work, I can include it in my data PR once I'm done.
I'm good with either putting it in description, adding it to the config, or loosening version formatting. I mostly don't have a full conceptual grasp of what each identifier ends up meaning in the datasets code so hard to evaluate the best approach.
For background, the multiple formats is a consequence of:
1. Each example is one multi-sentence trivia question
2. For training, its better to treat each sentence as an example
3. For evaluation, should test on: (1) first sentence, (2) full question, and (3) partial questions (does the model get the question right having seen the first half)
We use the date format for version since: (1) we expect some degree of updates since new questions come in every year and (2) the timestamp itself matches the Wikipedia dump that it is dependent on (so similar to the Wikipedia dataset).
perhaps this is better discussed in https://github.com/huggingface/nlp/pull/169 or update title? | [
0.05760304257273674,
0.24249693751335144,
-0.000598544254899025,
-0.016872867941856384,
-0.026223141700029373,
-0.10918831825256348,
0.3703441321849823,
0.27449801564216614,
0.0017391927540302277,
-0.07336340844631195,
0.19066615402698517,
0.1067383736371994,
-0.2590656578540802,
0.05271521955728531,
0.06369110941886902,
-0.17159409821033478,
0.06112443655729294,
0.205256849527359,
-0.09032115340232849,
0.19936902821063995,
-0.10669591277837753,
-0.01393563486635685,
-0.021723750978708267,
0.2025269865989685,
-0.09185992181301117,
-0.044857464730739594,
-0.290224552154541,
0.06356648355722427,
-0.35639968514442444,
-0.9518452882766724,
0.2559972405433655,
0.16132852435112,
0.21488924324512482,
0.39023557305336,
-0.00012299601803533733,
-0.13422223925590515,
0.5136099457740784,
-0.030447958037257195,
-0.7506924867630005,
-0.1976187378168106,
0.3274133801460266,
-0.4366213083267212,
0.3908313810825348,
-0.0833529680967331,
0.20270678400993347,
-0.2667604982852936,
0.31416061520576477,
0.2079792022705078,
0.1440405696630478,
0.2145276963710785,
0.07082146406173706,
0.2529842257499695,
0.02971867099404335,
-0.09841020405292511,
-0.04017750918865204,
0.11929966509342194,
-0.034477971494197845,
0.5099808573722839,
0.39377060532569885,
0.12621459364891052,
-0.16321870684623718,
0.11727796494960785,
0.14007452130317688,
0.3983493447303772,
0.2259792685508728,
-0.01795342192053795,
0.5039622783660889,
-0.047598786652088165,
-0.20237979292869568,
0.05471815541386604,
0.8494493961334229,
-0.5009220838546753,
-0.4326480031013489,
-0.14169380068778992,
0.032289765775203705,
-0.16478854417800903,
0.2154712677001953,
-0.10920235514640808,
-0.15507255494594574,
0.05712485313415527,
-0.24445389211177826,
-0.11133310943841934,
-0.15746980905532837,
0.336891770362854,
-0.22511881589889526,
0.2915149927139282,
-0.010365025140345097,
0.19610467553138733,
-0.030724529176950455,
-0.1835590898990631,
0.057907577604055405,
-0.2011939138174057,
0.07630202174186707,
0.17462009191513062,
0.016123972833156586,
-0.2886023223400116,
-0.29430362582206726,
-0.18726423382759094,
0.12454863637685776,
0.014857377856969833,
-0.4481185972690582,
-0.17962482571601868,
-0.03736473247408867,
0.2117084562778473,
0.25023096799850464,
0.3405122458934784,
0.3932395279407501,
0.19038574397563934,
0.15328194200992584,
0.08018219470977783,
0.15144771337509155,
0.1508202850818634,
-0.041883792728185654,
-0.22569634020328522,
-0.011925308033823967,
0.02554197423160076,
0.16613106429576874,
-0.2824716866016388,
-0.05167902633547783,
-0.12572945654392242,
-0.5409555435180664,
-0.07574271410703659,
-0.1315053552389145,
0.23289451003074646,
-0.17989923059940338,
-0.0450725182890892,
0.03212364763021469,
0.4197337031364441,
-0.1784875988960266,
-0.15913546085357666,
-0.015688810497522354,
0.0746147632598877,
-0.2581358551979065,
-0.04566466808319092,
0.174321711063385,
-0.09063209593296051,
0.4508668780326843,
-0.2195093035697937,
-0.33825039863586426,
-0.179396390914917,
0.06953290104866028,
0.013142002746462822,
-0.09206866472959518,
0.2377602905035019,
-0.195138081908226,
0.06764184683561325,
0.0803680494427681,
-0.41097766160964966,
-0.2782211899757385,
0.010887682437896729,
0.05627662315964699,
-0.34333714842796326,
-0.027284765616059303,
0.06280625611543655,
-0.4833716154098511,
-0.010563388466835022,
0.12420543283224106,
0.0902782678604126,
0.14917361736297607,
-0.3166505694389343,
0.10074393451213837,
-0.41337746381759644,
-0.2347722351551056,
-0.09195572882890701,
-0.1889968365430832,
0.3042604923248291,
-0.2840292155742645,
-0.27550458908081055,
-0.1664571464061737,
-0.31274059414863586,
0.09089353680610657,
-0.18867769837379456,
-0.0761040449142456,
0.2745271623134613,
-0.1902463138103485,
0.03018895536661148,
0.5996158719062805,
-0.5389538407325745,
-0.2087562531232834,
0.5325261354446411,
-0.2751666009426117,
-0.052935075014829636,
0.28938454389572144,
-0.073978491127491,
0.110174261033535,
-0.35946279764175415,
-0.1081964522600174,
0.05834294110536575,
0.003969097509980202,
-0.19246141612529755,
-0.21571467816829681,
-0.26801130175590515,
0.18028435111045837,
0.28513103723526,
-0.1920585185289383,
0.018702417612075806,
0.06548072397708893,
0.18505845963954926,
0.3273560106754303,
0.09518390893936157,
0.12832678854465485,
-0.18868356943130493,
-0.05513500049710274,
-0.07846146821975708,
-0.12363823503255844,
-0.01617143303155899,
-0.7373564839363098,
0.1525452435016632,
-0.10349711030721664,
0.20631973445415497,
0.04400281608104706,
0.0035772137343883514,
-0.4655626118183136,
-0.049690138548612595,
-0.07461187243461609,
-0.30068257451057434,
0.030343875288963318,
0.23752397298812866,
0.07605691254138947,
-0.003967924043536186,
0.00890287384390831,
-0.012331390753388405,
-0.3098595142364502,
0.24812154471874237,
-0.04932260885834694,
-0.18346983194351196,
-0.0836695060133934,
0.14995940029621124,
0.205399289727211,
0.25154605507850647,
0.033978402614593506,
-0.2759888768196106,
0.10466857999563217,
0.32568368315696716,
0.23714834451675415,
0.24148528277873993,
0.17153821885585785,
0.06900224834680557,
0.23371590673923492,
0.3315989673137665,
0.3070366680622101,
0.16558153927326202,
0.08676372468471527,
-0.26936161518096924,
-0.09193149954080582,
0.1549011915922165,
0.2427971512079239,
0.004586212337017059,
-0.16184183955192566,
-0.06739960610866547,
0.33853983879089355,
0.1212911605834961,
-0.2309657782316208,
-0.2655969262123108,
0.012635204941034317,
0.29515546560287476,
0.6402701735496521,
0.06318031251430511,
0.08673670887947083,
-0.03449440747499466,
-0.11137320101261139,
-0.46820640563964844,
-0.023292236030101776,
0.09991331398487091,
-0.2714596688747406,
-0.16550683975219727,
-0.019511381164193153,
0.2567764222621918,
0.7403609752655029,
0.014357052743434906,
0.28377461433410645,
0.043051786720752716,
-0.26060429215431213,
-0.2131253033876419,
0.1901426613330841,
0.29233241081237793,
-0.07247414439916611,
0.14260801672935486,
0.05944399535655975,
-0.22141100466251373,
-0.011801742017269135,
-0.14425168931484222,
0.3677428364753723,
0.3290640711784363,
-0.4422619044780731,
0.011568421497941017,
-0.22433897852897644,
-0.4463372230529785,
-0.5092363357543945,
-0.37744784355163574,
-0.2606242895126343,
-0.348259836435318,
-0.05424051731824875,
0.2230663299560547,
-0.09885327517986298,
0.20850633084774017,
-0.04445458948612213,
0.3514876663684845,
-0.33391475677490234,
-0.061890989542007446,
0.18121905624866486,
-0.2874465882778168,
-0.43042632937431335,
-0.02127774804830551,
0.37744420766830444,
0.010301250964403152,
0.3699018955230713,
-0.16296160221099854,
-0.3067917227745056,
-0.1718650460243225,
-0.35774680972099304,
0.17577336728572845,
-0.05133640766143799,
0.4902479350566864,
0.4374166429042816,
0.05680596083402634,
0.42201197147369385,
-0.07975700497627258,
-0.005827383138239384,
-0.061605677008628845,
-0.35395562648773193,
-0.19850434362888336,
0.00805377122014761,
0.011529458686709404,
-0.22299200296401978,
-0.46764835715293884,
-0.5795467495918274,
-0.06716534495353699,
0.23849734663963318,
0.02374003455042839,
0.1362578123807907,
0.3584892749786377,
-0.2352583259344101,
0.23094291985034943,
-0.11682120710611343,
0.06175294518470764,
-0.1307680606842041,
0.04842299595475197,
0.033469658344984055,
-0.1410067081451416,
-0.14650937914848328,
0.08306850492954254,
-0.06929121911525726,
-0.056239258497953415,
-0.12516795098781586,
-0.4092954397201538,
-0.46038907766342163,
0.19253312051296234,
-0.019878249615430832,
0.3854581415653229,
-0.11975400149822235,
0.19413024187088013,
0.22859154641628265,
0.15268848836421967,
-0.0922197699546814,
-0.25398755073547363,
0.3085111975669861,
0.0481681227684021,
0.2682611346244812,
0.2667809724807739,
0.30996257066726685,
-0.08249562233686447,
0.8548855185508728,
0.23433223366737366,
-0.2229716032743454,
-0.17823828756809235,
-0.028071874752640724,
-0.07432746887207031,
0.008990399539470673,
0.039054155349731445,
0.24598310887813568,
-0.19373923540115356,
-0.2576615810394287,
0.4539285898208618,
-0.11471707373857498,
-0.07941103726625443,
-0.012890700250864029,
0.28912875056266785,
-0.10928496718406677,
-0.005734983831644058,
0.19463348388671875,
-0.15763550996780396,
0.023471180349588394,
0.010373320430517197,
-0.033706650137901306,
-0.15833380818367004,
-0.06846459209918976,
-0.0331968329846859,
0.34193724393844604,
-0.11140764504671097,
0.21972520649433136,
-0.27268800139427185,
-0.06407055258750916,
-0.2533634603023529,
0.23277431726455688,
0.39788496494293213,
0.4647171199321747,
0.15090231597423553,
-0.0316687636077404,
0.21203121542930603,
0.20424798130989075,
0.08792264014482498,
-0.03190042823553085,
0.1063772439956665,
0.18112264573574066,
-0.22042010724544525,
-0.03037141263484955,
-0.30280011892318726,
-0.2254151701927185,
0.04275547340512276,
0.01996736414730549,
0.17918384075164795,
-0.4684464931488037,
-0.24010691046714783,
0.3211110830307007,
0.06214383244514465,
-0.05001574009656906,
-0.2363814115524292,
0.02350929006934166,
0.005604702979326248,
-0.04983554035425186,
-0.17327040433883667,
-0.19891439378261566,
-0.013889316469430923,
-0.11765550822019577,
0.42405927181243896,
-0.03836795687675476,
0.045314691960811615,
-0.021976172924041748,
0.24746011197566986,
0.09659837186336517,
-0.1492275893688202,
0.142380952835083,
0.2692519426345825,
0.14296641945838928,
0.2716633379459381,
0.1835295855998993,
-0.13022004067897797,
-0.22181808948516846,
0.051952674984931946,
-0.06875784695148468,
0.3754238188266754,
0.441513329744339,
0.20746377110481262,
0.031254470348358154,
-0.24363237619400024,
-0.17298300564289093,
-0.3376981317996979,
0.2777041494846344,
0.3622957766056061,
-0.1226685494184494,
-0.018863897770643234,
-0.3984578251838684,
0.7639327049255371,
0.11514200270175934,
-0.31864988803863525,
0.3197759687900543,
-0.1712692826986313,
-0.2754104435443878,
0.06674183160066605,
0.04492731764912605,
0.9632916450500488,
0.18758024275302887,
0.2697294056415558,
0.33561018109321594,
-0.30502283573150635,
0.5088148713111877,
0.07729946076869965,
0.08329827338457108,
-0.526681125164032,
-0.004951021634042263,
0.011898981407284737,
-0.08526362478733063,
0.2526697516441345,
-0.09175126254558563,
-0.2902084290981293,
0.3714599907398224,
0.15412487089633942,
0.3369047939777374,
0.26662394404411316,
0.3904864192008972,
-0.10265128314495087,
-0.08184851706027985,
-0.3148295283317566,
0.03274140506982803,
-0.18126249313354492,
0.29423069953918457,
-0.2555635869503021,
-0.05453521013259888,
-0.19459013640880585,
-0.0489114373922348,
-0.16635634005069733,
-0.232101172208786,
-0.17980781197547913,
0.044044747948646545,
0.09738385677337646,
-0.2445479780435562,
0.007083317264914513,
0.2463042289018631,
0.13479098677635193,
-0.3061772584915161,
-0.0829959437251091,
-0.0007392577826976776,
-0.20389783382415771,
0.19736739993095398,
0.2699483036994934,
-0.0520637109875679,
0.4594918489456177,
-0.2614249587059021,
0.004677951335906982,
0.06200576201081276,
-0.2999454140663147,
-0.011491157114505768,
-0.07748061418533325,
-0.1792587786912918,
0.1897275447845459,
-0.29735347628593445,
-0.275772362947464,
0.034674856811761856,
0.015729404985904694,
-0.016935501247644424,
-0.013131961226463318,
0.1991761028766632,
-0.2707010507583618,
0.01630931720137596,
-0.09080842137336731,
-0.23815381526947021,
-0.012713782489299774,
0.34332647919654846,
-0.08797552436590195,
-0.07147163152694702,
0.7205212116241455,
-0.1423330307006836,
-0.013048091903328896,
-0.08775792270898819,
0.07892707735300064,
-0.07721299678087234,
-0.21021470427513123,
-0.024668309837579727,
-0.09397958219051361,
-0.3097341060638428,
-0.11627878248691559,
0.6664244532585144,
0.5130177736282349,
0.08737722039222717,
-0.012764431536197662,
-0.39167970418930054,
-0.3361733555793762,
0.1102447584271431,
-0.2133309692144394,
0.20463064312934875,
-0.15378166735172272,
0.23010988533496857,
0.2059989869594574,
0.09173562377691269,
-0.19896355271339417,
-0.21286660432815552,
-0.05241968482732773,
0.3219778537750244,
-0.20810826122760773,
0.008621208369731903,
-0.022832272574305534,
0.07475611567497253,
-0.07202239334583282,
-0.03039177507162094,
-0.3601388931274414,
-0.0361163504421711,
-0.16067591309547424,
0.23085974156856537,
0.16787391901016235,
-0.10099488496780396,
0.051194820553064346,
-0.05666758865118027,
0.08302770555019379,
0.15836556255817413,
-0.0659610852599144,
-0.06922027468681335,
-0.046982504427433014,
0.31562042236328125,
0.22112752497196198,
0.2653515338897705,
-0.061261486262083054,
0.1533360630273819,
0.07793214172124863,
0.14180797338485718,
0.0833163633942604,
0.18333101272583008,
-0.32301101088523865,
0.01377502828836441,
0.07649018615484238,
0.29494187235832214,
-0.11261296272277832,
0.2398705780506134,
0.11625219881534576,
-0.03209961950778961,
0.14109624922275543,
0.08694121241569519,
0.2844572961330414,
0.8438327312469482,
-0.1847461611032486,
-0.2881440818309784,
0.4106006324291229,
0.017603598535060883,
-0.04218664765357971,
0.08298292011022568,
0.2660800516605377,
0.11460378766059875,
0.022273149341344833,
0.2854962646961212,
0.055850084871053696,
-0.0035331547260284424,
0.03952415660023689,
0.16859549283981323,
0.19243678450584412,
-0.21285240352153778,
-0.06870892643928528,
0.4142073392868042,
-0.2447899430990219,
0.2616272270679474,
0.3799400329589844,
0.05843599885702133,
0.21717175841331482,
-0.09376569092273712,
0.0666029304265976,
0.4720230996608734,
0.10343413054943085,
0.07247675955295563,
0.14047127962112427,
0.1095653623342514,
-0.05472439154982567,
0.4614467918872833,
0.027293212711811066,
0.019859664142131805,
0.2861618995666504,
0.6132856011390686,
-0.33437731862068176,
-0.3217318058013916,
-0.17343229055404663,
-0.07680444419384003,
0.10721223801374435,
-0.18119587004184723,
-0.52765953540802,
0.014906935393810272,
-0.25306904315948486,
-0.07244852930307388,
-0.2701844871044159,
-0.35571712255477905,
0.31993842124938965,
0.0411810539662838,
-0.3105320334434509,
-0.4160935878753662,
-0.360491544008255,
0.08546432852745056,
0.1281217634677887,
-0.3214928209781647,
0.2644851803779602,
0.23103877902030945,
0.0690561830997467,
0.4039289951324463,
0.33244723081588745,
0.40230700373649597,
0.09167840331792831,
-0.3861663341522217,
-0.3036430776119232,
-0.2539188861846924,
0.10707499086856842,
0.12506237626075745,
0.2783576250076294,
-0.042769819498062134,
-0.21499799191951752,
0.5813987255096436,
0.01551702618598938,
0.07906574010848999,
0.29227203130722046,
0.4092690944671631,
-0.5363081693649292,
-0.24184051156044006,
0.6709061861038208,
-0.0029571689665317535,
-0.2478887438774109,
0.10846426337957382,
0.15607410669326782,
-0.36080628633499146,
0.08438092470169067,
0.0010098125785589218,
0.07150506973266602,
0.19846251606941223,
0.09360723942518234,
0.026088673621416092,
-0.009924501180648804,
0.49392151832580566,
0.49144279956817627,
-0.10784625262022018,
-0.3457840085029602,
-0.10265505313873291,
-0.708646297454834,
0.02320411056280136,
-0.02492237463593483,
-0.3069426715373993,
-0.0286514051258564,
-0.1313231736421585,
0.1805087924003601,
0.0959317684173584,
-0.25933027267456055,
0.05915506184101105,
-0.03458626940846443,
0.07855816930532455,
-0.31683024764060974,
-0.2308543175458908,
-0.1634584665298462,
0.011753806844353676,
-0.11217958480119705,
-0.2473425567150116,
0.11470585316419601,
-0.390979140996933,
-0.14848636090755463,
0.22859202325344086,
0.048662856221199036,
0.47063031792640686,
0.04398009553551674,
0.16804176568984985,
-0.01494508795440197,
0.5717011094093323,
0.27138984203338623,
-0.12703824043273926,
-0.22806525230407715,
0.21541136503219604,
-0.1466309130191803,
0.17723961174488068,
-0.12875758111476898,
0.36341142654418945,
-0.1993665248155594,
0.5129457116127014,
-0.20585551857948303,
0.4702882766723633,
-0.04468383640050888,
0.057025883346796036,
-0.3319069445133209,
0.0854540541768074,
-0.22928383946418762,
0.04520866274833679,
0.33929333090782166,
0.3558689057826996,
-0.06925636529922485,
0.29817691445350647,
-0.26029518246650696,
-0.22530728578567505,
0.320079505443573,
-0.3188404142856598,
-0.11840410530567169,
0.1429828405380249,
0.2893074154853821,
0.14046311378479004,
0.024536065757274628,
-0.6277332305908203,
0.07381164282560349,
0.23111511766910553,
-0.17052239179611206,
-0.09328325092792511,
0.17623235285282135,
0.23813951015472412,
-0.06259158998727798,
-0.03592406585812569,
0.9138442277908325,
-0.07508876919746399,
-0.0677710548043251,
-0.10770955681800842,
-0.33352911472320557
] |
https://github.com/huggingface/datasets/issues/160 | caching in map causes same result to be returned for train, validation and test | Hi @dpressel,
thanks for posting your issue! Can you maybe add a complete code snippet that we can copy paste to reproduce the error? For example, I'm not sure where the variable `train_set` comes from in your code and it seems like you are loading multiple datasets at once? | hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
| 49 | caching in map causes same result to be returned for train, validation and test
hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
Hi @dpressel,
thanks for posting your issue! Can you maybe add a complete code snippet that we can copy paste to reproduce the error? For example, I'm not sure where the variable `train_set` comes from in your code and it seems like you are loading multiple datasets at once? | [
-0.1263233721256256,
-0.22070911526679993,
-0.10063229501247406,
0.27801111340522766,
0.24547500908374786,
-0.20522364974021912,
0.13721121847629547,
0.512859046459198,
0.18828602135181427,
-0.06233552098274231,
0.1278189718723297,
0.38913494348526,
0.0037763379514217377,
-0.16061760485172272,
-0.010743602178990841,
0.024212224408984184,
0.09608031809329987,
0.23505264520645142,
-0.1455627828836441,
-0.16482312977313995,
0.0818943977355957,
0.2129845768213272,
-0.042410045862197876,
0.11652722954750061,
-0.39034977555274963,
0.04128977656364441,
0.2123567909002304,
-0.230890691280365,
0.06845765560865402,
-0.2570657432079315,
0.16785027086734772,
-0.09324291348457336,
0.025834325700998306,
0.16631808876991272,
-0.00010973814642056823,
0.006797894835472107,
-0.015387743711471558,
-0.13856983184814453,
-0.007274414878338575,
0.04019510746002197,
0.11813420802354813,
-0.21172915399074554,
-0.10918302088975906,
-0.31213220953941345,
-0.33201220631599426,
-0.037661660462617874,
0.017809096723794937,
-0.3556599020957947,
0.3128577172756195,
0.14745266735553741,
0.2607105076313019,
0.22490960359573364,
-0.2538115978240967,
0.21113674342632294,
0.1451275497674942,
-0.02932754158973694,
-0.1741972714662552,
-0.04230468347668648,
-0.04397884011268616,
-0.3344639539718628,
-0.37676432728767395,
0.525456964969635,
-0.07658185809850693,
0.17014150321483612,
0.21466577053070068,
0.2250560224056244,
0.1726061850786209,
0.035937413573265076,
0.14293654263019562,
-0.11396264284849167,
0.011095292866230011,
-0.2269170582294464,
-0.02711626887321472,
-0.3733709454536438,
-0.41864001750946045,
-0.07852613925933838,
0.137624591588974,
0.18104572594165802,
-0.13639286160469055,
-0.06371629238128662,
-0.43193674087524414,
0.23928946256637573,
0.06524854898452759,
-0.012788370251655579,
0.11952775716781616,
0.2951611876487732,
0.043805740773677826,
0.19522324204444885,
0.1294461488723755,
-0.06973283737897873,
-0.02255835384130478,
-0.21451729536056519,
-0.058972302824258804,
0.22640188038349152,
-0.4359855055809021,
0.07208243757486343,
0.4315193295478821,
-0.1404145359992981,
-0.05324290320277214,
0.0306372232735157,
0.39193007349967957,
0.07921387255191803,
0.11681866645812988,
-0.008491560816764832,
-0.10416118800640106,
0.5898669958114624,
0.044322285801172256,
0.17118452489376068,
-0.01497051864862442,
-0.19827789068222046,
-0.3560173213481903,
0.004987429827451706,
0.2880176305770874,
-0.2866014540195465,
0.4284125566482544,
0.40236005187034607,
-0.0422595851123333,
-0.12152935564517975,
-0.030101587995886803,
0.09402371197938919,
-0.33085376024246216,
0.055669233202934265,
0.05872948467731476,
0.31395789980888367,
-0.22545060515403748,
0.1492653489112854,
-0.1737677901983261,
-0.10335496068000793,
-0.38496947288513184,
0.12735126912593842,
-0.33784639835357666,
-0.03332383185625076,
-0.4962179958820343,
0.0015164613723754883,
0.28538399934768677,
-0.002860570326447487,
0.28535300493240356,
-0.03844557702541351,
-0.13722029328346252,
-0.301989883184433,
0.10317452996969223,
-0.39851242303848267,
0.5702308416366577,
-0.1072293221950531,
-0.1970168650150299,
0.24102140963077545,
0.13037806749343872,
0.08526398241519928,
-0.29768770933151245,
-0.1983770728111267,
-0.16980770230293274,
-0.2090688943862915,
0.2598598897457123,
0.2422453612089157,
-0.07942710071802139,
0.1413964033126831,
0.09248155355453491,
0.07767830789089203,
0.3432585597038269,
-0.2328546792268753,
0.10284028947353363,
-0.2014889419078827,
-0.2819805443286896,
-0.20435944199562073,
0.16256943345069885,
0.2623099088668823,
0.0667768269777298,
-0.13737235963344574,
0.40179744362831116,
0.23718246817588806,
0.14729131758213043,
0.4138064980506897,
-0.196533665060997,
0.30949509143829346,
-0.4334923028945923,
0.34861892461776733,
0.5064778923988342,
-0.32673120498657227,
-0.49634435772895813,
0.09944827109575272,
-0.1563153862953186,
0.1002877876162529,
0.10244903713464737,
0.1513729840517044,
0.02908817119896412,
0.014419601298868656,
0.12853626906871796,
0.01870240643620491,
-0.0005144402384757996,
0.20842039585113525,
-0.3169277310371399,
-0.021933740004897118,
0.5500645041465759,
-0.25246739387512207,
0.028472337871789932,
-0.1312367022037506,
-0.05504260212182999,
0.021932099014520645,
0.006768524646759033,
-0.11218959093093872,
0.12185925245285034,
0.1146051287651062,
-0.05687848851084709,
-0.15818428993225098,
-0.10643843561410904,
-0.02469290792942047,
-0.2882624864578247,
0.23830124735832214,
-0.14981965720653534,
-0.09996873140335083,
0.06172499060630798,
-0.09704941511154175,
-0.1620030403137207,
-0.1292746216058731,
-0.1809171587228775,
-0.27306482195854187,
0.20130175352096558,
0.23052407801151276,
0.3202403485774994,
-0.07290694117546082,
0.22520966827869415,
0.3680819571018219,
0.04836329072713852,
-0.21607185900211334,
-0.4300349950790405,
0.08568014949560165,
-0.17773526906967163,
-0.21882861852645874,
-0.074846550822258,
0.22306931018829346,
0.2090265452861786,
-0.0479268915951252,
-0.14242854714393616,
0.1482759267091751,
-0.22208523750305176,
0.41891855001449585,
-0.13702836632728577,
0.2694522738456726,
-0.06965650618076324,
0.029306214302778244,
0.016667230054736137,
0.2540055215358734,
0.05882029980421066,
-0.08980119228363037,
-0.07270593196153641,
0.47423404455184937,
0.18140165507793427,
0.17011570930480957,
-0.04807114973664284,
-0.2162683755159378,
0.05198418349027634,
-0.1783173829317093,
-0.12091565877199173,
-0.11881639063358307,
0.1364068239927292,
-0.0805719643831253,
0.14888811111450195,
0.15232901275157928,
-0.10698775947093964,
0.3120076358318329,
0.7600834369659424,
0.19691896438598633,
-0.011016584932804108,
0.015740428119897842,
-0.05721340328454971,
-0.2177915871143341,
0.33385711908340454,
-0.058683205395936966,
0.31038856506347656,
0.10473139584064484,
0.12716472148895264,
-0.04620931297540665,
-0.21964949369430542,
-0.1544356644153595,
0.12464860081672668,
-0.21436886489391327,
-0.19197627902030945,
0.3080342710018158,
0.28208714723587036,
-0.1583673059940338,
-0.3537829518318176,
0.09401586651802063,
-0.01276421919465065,
0.02619149163365364,
-0.1580010950565338,
0.21723711490631104,
-0.166529580950737,
-0.2780844271183014,
-0.2864159643650055,
0.13615699112415314,
-0.1222032904624939,
-0.09216521680355072,
-0.04126402735710144,
0.42542994022369385,
-0.03665407374501228,
0.19515199959278107,
-0.3149715065956116,
0.0895179957151413,
0.2266039401292801,
-0.26632726192474365,
-0.07168534398078918,
-0.1902872771024704,
-0.39492014050483704,
0.042231734842061996,
-0.09523066878318787,
-0.0929960310459137,
0.3783302307128906,
-0.047316424548625946,
-0.06796006858348846,
-0.2881466746330261,
-0.17254027724266052,
0.10717801749706268,
-0.09261122345924377,
-0.15536727011203766,
0.16724826395511627,
-0.03133828938007355,
-0.10115892440080643,
-0.29874566197395325,
0.2937973141670227,
-0.30531302094459534,
-0.2991430461406708,
-0.05198727175593376,
0.09890619665384293,
0.030108986422419548,
-0.2803470194339752,
-0.4286248981952667,
0.27357742190361023,
-0.31724435091018677,
0.07546759396791458,
-0.14892880618572235,
0.18622717261314392,
0.33093392848968506,
0.008953814394772053,
-0.014561107382178307,
-0.06404063105583191,
0.16439421474933624,
-0.4674096703529358,
-0.14095471799373627,
0.32257843017578125,
0.01876021921634674,
-0.21630443632602692,
-0.3245909512042999,
-0.2757244110107422,
0.34772399067878723,
0.19238810241222382,
-0.5803955793380737,
-0.21442262828350067,
-0.048900216817855835,
0.2480318248271942,
-0.05125897377729416,
-0.04649518430233002,
0.5745418071746826,
0.01972545124590397,
-0.17946316301822662,
-0.16727802157402039,
-0.33183929324150085,
0.35973066091537476,
0.4192623794078827,
0.24948757886886597,
-0.011158477514982224,
0.17781516909599304,
0.20092011988162994,
0.6707470417022705,
0.2019203156232834,
-0.2590579092502594,
0.33173102140426636,
0.10723146051168442,
0.07499773055315018,
-0.2034967839717865,
-0.3130229413509369,
0.18576018512248993,
-0.18160304427146912,
0.01973230391740799,
0.27198368310928345,
0.006250595673918724,
-0.2801837921142578,
0.017742767930030823,
0.21881836652755737,
-0.2253446877002716,
-0.328058123588562,
0.2597455084323883,
-0.3424280285835266,
0.24094843864440918,
0.036369793117046356,
0.3157997131347656,
-0.5820137858390808,
-0.24272391200065613,
0.19462794065475464,
-0.3359457850456238,
0.27984461188316345,
0.04449816048145294,
-0.5836011171340942,
0.12147033214569092,
-0.5380215048789978,
0.18194156885147095,
0.31462806463241577,
0.27240774035453796,
-0.09202472865581512,
-0.2465253472328186,
0.043347518891096115,
-0.14713148772716522,
0.5711420178413391,
0.04097308963537216,
0.40857934951782227,
0.16992636024951935,
-0.13024693727493286,
-0.19947344064712524,
-0.22471317648887634,
0.017234940081834793,
0.28013670444488525,
0.3265002369880676,
0.400847464799881,
-0.345244437456131,
-0.3632737100124359,
-0.2657657265663147,
0.007363845594227314,
-0.046181585639715195,
0.007106936536729336,
-0.12583458423614502,
0.18938523530960083,
0.01648571901023388,
0.17434579133987427,
-0.014980330131947994,
0.11830316483974457,
0.016039708629250526,
-0.13654674589633942,
-0.03913415968418121,
-0.21942690014839172,
0.12824007868766785,
0.22643797099590302,
0.4735948443412781,
0.1503245085477829,
0.03246166184544563,
0.033214349299669266,
0.21515773236751556,
-0.5671082735061646,
0.2659573554992676,
-0.08884961903095245,
-0.004131801426410675,
0.07464389503002167,
0.14443765580654144,
-0.030300907790660858,
0.3378967344760895,
-0.04252535104751587,
0.1457139402627945,
-0.12862969934940338,
0.008957155048847198,
-0.5539682507514954,
0.4854547381401062,
0.3874596357345581,
0.13246718049049377,
-0.044888898730278015,
-0.24685737490653992,
0.17346280813217163,
0.07412064075469971,
-0.27653080224990845,
0.13225962221622467,
-0.43069255352020264,
-0.4319950044155121,
0.18579739332199097,
0.2094864398241043,
0.9232466220855713,
0.33202219009399414,
0.37195777893066406,
0.10070358961820602,
0.10358034074306488,
0.26425158977508545,
-0.23411162197589874,
0.40924984216690063,
-0.3693644404411316,
-0.0463179312646389,
0.024538787081837654,
-0.16673341393470764,
-0.22738268971443176,
-0.010426290333271027,
-0.010993778705596924,
0.30259543657302856,
0.32404959201812744,
0.5999362468719482,
-0.11212000250816345,
0.16670005023479462,
0.215691938996315,
-0.15810950100421906,
-0.24923086166381836,
0.20107315480709076,
-0.2923040986061096,
0.31524065136909485,
-0.11240848153829575,
-0.07410834729671478,
-0.01650886982679367,
-0.35134220123291016,
0.06714004278182983,
0.0609416738152504,
-0.3365170359611511,
0.3048418164253235,
0.13346192240715027,
-0.27266669273376465,
-0.29698777198791504,
0.2550782561302185,
0.11198711395263672,
0.08252803981304169,
-0.048599302768707275,
-0.035185206681489944,
0.4006449580192566,
0.35045796632766724,
-0.006891845725476742,
-0.20158877968788147,
0.18641246855258942,
0.06387515366077423,
-0.012894652783870697,
0.030242733657360077,
-0.05640551447868347,
-0.3015826344490051,
-0.2525118589401245,
0.14820465445518494,
0.0033729001879692078,
-0.4129619598388672,
-0.055318914353847504,
0.06144453212618828,
-0.0667886808514595,
-0.09413722157478333,
0.15088041126728058,
-0.026068218052387238,
-0.10794125497341156,
0.3151545822620392,
0.11733834445476532,
-0.24304209649562836,
0.05235828459262848,
0.47483235597610474,
-0.04039648920297623,
0.031818099319934845,
0.4154282510280609,
-0.15281841158866882,
-0.10380619764328003,
-0.25539109110832214,
-0.28417226672172546,
-0.10206017643213272,
-0.44884029030799866,
0.11220822483301163,
-0.2194056510925293,
-0.40191107988357544,
0.04423205554485321,
0.2808186709880829,
0.014706198126077652,
0.3184961974620819,
-0.011618245393037796,
-0.12495805323123932,
-0.3769727349281311,
-0.10379086434841156,
-0.10658213496208191,
0.26717838644981384,
0.27951928973197937,
0.2843479812145233,
-0.29586678743362427,
0.2492268979549408,
-0.38310953974723816,
-0.10714222490787506,
-0.1871705949306488,
0.4379130005836487,
-0.0391375795006752,
-0.36558276414871216,
-0.009147514589130878,
0.0018548620864748955,
0.12997101247310638,
0.17754510045051575,
-0.6386584639549255,
-0.29261907935142517,
-0.09099219739437103,
0.08186075091362,
-0.007588040083646774,
-0.1598217487335205,
-0.23928231000900269,
-0.01721424236893654,
0.18238495290279388,
-0.427402526140213,
0.09215688705444336,
0.15121665596961975,
0.04703199863433838,
0.23718711733818054,
-0.1610298752784729,
0.1214555948972702,
0.28816717863082886,
-0.18652743101119995,
-0.1841491460800171,
-0.07622881233692169,
0.08048095554113388,
0.25701695680618286,
-0.06946776062250137,
0.020479001104831696,
-0.2104034423828125,
0.030471812933683395,
0.08927443623542786,
0.14279493689537048,
0.23692923784255981,
-0.024752572178840637,
-0.21566128730773926,
0.0005505271255970001,
0.18279926478862762,
0.11411947757005692,
-0.07855326682329178,
-0.32897576689720154,
0.2802233397960663,
0.2783650755882263,
-0.11751837283372879,
-0.0102371945977211,
0.1677074134349823,
-0.09938855469226837,
0.25285133719444275,
0.20715340971946716,
0.10758769512176514,
0.05261163413524628,
0.26961183547973633,
0.12649410963058472,
0.40504008531570435,
-0.34832900762557983,
0.08942112326622009,
0.06441552191972733,
0.10164903104305267,
0.03777839243412018,
0.38121557235717773,
-0.1532439887523651,
0.08992154896259308,
0.14838308095932007,
0.18833690881729126,
0.20253999531269073,
0.26289018988609314,
0.21354106068611145,
-0.1878642439842224,
-0.03412104770541191,
-0.24108661711215973,
0.1436368077993393,
-0.14272664487361908,
0.4156598448753357,
0.15059244632720947,
0.19285538792610168,
-0.11485158652067184,
-0.4619392156600952,
-0.2462674379348755,
0.23536445200443268,
-0.3245418667793274,
-0.30920952558517456,
-0.04867886006832123,
-0.08018464595079422,
0.05592931807041168,
0.19456081092357635,
-0.07928960025310516,
0.2038593888282776,
0.3428382873535156,
-0.00865977257490158,
-0.013750068843364716,
-0.08435389399528503,
-0.170617014169693,
0.11397916823625565,
0.2748645842075348,
-0.08173888921737671,
0.446936696767807,
0.010800972580909729,
-0.051569364964962006,
-0.2344720959663391,
0.4114176034927368,
0.2861287593841553,
0.19494742155075073,
-0.1688622683286667,
0.06395319104194641,
0.20064730942249298,
0.03061327524483204,
-0.35468870401382446,
0.3286513686180115,
0.15114429593086243,
-0.2930281460285187,
0.3680053651332855,
0.12379556894302368,
-0.23215582966804504,
0.2764035165309906,
-0.1041957288980484,
-0.20146708190441132,
-0.049888961017131805,
0.3224371671676636,
0.09970720112323761,
-0.03993305563926697,
-0.1949632167816162,
0.1111203134059906,
-0.1445714384317398,
-0.28533875942230225,
0.15934628248214722,
-0.023898672312498093,
0.4676608443260193,
-0.2756762206554413,
0.11720523238182068,
-0.06182504817843437,
0.6220859885215759,
-0.02922816202044487,
0.12432920932769775,
-0.35013818740844727,
0.10264356434345245,
-0.3331668972969055,
0.198409765958786,
-0.08381709456443787,
0.15374305844306946,
-0.39758387207984924,
0.20426522195339203,
-0.11549905687570572,
-0.02346649393439293,
-0.11804220080375671,
-0.007886471226811409,
0.14740730822086334,
0.17893224954605103,
-0.3869178295135498,
0.1554817110300064,
-0.08625976741313934,
-0.006267093122005463,
0.29177382588386536,
-0.37667521834373474,
0.22199100255966187,
0.042478568851947784,
0.20691052079200745,
0.010985862463712692,
-0.02172362059354782,
-0.054806359112262726,
0.33657363057136536,
0.6232408881187439,
0.34702926874160767,
0.14255046844482422,
-0.10102763026952744,
0.08155438303947449,
-0.3474372923374176,
0.014104174450039864,
-0.06088797375559807,
-0.20964977145195007,
0.09756873548030853,
0.5258306264877319,
-0.22562795877456665,
0.13194617629051208,
-0.178046315908432,
0.23669393360614777,
0.3822764754295349,
-0.1527290940284729,
0.0618000254034996,
0.04822578281164169,
-0.2598402798175812,
-0.005199543200433254,
-0.12586651742458344,
0.45379629731178284,
0.007182497531175613,
0.32383060455322266,
-0.3592911958694458,
-0.5417625904083252,
0.43290984630584717,
-0.45112577080726624,
-0.30252525210380554,
0.12327728420495987,
0.23878571391105652,
0.34956857562065125,
-0.06000012159347534,
-0.5436676144599915,
-0.17249035835266113,
0.2691141963005066,
-0.030661150813102722,
-0.1570448875427246,
0.20768548548221588,
-0.14864324033260345,
-0.04107460752129555,
-0.1167544275522232,
0.17646947503089905,
0.10152687877416611,
-0.2914122939109802,
0.24369880557060242,
-0.3701038360595703
] |
https://github.com/huggingface/datasets/issues/160 | caching in map causes same result to be returned for train, validation and test | Hi, the full example was listed in the PR above, but here is the exact link:
https://github.com/dpressel/mead-baseline/blob/3c1aa3ca062cb23f303ca98ac40b6652b37ee971/api-examples/layers-classify-hf-datasets.py
The problem is coming from
```
if cache_file_name is None:
# we create a unique hash from the function, current dataset file and the mapping args
cache_kwargs = {
"with_indices": with_indices,
"batched": batched,
"batch_size": batch_size,
"remove_columns": remove_columns,
"keep_in_memory": keep_in_memory,
"load_from_cache_file": load_from_cache_file,
"cache_file_name": cache_file_name,
"writer_batch_size": writer_batch_size,
"arrow_schema": arrow_schema,
"disable_nullable": disable_nullable,
}
cache_file_name = self._get_cache_file_path(function, cache_kwargs)
```
The cached value is always the same, but I was able to change that by just renaming the function each time which seems to fix the issue. | hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
| 99 | caching in map causes same result to be returned for train, validation and test
hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
Hi, the full example was listed in the PR above, but here is the exact link:
https://github.com/dpressel/mead-baseline/blob/3c1aa3ca062cb23f303ca98ac40b6652b37ee971/api-examples/layers-classify-hf-datasets.py
The problem is coming from
```
if cache_file_name is None:
# we create a unique hash from the function, current dataset file and the mapping args
cache_kwargs = {
"with_indices": with_indices,
"batched": batched,
"batch_size": batch_size,
"remove_columns": remove_columns,
"keep_in_memory": keep_in_memory,
"load_from_cache_file": load_from_cache_file,
"cache_file_name": cache_file_name,
"writer_batch_size": writer_batch_size,
"arrow_schema": arrow_schema,
"disable_nullable": disable_nullable,
}
cache_file_name = self._get_cache_file_path(function, cache_kwargs)
```
The cached value is always the same, but I was able to change that by just renaming the function each time which seems to fix the issue. | [
-0.1263233721256256,
-0.22070911526679993,
-0.10063229501247406,
0.27801111340522766,
0.24547500908374786,
-0.20522364974021912,
0.13721121847629547,
0.512859046459198,
0.18828602135181427,
-0.06233552098274231,
0.1278189718723297,
0.38913494348526,
0.0037763379514217377,
-0.16061760485172272,
-0.010743602178990841,
0.024212224408984184,
0.09608031809329987,
0.23505264520645142,
-0.1455627828836441,
-0.16482312977313995,
0.0818943977355957,
0.2129845768213272,
-0.042410045862197876,
0.11652722954750061,
-0.39034977555274963,
0.04128977656364441,
0.2123567909002304,
-0.230890691280365,
0.06845765560865402,
-0.2570657432079315,
0.16785027086734772,
-0.09324291348457336,
0.025834325700998306,
0.16631808876991272,
-0.00010973814642056823,
0.006797894835472107,
-0.015387743711471558,
-0.13856983184814453,
-0.007274414878338575,
0.04019510746002197,
0.11813420802354813,
-0.21172915399074554,
-0.10918302088975906,
-0.31213220953941345,
-0.33201220631599426,
-0.037661660462617874,
0.017809096723794937,
-0.3556599020957947,
0.3128577172756195,
0.14745266735553741,
0.2607105076313019,
0.22490960359573364,
-0.2538115978240967,
0.21113674342632294,
0.1451275497674942,
-0.02932754158973694,
-0.1741972714662552,
-0.04230468347668648,
-0.04397884011268616,
-0.3344639539718628,
-0.37676432728767395,
0.525456964969635,
-0.07658185809850693,
0.17014150321483612,
0.21466577053070068,
0.2250560224056244,
0.1726061850786209,
0.035937413573265076,
0.14293654263019562,
-0.11396264284849167,
0.011095292866230011,
-0.2269170582294464,
-0.02711626887321472,
-0.3733709454536438,
-0.41864001750946045,
-0.07852613925933838,
0.137624591588974,
0.18104572594165802,
-0.13639286160469055,
-0.06371629238128662,
-0.43193674087524414,
0.23928946256637573,
0.06524854898452759,
-0.012788370251655579,
0.11952775716781616,
0.2951611876487732,
0.043805740773677826,
0.19522324204444885,
0.1294461488723755,
-0.06973283737897873,
-0.02255835384130478,
-0.21451729536056519,
-0.058972302824258804,
0.22640188038349152,
-0.4359855055809021,
0.07208243757486343,
0.4315193295478821,
-0.1404145359992981,
-0.05324290320277214,
0.0306372232735157,
0.39193007349967957,
0.07921387255191803,
0.11681866645812988,
-0.008491560816764832,
-0.10416118800640106,
0.5898669958114624,
0.044322285801172256,
0.17118452489376068,
-0.01497051864862442,
-0.19827789068222046,
-0.3560173213481903,
0.004987429827451706,
0.2880176305770874,
-0.2866014540195465,
0.4284125566482544,
0.40236005187034607,
-0.0422595851123333,
-0.12152935564517975,
-0.030101587995886803,
0.09402371197938919,
-0.33085376024246216,
0.055669233202934265,
0.05872948467731476,
0.31395789980888367,
-0.22545060515403748,
0.1492653489112854,
-0.1737677901983261,
-0.10335496068000793,
-0.38496947288513184,
0.12735126912593842,
-0.33784639835357666,
-0.03332383185625076,
-0.4962179958820343,
0.0015164613723754883,
0.28538399934768677,
-0.002860570326447487,
0.28535300493240356,
-0.03844557702541351,
-0.13722029328346252,
-0.301989883184433,
0.10317452996969223,
-0.39851242303848267,
0.5702308416366577,
-0.1072293221950531,
-0.1970168650150299,
0.24102140963077545,
0.13037806749343872,
0.08526398241519928,
-0.29768770933151245,
-0.1983770728111267,
-0.16980770230293274,
-0.2090688943862915,
0.2598598897457123,
0.2422453612089157,
-0.07942710071802139,
0.1413964033126831,
0.09248155355453491,
0.07767830789089203,
0.3432585597038269,
-0.2328546792268753,
0.10284028947353363,
-0.2014889419078827,
-0.2819805443286896,
-0.20435944199562073,
0.16256943345069885,
0.2623099088668823,
0.0667768269777298,
-0.13737235963344574,
0.40179744362831116,
0.23718246817588806,
0.14729131758213043,
0.4138064980506897,
-0.196533665060997,
0.30949509143829346,
-0.4334923028945923,
0.34861892461776733,
0.5064778923988342,
-0.32673120498657227,
-0.49634435772895813,
0.09944827109575272,
-0.1563153862953186,
0.1002877876162529,
0.10244903713464737,
0.1513729840517044,
0.02908817119896412,
0.014419601298868656,
0.12853626906871796,
0.01870240643620491,
-0.0005144402384757996,
0.20842039585113525,
-0.3169277310371399,
-0.021933740004897118,
0.5500645041465759,
-0.25246739387512207,
0.028472337871789932,
-0.1312367022037506,
-0.05504260212182999,
0.021932099014520645,
0.006768524646759033,
-0.11218959093093872,
0.12185925245285034,
0.1146051287651062,
-0.05687848851084709,
-0.15818428993225098,
-0.10643843561410904,
-0.02469290792942047,
-0.2882624864578247,
0.23830124735832214,
-0.14981965720653534,
-0.09996873140335083,
0.06172499060630798,
-0.09704941511154175,
-0.1620030403137207,
-0.1292746216058731,
-0.1809171587228775,
-0.27306482195854187,
0.20130175352096558,
0.23052407801151276,
0.3202403485774994,
-0.07290694117546082,
0.22520966827869415,
0.3680819571018219,
0.04836329072713852,
-0.21607185900211334,
-0.4300349950790405,
0.08568014949560165,
-0.17773526906967163,
-0.21882861852645874,
-0.074846550822258,
0.22306931018829346,
0.2090265452861786,
-0.0479268915951252,
-0.14242854714393616,
0.1482759267091751,
-0.22208523750305176,
0.41891855001449585,
-0.13702836632728577,
0.2694522738456726,
-0.06965650618076324,
0.029306214302778244,
0.016667230054736137,
0.2540055215358734,
0.05882029980421066,
-0.08980119228363037,
-0.07270593196153641,
0.47423404455184937,
0.18140165507793427,
0.17011570930480957,
-0.04807114973664284,
-0.2162683755159378,
0.05198418349027634,
-0.1783173829317093,
-0.12091565877199173,
-0.11881639063358307,
0.1364068239927292,
-0.0805719643831253,
0.14888811111450195,
0.15232901275157928,
-0.10698775947093964,
0.3120076358318329,
0.7600834369659424,
0.19691896438598633,
-0.011016584932804108,
0.015740428119897842,
-0.05721340328454971,
-0.2177915871143341,
0.33385711908340454,
-0.058683205395936966,
0.31038856506347656,
0.10473139584064484,
0.12716472148895264,
-0.04620931297540665,
-0.21964949369430542,
-0.1544356644153595,
0.12464860081672668,
-0.21436886489391327,
-0.19197627902030945,
0.3080342710018158,
0.28208714723587036,
-0.1583673059940338,
-0.3537829518318176,
0.09401586651802063,
-0.01276421919465065,
0.02619149163365364,
-0.1580010950565338,
0.21723711490631104,
-0.166529580950737,
-0.2780844271183014,
-0.2864159643650055,
0.13615699112415314,
-0.1222032904624939,
-0.09216521680355072,
-0.04126402735710144,
0.42542994022369385,
-0.03665407374501228,
0.19515199959278107,
-0.3149715065956116,
0.0895179957151413,
0.2266039401292801,
-0.26632726192474365,
-0.07168534398078918,
-0.1902872771024704,
-0.39492014050483704,
0.042231734842061996,
-0.09523066878318787,
-0.0929960310459137,
0.3783302307128906,
-0.047316424548625946,
-0.06796006858348846,
-0.2881466746330261,
-0.17254027724266052,
0.10717801749706268,
-0.09261122345924377,
-0.15536727011203766,
0.16724826395511627,
-0.03133828938007355,
-0.10115892440080643,
-0.29874566197395325,
0.2937973141670227,
-0.30531302094459534,
-0.2991430461406708,
-0.05198727175593376,
0.09890619665384293,
0.030108986422419548,
-0.2803470194339752,
-0.4286248981952667,
0.27357742190361023,
-0.31724435091018677,
0.07546759396791458,
-0.14892880618572235,
0.18622717261314392,
0.33093392848968506,
0.008953814394772053,
-0.014561107382178307,
-0.06404063105583191,
0.16439421474933624,
-0.4674096703529358,
-0.14095471799373627,
0.32257843017578125,
0.01876021921634674,
-0.21630443632602692,
-0.3245909512042999,
-0.2757244110107422,
0.34772399067878723,
0.19238810241222382,
-0.5803955793380737,
-0.21442262828350067,
-0.048900216817855835,
0.2480318248271942,
-0.05125897377729416,
-0.04649518430233002,
0.5745418071746826,
0.01972545124590397,
-0.17946316301822662,
-0.16727802157402039,
-0.33183929324150085,
0.35973066091537476,
0.4192623794078827,
0.24948757886886597,
-0.011158477514982224,
0.17781516909599304,
0.20092011988162994,
0.6707470417022705,
0.2019203156232834,
-0.2590579092502594,
0.33173102140426636,
0.10723146051168442,
0.07499773055315018,
-0.2034967839717865,
-0.3130229413509369,
0.18576018512248993,
-0.18160304427146912,
0.01973230391740799,
0.27198368310928345,
0.006250595673918724,
-0.2801837921142578,
0.017742767930030823,
0.21881836652755737,
-0.2253446877002716,
-0.328058123588562,
0.2597455084323883,
-0.3424280285835266,
0.24094843864440918,
0.036369793117046356,
0.3157997131347656,
-0.5820137858390808,
-0.24272391200065613,
0.19462794065475464,
-0.3359457850456238,
0.27984461188316345,
0.04449816048145294,
-0.5836011171340942,
0.12147033214569092,
-0.5380215048789978,
0.18194156885147095,
0.31462806463241577,
0.27240774035453796,
-0.09202472865581512,
-0.2465253472328186,
0.043347518891096115,
-0.14713148772716522,
0.5711420178413391,
0.04097308963537216,
0.40857934951782227,
0.16992636024951935,
-0.13024693727493286,
-0.19947344064712524,
-0.22471317648887634,
0.017234940081834793,
0.28013670444488525,
0.3265002369880676,
0.400847464799881,
-0.345244437456131,
-0.3632737100124359,
-0.2657657265663147,
0.007363845594227314,
-0.046181585639715195,
0.007106936536729336,
-0.12583458423614502,
0.18938523530960083,
0.01648571901023388,
0.17434579133987427,
-0.014980330131947994,
0.11830316483974457,
0.016039708629250526,
-0.13654674589633942,
-0.03913415968418121,
-0.21942690014839172,
0.12824007868766785,
0.22643797099590302,
0.4735948443412781,
0.1503245085477829,
0.03246166184544563,
0.033214349299669266,
0.21515773236751556,
-0.5671082735061646,
0.2659573554992676,
-0.08884961903095245,
-0.004131801426410675,
0.07464389503002167,
0.14443765580654144,
-0.030300907790660858,
0.3378967344760895,
-0.04252535104751587,
0.1457139402627945,
-0.12862969934940338,
0.008957155048847198,
-0.5539682507514954,
0.4854547381401062,
0.3874596357345581,
0.13246718049049377,
-0.044888898730278015,
-0.24685737490653992,
0.17346280813217163,
0.07412064075469971,
-0.27653080224990845,
0.13225962221622467,
-0.43069255352020264,
-0.4319950044155121,
0.18579739332199097,
0.2094864398241043,
0.9232466220855713,
0.33202219009399414,
0.37195777893066406,
0.10070358961820602,
0.10358034074306488,
0.26425158977508545,
-0.23411162197589874,
0.40924984216690063,
-0.3693644404411316,
-0.0463179312646389,
0.024538787081837654,
-0.16673341393470764,
-0.22738268971443176,
-0.010426290333271027,
-0.010993778705596924,
0.30259543657302856,
0.32404959201812744,
0.5999362468719482,
-0.11212000250816345,
0.16670005023479462,
0.215691938996315,
-0.15810950100421906,
-0.24923086166381836,
0.20107315480709076,
-0.2923040986061096,
0.31524065136909485,
-0.11240848153829575,
-0.07410834729671478,
-0.01650886982679367,
-0.35134220123291016,
0.06714004278182983,
0.0609416738152504,
-0.3365170359611511,
0.3048418164253235,
0.13346192240715027,
-0.27266669273376465,
-0.29698777198791504,
0.2550782561302185,
0.11198711395263672,
0.08252803981304169,
-0.048599302768707275,
-0.035185206681489944,
0.4006449580192566,
0.35045796632766724,
-0.006891845725476742,
-0.20158877968788147,
0.18641246855258942,
0.06387515366077423,
-0.012894652783870697,
0.030242733657360077,
-0.05640551447868347,
-0.3015826344490051,
-0.2525118589401245,
0.14820465445518494,
0.0033729001879692078,
-0.4129619598388672,
-0.055318914353847504,
0.06144453212618828,
-0.0667886808514595,
-0.09413722157478333,
0.15088041126728058,
-0.026068218052387238,
-0.10794125497341156,
0.3151545822620392,
0.11733834445476532,
-0.24304209649562836,
0.05235828459262848,
0.47483235597610474,
-0.04039648920297623,
0.031818099319934845,
0.4154282510280609,
-0.15281841158866882,
-0.10380619764328003,
-0.25539109110832214,
-0.28417226672172546,
-0.10206017643213272,
-0.44884029030799866,
0.11220822483301163,
-0.2194056510925293,
-0.40191107988357544,
0.04423205554485321,
0.2808186709880829,
0.014706198126077652,
0.3184961974620819,
-0.011618245393037796,
-0.12495805323123932,
-0.3769727349281311,
-0.10379086434841156,
-0.10658213496208191,
0.26717838644981384,
0.27951928973197937,
0.2843479812145233,
-0.29586678743362427,
0.2492268979549408,
-0.38310953974723816,
-0.10714222490787506,
-0.1871705949306488,
0.4379130005836487,
-0.0391375795006752,
-0.36558276414871216,
-0.009147514589130878,
0.0018548620864748955,
0.12997101247310638,
0.17754510045051575,
-0.6386584639549255,
-0.29261907935142517,
-0.09099219739437103,
0.08186075091362,
-0.007588040083646774,
-0.1598217487335205,
-0.23928231000900269,
-0.01721424236893654,
0.18238495290279388,
-0.427402526140213,
0.09215688705444336,
0.15121665596961975,
0.04703199863433838,
0.23718711733818054,
-0.1610298752784729,
0.1214555948972702,
0.28816717863082886,
-0.18652743101119995,
-0.1841491460800171,
-0.07622881233692169,
0.08048095554113388,
0.25701695680618286,
-0.06946776062250137,
0.020479001104831696,
-0.2104034423828125,
0.030471812933683395,
0.08927443623542786,
0.14279493689537048,
0.23692923784255981,
-0.024752572178840637,
-0.21566128730773926,
0.0005505271255970001,
0.18279926478862762,
0.11411947757005692,
-0.07855326682329178,
-0.32897576689720154,
0.2802233397960663,
0.2783650755882263,
-0.11751837283372879,
-0.0102371945977211,
0.1677074134349823,
-0.09938855469226837,
0.25285133719444275,
0.20715340971946716,
0.10758769512176514,
0.05261163413524628,
0.26961183547973633,
0.12649410963058472,
0.40504008531570435,
-0.34832900762557983,
0.08942112326622009,
0.06441552191972733,
0.10164903104305267,
0.03777839243412018,
0.38121557235717773,
-0.1532439887523651,
0.08992154896259308,
0.14838308095932007,
0.18833690881729126,
0.20253999531269073,
0.26289018988609314,
0.21354106068611145,
-0.1878642439842224,
-0.03412104770541191,
-0.24108661711215973,
0.1436368077993393,
-0.14272664487361908,
0.4156598448753357,
0.15059244632720947,
0.19285538792610168,
-0.11485158652067184,
-0.4619392156600952,
-0.2462674379348755,
0.23536445200443268,
-0.3245418667793274,
-0.30920952558517456,
-0.04867886006832123,
-0.08018464595079422,
0.05592931807041168,
0.19456081092357635,
-0.07928960025310516,
0.2038593888282776,
0.3428382873535156,
-0.00865977257490158,
-0.013750068843364716,
-0.08435389399528503,
-0.170617014169693,
0.11397916823625565,
0.2748645842075348,
-0.08173888921737671,
0.446936696767807,
0.010800972580909729,
-0.051569364964962006,
-0.2344720959663391,
0.4114176034927368,
0.2861287593841553,
0.19494742155075073,
-0.1688622683286667,
0.06395319104194641,
0.20064730942249298,
0.03061327524483204,
-0.35468870401382446,
0.3286513686180115,
0.15114429593086243,
-0.2930281460285187,
0.3680053651332855,
0.12379556894302368,
-0.23215582966804504,
0.2764035165309906,
-0.1041957288980484,
-0.20146708190441132,
-0.049888961017131805,
0.3224371671676636,
0.09970720112323761,
-0.03993305563926697,
-0.1949632167816162,
0.1111203134059906,
-0.1445714384317398,
-0.28533875942230225,
0.15934628248214722,
-0.023898672312498093,
0.4676608443260193,
-0.2756762206554413,
0.11720523238182068,
-0.06182504817843437,
0.6220859885215759,
-0.02922816202044487,
0.12432920932769775,
-0.35013818740844727,
0.10264356434345245,
-0.3331668972969055,
0.198409765958786,
-0.08381709456443787,
0.15374305844306946,
-0.39758387207984924,
0.20426522195339203,
-0.11549905687570572,
-0.02346649393439293,
-0.11804220080375671,
-0.007886471226811409,
0.14740730822086334,
0.17893224954605103,
-0.3869178295135498,
0.1554817110300064,
-0.08625976741313934,
-0.006267093122005463,
0.29177382588386536,
-0.37667521834373474,
0.22199100255966187,
0.042478568851947784,
0.20691052079200745,
0.010985862463712692,
-0.02172362059354782,
-0.054806359112262726,
0.33657363057136536,
0.6232408881187439,
0.34702926874160767,
0.14255046844482422,
-0.10102763026952744,
0.08155438303947449,
-0.3474372923374176,
0.014104174450039864,
-0.06088797375559807,
-0.20964977145195007,
0.09756873548030853,
0.5258306264877319,
-0.22562795877456665,
0.13194617629051208,
-0.178046315908432,
0.23669393360614777,
0.3822764754295349,
-0.1527290940284729,
0.0618000254034996,
0.04822578281164169,
-0.2598402798175812,
-0.005199543200433254,
-0.12586651742458344,
0.45379629731178284,
0.007182497531175613,
0.32383060455322266,
-0.3592911958694458,
-0.5417625904083252,
0.43290984630584717,
-0.45112577080726624,
-0.30252525210380554,
0.12327728420495987,
0.23878571391105652,
0.34956857562065125,
-0.06000012159347534,
-0.5436676144599915,
-0.17249035835266113,
0.2691141963005066,
-0.030661150813102722,
-0.1570448875427246,
0.20768548548221588,
-0.14864324033260345,
-0.04107460752129555,
-0.1167544275522232,
0.17646947503089905,
0.10152687877416611,
-0.2914122939109802,
0.24369880557060242,
-0.3701038360595703
] |
https://github.com/huggingface/datasets/issues/160 | caching in map causes same result to be returned for train, validation and test | Ok, I think @lhoestq has already found a solution :-) Maybe you can chime in @lhoestq | hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
| 16 | caching in map causes same result to be returned for train, validation and test
hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
Ok, I think @lhoestq has already found a solution :-) Maybe you can chime in @lhoestq | [
-0.1263233721256256,
-0.22070911526679993,
-0.10063229501247406,
0.27801111340522766,
0.24547500908374786,
-0.20522364974021912,
0.13721121847629547,
0.512859046459198,
0.18828602135181427,
-0.06233552098274231,
0.1278189718723297,
0.38913494348526,
0.0037763379514217377,
-0.16061760485172272,
-0.010743602178990841,
0.024212224408984184,
0.09608031809329987,
0.23505264520645142,
-0.1455627828836441,
-0.16482312977313995,
0.0818943977355957,
0.2129845768213272,
-0.042410045862197876,
0.11652722954750061,
-0.39034977555274963,
0.04128977656364441,
0.2123567909002304,
-0.230890691280365,
0.06845765560865402,
-0.2570657432079315,
0.16785027086734772,
-0.09324291348457336,
0.025834325700998306,
0.16631808876991272,
-0.00010973814642056823,
0.006797894835472107,
-0.015387743711471558,
-0.13856983184814453,
-0.007274414878338575,
0.04019510746002197,
0.11813420802354813,
-0.21172915399074554,
-0.10918302088975906,
-0.31213220953941345,
-0.33201220631599426,
-0.037661660462617874,
0.017809096723794937,
-0.3556599020957947,
0.3128577172756195,
0.14745266735553741,
0.2607105076313019,
0.22490960359573364,
-0.2538115978240967,
0.21113674342632294,
0.1451275497674942,
-0.02932754158973694,
-0.1741972714662552,
-0.04230468347668648,
-0.04397884011268616,
-0.3344639539718628,
-0.37676432728767395,
0.525456964969635,
-0.07658185809850693,
0.17014150321483612,
0.21466577053070068,
0.2250560224056244,
0.1726061850786209,
0.035937413573265076,
0.14293654263019562,
-0.11396264284849167,
0.011095292866230011,
-0.2269170582294464,
-0.02711626887321472,
-0.3733709454536438,
-0.41864001750946045,
-0.07852613925933838,
0.137624591588974,
0.18104572594165802,
-0.13639286160469055,
-0.06371629238128662,
-0.43193674087524414,
0.23928946256637573,
0.06524854898452759,
-0.012788370251655579,
0.11952775716781616,
0.2951611876487732,
0.043805740773677826,
0.19522324204444885,
0.1294461488723755,
-0.06973283737897873,
-0.02255835384130478,
-0.21451729536056519,
-0.058972302824258804,
0.22640188038349152,
-0.4359855055809021,
0.07208243757486343,
0.4315193295478821,
-0.1404145359992981,
-0.05324290320277214,
0.0306372232735157,
0.39193007349967957,
0.07921387255191803,
0.11681866645812988,
-0.008491560816764832,
-0.10416118800640106,
0.5898669958114624,
0.044322285801172256,
0.17118452489376068,
-0.01497051864862442,
-0.19827789068222046,
-0.3560173213481903,
0.004987429827451706,
0.2880176305770874,
-0.2866014540195465,
0.4284125566482544,
0.40236005187034607,
-0.0422595851123333,
-0.12152935564517975,
-0.030101587995886803,
0.09402371197938919,
-0.33085376024246216,
0.055669233202934265,
0.05872948467731476,
0.31395789980888367,
-0.22545060515403748,
0.1492653489112854,
-0.1737677901983261,
-0.10335496068000793,
-0.38496947288513184,
0.12735126912593842,
-0.33784639835357666,
-0.03332383185625076,
-0.4962179958820343,
0.0015164613723754883,
0.28538399934768677,
-0.002860570326447487,
0.28535300493240356,
-0.03844557702541351,
-0.13722029328346252,
-0.301989883184433,
0.10317452996969223,
-0.39851242303848267,
0.5702308416366577,
-0.1072293221950531,
-0.1970168650150299,
0.24102140963077545,
0.13037806749343872,
0.08526398241519928,
-0.29768770933151245,
-0.1983770728111267,
-0.16980770230293274,
-0.2090688943862915,
0.2598598897457123,
0.2422453612089157,
-0.07942710071802139,
0.1413964033126831,
0.09248155355453491,
0.07767830789089203,
0.3432585597038269,
-0.2328546792268753,
0.10284028947353363,
-0.2014889419078827,
-0.2819805443286896,
-0.20435944199562073,
0.16256943345069885,
0.2623099088668823,
0.0667768269777298,
-0.13737235963344574,
0.40179744362831116,
0.23718246817588806,
0.14729131758213043,
0.4138064980506897,
-0.196533665060997,
0.30949509143829346,
-0.4334923028945923,
0.34861892461776733,
0.5064778923988342,
-0.32673120498657227,
-0.49634435772895813,
0.09944827109575272,
-0.1563153862953186,
0.1002877876162529,
0.10244903713464737,
0.1513729840517044,
0.02908817119896412,
0.014419601298868656,
0.12853626906871796,
0.01870240643620491,
-0.0005144402384757996,
0.20842039585113525,
-0.3169277310371399,
-0.021933740004897118,
0.5500645041465759,
-0.25246739387512207,
0.028472337871789932,
-0.1312367022037506,
-0.05504260212182999,
0.021932099014520645,
0.006768524646759033,
-0.11218959093093872,
0.12185925245285034,
0.1146051287651062,
-0.05687848851084709,
-0.15818428993225098,
-0.10643843561410904,
-0.02469290792942047,
-0.2882624864578247,
0.23830124735832214,
-0.14981965720653534,
-0.09996873140335083,
0.06172499060630798,
-0.09704941511154175,
-0.1620030403137207,
-0.1292746216058731,
-0.1809171587228775,
-0.27306482195854187,
0.20130175352096558,
0.23052407801151276,
0.3202403485774994,
-0.07290694117546082,
0.22520966827869415,
0.3680819571018219,
0.04836329072713852,
-0.21607185900211334,
-0.4300349950790405,
0.08568014949560165,
-0.17773526906967163,
-0.21882861852645874,
-0.074846550822258,
0.22306931018829346,
0.2090265452861786,
-0.0479268915951252,
-0.14242854714393616,
0.1482759267091751,
-0.22208523750305176,
0.41891855001449585,
-0.13702836632728577,
0.2694522738456726,
-0.06965650618076324,
0.029306214302778244,
0.016667230054736137,
0.2540055215358734,
0.05882029980421066,
-0.08980119228363037,
-0.07270593196153641,
0.47423404455184937,
0.18140165507793427,
0.17011570930480957,
-0.04807114973664284,
-0.2162683755159378,
0.05198418349027634,
-0.1783173829317093,
-0.12091565877199173,
-0.11881639063358307,
0.1364068239927292,
-0.0805719643831253,
0.14888811111450195,
0.15232901275157928,
-0.10698775947093964,
0.3120076358318329,
0.7600834369659424,
0.19691896438598633,
-0.011016584932804108,
0.015740428119897842,
-0.05721340328454971,
-0.2177915871143341,
0.33385711908340454,
-0.058683205395936966,
0.31038856506347656,
0.10473139584064484,
0.12716472148895264,
-0.04620931297540665,
-0.21964949369430542,
-0.1544356644153595,
0.12464860081672668,
-0.21436886489391327,
-0.19197627902030945,
0.3080342710018158,
0.28208714723587036,
-0.1583673059940338,
-0.3537829518318176,
0.09401586651802063,
-0.01276421919465065,
0.02619149163365364,
-0.1580010950565338,
0.21723711490631104,
-0.166529580950737,
-0.2780844271183014,
-0.2864159643650055,
0.13615699112415314,
-0.1222032904624939,
-0.09216521680355072,
-0.04126402735710144,
0.42542994022369385,
-0.03665407374501228,
0.19515199959278107,
-0.3149715065956116,
0.0895179957151413,
0.2266039401292801,
-0.26632726192474365,
-0.07168534398078918,
-0.1902872771024704,
-0.39492014050483704,
0.042231734842061996,
-0.09523066878318787,
-0.0929960310459137,
0.3783302307128906,
-0.047316424548625946,
-0.06796006858348846,
-0.2881466746330261,
-0.17254027724266052,
0.10717801749706268,
-0.09261122345924377,
-0.15536727011203766,
0.16724826395511627,
-0.03133828938007355,
-0.10115892440080643,
-0.29874566197395325,
0.2937973141670227,
-0.30531302094459534,
-0.2991430461406708,
-0.05198727175593376,
0.09890619665384293,
0.030108986422419548,
-0.2803470194339752,
-0.4286248981952667,
0.27357742190361023,
-0.31724435091018677,
0.07546759396791458,
-0.14892880618572235,
0.18622717261314392,
0.33093392848968506,
0.008953814394772053,
-0.014561107382178307,
-0.06404063105583191,
0.16439421474933624,
-0.4674096703529358,
-0.14095471799373627,
0.32257843017578125,
0.01876021921634674,
-0.21630443632602692,
-0.3245909512042999,
-0.2757244110107422,
0.34772399067878723,
0.19238810241222382,
-0.5803955793380737,
-0.21442262828350067,
-0.048900216817855835,
0.2480318248271942,
-0.05125897377729416,
-0.04649518430233002,
0.5745418071746826,
0.01972545124590397,
-0.17946316301822662,
-0.16727802157402039,
-0.33183929324150085,
0.35973066091537476,
0.4192623794078827,
0.24948757886886597,
-0.011158477514982224,
0.17781516909599304,
0.20092011988162994,
0.6707470417022705,
0.2019203156232834,
-0.2590579092502594,
0.33173102140426636,
0.10723146051168442,
0.07499773055315018,
-0.2034967839717865,
-0.3130229413509369,
0.18576018512248993,
-0.18160304427146912,
0.01973230391740799,
0.27198368310928345,
0.006250595673918724,
-0.2801837921142578,
0.017742767930030823,
0.21881836652755737,
-0.2253446877002716,
-0.328058123588562,
0.2597455084323883,
-0.3424280285835266,
0.24094843864440918,
0.036369793117046356,
0.3157997131347656,
-0.5820137858390808,
-0.24272391200065613,
0.19462794065475464,
-0.3359457850456238,
0.27984461188316345,
0.04449816048145294,
-0.5836011171340942,
0.12147033214569092,
-0.5380215048789978,
0.18194156885147095,
0.31462806463241577,
0.27240774035453796,
-0.09202472865581512,
-0.2465253472328186,
0.043347518891096115,
-0.14713148772716522,
0.5711420178413391,
0.04097308963537216,
0.40857934951782227,
0.16992636024951935,
-0.13024693727493286,
-0.19947344064712524,
-0.22471317648887634,
0.017234940081834793,
0.28013670444488525,
0.3265002369880676,
0.400847464799881,
-0.345244437456131,
-0.3632737100124359,
-0.2657657265663147,
0.007363845594227314,
-0.046181585639715195,
0.007106936536729336,
-0.12583458423614502,
0.18938523530960083,
0.01648571901023388,
0.17434579133987427,
-0.014980330131947994,
0.11830316483974457,
0.016039708629250526,
-0.13654674589633942,
-0.03913415968418121,
-0.21942690014839172,
0.12824007868766785,
0.22643797099590302,
0.4735948443412781,
0.1503245085477829,
0.03246166184544563,
0.033214349299669266,
0.21515773236751556,
-0.5671082735061646,
0.2659573554992676,
-0.08884961903095245,
-0.004131801426410675,
0.07464389503002167,
0.14443765580654144,
-0.030300907790660858,
0.3378967344760895,
-0.04252535104751587,
0.1457139402627945,
-0.12862969934940338,
0.008957155048847198,
-0.5539682507514954,
0.4854547381401062,
0.3874596357345581,
0.13246718049049377,
-0.044888898730278015,
-0.24685737490653992,
0.17346280813217163,
0.07412064075469971,
-0.27653080224990845,
0.13225962221622467,
-0.43069255352020264,
-0.4319950044155121,
0.18579739332199097,
0.2094864398241043,
0.9232466220855713,
0.33202219009399414,
0.37195777893066406,
0.10070358961820602,
0.10358034074306488,
0.26425158977508545,
-0.23411162197589874,
0.40924984216690063,
-0.3693644404411316,
-0.0463179312646389,
0.024538787081837654,
-0.16673341393470764,
-0.22738268971443176,
-0.010426290333271027,
-0.010993778705596924,
0.30259543657302856,
0.32404959201812744,
0.5999362468719482,
-0.11212000250816345,
0.16670005023479462,
0.215691938996315,
-0.15810950100421906,
-0.24923086166381836,
0.20107315480709076,
-0.2923040986061096,
0.31524065136909485,
-0.11240848153829575,
-0.07410834729671478,
-0.01650886982679367,
-0.35134220123291016,
0.06714004278182983,
0.0609416738152504,
-0.3365170359611511,
0.3048418164253235,
0.13346192240715027,
-0.27266669273376465,
-0.29698777198791504,
0.2550782561302185,
0.11198711395263672,
0.08252803981304169,
-0.048599302768707275,
-0.035185206681489944,
0.4006449580192566,
0.35045796632766724,
-0.006891845725476742,
-0.20158877968788147,
0.18641246855258942,
0.06387515366077423,
-0.012894652783870697,
0.030242733657360077,
-0.05640551447868347,
-0.3015826344490051,
-0.2525118589401245,
0.14820465445518494,
0.0033729001879692078,
-0.4129619598388672,
-0.055318914353847504,
0.06144453212618828,
-0.0667886808514595,
-0.09413722157478333,
0.15088041126728058,
-0.026068218052387238,
-0.10794125497341156,
0.3151545822620392,
0.11733834445476532,
-0.24304209649562836,
0.05235828459262848,
0.47483235597610474,
-0.04039648920297623,
0.031818099319934845,
0.4154282510280609,
-0.15281841158866882,
-0.10380619764328003,
-0.25539109110832214,
-0.28417226672172546,
-0.10206017643213272,
-0.44884029030799866,
0.11220822483301163,
-0.2194056510925293,
-0.40191107988357544,
0.04423205554485321,
0.2808186709880829,
0.014706198126077652,
0.3184961974620819,
-0.011618245393037796,
-0.12495805323123932,
-0.3769727349281311,
-0.10379086434841156,
-0.10658213496208191,
0.26717838644981384,
0.27951928973197937,
0.2843479812145233,
-0.29586678743362427,
0.2492268979549408,
-0.38310953974723816,
-0.10714222490787506,
-0.1871705949306488,
0.4379130005836487,
-0.0391375795006752,
-0.36558276414871216,
-0.009147514589130878,
0.0018548620864748955,
0.12997101247310638,
0.17754510045051575,
-0.6386584639549255,
-0.29261907935142517,
-0.09099219739437103,
0.08186075091362,
-0.007588040083646774,
-0.1598217487335205,
-0.23928231000900269,
-0.01721424236893654,
0.18238495290279388,
-0.427402526140213,
0.09215688705444336,
0.15121665596961975,
0.04703199863433838,
0.23718711733818054,
-0.1610298752784729,
0.1214555948972702,
0.28816717863082886,
-0.18652743101119995,
-0.1841491460800171,
-0.07622881233692169,
0.08048095554113388,
0.25701695680618286,
-0.06946776062250137,
0.020479001104831696,
-0.2104034423828125,
0.030471812933683395,
0.08927443623542786,
0.14279493689537048,
0.23692923784255981,
-0.024752572178840637,
-0.21566128730773926,
0.0005505271255970001,
0.18279926478862762,
0.11411947757005692,
-0.07855326682329178,
-0.32897576689720154,
0.2802233397960663,
0.2783650755882263,
-0.11751837283372879,
-0.0102371945977211,
0.1677074134349823,
-0.09938855469226837,
0.25285133719444275,
0.20715340971946716,
0.10758769512176514,
0.05261163413524628,
0.26961183547973633,
0.12649410963058472,
0.40504008531570435,
-0.34832900762557983,
0.08942112326622009,
0.06441552191972733,
0.10164903104305267,
0.03777839243412018,
0.38121557235717773,
-0.1532439887523651,
0.08992154896259308,
0.14838308095932007,
0.18833690881729126,
0.20253999531269073,
0.26289018988609314,
0.21354106068611145,
-0.1878642439842224,
-0.03412104770541191,
-0.24108661711215973,
0.1436368077993393,
-0.14272664487361908,
0.4156598448753357,
0.15059244632720947,
0.19285538792610168,
-0.11485158652067184,
-0.4619392156600952,
-0.2462674379348755,
0.23536445200443268,
-0.3245418667793274,
-0.30920952558517456,
-0.04867886006832123,
-0.08018464595079422,
0.05592931807041168,
0.19456081092357635,
-0.07928960025310516,
0.2038593888282776,
0.3428382873535156,
-0.00865977257490158,
-0.013750068843364716,
-0.08435389399528503,
-0.170617014169693,
0.11397916823625565,
0.2748645842075348,
-0.08173888921737671,
0.446936696767807,
0.010800972580909729,
-0.051569364964962006,
-0.2344720959663391,
0.4114176034927368,
0.2861287593841553,
0.19494742155075073,
-0.1688622683286667,
0.06395319104194641,
0.20064730942249298,
0.03061327524483204,
-0.35468870401382446,
0.3286513686180115,
0.15114429593086243,
-0.2930281460285187,
0.3680053651332855,
0.12379556894302368,
-0.23215582966804504,
0.2764035165309906,
-0.1041957288980484,
-0.20146708190441132,
-0.049888961017131805,
0.3224371671676636,
0.09970720112323761,
-0.03993305563926697,
-0.1949632167816162,
0.1111203134059906,
-0.1445714384317398,
-0.28533875942230225,
0.15934628248214722,
-0.023898672312498093,
0.4676608443260193,
-0.2756762206554413,
0.11720523238182068,
-0.06182504817843437,
0.6220859885215759,
-0.02922816202044487,
0.12432920932769775,
-0.35013818740844727,
0.10264356434345245,
-0.3331668972969055,
0.198409765958786,
-0.08381709456443787,
0.15374305844306946,
-0.39758387207984924,
0.20426522195339203,
-0.11549905687570572,
-0.02346649393439293,
-0.11804220080375671,
-0.007886471226811409,
0.14740730822086334,
0.17893224954605103,
-0.3869178295135498,
0.1554817110300064,
-0.08625976741313934,
-0.006267093122005463,
0.29177382588386536,
-0.37667521834373474,
0.22199100255966187,
0.042478568851947784,
0.20691052079200745,
0.010985862463712692,
-0.02172362059354782,
-0.054806359112262726,
0.33657363057136536,
0.6232408881187439,
0.34702926874160767,
0.14255046844482422,
-0.10102763026952744,
0.08155438303947449,
-0.3474372923374176,
0.014104174450039864,
-0.06088797375559807,
-0.20964977145195007,
0.09756873548030853,
0.5258306264877319,
-0.22562795877456665,
0.13194617629051208,
-0.178046315908432,
0.23669393360614777,
0.3822764754295349,
-0.1527290940284729,
0.0618000254034996,
0.04822578281164169,
-0.2598402798175812,
-0.005199543200433254,
-0.12586651742458344,
0.45379629731178284,
0.007182497531175613,
0.32383060455322266,
-0.3592911958694458,
-0.5417625904083252,
0.43290984630584717,
-0.45112577080726624,
-0.30252525210380554,
0.12327728420495987,
0.23878571391105652,
0.34956857562065125,
-0.06000012159347534,
-0.5436676144599915,
-0.17249035835266113,
0.2691141963005066,
-0.030661150813102722,
-0.1570448875427246,
0.20768548548221588,
-0.14864324033260345,
-0.04107460752129555,
-0.1167544275522232,
0.17646947503089905,
0.10152687877416611,
-0.2914122939109802,
0.24369880557060242,
-0.3701038360595703
] |
https://github.com/huggingface/datasets/issues/160 | caching in map causes same result to be returned for train, validation and test | > Ok, I think @lhoestq has already found a solution :-) Maybe you can chime in @lhoestq
Oh, awesome! I see the PR, Ill check it out | hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
| 27 | caching in map causes same result to be returned for train, validation and test
hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
> Ok, I think @lhoestq has already found a solution :-) Maybe you can chime in @lhoestq
Oh, awesome! I see the PR, Ill check it out | [
-0.1263233721256256,
-0.22070911526679993,
-0.10063229501247406,
0.27801111340522766,
0.24547500908374786,
-0.20522364974021912,
0.13721121847629547,
0.512859046459198,
0.18828602135181427,
-0.06233552098274231,
0.1278189718723297,
0.38913494348526,
0.0037763379514217377,
-0.16061760485172272,
-0.010743602178990841,
0.024212224408984184,
0.09608031809329987,
0.23505264520645142,
-0.1455627828836441,
-0.16482312977313995,
0.0818943977355957,
0.2129845768213272,
-0.042410045862197876,
0.11652722954750061,
-0.39034977555274963,
0.04128977656364441,
0.2123567909002304,
-0.230890691280365,
0.06845765560865402,
-0.2570657432079315,
0.16785027086734772,
-0.09324291348457336,
0.025834325700998306,
0.16631808876991272,
-0.00010973814642056823,
0.006797894835472107,
-0.015387743711471558,
-0.13856983184814453,
-0.007274414878338575,
0.04019510746002197,
0.11813420802354813,
-0.21172915399074554,
-0.10918302088975906,
-0.31213220953941345,
-0.33201220631599426,
-0.037661660462617874,
0.017809096723794937,
-0.3556599020957947,
0.3128577172756195,
0.14745266735553741,
0.2607105076313019,
0.22490960359573364,
-0.2538115978240967,
0.21113674342632294,
0.1451275497674942,
-0.02932754158973694,
-0.1741972714662552,
-0.04230468347668648,
-0.04397884011268616,
-0.3344639539718628,
-0.37676432728767395,
0.525456964969635,
-0.07658185809850693,
0.17014150321483612,
0.21466577053070068,
0.2250560224056244,
0.1726061850786209,
0.035937413573265076,
0.14293654263019562,
-0.11396264284849167,
0.011095292866230011,
-0.2269170582294464,
-0.02711626887321472,
-0.3733709454536438,
-0.41864001750946045,
-0.07852613925933838,
0.137624591588974,
0.18104572594165802,
-0.13639286160469055,
-0.06371629238128662,
-0.43193674087524414,
0.23928946256637573,
0.06524854898452759,
-0.012788370251655579,
0.11952775716781616,
0.2951611876487732,
0.043805740773677826,
0.19522324204444885,
0.1294461488723755,
-0.06973283737897873,
-0.02255835384130478,
-0.21451729536056519,
-0.058972302824258804,
0.22640188038349152,
-0.4359855055809021,
0.07208243757486343,
0.4315193295478821,
-0.1404145359992981,
-0.05324290320277214,
0.0306372232735157,
0.39193007349967957,
0.07921387255191803,
0.11681866645812988,
-0.008491560816764832,
-0.10416118800640106,
0.5898669958114624,
0.044322285801172256,
0.17118452489376068,
-0.01497051864862442,
-0.19827789068222046,
-0.3560173213481903,
0.004987429827451706,
0.2880176305770874,
-0.2866014540195465,
0.4284125566482544,
0.40236005187034607,
-0.0422595851123333,
-0.12152935564517975,
-0.030101587995886803,
0.09402371197938919,
-0.33085376024246216,
0.055669233202934265,
0.05872948467731476,
0.31395789980888367,
-0.22545060515403748,
0.1492653489112854,
-0.1737677901983261,
-0.10335496068000793,
-0.38496947288513184,
0.12735126912593842,
-0.33784639835357666,
-0.03332383185625076,
-0.4962179958820343,
0.0015164613723754883,
0.28538399934768677,
-0.002860570326447487,
0.28535300493240356,
-0.03844557702541351,
-0.13722029328346252,
-0.301989883184433,
0.10317452996969223,
-0.39851242303848267,
0.5702308416366577,
-0.1072293221950531,
-0.1970168650150299,
0.24102140963077545,
0.13037806749343872,
0.08526398241519928,
-0.29768770933151245,
-0.1983770728111267,
-0.16980770230293274,
-0.2090688943862915,
0.2598598897457123,
0.2422453612089157,
-0.07942710071802139,
0.1413964033126831,
0.09248155355453491,
0.07767830789089203,
0.3432585597038269,
-0.2328546792268753,
0.10284028947353363,
-0.2014889419078827,
-0.2819805443286896,
-0.20435944199562073,
0.16256943345069885,
0.2623099088668823,
0.0667768269777298,
-0.13737235963344574,
0.40179744362831116,
0.23718246817588806,
0.14729131758213043,
0.4138064980506897,
-0.196533665060997,
0.30949509143829346,
-0.4334923028945923,
0.34861892461776733,
0.5064778923988342,
-0.32673120498657227,
-0.49634435772895813,
0.09944827109575272,
-0.1563153862953186,
0.1002877876162529,
0.10244903713464737,
0.1513729840517044,
0.02908817119896412,
0.014419601298868656,
0.12853626906871796,
0.01870240643620491,
-0.0005144402384757996,
0.20842039585113525,
-0.3169277310371399,
-0.021933740004897118,
0.5500645041465759,
-0.25246739387512207,
0.028472337871789932,
-0.1312367022037506,
-0.05504260212182999,
0.021932099014520645,
0.006768524646759033,
-0.11218959093093872,
0.12185925245285034,
0.1146051287651062,
-0.05687848851084709,
-0.15818428993225098,
-0.10643843561410904,
-0.02469290792942047,
-0.2882624864578247,
0.23830124735832214,
-0.14981965720653534,
-0.09996873140335083,
0.06172499060630798,
-0.09704941511154175,
-0.1620030403137207,
-0.1292746216058731,
-0.1809171587228775,
-0.27306482195854187,
0.20130175352096558,
0.23052407801151276,
0.3202403485774994,
-0.07290694117546082,
0.22520966827869415,
0.3680819571018219,
0.04836329072713852,
-0.21607185900211334,
-0.4300349950790405,
0.08568014949560165,
-0.17773526906967163,
-0.21882861852645874,
-0.074846550822258,
0.22306931018829346,
0.2090265452861786,
-0.0479268915951252,
-0.14242854714393616,
0.1482759267091751,
-0.22208523750305176,
0.41891855001449585,
-0.13702836632728577,
0.2694522738456726,
-0.06965650618076324,
0.029306214302778244,
0.016667230054736137,
0.2540055215358734,
0.05882029980421066,
-0.08980119228363037,
-0.07270593196153641,
0.47423404455184937,
0.18140165507793427,
0.17011570930480957,
-0.04807114973664284,
-0.2162683755159378,
0.05198418349027634,
-0.1783173829317093,
-0.12091565877199173,
-0.11881639063358307,
0.1364068239927292,
-0.0805719643831253,
0.14888811111450195,
0.15232901275157928,
-0.10698775947093964,
0.3120076358318329,
0.7600834369659424,
0.19691896438598633,
-0.011016584932804108,
0.015740428119897842,
-0.05721340328454971,
-0.2177915871143341,
0.33385711908340454,
-0.058683205395936966,
0.31038856506347656,
0.10473139584064484,
0.12716472148895264,
-0.04620931297540665,
-0.21964949369430542,
-0.1544356644153595,
0.12464860081672668,
-0.21436886489391327,
-0.19197627902030945,
0.3080342710018158,
0.28208714723587036,
-0.1583673059940338,
-0.3537829518318176,
0.09401586651802063,
-0.01276421919465065,
0.02619149163365364,
-0.1580010950565338,
0.21723711490631104,
-0.166529580950737,
-0.2780844271183014,
-0.2864159643650055,
0.13615699112415314,
-0.1222032904624939,
-0.09216521680355072,
-0.04126402735710144,
0.42542994022369385,
-0.03665407374501228,
0.19515199959278107,
-0.3149715065956116,
0.0895179957151413,
0.2266039401292801,
-0.26632726192474365,
-0.07168534398078918,
-0.1902872771024704,
-0.39492014050483704,
0.042231734842061996,
-0.09523066878318787,
-0.0929960310459137,
0.3783302307128906,
-0.047316424548625946,
-0.06796006858348846,
-0.2881466746330261,
-0.17254027724266052,
0.10717801749706268,
-0.09261122345924377,
-0.15536727011203766,
0.16724826395511627,
-0.03133828938007355,
-0.10115892440080643,
-0.29874566197395325,
0.2937973141670227,
-0.30531302094459534,
-0.2991430461406708,
-0.05198727175593376,
0.09890619665384293,
0.030108986422419548,
-0.2803470194339752,
-0.4286248981952667,
0.27357742190361023,
-0.31724435091018677,
0.07546759396791458,
-0.14892880618572235,
0.18622717261314392,
0.33093392848968506,
0.008953814394772053,
-0.014561107382178307,
-0.06404063105583191,
0.16439421474933624,
-0.4674096703529358,
-0.14095471799373627,
0.32257843017578125,
0.01876021921634674,
-0.21630443632602692,
-0.3245909512042999,
-0.2757244110107422,
0.34772399067878723,
0.19238810241222382,
-0.5803955793380737,
-0.21442262828350067,
-0.048900216817855835,
0.2480318248271942,
-0.05125897377729416,
-0.04649518430233002,
0.5745418071746826,
0.01972545124590397,
-0.17946316301822662,
-0.16727802157402039,
-0.33183929324150085,
0.35973066091537476,
0.4192623794078827,
0.24948757886886597,
-0.011158477514982224,
0.17781516909599304,
0.20092011988162994,
0.6707470417022705,
0.2019203156232834,
-0.2590579092502594,
0.33173102140426636,
0.10723146051168442,
0.07499773055315018,
-0.2034967839717865,
-0.3130229413509369,
0.18576018512248993,
-0.18160304427146912,
0.01973230391740799,
0.27198368310928345,
0.006250595673918724,
-0.2801837921142578,
0.017742767930030823,
0.21881836652755737,
-0.2253446877002716,
-0.328058123588562,
0.2597455084323883,
-0.3424280285835266,
0.24094843864440918,
0.036369793117046356,
0.3157997131347656,
-0.5820137858390808,
-0.24272391200065613,
0.19462794065475464,
-0.3359457850456238,
0.27984461188316345,
0.04449816048145294,
-0.5836011171340942,
0.12147033214569092,
-0.5380215048789978,
0.18194156885147095,
0.31462806463241577,
0.27240774035453796,
-0.09202472865581512,
-0.2465253472328186,
0.043347518891096115,
-0.14713148772716522,
0.5711420178413391,
0.04097308963537216,
0.40857934951782227,
0.16992636024951935,
-0.13024693727493286,
-0.19947344064712524,
-0.22471317648887634,
0.017234940081834793,
0.28013670444488525,
0.3265002369880676,
0.400847464799881,
-0.345244437456131,
-0.3632737100124359,
-0.2657657265663147,
0.007363845594227314,
-0.046181585639715195,
0.007106936536729336,
-0.12583458423614502,
0.18938523530960083,
0.01648571901023388,
0.17434579133987427,
-0.014980330131947994,
0.11830316483974457,
0.016039708629250526,
-0.13654674589633942,
-0.03913415968418121,
-0.21942690014839172,
0.12824007868766785,
0.22643797099590302,
0.4735948443412781,
0.1503245085477829,
0.03246166184544563,
0.033214349299669266,
0.21515773236751556,
-0.5671082735061646,
0.2659573554992676,
-0.08884961903095245,
-0.004131801426410675,
0.07464389503002167,
0.14443765580654144,
-0.030300907790660858,
0.3378967344760895,
-0.04252535104751587,
0.1457139402627945,
-0.12862969934940338,
0.008957155048847198,
-0.5539682507514954,
0.4854547381401062,
0.3874596357345581,
0.13246718049049377,
-0.044888898730278015,
-0.24685737490653992,
0.17346280813217163,
0.07412064075469971,
-0.27653080224990845,
0.13225962221622467,
-0.43069255352020264,
-0.4319950044155121,
0.18579739332199097,
0.2094864398241043,
0.9232466220855713,
0.33202219009399414,
0.37195777893066406,
0.10070358961820602,
0.10358034074306488,
0.26425158977508545,
-0.23411162197589874,
0.40924984216690063,
-0.3693644404411316,
-0.0463179312646389,
0.024538787081837654,
-0.16673341393470764,
-0.22738268971443176,
-0.010426290333271027,
-0.010993778705596924,
0.30259543657302856,
0.32404959201812744,
0.5999362468719482,
-0.11212000250816345,
0.16670005023479462,
0.215691938996315,
-0.15810950100421906,
-0.24923086166381836,
0.20107315480709076,
-0.2923040986061096,
0.31524065136909485,
-0.11240848153829575,
-0.07410834729671478,
-0.01650886982679367,
-0.35134220123291016,
0.06714004278182983,
0.0609416738152504,
-0.3365170359611511,
0.3048418164253235,
0.13346192240715027,
-0.27266669273376465,
-0.29698777198791504,
0.2550782561302185,
0.11198711395263672,
0.08252803981304169,
-0.048599302768707275,
-0.035185206681489944,
0.4006449580192566,
0.35045796632766724,
-0.006891845725476742,
-0.20158877968788147,
0.18641246855258942,
0.06387515366077423,
-0.012894652783870697,
0.030242733657360077,
-0.05640551447868347,
-0.3015826344490051,
-0.2525118589401245,
0.14820465445518494,
0.0033729001879692078,
-0.4129619598388672,
-0.055318914353847504,
0.06144453212618828,
-0.0667886808514595,
-0.09413722157478333,
0.15088041126728058,
-0.026068218052387238,
-0.10794125497341156,
0.3151545822620392,
0.11733834445476532,
-0.24304209649562836,
0.05235828459262848,
0.47483235597610474,
-0.04039648920297623,
0.031818099319934845,
0.4154282510280609,
-0.15281841158866882,
-0.10380619764328003,
-0.25539109110832214,
-0.28417226672172546,
-0.10206017643213272,
-0.44884029030799866,
0.11220822483301163,
-0.2194056510925293,
-0.40191107988357544,
0.04423205554485321,
0.2808186709880829,
0.014706198126077652,
0.3184961974620819,
-0.011618245393037796,
-0.12495805323123932,
-0.3769727349281311,
-0.10379086434841156,
-0.10658213496208191,
0.26717838644981384,
0.27951928973197937,
0.2843479812145233,
-0.29586678743362427,
0.2492268979549408,
-0.38310953974723816,
-0.10714222490787506,
-0.1871705949306488,
0.4379130005836487,
-0.0391375795006752,
-0.36558276414871216,
-0.009147514589130878,
0.0018548620864748955,
0.12997101247310638,
0.17754510045051575,
-0.6386584639549255,
-0.29261907935142517,
-0.09099219739437103,
0.08186075091362,
-0.007588040083646774,
-0.1598217487335205,
-0.23928231000900269,
-0.01721424236893654,
0.18238495290279388,
-0.427402526140213,
0.09215688705444336,
0.15121665596961975,
0.04703199863433838,
0.23718711733818054,
-0.1610298752784729,
0.1214555948972702,
0.28816717863082886,
-0.18652743101119995,
-0.1841491460800171,
-0.07622881233692169,
0.08048095554113388,
0.25701695680618286,
-0.06946776062250137,
0.020479001104831696,
-0.2104034423828125,
0.030471812933683395,
0.08927443623542786,
0.14279493689537048,
0.23692923784255981,
-0.024752572178840637,
-0.21566128730773926,
0.0005505271255970001,
0.18279926478862762,
0.11411947757005692,
-0.07855326682329178,
-0.32897576689720154,
0.2802233397960663,
0.2783650755882263,
-0.11751837283372879,
-0.0102371945977211,
0.1677074134349823,
-0.09938855469226837,
0.25285133719444275,
0.20715340971946716,
0.10758769512176514,
0.05261163413524628,
0.26961183547973633,
0.12649410963058472,
0.40504008531570435,
-0.34832900762557983,
0.08942112326622009,
0.06441552191972733,
0.10164903104305267,
0.03777839243412018,
0.38121557235717773,
-0.1532439887523651,
0.08992154896259308,
0.14838308095932007,
0.18833690881729126,
0.20253999531269073,
0.26289018988609314,
0.21354106068611145,
-0.1878642439842224,
-0.03412104770541191,
-0.24108661711215973,
0.1436368077993393,
-0.14272664487361908,
0.4156598448753357,
0.15059244632720947,
0.19285538792610168,
-0.11485158652067184,
-0.4619392156600952,
-0.2462674379348755,
0.23536445200443268,
-0.3245418667793274,
-0.30920952558517456,
-0.04867886006832123,
-0.08018464595079422,
0.05592931807041168,
0.19456081092357635,
-0.07928960025310516,
0.2038593888282776,
0.3428382873535156,
-0.00865977257490158,
-0.013750068843364716,
-0.08435389399528503,
-0.170617014169693,
0.11397916823625565,
0.2748645842075348,
-0.08173888921737671,
0.446936696767807,
0.010800972580909729,
-0.051569364964962006,
-0.2344720959663391,
0.4114176034927368,
0.2861287593841553,
0.19494742155075073,
-0.1688622683286667,
0.06395319104194641,
0.20064730942249298,
0.03061327524483204,
-0.35468870401382446,
0.3286513686180115,
0.15114429593086243,
-0.2930281460285187,
0.3680053651332855,
0.12379556894302368,
-0.23215582966804504,
0.2764035165309906,
-0.1041957288980484,
-0.20146708190441132,
-0.049888961017131805,
0.3224371671676636,
0.09970720112323761,
-0.03993305563926697,
-0.1949632167816162,
0.1111203134059906,
-0.1445714384317398,
-0.28533875942230225,
0.15934628248214722,
-0.023898672312498093,
0.4676608443260193,
-0.2756762206554413,
0.11720523238182068,
-0.06182504817843437,
0.6220859885215759,
-0.02922816202044487,
0.12432920932769775,
-0.35013818740844727,
0.10264356434345245,
-0.3331668972969055,
0.198409765958786,
-0.08381709456443787,
0.15374305844306946,
-0.39758387207984924,
0.20426522195339203,
-0.11549905687570572,
-0.02346649393439293,
-0.11804220080375671,
-0.007886471226811409,
0.14740730822086334,
0.17893224954605103,
-0.3869178295135498,
0.1554817110300064,
-0.08625976741313934,
-0.006267093122005463,
0.29177382588386536,
-0.37667521834373474,
0.22199100255966187,
0.042478568851947784,
0.20691052079200745,
0.010985862463712692,
-0.02172362059354782,
-0.054806359112262726,
0.33657363057136536,
0.6232408881187439,
0.34702926874160767,
0.14255046844482422,
-0.10102763026952744,
0.08155438303947449,
-0.3474372923374176,
0.014104174450039864,
-0.06088797375559807,
-0.20964977145195007,
0.09756873548030853,
0.5258306264877319,
-0.22562795877456665,
0.13194617629051208,
-0.178046315908432,
0.23669393360614777,
0.3822764754295349,
-0.1527290940284729,
0.0618000254034996,
0.04822578281164169,
-0.2598402798175812,
-0.005199543200433254,
-0.12586651742458344,
0.45379629731178284,
0.007182497531175613,
0.32383060455322266,
-0.3592911958694458,
-0.5417625904083252,
0.43290984630584717,
-0.45112577080726624,
-0.30252525210380554,
0.12327728420495987,
0.23878571391105652,
0.34956857562065125,
-0.06000012159347534,
-0.5436676144599915,
-0.17249035835266113,
0.2691141963005066,
-0.030661150813102722,
-0.1570448875427246,
0.20768548548221588,
-0.14864324033260345,
-0.04107460752129555,
-0.1167544275522232,
0.17646947503089905,
0.10152687877416611,
-0.2914122939109802,
0.24369880557060242,
-0.3701038360595703
] |
https://github.com/huggingface/datasets/issues/160 | caching in map causes same result to be returned for train, validation and test | The PR should prevent the cache from losing track of the of the dataset type (based on the location of its data). Not sure about your second problem though (cache off). | hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
| 31 | caching in map causes same result to be returned for train, validation and test
hello,
I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.dataset)
...
# Create feature vocabs
vocabs = create_vocabs(dataset.values(), vectorizers)
...
# Create a function to vectorize based on vectorizers and vocabs:
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
# factory method to create a `convert_to_features` function based on vocabs
convert_to_features = create_featurizer(vectorizers, vocabs)
train_set = train_set.map(convert_to_features, batched=True)
train_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
train_loader = torch.utils.data.DataLoader(train_set, batch_size=args.batchsz)
valid_set = valid_set.map(convert_to_features, batched=True)
valid_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
valid_loader = torch.utils.data.DataLoader(valid_set, batch_size=args.batchsz)
test_set = test_set.map(convert_to_features, batched=True)
test_set.set_format(type='torch', columns=list(vectorizers.keys()) + ['y', 'lengths'])
test_loader = torch.utils.data.DataLoader(test_set, batch_size=args.batchsz)
print('TS', train_set.num_rows)
print('VS', valid_set.num_rows)
print('ES', test_set.num_rows)
```
Im not sure if Im using it incorrectly, but the results are not what I expect. Namely, the `.map()` seems to grab the datset from the cache and then loses track of what the specific dataset is, instead using my training data for all datasets:
```
TS 67349
VS 872
ES 1821
TS 67349
VS 67349
ES 67349
```
The behavior changes if I turn off the caching but then the results fail:
```
train_set = train_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
valid_set = valid_set.map(convert_to_features, batched=True, load_from_cache_file=False)
...
test_set = test_set.map(convert_to_features, batched=True, load_from_cache_file=False)
```
Now I get the right set of features back...
```
TS 67349
VS 872
ES 1821
100%|██████████| 68/68 [00:00<00:00, 92.78it/s]
100%|██████████| 1/1 [00:00<00:00, 75.47it/s]
0%| | 0/2 [00:00<?, ?it/s]TS 67349
VS 872
ES 1821
100%|██████████| 2/2 [00:00<00:00, 77.19it/s]
```
but I think its losing track of the original training set:
```
Traceback (most recent call last):
File "/home/dpressel/dev/work/baseline/api-examples/layers-classify-hf-datasets.py", line 148, in <module>
for x in train_loader:
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in __next__
data = self._next_data()
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
output_all_columns=self._output_all_columns,
File "/home/dpressel/anaconda3/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 294, in _getitem
outputs = self._unnest(self._data.slice(key, 1).to_pydict())
File "pyarrow/table.pxi", line 1211, in pyarrow.lib.Table.slice
File "pyarrow/public-api.pxi", line 390, in pyarrow.lib.pyarrow_wrap_table
File "pyarrow/error.pxi", line 85, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 3: In chunk 0: Invalid: Length spanned by list offsets (15859698) larger than values array (length 100000)
Process finished with exit code 1
```
The full-example program (minus the print stmts) is here:
https://github.com/dpressel/mead-baseline/pull/620/files
The PR should prevent the cache from losing track of the of the dataset type (based on the location of its data). Not sure about your second problem though (cache off). | [
-0.1263233721256256,
-0.22070911526679993,
-0.10063229501247406,
0.27801111340522766,
0.24547500908374786,
-0.20522364974021912,
0.13721121847629547,
0.512859046459198,
0.18828602135181427,
-0.06233552098274231,
0.1278189718723297,
0.38913494348526,
0.0037763379514217377,
-0.16061760485172272,
-0.010743602178990841,
0.024212224408984184,
0.09608031809329987,
0.23505264520645142,
-0.1455627828836441,
-0.16482312977313995,
0.0818943977355957,
0.2129845768213272,
-0.042410045862197876,
0.11652722954750061,
-0.39034977555274963,
0.04128977656364441,
0.2123567909002304,
-0.230890691280365,
0.06845765560865402,
-0.2570657432079315,
0.16785027086734772,
-0.09324291348457336,
0.025834325700998306,
0.16631808876991272,
-0.00010973814642056823,
0.006797894835472107,
-0.015387743711471558,
-0.13856983184814453,
-0.007274414878338575,
0.04019510746002197,
0.11813420802354813,
-0.21172915399074554,
-0.10918302088975906,
-0.31213220953941345,
-0.33201220631599426,
-0.037661660462617874,
0.017809096723794937,
-0.3556599020957947,
0.3128577172756195,
0.14745266735553741,
0.2607105076313019,
0.22490960359573364,
-0.2538115978240967,
0.21113674342632294,
0.1451275497674942,
-0.02932754158973694,
-0.1741972714662552,
-0.04230468347668648,
-0.04397884011268616,
-0.3344639539718628,
-0.37676432728767395,
0.525456964969635,
-0.07658185809850693,
0.17014150321483612,
0.21466577053070068,
0.2250560224056244,
0.1726061850786209,
0.035937413573265076,
0.14293654263019562,
-0.11396264284849167,
0.011095292866230011,
-0.2269170582294464,
-0.02711626887321472,
-0.3733709454536438,
-0.41864001750946045,
-0.07852613925933838,
0.137624591588974,
0.18104572594165802,
-0.13639286160469055,
-0.06371629238128662,
-0.43193674087524414,
0.23928946256637573,
0.06524854898452759,
-0.012788370251655579,
0.11952775716781616,
0.2951611876487732,
0.043805740773677826,
0.19522324204444885,
0.1294461488723755,
-0.06973283737897873,
-0.02255835384130478,
-0.21451729536056519,
-0.058972302824258804,
0.22640188038349152,
-0.4359855055809021,
0.07208243757486343,
0.4315193295478821,
-0.1404145359992981,
-0.05324290320277214,
0.0306372232735157,
0.39193007349967957,
0.07921387255191803,
0.11681866645812988,
-0.008491560816764832,
-0.10416118800640106,
0.5898669958114624,
0.044322285801172256,
0.17118452489376068,
-0.01497051864862442,
-0.19827789068222046,
-0.3560173213481903,
0.004987429827451706,
0.2880176305770874,
-0.2866014540195465,
0.4284125566482544,
0.40236005187034607,
-0.0422595851123333,
-0.12152935564517975,
-0.030101587995886803,
0.09402371197938919,
-0.33085376024246216,
0.055669233202934265,
0.05872948467731476,
0.31395789980888367,
-0.22545060515403748,
0.1492653489112854,
-0.1737677901983261,
-0.10335496068000793,
-0.38496947288513184,
0.12735126912593842,
-0.33784639835357666,
-0.03332383185625076,
-0.4962179958820343,
0.0015164613723754883,
0.28538399934768677,
-0.002860570326447487,
0.28535300493240356,
-0.03844557702541351,
-0.13722029328346252,
-0.301989883184433,
0.10317452996969223,
-0.39851242303848267,
0.5702308416366577,
-0.1072293221950531,
-0.1970168650150299,
0.24102140963077545,
0.13037806749343872,
0.08526398241519928,
-0.29768770933151245,
-0.1983770728111267,
-0.16980770230293274,
-0.2090688943862915,
0.2598598897457123,
0.2422453612089157,
-0.07942710071802139,
0.1413964033126831,
0.09248155355453491,
0.07767830789089203,
0.3432585597038269,
-0.2328546792268753,
0.10284028947353363,
-0.2014889419078827,
-0.2819805443286896,
-0.20435944199562073,
0.16256943345069885,
0.2623099088668823,
0.0667768269777298,
-0.13737235963344574,
0.40179744362831116,
0.23718246817588806,
0.14729131758213043,
0.4138064980506897,
-0.196533665060997,
0.30949509143829346,
-0.4334923028945923,
0.34861892461776733,
0.5064778923988342,
-0.32673120498657227,
-0.49634435772895813,
0.09944827109575272,
-0.1563153862953186,
0.1002877876162529,
0.10244903713464737,
0.1513729840517044,
0.02908817119896412,
0.014419601298868656,
0.12853626906871796,
0.01870240643620491,
-0.0005144402384757996,
0.20842039585113525,
-0.3169277310371399,
-0.021933740004897118,
0.5500645041465759,
-0.25246739387512207,
0.028472337871789932,
-0.1312367022037506,
-0.05504260212182999,
0.021932099014520645,
0.006768524646759033,
-0.11218959093093872,
0.12185925245285034,
0.1146051287651062,
-0.05687848851084709,
-0.15818428993225098,
-0.10643843561410904,
-0.02469290792942047,
-0.2882624864578247,
0.23830124735832214,
-0.14981965720653534,
-0.09996873140335083,
0.06172499060630798,
-0.09704941511154175,
-0.1620030403137207,
-0.1292746216058731,
-0.1809171587228775,
-0.27306482195854187,
0.20130175352096558,
0.23052407801151276,
0.3202403485774994,
-0.07290694117546082,
0.22520966827869415,
0.3680819571018219,
0.04836329072713852,
-0.21607185900211334,
-0.4300349950790405,
0.08568014949560165,
-0.17773526906967163,
-0.21882861852645874,
-0.074846550822258,
0.22306931018829346,
0.2090265452861786,
-0.0479268915951252,
-0.14242854714393616,
0.1482759267091751,
-0.22208523750305176,
0.41891855001449585,
-0.13702836632728577,
0.2694522738456726,
-0.06965650618076324,
0.029306214302778244,
0.016667230054736137,
0.2540055215358734,
0.05882029980421066,
-0.08980119228363037,
-0.07270593196153641,
0.47423404455184937,
0.18140165507793427,
0.17011570930480957,
-0.04807114973664284,
-0.2162683755159378,
0.05198418349027634,
-0.1783173829317093,
-0.12091565877199173,
-0.11881639063358307,
0.1364068239927292,
-0.0805719643831253,
0.14888811111450195,
0.15232901275157928,
-0.10698775947093964,
0.3120076358318329,
0.7600834369659424,
0.19691896438598633,
-0.011016584932804108,
0.015740428119897842,
-0.05721340328454971,
-0.2177915871143341,
0.33385711908340454,
-0.058683205395936966,
0.31038856506347656,
0.10473139584064484,
0.12716472148895264,
-0.04620931297540665,
-0.21964949369430542,
-0.1544356644153595,
0.12464860081672668,
-0.21436886489391327,
-0.19197627902030945,
0.3080342710018158,
0.28208714723587036,
-0.1583673059940338,
-0.3537829518318176,
0.09401586651802063,
-0.01276421919465065,
0.02619149163365364,
-0.1580010950565338,
0.21723711490631104,
-0.166529580950737,
-0.2780844271183014,
-0.2864159643650055,
0.13615699112415314,
-0.1222032904624939,
-0.09216521680355072,
-0.04126402735710144,
0.42542994022369385,
-0.03665407374501228,
0.19515199959278107,
-0.3149715065956116,
0.0895179957151413,
0.2266039401292801,
-0.26632726192474365,
-0.07168534398078918,
-0.1902872771024704,
-0.39492014050483704,
0.042231734842061996,
-0.09523066878318787,
-0.0929960310459137,
0.3783302307128906,
-0.047316424548625946,
-0.06796006858348846,
-0.2881466746330261,
-0.17254027724266052,
0.10717801749706268,
-0.09261122345924377,
-0.15536727011203766,
0.16724826395511627,
-0.03133828938007355,
-0.10115892440080643,
-0.29874566197395325,
0.2937973141670227,
-0.30531302094459534,
-0.2991430461406708,
-0.05198727175593376,
0.09890619665384293,
0.030108986422419548,
-0.2803470194339752,
-0.4286248981952667,
0.27357742190361023,
-0.31724435091018677,
0.07546759396791458,
-0.14892880618572235,
0.18622717261314392,
0.33093392848968506,
0.008953814394772053,
-0.014561107382178307,
-0.06404063105583191,
0.16439421474933624,
-0.4674096703529358,
-0.14095471799373627,
0.32257843017578125,
0.01876021921634674,
-0.21630443632602692,
-0.3245909512042999,
-0.2757244110107422,
0.34772399067878723,
0.19238810241222382,
-0.5803955793380737,
-0.21442262828350067,
-0.048900216817855835,
0.2480318248271942,
-0.05125897377729416,
-0.04649518430233002,
0.5745418071746826,
0.01972545124590397,
-0.17946316301822662,
-0.16727802157402039,
-0.33183929324150085,
0.35973066091537476,
0.4192623794078827,
0.24948757886886597,
-0.011158477514982224,
0.17781516909599304,
0.20092011988162994,
0.6707470417022705,
0.2019203156232834,
-0.2590579092502594,
0.33173102140426636,
0.10723146051168442,
0.07499773055315018,
-0.2034967839717865,
-0.3130229413509369,
0.18576018512248993,
-0.18160304427146912,
0.01973230391740799,
0.27198368310928345,
0.006250595673918724,
-0.2801837921142578,
0.017742767930030823,
0.21881836652755737,
-0.2253446877002716,
-0.328058123588562,
0.2597455084323883,
-0.3424280285835266,
0.24094843864440918,
0.036369793117046356,
0.3157997131347656,
-0.5820137858390808,
-0.24272391200065613,
0.19462794065475464,
-0.3359457850456238,
0.27984461188316345,
0.04449816048145294,
-0.5836011171340942,
0.12147033214569092,
-0.5380215048789978,
0.18194156885147095,
0.31462806463241577,
0.27240774035453796,
-0.09202472865581512,
-0.2465253472328186,
0.043347518891096115,
-0.14713148772716522,
0.5711420178413391,
0.04097308963537216,
0.40857934951782227,
0.16992636024951935,
-0.13024693727493286,
-0.19947344064712524,
-0.22471317648887634,
0.017234940081834793,
0.28013670444488525,
0.3265002369880676,
0.400847464799881,
-0.345244437456131,
-0.3632737100124359,
-0.2657657265663147,
0.007363845594227314,
-0.046181585639715195,
0.007106936536729336,
-0.12583458423614502,
0.18938523530960083,
0.01648571901023388,
0.17434579133987427,
-0.014980330131947994,
0.11830316483974457,
0.016039708629250526,
-0.13654674589633942,
-0.03913415968418121,
-0.21942690014839172,
0.12824007868766785,
0.22643797099590302,
0.4735948443412781,
0.1503245085477829,
0.03246166184544563,
0.033214349299669266,
0.21515773236751556,
-0.5671082735061646,
0.2659573554992676,
-0.08884961903095245,
-0.004131801426410675,
0.07464389503002167,
0.14443765580654144,
-0.030300907790660858,
0.3378967344760895,
-0.04252535104751587,
0.1457139402627945,
-0.12862969934940338,
0.008957155048847198,
-0.5539682507514954,
0.4854547381401062,
0.3874596357345581,
0.13246718049049377,
-0.044888898730278015,
-0.24685737490653992,
0.17346280813217163,
0.07412064075469971,
-0.27653080224990845,
0.13225962221622467,
-0.43069255352020264,
-0.4319950044155121,
0.18579739332199097,
0.2094864398241043,
0.9232466220855713,
0.33202219009399414,
0.37195777893066406,
0.10070358961820602,
0.10358034074306488,
0.26425158977508545,
-0.23411162197589874,
0.40924984216690063,
-0.3693644404411316,
-0.0463179312646389,
0.024538787081837654,
-0.16673341393470764,
-0.22738268971443176,
-0.010426290333271027,
-0.010993778705596924,
0.30259543657302856,
0.32404959201812744,
0.5999362468719482,
-0.11212000250816345,
0.16670005023479462,
0.215691938996315,
-0.15810950100421906,
-0.24923086166381836,
0.20107315480709076,
-0.2923040986061096,
0.31524065136909485,
-0.11240848153829575,
-0.07410834729671478,
-0.01650886982679367,
-0.35134220123291016,
0.06714004278182983,
0.0609416738152504,
-0.3365170359611511,
0.3048418164253235,
0.13346192240715027,
-0.27266669273376465,
-0.29698777198791504,
0.2550782561302185,
0.11198711395263672,
0.08252803981304169,
-0.048599302768707275,
-0.035185206681489944,
0.4006449580192566,
0.35045796632766724,
-0.006891845725476742,
-0.20158877968788147,
0.18641246855258942,
0.06387515366077423,
-0.012894652783870697,
0.030242733657360077,
-0.05640551447868347,
-0.3015826344490051,
-0.2525118589401245,
0.14820465445518494,
0.0033729001879692078,
-0.4129619598388672,
-0.055318914353847504,
0.06144453212618828,
-0.0667886808514595,
-0.09413722157478333,
0.15088041126728058,
-0.026068218052387238,
-0.10794125497341156,
0.3151545822620392,
0.11733834445476532,
-0.24304209649562836,
0.05235828459262848,
0.47483235597610474,
-0.04039648920297623,
0.031818099319934845,
0.4154282510280609,
-0.15281841158866882,
-0.10380619764328003,
-0.25539109110832214,
-0.28417226672172546,
-0.10206017643213272,
-0.44884029030799866,
0.11220822483301163,
-0.2194056510925293,
-0.40191107988357544,
0.04423205554485321,
0.2808186709880829,
0.014706198126077652,
0.3184961974620819,
-0.011618245393037796,
-0.12495805323123932,
-0.3769727349281311,
-0.10379086434841156,
-0.10658213496208191,
0.26717838644981384,
0.27951928973197937,
0.2843479812145233,
-0.29586678743362427,
0.2492268979549408,
-0.38310953974723816,
-0.10714222490787506,
-0.1871705949306488,
0.4379130005836487,
-0.0391375795006752,
-0.36558276414871216,
-0.009147514589130878,
0.0018548620864748955,
0.12997101247310638,
0.17754510045051575,
-0.6386584639549255,
-0.29261907935142517,
-0.09099219739437103,
0.08186075091362,
-0.007588040083646774,
-0.1598217487335205,
-0.23928231000900269,
-0.01721424236893654,
0.18238495290279388,
-0.427402526140213,
0.09215688705444336,
0.15121665596961975,
0.04703199863433838,
0.23718711733818054,
-0.1610298752784729,
0.1214555948972702,
0.28816717863082886,
-0.18652743101119995,
-0.1841491460800171,
-0.07622881233692169,
0.08048095554113388,
0.25701695680618286,
-0.06946776062250137,
0.020479001104831696,
-0.2104034423828125,
0.030471812933683395,
0.08927443623542786,
0.14279493689537048,
0.23692923784255981,
-0.024752572178840637,
-0.21566128730773926,
0.0005505271255970001,
0.18279926478862762,
0.11411947757005692,
-0.07855326682329178,
-0.32897576689720154,
0.2802233397960663,
0.2783650755882263,
-0.11751837283372879,
-0.0102371945977211,
0.1677074134349823,
-0.09938855469226837,
0.25285133719444275,
0.20715340971946716,
0.10758769512176514,
0.05261163413524628,
0.26961183547973633,
0.12649410963058472,
0.40504008531570435,
-0.34832900762557983,
0.08942112326622009,
0.06441552191972733,
0.10164903104305267,
0.03777839243412018,
0.38121557235717773,
-0.1532439887523651,
0.08992154896259308,
0.14838308095932007,
0.18833690881729126,
0.20253999531269073,
0.26289018988609314,
0.21354106068611145,
-0.1878642439842224,
-0.03412104770541191,
-0.24108661711215973,
0.1436368077993393,
-0.14272664487361908,
0.4156598448753357,
0.15059244632720947,
0.19285538792610168,
-0.11485158652067184,
-0.4619392156600952,
-0.2462674379348755,
0.23536445200443268,
-0.3245418667793274,
-0.30920952558517456,
-0.04867886006832123,
-0.08018464595079422,
0.05592931807041168,
0.19456081092357635,
-0.07928960025310516,
0.2038593888282776,
0.3428382873535156,
-0.00865977257490158,
-0.013750068843364716,
-0.08435389399528503,
-0.170617014169693,
0.11397916823625565,
0.2748645842075348,
-0.08173888921737671,
0.446936696767807,
0.010800972580909729,
-0.051569364964962006,
-0.2344720959663391,
0.4114176034927368,
0.2861287593841553,
0.19494742155075073,
-0.1688622683286667,
0.06395319104194641,
0.20064730942249298,
0.03061327524483204,
-0.35468870401382446,
0.3286513686180115,
0.15114429593086243,
-0.2930281460285187,
0.3680053651332855,
0.12379556894302368,
-0.23215582966804504,
0.2764035165309906,
-0.1041957288980484,
-0.20146708190441132,
-0.049888961017131805,
0.3224371671676636,
0.09970720112323761,
-0.03993305563926697,
-0.1949632167816162,
0.1111203134059906,
-0.1445714384317398,
-0.28533875942230225,
0.15934628248214722,
-0.023898672312498093,
0.4676608443260193,
-0.2756762206554413,
0.11720523238182068,
-0.06182504817843437,
0.6220859885215759,
-0.02922816202044487,
0.12432920932769775,
-0.35013818740844727,
0.10264356434345245,
-0.3331668972969055,
0.198409765958786,
-0.08381709456443787,
0.15374305844306946,
-0.39758387207984924,
0.20426522195339203,
-0.11549905687570572,
-0.02346649393439293,
-0.11804220080375671,
-0.007886471226811409,
0.14740730822086334,
0.17893224954605103,
-0.3869178295135498,
0.1554817110300064,
-0.08625976741313934,
-0.006267093122005463,
0.29177382588386536,
-0.37667521834373474,
0.22199100255966187,
0.042478568851947784,
0.20691052079200745,
0.010985862463712692,
-0.02172362059354782,
-0.054806359112262726,
0.33657363057136536,
0.6232408881187439,
0.34702926874160767,
0.14255046844482422,
-0.10102763026952744,
0.08155438303947449,
-0.3474372923374176,
0.014104174450039864,
-0.06088797375559807,
-0.20964977145195007,
0.09756873548030853,
0.5258306264877319,
-0.22562795877456665,
0.13194617629051208,
-0.178046315908432,
0.23669393360614777,
0.3822764754295349,
-0.1527290940284729,
0.0618000254034996,
0.04822578281164169,
-0.2598402798175812,
-0.005199543200433254,
-0.12586651742458344,
0.45379629731178284,
0.007182497531175613,
0.32383060455322266,
-0.3592911958694458,
-0.5417625904083252,
0.43290984630584717,
-0.45112577080726624,
-0.30252525210380554,
0.12327728420495987,
0.23878571391105652,
0.34956857562065125,
-0.06000012159347534,
-0.5436676144599915,
-0.17249035835266113,
0.2691141963005066,
-0.030661150813102722,
-0.1570448875427246,
0.20768548548221588,
-0.14864324033260345,
-0.04107460752129555,
-0.1167544275522232,
0.17646947503089905,
0.10152687877416611,
-0.2914122939109802,
0.24369880557060242,
-0.3701038360595703
] |