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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007809 / 0.011353 (-0.003544) | 0.004573 / 0.011008 (-0.006435) | 0.101201 / 0.038508 (0.062693) | 0.089703 / 0.023109 (0.066594) | 0.416502 / 0.275898 (0.140604) | 0.463352 / 0.323480 (0.139872) | 0.006101 / 0.007986 (-0.001885) | 0.003783 / 0.004328 (-0.000545) | 0.076531 / 0.004250 (0.072281) | 0.064017 / 0.037052 (0.026964) | 0.422453 / 0.258489 (0.163964) | 0.485926 / 0.293841 (0.192085) | 0.036797 / 0.128546 (-0.091749) | 0.010172 / 0.075646 (-0.065474) | 0.344442 / 0.419271 (-0.074829) | 0.062240 / 0.043533 (0.018707) | 0.422685 / 0.255139 (0.167546) | 0.451457 / 0.283200 (0.168257) | 0.027831 / 0.141683 (-0.113852) | 1.737187 / 1.452155 (0.285033) | 1.847631 / 1.492716 (0.354915) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.270336 / 0.018006 (0.252330) | 0.500540 / 0.000490 (0.500050) | 0.017042 / 0.000200 (0.016842) | 0.000704 / 0.000054 (0.000650) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033450 / 0.037411 (-0.003962) | 0.100314 / 0.014526 (0.085788) | 0.117216 / 0.176557 (-0.059340) | 0.182352 / 0.737135 (-0.554784) | 0.114903 / 0.296338 (-0.181436) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.458562 / 0.215209 (0.243353) | 4.570492 / 2.077655 (2.492837) | 2.230286 / 1.504120 (0.726167) | 2.032229 / 1.541195 (0.491034) | 2.130431 / 1.468490 (0.661941) | 0.563254 / 4.584777 (-4.021523) | 4.108455 / 3.745712 (0.362743) | 3.994059 / 5.269862 (-1.275802) | 2.424589 / 4.565676 (-2.141087) | 0.067534 / 0.424275 (-0.356741) | 0.008774 / 0.007607 (0.001167) | 0.546356 / 0.226044 (0.320312) | 5.527772 / 2.268929 (3.258843) | 2.934410 / 55.444624 (-52.510215) | 2.536871 / 6.876477 (-4.339605) | 2.598704 / 2.142072 (0.456632) | 0.676721 / 4.805227 (-4.128506) | 0.155904 / 6.500664 (-6.344760) | 0.073274 / 0.075469 (-0.002195) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.559170 / 1.841788 (-0.282618) | 23.228524 / 8.074308 (15.154216) | 16.743246 / 10.191392 (6.551854) | 0.184113 / 0.680424 (-0.496310) | 0.021804 / 0.534201 (-0.512397) | 0.466158 / 0.579283 (-0.113125) | 0.539911 / 0.434364 (0.105547) | 0.544377 / 0.540337 (0.004040) | 0.765779 / 1.386936 (-0.621157) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008249 / 0.011353 (-0.003104) | 0.004734 / 0.011008 (-0.006275) | 0.077083 / 0.038508 (0.038575) | 0.096959 / 0.023109 (0.073850) | 0.497501 / 0.275898 (0.221603) | 0.530687 / 0.323480 (0.207207) | 0.006379 / 0.007986 (-0.001607) | 0.003899 / 0.004328 (-0.000430) | 0.076165 / 0.004250 (0.071915) | 0.069406 / 0.037052 (0.032354) | 0.515847 / 0.258489 (0.257358) | 0.540639 / 0.293841 (0.246798) | 0.038334 / 0.128546 (-0.090213) | 0.010112 / 0.075646 (-0.065534) | 0.084918 / 0.419271 (-0.334353) | 0.056866 / 0.043533 (0.013333) | 0.495555 / 0.255139 (0.240416) | 0.518988 / 0.283200 (0.235789) | 0.028556 / 0.141683 (-0.113127) | 1.799320 / 1.452155 (0.347165) | 1.874647 / 1.492716 (0.381931) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.264283 / 0.018006 (0.246277) | 0.510278 / 0.000490 (0.509788) | 0.015219 / 0.000200 (0.015019) | 0.000160 / 0.000054 (0.000105) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038462 / 0.037411 (0.001051) | 0.115420 / 0.014526 (0.100894) | 0.124250 / 0.176557 (-0.052306) | 0.187724 / 0.737135 (-0.549411) | 0.126674 / 0.296338 (-0.169664) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.499345 / 0.215209 (0.284136) | 4.983924 / 2.077655 (2.906269) | 2.705099 / 1.504120 (1.200980) | 2.516344 / 1.541195 (0.975149) | 2.621103 / 1.468490 (1.152613) | 0.583254 / 4.584777 (-4.001523) | 4.231215 / 3.745712 (0.485503) | 4.028326 / 5.269862 (-1.241536) | 2.459171 / 4.565676 (-2.106505) | 0.069194 / 0.424275 (-0.355081) | 0.008850 / 0.007607 (0.001243) | 0.593878 / 0.226044 (0.367834) | 5.926478 / 2.268929 (3.657549) | 3.287435 / 55.444624 (-52.157189) | 2.902104 / 6.876477 (-3.974372) | 3.151307 / 2.142072 (1.009234) | 0.696922 / 4.805227 (-4.108306) | 0.161140 / 6.500664 (-6.339524) | 0.073728 / 0.075469 (-0.001741) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.636456 / 1.841788 (-0.205331) | 23.884606 / 8.074308 (15.810298) | 17.180875 / 10.191392 (6.989483) | 0.176782 / 0.680424 (-0.503642) | 0.023731 / 0.534201 (-0.510470) | 0.475191 / 0.579283 (-0.104092) | 0.506603 / 0.434364 (0.072239) | 0.571976 / 0.540337 (0.031638) | 0.826935 / 1.386936 (-0.560002) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#2b19f6b30f49e09b0d1f0c4a38b10d76f35ac483 \"CML watermark\")\n" ]

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[ "The expression \"train+test\" concatenates the splits.\r\n\r\nThe individual splits as separate datasets can be obtained as follows:\r\n```python\r\ntrain_ds, test_ds = load_dataset(\"<dataset_name>\", split=[\"train\", \"test\"])\r\ntrain_10pct_ds, test_10pct_ds = load_dataset(\"<dataset_name>\", split=[\"train[:10%]\", \"test[:%10]\"])\r\n```" ]

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[ "Hi! Instead of processing a single example at a time, you should use the batched `map` for the best performance (with `num_proc=1`) - the fast tokenizers can process a batch's samples in parallel in that scenario.\r\n\r\nE.g., the following code in Colab takes an hour to complete:\r\n```python\r\n# !pip install datasets transformers\r\nfrom datasets import load_dataset\r\nfrom transformers import AutoTokenizer\r\ntokenizer = AutoTokenizer.from_pretrained(\"bert-base-cased\")\r\ndataset = dataset.map(lambda ex: tokenizer(ex[\"text\"]), batched=True, remove_columns=[\"text\", \"meta\"])\r\n```", "Batched is far worse. A single batch of 1000 took hours and that was only 1%\r\n\r\n\r\nOn Thu, Oct 19, 2023, 2:26 PM Mario Šaško ***@***.***> wrote:\r\n\r\n> Hi! You should use the batched map for the best performance (with\r\n> num_proc=1) - the fast tokenizers can process a batch's samples in\r\n> parallel.\r\n>\r\n> E.g., the following code in Colab takes an hour to complete:\r\n>\r\n> # !pip install datasets transformersfrom datasets import load_datasetfrom transformers import AutoTokenizertokenizer = AutoTokenizer.from_pretrained(\"bert-base-cased\")dataset = dataset.map(lambda ex: tokenizer(ex[\"text\"]), batched=True, remove_columns=[\"text\", \"meta\"])\r\n>\r\n> —\r\n> Reply to this email directly, view it on GitHub\r\n> <https://github.com/huggingface/datasets/issues/6319#issuecomment-1771503757>,\r\n> or unsubscribe\r\n> <https://github.com/notifications/unsubscribe-auth/ABDD3ZJHPSRVDEXFNMXR2N3YAFWFZAVCNFSM6AAAAAA6HDKPSCVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTONZRGUYDGNZVG4>\r\n> .\r\n> You are receiving this because you authored the thread.Message ID:\r\n> ***@***.***>\r\n>\r\n", "Can you please provide a self-contained reproducer?", "Which specific version of datasets are you using?\r\n\r\nWhat is the architecture of your colab setup? Ram? Cores? OS?\r\n\r\n\r\nOn Thu, Oct 19, 2023, 2:27 PM pensive introvert ***@***.***>\r\nwrote:\r\n\r\n> Batched is far worse. A single batch of 1000 took hours and that was only\r\n> 1%\r\n>\r\n>\r\n> On Thu, Oct 19, 2023, 2:26 PM Mario Šaško ***@***.***>\r\n> wrote:\r\n>\r\n>> Hi! You should use the batched map for the best performance (with\r\n>> num_proc=1) - the fast tokenizers can process a batch's samples in\r\n>> parallel.\r\n>>\r\n>> E.g., the following code in Colab takes an hour to complete:\r\n>>\r\n>> # !pip install datasets transformersfrom datasets import load_datasetfrom transformers import AutoTokenizertokenizer = AutoTokenizer.from_pretrained(\"bert-base-cased\")dataset = dataset.map(lambda ex: tokenizer(ex[\"text\"]), batched=True, remove_columns=[\"text\", \"meta\"])\r\n>>\r\n>> —\r\n>> Reply to this email directly, view it on GitHub\r\n>> <https://github.com/huggingface/datasets/issues/6319#issuecomment-1771503757>,\r\n>> or unsubscribe\r\n>> <https://github.com/notifications/unsubscribe-auth/ABDD3ZJHPSRVDEXFNMXR2N3YAFWFZAVCNFSM6AAAAAA6HDKPSCVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTONZRGUYDGNZVG4>\r\n>> .\r\n>> You are receiving this because you authored the thread.Message ID:\r\n>> ***@***.***>\r\n>>\r\n>\r\n", "from functools import partial\r\nimport transformers\r\nfrom datasets import load_dataset, concatenate_datasets, load_from_disk\r\n\r\nmodel_name_or_path=\"/opt/data/data/daryl149/llama-2-7b-chat-hf\"\r\noutput_dir=\"/opt/data/data/LongLoRA/checkpoints\"\r\ncache_dir=\"/opt/data/data/LongLoRA/cache\"\r\nmodel_max_length=16384\r\n\r\nIGNORE_INDEX = -100\r\nDEFAULT_PAD_TOKEN = \"[PAD]\"\r\nDEFAULT_EOS_TOKEN = \"</s>\"\r\nDEFAULT_BOS_TOKEN = \"<s>\"\r\nDEFAULT_UNK_TOKEN = \"<unk>\"\r\n\r\n\r\ntokenizer = transformers.LlamaTokenizerFast.from_pretrained(\r\n model_name_or_path,\r\n cache_dir=cache_dir,\r\n model_max_length=model_max_length,\r\n padding_side=\"right\",\r\n use_fast=True,\r\n #use_fast=False\r\n)\r\n\r\nspecial_tokens_dict = dict()\r\nif tokenizer.pad_token is None:\r\n special_tokens_dict[\"pad_token\"] = DEFAULT_PAD_TOKEN\r\nif tokenizer.eos_token is None:\r\n special_tokens_dict[\"eos_token\"] = DEFAULT_EOS_TOKEN\r\nif tokenizer.bos_token is None:\r\n special_tokens_dict[\"bos_token\"] = DEFAULT_BOS_TOKEN\r\nif tokenizer.unk_token is None:\r\n special_tokens_dict[\"unk_token\"] = DEFAULT_UNK_TOKEN\r\n\r\ntokenizer.add_special_tokens(special_tokens_dict)\r\n\r\ndef tokenize_fn(tokenizer, example):\r\n context_length = tokenizer.model_max_length\r\n outputs = tokenizer(\r\n tokenizer.eos_token.join(example[\"text\"]),\r\n #truncation=False,\r\n truncation=True,\r\n return_tensors=\"pt\",\r\n #return_tensors=\"np\",\r\n pad_to_multiple_of=context_length,\r\n padding=True,\r\n )\r\n return {\"input_ids\": outputs[\"input_ids\"].view(-1, context_length)}\r\n\r\nfor idx in range(100):\r\n dataset = load_dataset(\"togethercomputer/RedPajama-Data-1T-Sample\",\r\ncache_dir=cache_dir, split=f'train[{idx}%:{idx+1}%]')\r\n dataset = dataset.map(partial(tokenize_fn, tokenizer), batched=False,\r\nnum_proc=16, remove_columns=[\"text\", \"meta\"])\r\n dataset.save_to_disk(training_args.cache_dir + f\"/training_data_{idx}\")\r\n\r\n\r\nOn Thu, Oct 19, 2023 at 2:30 PM Mario Šaško ***@***.***>\r\nwrote:\r\n\r\n> Can you please provide a self-contained reproducer?\r\n>\r\n> —\r\n> Reply to this email directly, view it on GitHub\r\n> <https://github.com/huggingface/datasets/issues/6319#issuecomment-1771509229>,\r\n> or unsubscribe\r\n> <https://github.com/notifications/unsubscribe-auth/ABDD3ZNBZ3BE7Q4EQZZK6MLYAFWURAVCNFSM6AAAAAA6HDKPSCVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTONZRGUYDSMRSHE>\r\n> .\r\n> You are receiving this because you authored the thread.Message ID:\r\n> ***@***.***>\r\n>\r\n", "I changed the tokenizer to one without \"Fast suffix, and something changed.\r\nThe fraction, although still slowed a lot at 80% was able to get over the\r\nfinish line of 100%\r\n\r\nI have to do more testng, see if the whole set can be processed\r\n\r\n\r\n\r\nOn Thu, Oct 19, 2023 at 3:03 PM pensive introvert <\r\n***@***.***> wrote:\r\n\r\n> from functools import partial\r\n> import transformers\r\n> from datasets import load_dataset, concatenate_datasets, load_from_disk\r\n>\r\n> model_name_or_path=\"/opt/data/data/daryl149/llama-2-7b-chat-hf\"\r\n> output_dir=\"/opt/data/data/LongLoRA/checkpoints\"\r\n> cache_dir=\"/opt/data/data/LongLoRA/cache\"\r\n> model_max_length=16384\r\n>\r\n> IGNORE_INDEX = -100\r\n> DEFAULT_PAD_TOKEN = \"[PAD]\"\r\n> DEFAULT_EOS_TOKEN = \"</s>\"\r\n> DEFAULT_BOS_TOKEN = \"<s>\"\r\n> DEFAULT_UNK_TOKEN = \"<unk>\"\r\n>\r\n>\r\n> tokenizer = transformers.LlamaTokenizerFast.from_pretrained(\r\n> model_name_or_path,\r\n> cache_dir=cache_dir,\r\n> model_max_length=model_max_length,\r\n> padding_side=\"right\",\r\n> use_fast=True,\r\n> #use_fast=False\r\n> )\r\n>\r\n> special_tokens_dict = dict()\r\n> if tokenizer.pad_token is None:\r\n> special_tokens_dict[\"pad_token\"] = DEFAULT_PAD_TOKEN\r\n> if tokenizer.eos_token is None:\r\n> special_tokens_dict[\"eos_token\"] = DEFAULT_EOS_TOKEN\r\n> if tokenizer.bos_token is None:\r\n> special_tokens_dict[\"bos_token\"] = DEFAULT_BOS_TOKEN\r\n> if tokenizer.unk_token is None:\r\n> special_tokens_dict[\"unk_token\"] = DEFAULT_UNK_TOKEN\r\n>\r\n> tokenizer.add_special_tokens(special_tokens_dict)\r\n>\r\n> def tokenize_fn(tokenizer, example):\r\n> context_length = tokenizer.model_max_length\r\n> outputs = tokenizer(\r\n> tokenizer.eos_token.join(example[\"text\"]),\r\n> #truncation=False,\r\n> truncation=True,\r\n> return_tensors=\"pt\",\r\n> #return_tensors=\"np\",\r\n> pad_to_multiple_of=context_length,\r\n> padding=True,\r\n> )\r\n> return {\"input_ids\": outputs[\"input_ids\"].view(-1, context_length)}\r\n>\r\n> for idx in range(100):\r\n> dataset = load_dataset(\"togethercomputer/RedPajama-Data-1T-Sample\",\r\n> cache_dir=cache_dir, split=f'train[{idx}%:{idx+1}%]')\r\n> dataset = dataset.map(partial(tokenize_fn, tokenizer), batched=False,\r\n> num_proc=16, remove_columns=[\"text\", \"meta\"])\r\n> dataset.save_to_disk(training_args.cache_dir + f\"/training_data_{idx}\")\r\n>\r\n>\r\n> On Thu, Oct 19, 2023 at 2:30 PM Mario Šaško ***@***.***>\r\n> wrote:\r\n>\r\n>> Can you please provide a self-contained reproducer?\r\n>>\r\n>> —\r\n>> Reply to this email directly, view it on GitHub\r\n>> <https://github.com/huggingface/datasets/issues/6319#issuecomment-1771509229>,\r\n>> or unsubscribe\r\n>> <https://github.com/notifications/unsubscribe-auth/ABDD3ZNBZ3BE7Q4EQZZK6MLYAFWURAVCNFSM6AAAAAA6HDKPSCVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTONZRGUYDSMRSHE>\r\n>> .\r\n>> You are receiving this because you authored the thread.Message ID:\r\n>> ***@***.***>\r\n>>\r\n>\r\n", "So, using LlamaTokenizerFast was the problem. Changing it to LlamaTokenizer\r\nfixed things,\r\n\r\nOn Thu, Oct 19, 2023 at 4:04 PM pensive introvert <\r\n***@***.***> wrote:\r\n\r\n> I changed the tokenizer to one without \"Fast suffix, and something\r\n> changed. The fraction, although still slowed a lot at 80% was able to get\r\n> over the finish line of 100%\r\n>\r\n> I have to do more testng, see if the whole set can be processed\r\n>\r\n>\r\n>\r\n> On Thu, Oct 19, 2023 at 3:03 PM pensive introvert <\r\n> ***@***.***> wrote:\r\n>\r\n>> from functools import partial\r\n>> import transformers\r\n>> from datasets import load_dataset, concatenate_datasets, load_from_disk\r\n>>\r\n>> model_name_or_path=\"/opt/data/data/daryl149/llama-2-7b-chat-hf\"\r\n>> output_dir=\"/opt/data/data/LongLoRA/checkpoints\"\r\n>> cache_dir=\"/opt/data/data/LongLoRA/cache\"\r\n>> model_max_length=16384\r\n>>\r\n>> IGNORE_INDEX = -100\r\n>> DEFAULT_PAD_TOKEN = \"[PAD]\"\r\n>> DEFAULT_EOS_TOKEN = \"</s>\"\r\n>> DEFAULT_BOS_TOKEN = \"<s>\"\r\n>> DEFAULT_UNK_TOKEN = \"<unk>\"\r\n>>\r\n>>\r\n>> tokenizer = transformers.LlamaTokenizerFast.from_pretrained(\r\n>> model_name_or_path,\r\n>> cache_dir=cache_dir,\r\n>> model_max_length=model_max_length,\r\n>> padding_side=\"right\",\r\n>> use_fast=True,\r\n>> #use_fast=False\r\n>> )\r\n>>\r\n>> special_tokens_dict = dict()\r\n>> if tokenizer.pad_token is None:\r\n>> special_tokens_dict[\"pad_token\"] = DEFAULT_PAD_TOKEN\r\n>> if tokenizer.eos_token is None:\r\n>> special_tokens_dict[\"eos_token\"] = DEFAULT_EOS_TOKEN\r\n>> if tokenizer.bos_token is None:\r\n>> special_tokens_dict[\"bos_token\"] = DEFAULT_BOS_TOKEN\r\n>> if tokenizer.unk_token is None:\r\n>> special_tokens_dict[\"unk_token\"] = DEFAULT_UNK_TOKEN\r\n>>\r\n>> tokenizer.add_special_tokens(special_tokens_dict)\r\n>>\r\n>> def tokenize_fn(tokenizer, example):\r\n>> context_length = tokenizer.model_max_length\r\n>> outputs = tokenizer(\r\n>> tokenizer.eos_token.join(example[\"text\"]),\r\n>> #truncation=False,\r\n>> truncation=True,\r\n>> return_tensors=\"pt\",\r\n>> #return_tensors=\"np\",\r\n>> pad_to_multiple_of=context_length,\r\n>> padding=True,\r\n>> )\r\n>> return {\"input_ids\": outputs[\"input_ids\"].view(-1, context_length)}\r\n>>\r\n>> for idx in range(100):\r\n>> dataset = load_dataset(\"togethercomputer/RedPajama-Data-1T-Sample\",\r\n>> cache_dir=cache_dir, split=f'train[{idx}%:{idx+1}%]')\r\n>> dataset = dataset.map(partial(tokenize_fn, tokenizer), batched=False,\r\n>> num_proc=16, remove_columns=[\"text\", \"meta\"])\r\n>> dataset.save_to_disk(training_args.cache_dir +\r\n>> f\"/training_data_{idx}\")\r\n>>\r\n>>\r\n>> On Thu, Oct 19, 2023 at 2:30 PM Mario Šaško ***@***.***>\r\n>> wrote:\r\n>>\r\n>>> Can you please provide a self-contained reproducer?\r\n>>>\r\n>>> —\r\n>>> Reply to this email directly, view it on GitHub\r\n>>> <https://github.com/huggingface/datasets/issues/6319#issuecomment-1771509229>,\r\n>>> or unsubscribe\r\n>>> <https://github.com/notifications/unsubscribe-auth/ABDD3ZNBZ3BE7Q4EQZZK6MLYAFWURAVCNFSM6AAAAAA6HDKPSCVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTONZRGUYDSMRSHE>\r\n>>> .\r\n>>> You are receiving this because you authored the thread.Message ID:\r\n>>> ***@***.***>\r\n>>>\r\n>>\r\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006827 / 0.011353 (-0.004526) | 0.004468 / 0.011008 (-0.006540) | 0.088687 / 0.038508 (0.050179) | 0.072560 / 0.023109 (0.049451) | 0.333421 / 0.275898 (0.057523) | 0.374977 / 0.323480 (0.051497) | 0.005829 / 0.007986 (-0.002156) | 0.003284 / 0.004328 (-0.001045) | 0.068929 / 0.004250 (0.064678) | 0.057212 / 0.037052 (0.020160) | 0.328911 / 0.258489 (0.070422) | 0.389107 / 0.293841 (0.095266) | 0.033518 / 0.128546 (-0.095029) | 0.009919 / 0.075646 (-0.065728) | 0.308100 / 0.419271 (-0.111171) | 0.059380 / 0.043533 (0.015847) | 0.345587 / 0.255139 (0.090448) | 0.353703 / 0.283200 (0.070503) | 0.026454 / 0.141683 (-0.115229) | 1.573309 / 1.452155 (0.121155) | 1.663812 / 1.492716 (0.171095) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.255081 / 0.018006 (0.237075) | 0.472613 / 0.000490 (0.472123) | 0.016120 / 0.000200 (0.015920) | 0.000383 / 0.000054 (0.000328) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028219 / 0.037411 (-0.009192) | 0.086600 / 0.014526 (0.072074) | 0.099484 / 0.176557 (-0.077073) | 0.154604 / 0.737135 (-0.582531) | 0.099168 / 0.296338 (-0.197171) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.421703 / 0.215209 (0.206494) | 4.188600 / 2.077655 (2.110945) | 2.037575 / 1.504120 (0.533456) | 1.843389 / 1.541195 (0.302194) | 1.912554 / 1.468490 (0.444064) | 0.517452 / 4.584777 (-4.067325) | 3.838002 / 3.745712 (0.092290) | 3.698899 / 5.269862 (-1.570963) | 2.175393 / 4.565676 (-2.390283) | 0.066059 / 0.424275 (-0.358216) | 0.008455 / 0.007607 (0.000848) | 0.506813 / 0.226044 (0.280768) | 4.826994 / 2.268929 (2.558066) | 2.544437 / 55.444624 (-52.900187) | 2.164938 / 6.876477 (-4.711539) | 2.171725 / 2.142072 (0.029652) | 0.603757 / 4.805227 (-4.201470) | 0.149113 / 6.500664 (-6.351551) | 0.065093 / 0.075469 (-0.010376) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.366887 / 1.841788 (-0.474901) | 20.508089 / 8.074308 (12.433780) | 14.836531 / 10.191392 (4.645139) | 0.167418 / 0.680424 (-0.513006) | 0.019707 / 0.534201 (-0.514494) | 0.409897 / 0.579283 (-0.169387) | 0.439412 / 0.434364 (0.005048) | 0.495784 / 0.540337 (-0.044553) | 0.685367 / 1.386936 (-0.701569) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007604 / 0.011353 (-0.003749) | 0.004368 / 0.011008 (-0.006640) | 0.072628 / 0.038508 (0.034120) | 0.084187 / 0.023109 (0.061077) | 0.461396 / 0.275898 (0.185498) | 0.481429 / 0.323480 (0.157949) | 0.005894 / 0.007986 (-0.002092) | 0.003472 / 0.004328 (-0.000857) | 0.068717 / 0.004250 (0.064466) | 0.061066 / 0.037052 (0.024014) | 0.464217 / 0.258489 (0.205728) | 0.498061 / 0.293841 (0.204220) | 0.035458 / 0.128546 (-0.093089) | 0.009474 / 0.075646 (-0.066173) | 0.079633 / 0.419271 (-0.339639) | 0.053966 / 0.043533 (0.010433) | 0.454911 / 0.255139 (0.199772) | 0.470837 / 0.283200 (0.187637) | 0.026358 / 0.141683 (-0.115325) | 1.665131 / 1.452155 (0.212976) | 1.730365 / 1.492716 (0.237648) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.234810 / 0.018006 (0.216804) | 0.453672 / 0.000490 (0.453183) | 0.004620 / 0.000200 (0.004420) | 0.000119 / 0.000054 (0.000064) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035310 / 0.037411 (-0.002101) | 0.100379 / 0.014526 (0.085853) | 0.118802 / 0.176557 (-0.057754) | 0.173853 / 0.737135 (-0.563282) | 0.115714 / 0.296338 (-0.180624) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.466797 / 0.215209 (0.251588) | 4.698324 / 2.077655 (2.620670) | 2.446897 / 1.504120 (0.942777) | 2.277346 / 1.541195 (0.736151) | 2.347211 / 1.468490 (0.878721) | 0.514377 / 4.584777 (-4.070400) | 3.931269 / 3.745712 (0.185557) | 3.573575 / 5.269862 (-1.696286) | 2.208122 / 4.565676 (-2.357554) | 0.061081 / 0.424275 (-0.363194) | 0.007803 / 0.007607 (0.000196) | 0.544376 / 0.226044 (0.318332) | 5.440003 / 2.268929 (3.171074) | 3.012559 / 55.444624 (-52.432065) | 2.617286 / 6.876477 (-4.259191) | 2.863978 / 2.142072 (0.721906) | 0.610024 / 4.805227 (-4.195203) | 0.133643 / 6.500664 (-6.367021) | 0.064766 / 0.075469 (-0.010703) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.465225 / 1.841788 (-0.376563) | 21.308351 / 8.074308 (13.234043) | 15.176634 / 10.191392 (4.985242) | 0.172701 / 0.680424 (-0.507723) | 0.020345 / 0.534201 (-0.513855) | 0.433923 / 0.579283 (-0.145360) | 0.450183 / 0.434364 (0.015819) | 0.514048 / 0.540337 (-0.026289) | 0.736302 / 1.386936 (-0.650634) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7f1a7d621fff3b08ace02643466097654a5e010f \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008305 / 0.011353 (-0.003048) | 0.006007 / 0.011008 (-0.005001) | 0.103521 / 0.038508 (0.065013) | 0.075776 / 0.023109 (0.052666) | 0.378888 / 0.275898 (0.102990) | 0.405245 / 0.323480 (0.081765) | 0.004596 / 0.007986 (-0.003390) | 0.003687 / 0.004328 (-0.000641) | 0.079043 / 0.004250 (0.074792) | 0.055895 / 0.037052 (0.018843) | 0.406565 / 0.258489 (0.148076) | 0.433869 / 0.293841 (0.140028) | 0.045321 / 0.128546 (-0.083226) | 0.014317 / 0.075646 (-0.061329) | 0.345312 / 0.419271 (-0.073960) | 0.064485 / 0.043533 (0.020953) | 0.381744 / 0.255139 (0.126605) | 0.401162 / 0.283200 (0.117962) | 0.035973 / 0.141683 (-0.105709) | 1.829616 / 1.452155 (0.377461) | 1.868487 / 1.492716 (0.375771) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.245432 / 0.018006 (0.227426) | 0.494249 / 0.000490 (0.493759) | 0.010878 / 0.000200 (0.010678) | 0.000492 / 0.000054 (0.000437) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032778 / 0.037411 (-0.004633) | 0.103418 / 0.014526 (0.088892) | 0.108010 / 0.176557 (-0.068547) | 0.176477 / 0.737135 (-0.560658) | 0.107732 / 0.296338 (-0.188606) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.572471 / 0.215209 (0.357262) | 5.647039 / 2.077655 (3.569384) | 2.385069 / 1.504120 (0.880949) | 2.048928 / 1.541195 (0.507733) | 2.108538 / 1.468490 (0.640048) | 0.861436 / 4.584777 (-3.723341) | 4.933452 / 3.745712 (1.187739) | 4.735219 / 5.269862 (-0.534642) | 2.926971 / 4.565676 (-1.638705) | 0.097687 / 0.424275 (-0.326588) | 0.008346 / 0.007607 (0.000739) | 0.677754 / 0.226044 (0.451709) | 6.798433 / 2.268929 (4.529504) | 3.129862 / 55.444624 (-52.314762) | 2.454033 / 6.876477 (-4.422444) | 2.464590 / 2.142072 (0.322517) | 1.034497 / 4.805227 (-3.770730) | 0.205753 / 6.500664 (-6.294911) | 0.076618 / 0.075469 (0.001149) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.617569 / 1.841788 (-0.224219) | 22.091489 / 8.074308 (14.017181) | 20.406312 / 10.191392 (10.214920) | 0.222012 / 0.680424 (-0.458411) | 0.027787 / 0.534201 (-0.506414) | 0.441669 / 0.579283 (-0.137615) | 0.564773 / 0.434364 (0.130409) | 0.510389 / 0.540337 (-0.029948) | 0.753672 / 1.386936 (-0.633264) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011107 / 0.011353 (-0.000246) | 0.004973 / 0.011008 (-0.006035) | 0.078331 / 0.038508 (0.039823) | 0.083964 / 0.023109 (0.060855) | 0.518980 / 0.275898 (0.243082) | 0.528264 / 0.323480 (0.204784) | 0.007452 / 0.007986 (-0.000534) | 0.003931 / 0.004328 (-0.000397) | 0.079724 / 0.004250 (0.075474) | 0.061739 / 0.037052 (0.024686) | 0.517804 / 0.258489 (0.259315) | 0.582764 / 0.293841 (0.288923) | 0.049674 / 0.128546 (-0.078873) | 0.014540 / 0.075646 (-0.061106) | 0.093130 / 0.419271 (-0.326141) | 0.060647 / 0.043533 (0.017114) | 0.492628 / 0.255139 (0.237489) | 0.549761 / 0.283200 (0.266562) | 0.034313 / 0.141683 (-0.107369) | 1.824574 / 1.452155 (0.372419) | 2.013664 / 1.492716 (0.520947) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.231335 / 0.018006 (0.213329) | 0.521477 / 0.000490 (0.520987) | 0.011314 / 0.000200 (0.011114) | 0.000397 / 0.000054 (0.000343) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033303 / 0.037411 (-0.004108) | 0.098238 / 0.014526 (0.083712) | 0.119527 / 0.176557 (-0.057030) | 0.169163 / 0.737135 (-0.567972) | 0.114536 / 0.296338 (-0.181803) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.578401 / 0.215209 (0.363191) | 5.966438 / 2.077655 (3.888783) | 2.646370 / 1.504120 (1.142250) | 2.361833 / 1.541195 (0.820638) | 2.476573 / 1.468490 (1.008083) | 0.777411 / 4.584777 (-3.807366) | 4.811070 / 3.745712 (1.065357) | 4.314221 / 5.269862 (-0.955641) | 2.743317 / 4.565676 (-1.822359) | 0.110394 / 0.424275 (-0.313881) | 0.008333 / 0.007607 (0.000726) | 0.729588 / 0.226044 (0.503543) | 7.743226 / 2.268929 (5.474298) | 3.606294 / 55.444624 (-51.838330) | 2.838069 / 6.876477 (-4.038408) | 3.087494 / 2.142072 (0.945421) | 1.053341 / 4.805227 (-3.751886) | 0.205105 / 6.500664 (-6.295559) | 0.075204 / 0.075469 (-0.000265) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.561959 / 1.841788 (-0.279829) | 21.407849 / 8.074308 (13.333541) | 19.084263 / 10.191392 (8.892871) | 0.226129 / 0.680424 (-0.454295) | 0.029695 / 0.534201 (-0.504506) | 0.427035 / 0.579283 (-0.152248) | 0.565353 / 0.434364 (0.130989) | 0.526789 / 0.540337 (-0.013548) | 0.734820 / 1.386936 (-0.652116) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5b52536f4e39df3b98f7e0b03ee71b24c4fff49a \"CML watermark\")\n" ]

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[ "Thanks for reporting. We are investigating the issue.", "We have opened an issue in the corresponding Hub dataset: https://huggingface.co/datasets/sentiment140/discussions/3\r\n\r\nLet's continue the discussion there." ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008896 / 0.011353 (-0.002456) | 0.005811 / 0.011008 (-0.005197) | 0.108582 / 0.038508 (0.070074) | 0.096509 / 0.023109 (0.073399) | 0.481725 / 0.275898 (0.205827) | 0.534743 / 0.323480 (0.211263) | 0.005517 / 0.007986 (-0.002468) | 0.006479 / 0.004328 (0.002151) | 0.081313 / 0.004250 (0.077062) | 0.063578 / 0.037052 (0.026525) | 0.493977 / 0.258489 (0.235488) | 0.551897 / 0.293841 (0.258056) | 0.051835 / 0.128546 (-0.076711) | 0.014105 / 0.075646 (-0.061541) | 0.385866 / 0.419271 (-0.033405) | 0.069131 / 0.043533 (0.025598) | 0.484780 / 0.255139 (0.229641) | 0.493221 / 0.283200 (0.210021) | 0.039560 / 0.141683 (-0.102123) | 1.782331 / 1.452155 (0.330176) | 1.899193 / 1.492716 (0.406477) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.329978 / 0.018006 (0.311972) | 0.600839 / 0.000490 (0.600349) | 0.013187 / 0.000200 (0.012987) | 0.000499 / 0.000054 (0.000444) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031835 / 0.037411 (-0.005576) | 0.103740 / 0.014526 (0.089214) | 0.115875 / 0.176557 (-0.060681) | 0.189880 / 0.737135 (-0.547255) | 0.132614 / 0.296338 (-0.163725) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.596255 / 0.215209 (0.381046) | 5.967993 / 2.077655 (3.890339) | 2.612675 / 1.504120 (1.108555) | 2.251461 / 1.541195 (0.710266) | 2.308585 / 1.468490 (0.840095) | 0.816516 / 4.584777 (-3.768261) | 5.241791 / 3.745712 (1.496079) | 4.680745 / 5.269862 (-0.589117) | 2.997370 / 4.565676 (-1.568307) | 0.098632 / 0.424275 (-0.325643) | 0.010912 / 0.007607 (0.003305) | 0.659092 / 0.226044 (0.433047) | 6.825562 / 2.268929 (4.556634) | 3.323844 / 55.444624 (-52.120780) | 2.796203 / 6.876477 (-4.080274) | 2.946994 / 2.142072 (0.804922) | 1.002814 / 4.805227 (-3.802413) | 0.202613 / 6.500664 (-6.298051) | 0.072011 / 0.075469 (-0.003459) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.613873 / 1.841788 (-0.227914) | 24.500990 / 8.074308 (16.426682) | 21.941599 / 10.191392 (11.750207) | 0.214450 / 0.680424 (-0.465974) | 0.031227 / 0.534201 (-0.502974) | 0.498297 / 0.579283 (-0.080986) | 0.597460 / 0.434364 (0.163096) | 0.558152 / 0.540337 (0.017815) | 0.789693 / 1.386936 (-0.597243) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011299 / 0.011353 (-0.000053) | 0.005103 / 0.011008 (-0.005905) | 0.083161 / 0.038508 (0.044653) | 0.094201 / 0.023109 (0.071092) | 0.560457 / 0.275898 (0.284559) | 0.590459 / 0.323480 (0.266980) | 0.007059 / 0.007986 (-0.000926) | 0.004418 / 0.004328 (0.000090) | 0.081343 / 0.004250 (0.077093) | 0.067069 / 0.037052 (0.030016) | 0.538137 / 0.258489 (0.279648) | 0.600416 / 0.293841 (0.306575) | 0.049046 / 0.128546 (-0.079500) | 0.014299 / 0.075646 (-0.061347) | 0.093631 / 0.419271 (-0.325641) | 0.062536 / 0.043533 (0.019003) | 0.557238 / 0.255139 (0.302099) | 0.571050 / 0.283200 (0.287850) | 0.035881 / 0.141683 (-0.105802) | 1.918487 / 1.452155 (0.466332) | 2.013979 / 1.492716 (0.521263) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.400995 / 0.018006 (0.382989) | 0.634898 / 0.000490 (0.634408) | 0.041809 / 0.000200 (0.041609) | 0.000279 / 0.000054 (0.000224) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034160 / 0.037411 (-0.003251) | 0.109996 / 0.014526 (0.095470) | 0.124335 / 0.176557 (-0.052222) | 0.188100 / 0.737135 (-0.549035) | 0.135897 / 0.296338 (-0.160442) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.639751 / 0.215209 (0.424542) | 6.403312 / 2.077655 (4.325657) | 3.146453 / 1.504120 (1.642333) | 2.840358 / 1.541195 (1.299164) | 2.908667 / 1.468490 (1.440177) | 0.818767 / 4.584777 (-3.766010) | 5.416939 / 3.745712 (1.671227) | 4.853498 / 5.269862 (-0.416364) | 3.023526 / 4.565676 (-1.542150) | 0.110850 / 0.424275 (-0.313425) | 0.013103 / 0.007607 (0.005496) | 0.799720 / 0.226044 (0.573676) | 7.837704 / 2.268929 (5.568775) | 4.016526 / 55.444624 (-51.428099) | 3.338965 / 6.876477 (-3.537512) | 3.715721 / 2.142072 (1.573648) | 1.088340 / 4.805227 (-3.716887) | 0.213610 / 6.500664 (-6.287054) | 0.079244 / 0.075469 (0.003775) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.833175 / 1.841788 (-0.008612) | 25.307218 / 8.074308 (17.232910) | 23.716075 / 10.191392 (13.524683) | 0.259114 / 0.680424 (-0.421310) | 0.035171 / 0.534201 (-0.499029) | 0.530128 / 0.579283 (-0.049155) | 0.651484 / 0.434364 (0.217120) | 0.589414 / 0.540337 (0.049077) | 0.862691 / 1.386936 (-0.524245) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1bdfba93b8a739b9d885b8fb1909d47ff689bbc2 \"CML watermark\")\n", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6316). All of your documentation changes will be reflected on that endpoint." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6313). All of your documentation changes will be reflected on that endpoint." ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006209 / 0.011353 (-0.005144) | 0.003708 / 0.011008 (-0.007300) | 0.080435 / 0.038508 (0.041926) | 0.060105 / 0.023109 (0.036995) | 0.392962 / 0.275898 (0.117064) | 0.429381 / 0.323480 (0.105902) | 0.003596 / 0.007986 (-0.004390) | 0.003849 / 0.004328 (-0.000480) | 0.062377 / 0.004250 (0.058127) | 0.048718 / 0.037052 (0.011666) | 0.400906 / 0.258489 (0.142417) | 0.440335 / 0.293841 (0.146494) | 0.027807 / 0.128546 (-0.100739) | 0.008066 / 0.075646 (-0.067580) | 0.262542 / 0.419271 (-0.156730) | 0.045513 / 0.043533 (0.001980) | 0.399608 / 0.255139 (0.144469) | 0.418007 / 0.283200 (0.134807) | 0.023475 / 0.141683 (-0.118208) | 1.476563 / 1.452155 (0.024409) | 1.528898 / 1.492716 (0.036182) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223798 / 0.018006 (0.205792) | 0.430526 / 0.000490 (0.430036) | 0.009232 / 0.000200 (0.009032) | 0.000082 / 0.000054 (0.000028) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024921 / 0.037411 (-0.012490) | 0.077692 / 0.014526 (0.063166) | 0.085382 / 0.176557 (-0.091174) | 0.146220 / 0.737135 (-0.590915) | 0.086396 / 0.296338 (-0.209943) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.439986 / 0.215209 (0.224777) | 4.384552 / 2.077655 (2.306897) | 2.373697 / 1.504120 (0.869577) | 2.176138 / 1.541195 (0.634943) | 2.225914 / 1.468490 (0.757424) | 0.505776 / 4.584777 (-4.079001) | 3.053744 / 3.745712 (-0.691968) | 3.080443 / 5.269862 (-2.189419) | 1.904392 / 4.565676 (-2.661285) | 0.058112 / 0.424275 (-0.366163) | 0.006631 / 0.007607 (-0.000976) | 0.503409 / 0.226044 (0.277365) | 5.053375 / 2.268929 (2.784447) | 2.789963 / 55.444624 (-52.654661) | 2.452659 / 6.876477 (-4.423818) | 2.512353 / 2.142072 (0.370280) | 0.590095 / 4.805227 (-4.215132) | 0.126267 / 6.500664 (-6.374397) | 0.061246 / 0.075469 (-0.014223) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.249884 / 1.841788 (-0.591903) | 17.684730 / 8.074308 (9.610422) | 13.967467 / 10.191392 (3.776075) | 0.144202 / 0.680424 (-0.536222) | 0.017004 / 0.534201 (-0.517197) | 0.333634 / 0.579283 (-0.245649) | 0.387251 / 0.434364 (-0.047113) | 0.390189 / 0.540337 (-0.150148) | 0.535662 / 1.386936 (-0.851274) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006379 / 0.011353 (-0.004974) | 0.003681 / 0.011008 (-0.007327) | 0.063005 / 0.038508 (0.024497) | 0.064221 / 0.023109 (0.041112) | 0.446074 / 0.275898 (0.170176) | 0.471997 / 0.323480 (0.148517) | 0.005074 / 0.007986 (-0.002911) | 0.002945 / 0.004328 (-0.001383) | 0.063305 / 0.004250 (0.059054) | 0.050608 / 0.037052 (0.013556) | 0.443260 / 0.258489 (0.184771) | 0.478497 / 0.293841 (0.184656) | 0.028980 / 0.128546 (-0.099566) | 0.008145 / 0.075646 (-0.067502) | 0.068412 / 0.419271 (-0.350859) | 0.041552 / 0.043533 (-0.001980) | 0.436649 / 0.255139 (0.181510) | 0.462397 / 0.283200 (0.179198) | 0.019929 / 0.141683 (-0.121753) | 1.530248 / 1.452155 (0.078093) | 1.611117 / 1.492716 (0.118401) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.232894 / 0.018006 (0.214888) | 0.421451 / 0.000490 (0.420961) | 0.003984 / 0.000200 (0.003784) | 0.000084 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027776 / 0.037411 (-0.009635) | 0.081632 / 0.014526 (0.067106) | 0.094031 / 0.176557 (-0.082526) | 0.147930 / 0.737135 (-0.589206) | 0.094226 / 0.296338 (-0.202112) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.471722 / 0.215209 (0.256513) | 4.713241 / 2.077655 (2.635587) | 2.662660 / 1.504120 (1.158540) | 2.490778 / 1.541195 (0.949583) | 2.555786 / 1.468490 (1.087296) | 0.512209 / 4.584777 (-4.072568) | 3.210612 / 3.745712 (-0.535100) | 2.863346 / 5.269862 (-2.406516) | 1.884664 / 4.565676 (-2.681012) | 0.058514 / 0.424275 (-0.365761) | 0.006473 / 0.007607 (-0.001134) | 0.543279 / 0.226044 (0.317235) | 5.441485 / 2.268929 (3.172556) | 3.145398 / 55.444624 (-52.299226) | 2.749603 / 6.876477 (-4.126874) | 2.925738 / 2.142072 (0.783666) | 0.598725 / 4.805227 (-4.206502) | 0.125616 / 6.500664 (-6.375048) | 0.061314 / 0.075469 (-0.014155) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.384270 / 1.841788 (-0.457518) | 18.307618 / 8.074308 (10.233310) | 14.635768 / 10.191392 (4.444376) | 0.148787 / 0.680424 (-0.531637) | 0.018191 / 0.534201 (-0.516010) | 0.333166 / 0.579283 (-0.246117) | 0.405116 / 0.434364 (-0.029247) | 0.392798 / 0.540337 (-0.147540) | 0.582299 / 1.386936 (-0.804637) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7004f0f2ec59832fe53af033efdca10d00377760 \"CML watermark\")\n" ]

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[ "Thanks for reporting! We've spotted the bugs with the `array.values` handling and are fixing them in https://github.com/huggingface/datasets/pull/6283 (should be part of the next release)." ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006461 / 0.011353 (-0.004891) | 0.004035 / 0.011008 (-0.006973) | 0.085037 / 0.038508 (0.046529) | 0.072434 / 0.023109 (0.049325) | 0.308565 / 0.275898 (0.032667) | 0.330455 / 0.323480 (0.006975) | 0.003782 / 0.007986 (-0.004204) | 0.004363 / 0.004328 (0.000034) | 0.065242 / 0.004250 (0.060991) | 0.056111 / 0.037052 (0.019058) | 0.318008 / 0.258489 (0.059519) | 0.357904 / 0.293841 (0.064063) | 0.030702 / 0.128546 (-0.097844) | 0.008741 / 0.075646 (-0.066905) | 0.287666 / 0.419271 (-0.131605) | 0.052281 / 0.043533 (0.008748) | 0.306894 / 0.255139 (0.051755) | 0.335739 / 0.283200 (0.052540) | 0.023712 / 0.141683 (-0.117971) | 1.492304 / 1.452155 (0.040149) | 1.544540 / 1.492716 (0.051823) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.299419 / 0.018006 (0.281413) | 0.547195 / 0.000490 (0.546705) | 0.011571 / 0.000200 (0.011371) | 0.000223 / 0.000054 (0.000168) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028364 / 0.037411 (-0.009048) | 0.081445 / 0.014526 (0.066919) | 0.626670 / 0.176557 (0.450114) | 0.159964 / 0.737135 (-0.577171) | 0.100528 / 0.296338 (-0.195811) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.409915 / 0.215209 (0.194705) | 4.108689 / 2.077655 (2.031034) | 2.046247 / 1.504120 (0.542127) | 1.851081 / 1.541195 (0.309887) | 1.857857 / 1.468490 (0.389367) | 0.493246 / 4.584777 (-4.091531) | 3.581557 / 3.745712 (-0.164155) | 3.456708 / 5.269862 (-1.813153) | 2.051054 / 4.565676 (-2.514623) | 0.057553 / 0.424275 (-0.366722) | 0.007287 / 0.007607 (-0.000320) | 0.493094 / 0.226044 (0.267050) | 4.873051 / 2.268929 (2.604122) | 2.515266 / 55.444624 (-52.929358) | 2.144743 / 6.876477 (-4.731733) | 2.159412 / 2.142072 (0.017340) | 0.595627 / 4.805227 (-4.209601) | 0.133773 / 6.500664 (-6.366891) | 0.059965 / 0.075469 (-0.015504) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.259625 / 1.841788 (-0.582163) | 19.030742 / 8.074308 (10.956434) | 14.039246 / 10.191392 (3.847854) | 0.168116 / 0.680424 (-0.512308) | 0.018168 / 0.534201 (-0.516033) | 0.391187 / 0.579283 (-0.188096) | 0.420901 / 0.434364 (-0.013463) | 0.465827 / 0.540337 (-0.074511) | 0.718373 / 1.386936 (-0.668563) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006616 / 0.011353 (-0.004737) | 0.004048 / 0.011008 (-0.006960) | 0.064568 / 0.038508 (0.026060) | 0.075933 / 0.023109 (0.052824) | 0.396353 / 0.275898 (0.120455) | 0.424159 / 0.323480 (0.100679) | 0.005446 / 0.007986 (-0.002540) | 0.003393 / 0.004328 (-0.000935) | 0.064673 / 0.004250 (0.060422) | 0.056983 / 0.037052 (0.019930) | 0.402478 / 0.258489 (0.143989) | 0.433240 / 0.293841 (0.139399) | 0.032100 / 0.128546 (-0.096446) | 0.008664 / 0.075646 (-0.066983) | 0.070502 / 0.419271 (-0.348770) | 0.047800 / 0.043533 (0.004267) | 0.399506 / 0.255139 (0.144367) | 0.418376 / 0.283200 (0.135176) | 0.022654 / 0.141683 (-0.119029) | 1.487280 / 1.452155 (0.035125) | 1.543733 / 1.492716 (0.051017) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.317660 / 0.018006 (0.299654) | 0.523922 / 0.000490 (0.523432) | 0.007086 / 0.000200 (0.006886) | 0.000109 / 0.000054 (0.000055) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032381 / 0.037411 (-0.005030) | 0.091636 / 0.014526 (0.077110) | 0.104743 / 0.176557 (-0.071814) | 0.158793 / 0.737135 (-0.578342) | 0.103164 / 0.296338 (-0.193175) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434081 / 0.215209 (0.218872) | 4.329448 / 2.077655 (2.251794) | 2.335855 / 1.504120 (0.831735) | 2.177513 / 1.541195 (0.636319) | 2.205406 / 1.468490 (0.736916) | 0.500117 / 4.584777 (-4.084660) | 3.693715 / 3.745712 (-0.051997) | 3.305803 / 5.269862 (-1.964059) | 2.048283 / 4.565676 (-2.517394) | 0.058301 / 0.424275 (-0.365974) | 0.007196 / 0.007607 (-0.000411) | 0.512917 / 0.226044 (0.286873) | 5.129283 / 2.268929 (2.860355) | 2.836200 / 55.444624 (-52.608425) | 2.499022 / 6.876477 (-4.377455) | 2.652305 / 2.142072 (0.510232) | 0.604219 / 4.805227 (-4.201008) | 0.137310 / 6.500664 (-6.363354) | 0.060880 / 0.075469 (-0.014589) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.346948 / 1.841788 (-0.494839) | 19.499516 / 8.074308 (11.425208) | 14.701500 / 10.191392 (4.510108) | 0.168626 / 0.680424 (-0.511798) | 0.020002 / 0.534201 (-0.514199) | 0.394729 / 0.579283 (-0.184554) | 0.428323 / 0.434364 (-0.006040) | 0.481202 / 0.540337 (-0.059136) | 0.684768 / 1.386936 (-0.702169) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#fed9c07458afc73870e8ec9846bf1fc5cac0b378 \"CML watermark\")\n", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6309). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007033 / 0.011353 (-0.004320) | 0.004411 / 0.011008 (-0.006597) | 0.086146 / 0.038508 (0.047638) | 0.086669 / 0.023109 (0.063560) | 0.329145 / 0.275898 (0.053247) | 0.348728 / 0.323480 (0.025248) | 0.004404 / 0.007986 (-0.003582) | 0.003656 / 0.004328 (-0.000673) | 0.066120 / 0.004250 (0.061869) | 0.059157 / 0.037052 (0.022105) | 0.316537 / 0.258489 (0.058048) | 0.369065 / 0.293841 (0.075224) | 0.031921 / 0.128546 (-0.096625) | 0.008877 / 0.075646 (-0.066770) | 0.290068 / 0.419271 (-0.129204) | 0.054007 / 0.043533 (0.010475) | 0.308823 / 0.255139 (0.053684) | 0.331189 / 0.283200 (0.047989) | 0.027313 / 0.141683 (-0.114370) | 1.486772 / 1.452155 (0.034617) | 1.570359 / 1.492716 (0.077643) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.315991 / 0.018006 (0.297985) | 0.577876 / 0.000490 (0.577386) | 0.011207 / 0.000200 (0.011007) | 0.000089 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031753 / 0.037411 (-0.005658) | 0.089270 / 0.014526 (0.074744) | 0.102518 / 0.176557 (-0.074038) | 0.160260 / 0.737135 (-0.576875) | 0.103365 / 0.296338 (-0.192973) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.405789 / 0.215209 (0.190580) | 4.052740 / 2.077655 (1.975085) | 2.052076 / 1.504120 (0.547956) | 1.873966 / 1.541195 (0.332771) | 1.997156 / 1.468490 (0.528665) | 0.494975 / 4.584777 (-4.089802) | 3.600007 / 3.745712 (-0.145705) | 3.626459 / 5.269862 (-1.643403) | 2.176927 / 4.565676 (-2.388750) | 0.057894 / 0.424275 (-0.366381) | 0.007469 / 0.007607 (-0.000138) | 0.487422 / 0.226044 (0.261377) | 4.868744 / 2.268929 (2.599815) | 2.528707 / 55.444624 (-52.915918) | 2.149520 / 6.876477 (-4.726956) | 2.275491 / 2.142072 (0.133419) | 0.589112 / 4.805227 (-4.216115) | 0.136644 / 6.500664 (-6.364020) | 0.062144 / 0.075469 (-0.013325) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.286625 / 1.841788 (-0.555163) | 20.528128 / 8.074308 (12.453819) | 15.290866 / 10.191392 (5.099474) | 0.168380 / 0.680424 (-0.512044) | 0.018908 / 0.534201 (-0.515293) | 0.397210 / 0.579283 (-0.182073) | 0.426133 / 0.434364 (-0.008231) | 0.471754 / 0.540337 (-0.068584) | 0.653343 / 1.386936 (-0.733593) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007599 / 0.011353 (-0.003754) | 0.004499 / 0.011008 (-0.006509) | 0.066248 / 0.038508 (0.027740) | 0.097704 / 0.023109 (0.074595) | 0.414558 / 0.275898 (0.138660) | 0.451088 / 0.323480 (0.127609) | 0.005932 / 0.007986 (-0.002054) | 0.003698 / 0.004328 (-0.000630) | 0.065784 / 0.004250 (0.061534) | 0.064777 / 0.037052 (0.027725) | 0.443318 / 0.258489 (0.184829) | 0.456896 / 0.293841 (0.163055) | 0.033436 / 0.128546 (-0.095111) | 0.008977 / 0.075646 (-0.066669) | 0.072067 / 0.419271 (-0.347205) | 0.049571 / 0.043533 (0.006038) | 0.420325 / 0.255139 (0.165186) | 0.443588 / 0.283200 (0.160388) | 0.026723 / 0.141683 (-0.114960) | 1.512566 / 1.452155 (0.060411) | 1.647591 / 1.492716 (0.154875) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.326410 / 0.018006 (0.308404) | 0.532878 / 0.000490 (0.532388) | 0.006257 / 0.000200 (0.006057) | 0.000104 / 0.000054 (0.000049) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037289 / 0.037411 (-0.000122) | 0.104940 / 0.014526 (0.090414) | 0.113597 / 0.176557 (-0.062960) | 0.170562 / 0.737135 (-0.566573) | 0.114583 / 0.296338 (-0.181755) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.435530 / 0.215209 (0.220321) | 4.332659 / 2.077655 (2.255005) | 2.343576 / 1.504120 (0.839456) | 2.190517 / 1.541195 (0.649322) | 2.323101 / 1.468490 (0.854611) | 0.493019 / 4.584777 (-4.091758) | 3.686726 / 3.745712 (-0.058986) | 3.437143 / 5.269862 (-1.832719) | 2.167193 / 4.565676 (-2.398483) | 0.059636 / 0.424275 (-0.364639) | 0.007696 / 0.007607 (0.000089) | 0.511159 / 0.226044 (0.285115) | 5.119358 / 2.268929 (2.850429) | 2.814934 / 55.444624 (-52.629690) | 2.477871 / 6.876477 (-4.398606) | 2.774473 / 2.142072 (0.632401) | 0.590258 / 4.805227 (-4.214969) | 0.135923 / 6.500664 (-6.364741) | 0.062793 / 0.075469 (-0.012676) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350192 / 1.841788 (-0.491596) | 21.382135 / 8.074308 (13.307827) | 16.024198 / 10.191392 (5.832806) | 0.163623 / 0.680424 (-0.516801) | 0.020749 / 0.534201 (-0.513452) | 0.402578 / 0.579283 (-0.176705) | 0.436569 / 0.434364 (0.002205) | 0.477217 / 0.540337 (-0.063121) | 0.682929 / 1.386936 (-0.704007) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#fa36173f2e8c6f266efd236933eff3a95af0382c \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006671 / 0.011353 (-0.004681) | 0.004176 / 0.011008 (-0.006832) | 0.084095 / 0.038508 (0.045587) | 0.076345 / 0.023109 (0.053236) | 0.341201 / 0.275898 (0.065303) | 0.381920 / 0.323480 (0.058440) | 0.005578 / 0.007986 (-0.002408) | 0.003535 / 0.004328 (-0.000794) | 0.065227 / 0.004250 (0.060976) | 0.054983 / 0.037052 (0.017931) | 0.345938 / 0.258489 (0.087449) | 0.398708 / 0.293841 (0.104867) | 0.031029 / 0.128546 (-0.097518) | 0.008643 / 0.075646 (-0.067004) | 0.287286 / 0.419271 (-0.131985) | 0.052424 / 0.043533 (0.008892) | 0.342914 / 0.255139 (0.087775) | 0.366982 / 0.283200 (0.083782) | 0.024511 / 0.141683 (-0.117172) | 1.510575 / 1.452155 (0.058421) | 1.593214 / 1.492716 (0.100497) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.272703 / 0.018006 (0.254697) | 0.583235 / 0.000490 (0.582746) | 0.008467 / 0.000200 (0.008267) | 0.000295 / 0.000054 (0.000240) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029654 / 0.037411 (-0.007757) | 0.085078 / 0.014526 (0.070552) | 0.106391 / 0.176557 (-0.070165) | 0.155790 / 0.737135 (-0.581345) | 0.104835 / 0.296338 (-0.191503) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.408584 / 0.215209 (0.193375) | 4.082557 / 2.077655 (2.004902) | 2.054001 / 1.504120 (0.549881) | 1.868470 / 1.541195 (0.327275) | 1.950600 / 1.468490 (0.482110) | 0.492572 / 4.584777 (-4.092205) | 3.497105 / 3.745712 (-0.248607) | 3.464596 / 5.269862 (-1.805265) | 2.106399 / 4.565676 (-2.459278) | 0.057413 / 0.424275 (-0.366862) | 0.007449 / 0.007607 (-0.000158) | 0.482900 / 0.226044 (0.256856) | 4.844152 / 2.268929 (2.575223) | 2.499930 / 55.444624 (-52.944695) | 2.180396 / 6.876477 (-4.696081) | 2.282830 / 2.142072 (0.140758) | 0.581371 / 4.805227 (-4.223857) | 0.134641 / 6.500664 (-6.366023) | 0.063137 / 0.075469 (-0.012332) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.274291 / 1.841788 (-0.567496) | 19.426189 / 8.074308 (11.351881) | 14.292833 / 10.191392 (4.101441) | 0.166321 / 0.680424 (-0.514102) | 0.018419 / 0.534201 (-0.515782) | 0.392433 / 0.579283 (-0.186850) | 0.415128 / 0.434364 (-0.019236) | 0.459274 / 0.540337 (-0.081063) | 0.714668 / 1.386936 (-0.672268) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006740 / 0.011353 (-0.004613) | 0.004283 / 0.011008 (-0.006725) | 0.063845 / 0.038508 (0.025337) | 0.077037 / 0.023109 (0.053927) | 0.425103 / 0.275898 (0.149205) | 0.445525 / 0.323480 (0.122046) | 0.005755 / 0.007986 (-0.002230) | 0.003589 / 0.004328 (-0.000739) | 0.064515 / 0.004250 (0.060265) | 0.057398 / 0.037052 (0.020346) | 0.424781 / 0.258489 (0.166292) | 0.452162 / 0.293841 (0.158321) | 0.032164 / 0.128546 (-0.096382) | 0.008660 / 0.075646 (-0.066986) | 0.069873 / 0.419271 (-0.349399) | 0.048100 / 0.043533 (0.004567) | 0.409097 / 0.255139 (0.153958) | 0.441533 / 0.283200 (0.158333) | 0.024122 / 0.141683 (-0.117560) | 1.503431 / 1.452155 (0.051277) | 1.577518 / 1.492716 (0.084802) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.264433 / 0.018006 (0.246426) | 0.553631 / 0.000490 (0.553141) | 0.006354 / 0.000200 (0.006154) | 0.000106 / 0.000054 (0.000051) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033259 / 0.037411 (-0.004152) | 0.094908 / 0.014526 (0.080382) | 0.108238 / 0.176557 (-0.068318) | 0.161354 / 0.737135 (-0.575781) | 0.109073 / 0.296338 (-0.187265) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434450 / 0.215209 (0.219241) | 4.347501 / 2.077655 (2.269847) | 2.362225 / 1.504120 (0.858105) | 2.189285 / 1.541195 (0.648090) | 2.288797 / 1.468490 (0.820307) | 0.487782 / 4.584777 (-4.096995) | 3.598732 / 3.745712 (-0.146980) | 3.343263 / 5.269862 (-1.926599) | 2.086256 / 4.565676 (-2.479420) | 0.057838 / 0.424275 (-0.366437) | 0.007412 / 0.007607 (-0.000195) | 0.510098 / 0.226044 (0.284054) | 5.088743 / 2.268929 (2.819814) | 2.809105 / 55.444624 (-52.635519) | 2.476005 / 6.876477 (-4.400471) | 2.753785 / 2.142072 (0.611712) | 0.585045 / 4.805227 (-4.220182) | 0.131162 / 6.500664 (-6.369502) | 0.060431 / 0.075469 (-0.015038) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.342149 / 1.841788 (-0.499639) | 20.602369 / 8.074308 (12.528061) | 14.973301 / 10.191392 (4.781909) | 0.151655 / 0.680424 (-0.528769) | 0.020793 / 0.534201 (-0.513408) | 0.401657 / 0.579283 (-0.177626) | 0.419845 / 0.434364 (-0.014519) | 0.467225 / 0.540337 (-0.073113) | 0.672469 / 1.386936 (-0.714467) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#474beafbc1c2735ff4747f5675855583be2ede06 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007006 / 0.011353 (-0.004346) | 0.004282 / 0.011008 (-0.006726) | 0.085413 / 0.038508 (0.046905) | 0.085148 / 0.023109 (0.062038) | 0.336543 / 0.275898 (0.060645) | 0.367959 / 0.323480 (0.044479) | 0.004337 / 0.007986 (-0.003648) | 0.004535 / 0.004328 (0.000207) | 0.065379 / 0.004250 (0.061128) | 0.059993 / 0.037052 (0.022941) | 0.343162 / 0.258489 (0.084673) | 0.383766 / 0.293841 (0.089925) | 0.031520 / 0.128546 (-0.097026) | 0.008605 / 0.075646 (-0.067042) | 0.288620 / 0.419271 (-0.130651) | 0.053617 / 0.043533 (0.010084) | 0.339389 / 0.255139 (0.084250) | 0.350842 / 0.283200 (0.067642) | 0.027816 / 0.141683 (-0.113867) | 1.505500 / 1.452155 (0.053346) | 1.566511 / 1.492716 (0.073795) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.272203 / 0.018006 (0.254197) | 0.569729 / 0.000490 (0.569240) | 0.010061 / 0.000200 (0.009861) | 0.000328 / 0.000054 (0.000273) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030015 / 0.037411 (-0.007396) | 0.083991 / 0.014526 (0.069465) | 0.099796 / 0.176557 (-0.076761) | 0.159131 / 0.737135 (-0.578004) | 0.099102 / 0.296338 (-0.197237) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.390076 / 0.215209 (0.174867) | 3.897157 / 2.077655 (1.819502) | 1.935912 / 1.504120 (0.431793) | 1.815109 / 1.541195 (0.273915) | 1.875041 / 1.468490 (0.406551) | 0.482168 / 4.584777 (-4.102609) | 3.556140 / 3.745712 (-0.189572) | 3.528889 / 5.269862 (-1.740972) | 2.132767 / 4.565676 (-2.432909) | 0.057761 / 0.424275 (-0.366514) | 0.007353 / 0.007607 (-0.000254) | 0.464801 / 0.226044 (0.238757) | 4.637301 / 2.268929 (2.368372) | 2.362239 / 55.444624 (-53.082386) | 2.049811 / 6.876477 (-4.826665) | 2.143485 / 2.142072 (0.001412) | 0.580929 / 4.805227 (-4.224299) | 0.140252 / 6.500664 (-6.360412) | 0.061352 / 0.075469 (-0.014117) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.257487 / 1.841788 (-0.584301) | 19.453319 / 8.074308 (11.379011) | 14.276332 / 10.191392 (4.084940) | 0.166772 / 0.680424 (-0.513652) | 0.018339 / 0.534201 (-0.515862) | 0.393008 / 0.579283 (-0.186275) | 0.420960 / 0.434364 (-0.013404) | 0.464331 / 0.540337 (-0.076007) | 0.717973 / 1.386936 (-0.668963) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007255 / 0.011353 (-0.004098) | 0.004230 / 0.011008 (-0.006778) | 0.065191 / 0.038508 (0.026683) | 0.085765 / 0.023109 (0.062655) | 0.412464 / 0.275898 (0.136566) | 0.446067 / 0.323480 (0.122587) | 0.005875 / 0.007986 (-0.002110) | 0.003700 / 0.004328 (-0.000628) | 0.065430 / 0.004250 (0.061179) | 0.060284 / 0.037052 (0.023231) | 0.419984 / 0.258489 (0.161495) | 0.453779 / 0.293841 (0.159938) | 0.032595 / 0.128546 (-0.095952) | 0.008873 / 0.075646 (-0.066773) | 0.072124 / 0.419271 (-0.347148) | 0.048072 / 0.043533 (0.004539) | 0.408725 / 0.255139 (0.153586) | 0.432485 / 0.283200 (0.149285) | 0.024662 / 0.141683 (-0.117021) | 1.540434 / 1.452155 (0.088279) | 1.624768 / 1.492716 (0.132051) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.253220 / 0.018006 (0.235214) | 0.555469 / 0.000490 (0.554980) | 0.007765 / 0.000200 (0.007565) | 0.000101 / 0.000054 (0.000046) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032666 / 0.037411 (-0.004745) | 0.094786 / 0.014526 (0.080260) | 0.108219 / 0.176557 (-0.068337) | 0.161546 / 0.737135 (-0.575589) | 0.109828 / 0.296338 (-0.186510) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.437024 / 0.215209 (0.221815) | 4.354065 / 2.077655 (2.276411) | 2.336832 / 1.504120 (0.832713) | 2.161959 / 1.541195 (0.620764) | 2.257214 / 1.468490 (0.788724) | 0.501576 / 4.584777 (-4.083201) | 3.654292 / 3.745712 (-0.091420) | 3.349504 / 5.269862 (-1.920357) | 2.092998 / 4.565676 (-2.472679) | 0.058740 / 0.424275 (-0.365535) | 0.007420 / 0.007607 (-0.000187) | 0.513443 / 0.226044 (0.287399) | 5.151247 / 2.268929 (2.882319) | 2.816036 / 55.444624 (-52.628589) | 2.451863 / 6.876477 (-4.424613) | 2.709908 / 2.142072 (0.567836) | 0.597834 / 4.805227 (-4.207394) | 0.136547 / 6.500664 (-6.364117) | 0.062030 / 0.075469 (-0.013439) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.371412 / 1.841788 (-0.470375) | 20.398981 / 8.074308 (12.324673) | 14.932307 / 10.191392 (4.740915) | 0.167796 / 0.680424 (-0.512628) | 0.020740 / 0.534201 (-0.513461) | 0.397162 / 0.579283 (-0.182121) | 0.435493 / 0.434364 (0.001129) | 0.477074 / 0.540337 (-0.063264) | 0.697546 / 1.386936 (-0.689390) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#017cefbc832bfe662afd87d9d1241104bf67c53e \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007388 / 0.011353 (-0.003964) | 0.004408 / 0.011008 (-0.006600) | 0.098225 / 0.038508 (0.059717) | 0.079368 / 0.023109 (0.056259) | 0.381866 / 0.275898 (0.105968) | 0.425942 / 0.323480 (0.102462) | 0.005978 / 0.007986 (-0.002007) | 0.003677 / 0.004328 (-0.000651) | 0.075488 / 0.004250 (0.071238) | 0.061725 / 0.037052 (0.024672) | 0.389126 / 0.258489 (0.130637) | 0.444099 / 0.293841 (0.150258) | 0.036222 / 0.128546 (-0.092324) | 0.009926 / 0.075646 (-0.065720) | 0.336632 / 0.419271 (-0.082640) | 0.060867 / 0.043533 (0.017335) | 0.385437 / 0.255139 (0.130298) | 0.416599 / 0.283200 (0.133399) | 0.025118 / 0.141683 (-0.116565) | 1.728073 / 1.452155 (0.275919) | 1.847750 / 1.492716 (0.355033) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.263774 / 0.018006 (0.245768) | 0.491242 / 0.000490 (0.490752) | 0.013621 / 0.000200 (0.013421) | 0.000333 / 0.000054 (0.000279) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032911 / 0.037411 (-0.004500) | 0.095738 / 0.014526 (0.081212) | 0.110482 / 0.176557 (-0.066075) | 0.175533 / 0.737135 (-0.561603) | 0.109240 / 0.296338 (-0.187098) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.453967 / 0.215209 (0.238758) | 4.489384 / 2.077655 (2.411730) | 2.185496 / 1.504120 (0.681376) | 1.979126 / 1.541195 (0.437931) | 2.016364 / 1.468490 (0.547874) | 0.565539 / 4.584777 (-4.019238) | 4.106561 / 3.745712 (0.360849) | 3.906402 / 5.269862 (-1.363460) | 2.342186 / 4.565676 (-2.223491) | 0.067815 / 0.424275 (-0.356460) | 0.008663 / 0.007607 (0.001056) | 0.543841 / 0.226044 (0.317796) | 5.433491 / 2.268929 (3.164563) | 2.785723 / 55.444624 (-52.658901) | 2.355716 / 6.876477 (-4.520760) | 2.397563 / 2.142072 (0.255491) | 0.682587 / 4.805227 (-4.122641) | 0.156548 / 6.500664 (-6.344116) | 0.070654 / 0.075469 (-0.004815) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.475183 / 1.841788 (-0.366605) | 21.353030 / 8.074308 (13.278722) | 15.938324 / 10.191392 (5.746932) | 0.167010 / 0.680424 (-0.513413) | 0.020931 / 0.534201 (-0.513270) | 0.464376 / 0.579283 (-0.114907) | 0.472546 / 0.434364 (0.038182) | 0.544645 / 0.540337 (0.004308) | 0.752940 / 1.386936 (-0.633996) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007359 / 0.011353 (-0.003994) | 0.004276 / 0.011008 (-0.006732) | 0.075345 / 0.038508 (0.036837) | 0.080105 / 0.023109 (0.056995) | 0.480456 / 0.275898 (0.204558) | 0.514974 / 0.323480 (0.191494) | 0.006087 / 0.007986 (-0.001899) | 0.003717 / 0.004328 (-0.000611) | 0.075067 / 0.004250 (0.070816) | 0.063739 / 0.037052 (0.026686) | 0.487569 / 0.258489 (0.229080) | 0.530198 / 0.293841 (0.236357) | 0.036056 / 0.128546 (-0.092491) | 0.009606 / 0.075646 (-0.066041) | 0.082343 / 0.419271 (-0.336929) | 0.055488 / 0.043533 (0.011956) | 0.484789 / 0.255139 (0.229650) | 0.501918 / 0.283200 (0.218718) | 0.025340 / 0.141683 (-0.116342) | 1.784417 / 1.452155 (0.332262) | 1.854202 / 1.492716 (0.361486) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.252476 / 0.018006 (0.234470) | 0.484967 / 0.000490 (0.484478) | 0.005471 / 0.000200 (0.005271) | 0.000111 / 0.000054 (0.000057) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037084 / 0.037411 (-0.000327) | 0.106648 / 0.014526 (0.092122) | 0.123393 / 0.176557 (-0.053164) | 0.183088 / 0.737135 (-0.554047) | 0.122572 / 0.296338 (-0.173767) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.516003 / 0.215209 (0.300793) | 5.107748 / 2.077655 (3.030093) | 2.778044 / 1.504120 (1.273924) | 2.589944 / 1.541195 (1.048749) | 2.649921 / 1.468490 (1.181431) | 0.572783 / 4.584777 (-4.011994) | 4.211331 / 3.745712 (0.465619) | 3.738859 / 5.269862 (-1.531003) | 2.331628 / 4.565676 (-2.234048) | 0.067347 / 0.424275 (-0.356928) | 0.008513 / 0.007607 (0.000905) | 0.601056 / 0.226044 (0.375012) | 5.990921 / 2.268929 (3.721992) | 3.311544 / 55.444624 (-52.133081) | 2.929850 / 6.876477 (-3.946627) | 3.118741 / 2.142072 (0.976669) | 0.685975 / 4.805227 (-4.119253) | 0.155105 / 6.500664 (-6.345559) | 0.069629 / 0.075469 (-0.005840) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.602367 / 1.841788 (-0.239421) | 22.577072 / 8.074308 (14.502764) | 17.049655 / 10.191392 (6.858263) | 0.182412 / 0.680424 (-0.498011) | 0.023137 / 0.534201 (-0.511064) | 0.466988 / 0.579283 (-0.112295) | 0.483887 / 0.434364 (0.049523) | 0.556099 / 0.540337 (0.015761) | 0.798332 / 1.386936 (-0.588604) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3e6d8318bd73a91852c22d14f1d788ac6dc8ae90 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009086 / 0.011353 (-0.002267) | 0.004755 / 0.011008 (-0.006253) | 0.128866 / 0.038508 (0.090358) | 0.086099 / 0.023109 (0.062990) | 0.378079 / 0.275898 (0.102181) | 0.487431 / 0.323480 (0.163951) | 0.004712 / 0.007986 (-0.003274) | 0.003622 / 0.004328 (-0.000706) | 0.081214 / 0.004250 (0.076963) | 0.057226 / 0.037052 (0.020174) | 0.407655 / 0.258489 (0.149166) | 0.448630 / 0.293841 (0.154789) | 0.049051 / 0.128546 (-0.079495) | 0.014537 / 0.075646 (-0.061110) | 0.467343 / 0.419271 (0.048071) | 0.070482 / 0.043533 (0.026949) | 0.379664 / 0.255139 (0.124525) | 0.464181 / 0.283200 (0.180981) | 0.039973 / 0.141683 (-0.101710) | 1.731164 / 1.452155 (0.279010) | 1.886895 / 1.492716 (0.394178) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.251327 / 0.018006 (0.233321) | 0.502670 / 0.000490 (0.502180) | 0.012183 / 0.000200 (0.011984) | 0.000111 / 0.000054 (0.000057) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028892 / 0.037411 (-0.008519) | 0.093789 / 0.014526 (0.079263) | 0.104255 / 0.176557 (-0.072301) | 0.170257 / 0.737135 (-0.566879) | 0.115430 / 0.296338 (-0.180909) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.573745 / 0.215209 (0.358536) | 5.873732 / 2.077655 (3.796077) | 2.485188 / 1.504120 (0.981068) | 2.018476 / 1.541195 (0.477282) | 2.062765 / 1.468490 (0.594275) | 0.913816 / 4.584777 (-3.670961) | 5.362338 / 3.745712 (1.616626) | 4.698758 / 5.269862 (-0.571103) | 3.132973 / 4.565676 (-1.432703) | 0.093594 / 0.424275 (-0.330681) | 0.008359 / 0.007607 (0.000751) | 0.693997 / 0.226044 (0.467953) | 7.042645 / 2.268929 (4.773717) | 3.196180 / 55.444624 (-52.248445) | 2.384585 / 6.876477 (-4.491892) | 2.301256 / 2.142072 (0.159183) | 1.048025 / 4.805227 (-3.757202) | 0.206931 / 6.500664 (-6.293733) | 0.069401 / 0.075469 (-0.006068) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.598898 / 1.841788 (-0.242889) | 22.963667 / 8.074308 (14.889359) | 20.373688 / 10.191392 (10.182296) | 0.239716 / 0.680424 (-0.440707) | 0.040213 / 0.534201 (-0.493988) | 0.503268 / 0.579283 (-0.076015) | 0.630750 / 0.434364 (0.196386) | 0.578007 / 0.540337 (0.037669) | 0.789564 / 1.386936 (-0.597372) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009129 / 0.011353 (-0.002224) | 0.005453 / 0.011008 (-0.005555) | 0.101040 / 0.038508 (0.062532) | 0.099172 / 0.023109 (0.076062) | 0.508453 / 0.275898 (0.232555) | 0.570858 / 0.323480 (0.247378) | 0.006584 / 0.007986 (-0.001401) | 0.003800 / 0.004328 (-0.000528) | 0.094349 / 0.004250 (0.090098) | 0.064642 / 0.037052 (0.027590) | 0.563008 / 0.258489 (0.304518) | 0.625560 / 0.293841 (0.331719) | 0.050121 / 0.128546 (-0.078426) | 0.014183 / 0.075646 (-0.061463) | 0.106564 / 0.419271 (-0.312707) | 0.061030 / 0.043533 (0.017498) | 0.522311 / 0.255139 (0.267172) | 0.598356 / 0.283200 (0.315156) | 0.042008 / 0.141683 (-0.099675) | 1.879999 / 1.452155 (0.427844) | 1.963879 / 1.492716 (0.471162) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.270573 / 0.018006 (0.252567) | 0.554356 / 0.000490 (0.553866) | 0.008145 / 0.000200 (0.007945) | 0.000218 / 0.000054 (0.000163) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031089 / 0.037411 (-0.006322) | 0.099568 / 0.014526 (0.085043) | 0.118304 / 0.176557 (-0.058253) | 0.182991 / 0.737135 (-0.554144) | 0.115874 / 0.296338 (-0.180465) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.615020 / 0.215209 (0.399811) | 6.279740 / 2.077655 (4.202085) | 2.882094 / 1.504120 (1.377974) | 2.559265 / 1.541195 (1.018070) | 2.639259 / 1.468490 (1.170769) | 0.903727 / 4.584777 (-3.681050) | 5.248555 / 3.745712 (1.502843) | 4.817340 / 5.269862 (-0.452522) | 3.056880 / 4.565676 (-1.508797) | 0.096602 / 0.424275 (-0.327673) | 0.008660 / 0.007607 (0.001053) | 0.794347 / 0.226044 (0.568303) | 7.625127 / 2.268929 (5.356198) | 3.766826 / 55.444624 (-51.677798) | 2.968254 / 6.876477 (-3.908223) | 3.260595 / 2.142072 (1.118523) | 1.066228 / 4.805227 (-3.739000) | 0.207158 / 6.500664 (-6.293506) | 0.076920 / 0.075469 (0.001451) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.741442 / 1.841788 (-0.100345) | 23.499552 / 8.074308 (15.425244) | 22.064966 / 10.191392 (11.873574) | 0.239173 / 0.680424 (-0.441251) | 0.032105 / 0.534201 (-0.502096) | 0.484709 / 0.579283 (-0.094574) | 0.583632 / 0.434364 (0.149268) | 0.569018 / 0.540337 (0.028681) | 0.815764 / 1.386936 (-0.571172) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3aeb078ba1afd713e901df43343c160877403d07 \"CML watermark\")\n" ]

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[ "This (Windows) issue was fixed in `fsspec` in https://github.com/fsspec/filesystem_spec/pull/1275. So, to avoid the error, update the `fsspec` installation with `pip install -U fsspec`.", "> This (Windows) issue was fixed in `fsspec` in [fsspec/filesystem_spec#1275](https://github.com/fsspec/filesystem_spec/pull/1275). So, to avoid the error, update the `fsspec` installation with `pip install -U fsspec`.\r\n\r\nafter I run `pip install -U fsspec`\r\n\r\nit occurs a new error:\r\n```\r\nERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflict\r\ns.\r\ndatasets 2.14.5 requires fsspec[http]<2023.9.0,>=2023.1.0, but you have fsspec 2023.9.2 which is incompatible.\r\n\r\n```", "The `fsspec<2023.9.0` upper bound will be removed in the next release. The `ResourceError` fix is also present in version 2023.6.0, so use that version in the meantime (`pip install fsspec==2023.6.0`)." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011548 / 0.011353 (0.000196) | 0.004630 / 0.011008 (-0.006378) | 0.105349 / 0.038508 (0.066841) | 0.110557 / 0.023109 (0.087448) | 0.395463 / 0.275898 (0.119565) | 0.448391 / 0.323480 (0.124912) | 0.005112 / 0.007986 (-0.002873) | 0.003854 / 0.004328 (-0.000474) | 0.088513 / 0.004250 (0.084263) | 0.073081 / 0.037052 (0.036028) | 0.391572 / 0.258489 (0.133083) | 0.459543 / 0.293841 (0.165702) | 0.040424 / 0.128546 (-0.088122) | 0.010306 / 0.075646 (-0.065340) | 0.365493 / 0.419271 (-0.053778) | 0.068154 / 0.043533 (0.024622) | 0.397675 / 0.255139 (0.142536) | 0.447147 / 0.283200 (0.163947) | 0.033482 / 0.141683 (-0.108201) | 1.857087 / 1.452155 (0.404932) | 1.973311 / 1.492716 (0.480595) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.257938 / 0.018006 (0.239932) | 0.569572 / 0.000490 (0.569083) | 0.012155 / 0.000200 (0.011955) | 0.000112 / 0.000054 (0.000058) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033094 / 0.037411 (-0.004318) | 0.102370 / 0.014526 (0.087844) | 0.122421 / 0.176557 (-0.054136) | 0.189983 / 0.737135 (-0.547152) | 0.117902 / 0.296338 (-0.178437) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.468419 / 0.215209 (0.253210) | 4.671410 / 2.077655 (2.593755) | 2.371136 / 1.504120 (0.867016) | 2.191877 / 1.541195 (0.650682) | 2.301894 / 1.468490 (0.833404) | 0.572260 / 4.584777 (-4.012517) | 4.302031 / 3.745712 (0.556319) | 4.128431 / 5.269862 (-1.141431) | 2.464543 / 4.565676 (-2.101133) | 0.067663 / 0.424275 (-0.356612) | 0.008947 / 0.007607 (0.001340) | 0.570063 / 0.226044 (0.344018) | 5.684460 / 2.268929 (3.415531) | 2.969708 / 55.444624 (-52.474916) | 2.573568 / 6.876477 (-4.302909) | 2.666074 / 2.142072 (0.524001) | 0.710098 / 4.805227 (-4.095129) | 0.158413 / 6.500664 (-6.342251) | 0.072776 / 0.075469 (-0.002693) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.564166 / 1.841788 (-0.277622) | 23.612774 / 8.074308 (15.538465) | 17.725070 / 10.191392 (7.533678) | 0.178982 / 0.680424 (-0.501442) | 0.021615 / 0.534201 (-0.512586) | 0.467090 / 0.579283 (-0.112193) | 0.472648 / 0.434364 (0.038284) | 0.578820 / 0.540337 (0.038483) | 0.783533 / 1.386936 (-0.603403) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008895 / 0.011353 (-0.002458) | 0.004617 / 0.011008 (-0.006392) | 0.077677 / 0.038508 (0.039169) | 0.090283 / 0.023109 (0.067174) | 0.491115 / 0.275898 (0.215217) | 0.525189 / 0.323480 (0.201709) | 0.007845 / 0.007986 (-0.000141) | 0.003742 / 0.004328 (-0.000586) | 0.077856 / 0.004250 (0.073606) | 0.067447 / 0.037052 (0.030394) | 0.488423 / 0.258489 (0.229933) | 0.532938 / 0.293841 (0.239097) | 0.041035 / 0.128546 (-0.087511) | 0.009917 / 0.075646 (-0.065730) | 0.085313 / 0.419271 (-0.333958) | 0.063374 / 0.043533 (0.019841) | 0.472287 / 0.255139 (0.217148) | 0.509773 / 0.283200 (0.226573) | 0.028706 / 0.141683 (-0.112977) | 1.775558 / 1.452155 (0.323403) | 1.967778 / 1.492716 (0.475061) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.249834 / 0.018006 (0.231828) | 0.467266 / 0.000490 (0.466776) | 0.005837 / 0.000200 (0.005637) | 0.000128 / 0.000054 (0.000074) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038759 / 0.037411 (0.001347) | 0.113156 / 0.014526 (0.098630) | 0.123936 / 0.176557 (-0.052621) | 0.186831 / 0.737135 (-0.550304) | 0.125195 / 0.296338 (-0.171143) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.545666 / 0.215209 (0.330457) | 5.465713 / 2.077655 (3.388058) | 2.941279 / 1.504120 (1.437159) | 2.688377 / 1.541195 (1.147182) | 2.619501 / 1.468490 (1.151010) | 0.577974 / 4.584777 (-4.006803) | 4.300966 / 3.745712 (0.555254) | 3.879552 / 5.269862 (-1.390310) | 2.454932 / 4.565676 (-2.110745) | 0.069233 / 0.424275 (-0.355043) | 0.009729 / 0.007607 (0.002122) | 0.595290 / 0.226044 (0.369245) | 5.945445 / 2.268929 (3.676516) | 3.314607 / 55.444624 (-52.130017) | 2.894474 / 6.876477 (-3.982002) | 3.140790 / 2.142072 (0.998718) | 0.695808 / 4.805227 (-4.109419) | 0.158087 / 6.500664 (-6.342577) | 0.071374 / 0.075469 (-0.004095) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.706482 / 1.841788 (-0.135306) | 24.022666 / 8.074308 (15.948358) | 17.658003 / 10.191392 (7.466611) | 0.196771 / 0.680424 (-0.483653) | 0.023928 / 0.534201 (-0.510273) | 0.471992 / 0.579283 (-0.107291) | 0.510463 / 0.434364 (0.076099) | 0.621250 / 0.540337 (0.080912) | 0.807670 / 1.386936 (-0.579266) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f77539cbd88d00ec1ab2b9d4edfd01d5a58ef88a \"CML watermark\")\n" ]

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[ "more information：\r\n``` \r\nFile \"text2vec\\__init__.py\", line 8, in <module>\r\nFile \"<frozen importlib._bootstrap>\", line 1027, in _find_and_load\r\nFile \"<frozen importlib._bootstrap>\", line 1006, in _find_and_load_unlocked\r\nFile \"<frozen importlib._bootstrap>\", line 688, in _load_unlocked\r\nFile \"PyInstaller\\loader\\pyimod02_importers.py\", line 499, in exec_module\r\nFile \"text2vec\\bertmatching_model.py\", line 19, in <module>\r\nFile \"<frozen importlib._bootstrap>\", line 1027, in _find_and_load\r\nFile \"<frozen importlib._bootstrap>\", line 1006, in _find_and_load_unlocked\r\nFile \"<frozen importlib._bootstrap>\", line 688, in _load_unlocked\r\nFile \"PyInstaller\\loader\\pyimod02_importers.py\", line 499, in exec_module\r\nFile \"text2vec\\bertmatching_dataset.py\", line 7, in <module>\r\nFile \"<frozen importlib._bootstrap>\", line 1027, in _find_and_load\r\nFile \"<frozen importlib._bootstrap>\", line 1006, in _find_and_load_unlocked\r\nFile \"<frozen importlib._bootstrap>\", line 688, in _load_unlocked\r\nFile \"PyInstaller\\loader\\pyimod02_importers.py\", line 499, in exec_module\r\nFile \"datasets\\__init__.py\", line 52, in <module>\r\nFile \"<frozen importlib._bootstrap>\", line 1027, in _find_and_load\r\nFile \"<frozen importlib._bootstrap>\", line 1006, in _find_and_load_unlocked\r\nFile \"<frozen importlib._bootstrap>\", line 688, in _load_unlocked\r\nFile \"PyInstaller\\loader\\pyimod02_importers.py\", line 499, in exec_module\r\nFile \"datasets\\inspect.py\", line 30, in <module>\r\nFile \"<frozen importlib._bootstrap>\", line 1027, in _find_and_load\r\nFile \"<frozen importlib._bootstrap>\", line 1006, in _find_and_load_unlocked\r\nFile \"<frozen importlib._bootstrap>\", line 688, in _load_unlocked\r\nFile \"PyInstaller\\loader\\pyimod02_importers.py\", line 499, in exec_module\r\nFile \"datasets\\load.py\", line 58, in <module>\r\nFile \"<frozen importlib._bootstrap>\", line 1027, in _find_and_load\r\nFile \"<frozen importlib._bootstrap>\", line 1006, in _find_and_load_unlocked\r\nFile \"<frozen importlib._bootstrap>\", line 688, in _load_unlocked\r\nFile \"PyInstaller\\loader\\pyimod02_importers.py\", line 499, in exec_module\r\nFile \"datasets\\packaged_modules\\__init__.py\", line 31, in <module>\r\nFile \"inspect.py\", line 1147, in getsource\r\nFile \"inspect.py\", line 1129, in getsourcelines\r\nFile \"inspect.py\", line 958, in findsource\r\nOSError: could not get source code\r\n```\r\n", "Can you share a reproducer? I haven't been able to reproduce the error myself.", "> '\r\n\r\nthanks,I solve it.it's about pyinstaller.", "1" ]

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[ "Thanks for reporting, @finiteautomata.\r\n\r\nWe are investigating it. ", "There is a bug in `datasets`. You can see our proposed fix:\r\n- #6309 " ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006678 / 0.011353 (-0.004675) | 0.004013 / 0.011008 (-0.006995) | 0.083372 / 0.038508 (0.044864) | 0.070339 / 0.023109 (0.047230) | 0.339026 / 0.275898 (0.063128) | 0.370945 / 0.323480 (0.047465) | 0.004050 / 0.007986 (-0.003935) | 0.003283 / 0.004328 (-0.001046) | 0.064956 / 0.004250 (0.060705) | 0.055427 / 0.037052 (0.018374) | 0.341787 / 0.258489 (0.083297) | 0.385030 / 0.293841 (0.091189) | 0.031791 / 0.128546 (-0.096755) | 0.008511 / 0.075646 (-0.067135) | 0.286538 / 0.419271 (-0.132734) | 0.052893 / 0.043533 (0.009360) | 0.338522 / 0.255139 (0.083383) | 0.371821 / 0.283200 (0.088622) | 0.023731 / 0.141683 (-0.117951) | 1.485857 / 1.452155 (0.033702) | 1.515218 / 1.492716 (0.022502) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.232798 / 0.018006 (0.214792) | 0.446783 / 0.000490 (0.446293) | 0.007395 / 0.000200 (0.007195) | 0.000385 / 0.000054 (0.000330) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028866 / 0.037411 (-0.008545) | 0.081653 / 0.014526 (0.067127) | 0.094457 / 0.176557 (-0.082099) | 0.151761 / 0.737135 (-0.585375) | 0.095579 / 0.296338 (-0.200760) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.379926 / 0.215209 (0.164717) | 3.801839 / 2.077655 (1.724184) | 1.830302 / 1.504120 (0.326182) | 1.686912 / 1.541195 (0.145717) | 1.803418 / 1.468490 (0.334928) | 0.484431 / 4.584777 (-4.100346) | 3.592748 / 3.745712 (-0.152964) | 3.402578 / 5.269862 (-1.867284) | 2.043434 / 4.565676 (-2.522242) | 0.057274 / 0.424275 (-0.367001) | 0.007211 / 0.007607 (-0.000396) | 0.462611 / 0.226044 (0.236567) | 4.610703 / 2.268929 (2.341775) | 2.397668 / 55.444624 (-53.046956) | 2.149983 / 6.876477 (-4.726494) | 2.199100 / 2.142072 (0.057028) | 0.575883 / 4.805227 (-4.229344) | 0.133421 / 6.500664 (-6.367243) | 0.061168 / 0.075469 (-0.014301) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.246792 / 1.841788 (-0.594995) | 18.974385 / 8.074308 (10.900077) | 14.268859 / 10.191392 (4.077467) | 0.166340 / 0.680424 (-0.514084) | 0.018227 / 0.534201 (-0.515974) | 0.389646 / 0.579283 (-0.189637) | 0.418780 / 0.434364 (-0.015584) | 0.458063 / 0.540337 (-0.082275) | 0.635156 / 1.386936 (-0.751780) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006613 / 0.011353 (-0.004740) | 0.003977 / 0.011008 (-0.007031) | 0.064609 / 0.038508 (0.026101) | 0.070418 / 0.023109 (0.047308) | 0.395814 / 0.275898 (0.119916) | 0.424803 / 0.323480 (0.101323) | 0.005342 / 0.007986 (-0.002644) | 0.003252 / 0.004328 (-0.001076) | 0.065177 / 0.004250 (0.060927) | 0.055299 / 0.037052 (0.018247) | 0.403983 / 0.258489 (0.145494) | 0.438522 / 0.293841 (0.144681) | 0.032336 / 0.128546 (-0.096210) | 0.008524 / 0.075646 (-0.067122) | 0.071645 / 0.419271 (-0.347627) | 0.048137 / 0.043533 (0.004604) | 0.395170 / 0.255139 (0.140031) | 0.421727 / 0.283200 (0.138528) | 0.023028 / 0.141683 (-0.118655) | 1.500739 / 1.452155 (0.048584) | 1.568887 / 1.492716 (0.076170) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227542 / 0.018006 (0.209536) | 0.447882 / 0.000490 (0.447393) | 0.005416 / 0.000200 (0.005216) | 0.000089 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032954 / 0.037411 (-0.004457) | 0.091994 / 0.014526 (0.077468) | 0.105957 / 0.176557 (-0.070600) | 0.158728 / 0.737135 (-0.578407) | 0.104734 / 0.296338 (-0.191605) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436275 / 0.215209 (0.221066) | 4.344864 / 2.077655 (2.267209) | 2.304949 / 1.504120 (0.800829) | 2.123963 / 1.541195 (0.582768) | 2.189099 / 1.468490 (0.720609) | 0.492662 / 4.584777 (-4.092115) | 3.633662 / 3.745712 (-0.112051) | 3.251338 / 5.269862 (-2.018524) | 2.061378 / 4.565676 (-2.504299) | 0.058100 / 0.424275 (-0.366175) | 0.007311 / 0.007607 (-0.000297) | 0.516227 / 0.226044 (0.290183) | 5.184228 / 2.268929 (2.915300) | 2.780343 / 55.444624 (-52.664281) | 2.423428 / 6.876477 (-4.453048) | 2.617371 / 2.142072 (0.475298) | 0.590455 / 4.805227 (-4.214772) | 0.131728 / 6.500664 (-6.368936) | 0.059994 / 0.075469 (-0.015475) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.354920 / 1.841788 (-0.486868) | 19.427822 / 8.074308 (11.353514) | 15.289037 / 10.191392 (5.097645) | 0.170437 / 0.680424 (-0.509987) | 0.020242 / 0.534201 (-0.513959) | 0.394921 / 0.579283 (-0.184362) | 0.426447 / 0.434364 (-0.007917) | 0.468321 / 0.540337 (-0.072017) | 0.671052 / 1.386936 (-0.715884) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#bade7af74437347a760830466eb74f7a8ce0d799 \"CML watermark\")\n" ]

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[ "You can find the reasoning behind this naming scheme [here](https://github.com/huggingface/transformers/pull/16343#discussion_r931182168).\r\n\r\nThis point has been raised several times, so I'd be okay with starting with `00001-` (also to be consistent with the `transformers` sharding), but I'm not sure @lhoestq agrees.", "We start at 0 in `datasets` for consistency with Apache Spark, Apache Beam, Dask and others.\r\n\r\nAlso note `transformers` isn't a good reference on this topic. I talked with the maintainers when they added shards but it was already released this way. Though we found that there is a backward-compatible way in `transformers` to start at 0, but no request from `transformers` users to changes this AFAIK.", "not sure it would be a good idea to break the consistency now, IMO", "Makes sense to start at 0 for plenty of good reasons so I'm on board.\r\n\r\nWhat about the second part `-of-0000X`? With single commit PR #6269 just getting merged, there was a note about issues with 100+ file edits https://github.com/huggingface/datasets/pull/6269#issuecomment-1755428581.\r\n\r\nThat would be my last remaining concern in the context of the `push_to_hub(..., append=True)` work to be done, where appending a single file to the full dataset will require renaming every other existing file in the dataset. If it doesn't seem like a big issue for this work then all the better 👍" ]

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[ "`writer._num_bytes` is updated every `writer_batch_size`-th call to the `write` method (default `writer_batch_size` is 1000 (examples)). You should be able to see the update by passing a smaller `writer_batch_size` to the `load_dataset_builder`.\r\n\r\nWe could improve this by supporting the string `writer_batch_size` version as we do with `max_shard_size`, and capping `writer_batch_size` to `max_shard_size` in scenarios where the default `writer_batch_size` > `max_shard_size`. ", "Thanks, reducing `writer_batch_size` solved my problem :)" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006663 / 0.011353 (-0.004690) | 0.004091 / 0.011008 (-0.006918) | 0.084954 / 0.038508 (0.046445) | 0.071869 / 0.023109 (0.048760) | 0.314706 / 0.275898 (0.038808) | 0.352794 / 0.323480 (0.029314) | 0.004027 / 0.007986 (-0.003959) | 0.003371 / 0.004328 (-0.000957) | 0.065456 / 0.004250 (0.061205) | 0.055828 / 0.037052 (0.018775) | 0.316502 / 0.258489 (0.058013) | 0.377979 / 0.293841 (0.084138) | 0.030870 / 0.128546 (-0.097676) | 0.008616 / 0.075646 (-0.067030) | 0.288625 / 0.419271 (-0.130646) | 0.052314 / 0.043533 (0.008781) | 0.322725 / 0.255139 (0.067586) | 0.351810 / 0.283200 (0.068611) | 0.025726 / 0.141683 (-0.115957) | 1.439308 / 1.452155 (-0.012847) | 1.524484 / 1.492716 (0.031768) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.235212 / 0.018006 (0.217206) | 0.444926 / 0.000490 (0.444437) | 0.009887 / 0.000200 (0.009687) | 0.000402 / 0.000054 (0.000347) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028956 / 0.037411 (-0.008455) | 0.084401 / 0.014526 (0.069875) | 0.339686 / 0.176557 (0.163130) | 0.186785 / 0.737135 (-0.550350) | 0.195017 / 0.296338 (-0.101322) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.405480 / 0.215209 (0.190271) | 4.024315 / 2.077655 (1.946661) | 2.056398 / 1.504120 (0.552278) | 1.912099 / 1.541195 (0.370904) | 1.950119 / 1.468490 (0.481629) | 0.486071 / 4.584777 (-4.098706) | 3.578501 / 3.745712 (-0.167211) | 3.268980 / 5.269862 (-2.000881) | 2.018114 / 4.565676 (-2.547563) | 0.057440 / 0.424275 (-0.366835) | 0.007281 / 0.007607 (-0.000326) | 0.474760 / 0.226044 (0.248716) | 4.746908 / 2.268929 (2.477979) | 2.550111 / 55.444624 (-52.894513) | 2.171932 / 6.876477 (-4.704544) | 2.392235 / 2.142072 (0.250162) | 0.585940 / 4.805227 (-4.219287) | 0.136445 / 6.500664 (-6.364219) | 0.062125 / 0.075469 (-0.013344) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.270763 / 1.841788 (-0.571025) | 19.213516 / 8.074308 (11.139208) | 13.992620 / 10.191392 (3.801228) | 0.167356 / 0.680424 (-0.513068) | 0.018261 / 0.534201 (-0.515940) | 0.392489 / 0.579283 (-0.186794) | 0.418845 / 0.434364 (-0.015519) | 0.461824 / 0.540337 (-0.078513) | 0.649661 / 1.386936 (-0.737275) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006675 / 0.011353 (-0.004678) | 0.003913 / 0.011008 (-0.007096) | 0.064943 / 0.038508 (0.026435) | 0.072426 / 0.023109 (0.049317) | 0.400785 / 0.275898 (0.124887) | 0.434359 / 0.323480 (0.110879) | 0.005370 / 0.007986 (-0.002616) | 0.003290 / 0.004328 (-0.001038) | 0.065035 / 0.004250 (0.060785) | 0.054924 / 0.037052 (0.017872) | 0.404442 / 0.258489 (0.145953) | 0.439027 / 0.293841 (0.145186) | 0.032467 / 0.128546 (-0.096080) | 0.008565 / 0.075646 (-0.067081) | 0.070653 / 0.419271 (-0.348619) | 0.048034 / 0.043533 (0.004501) | 0.400869 / 0.255139 (0.145730) | 0.423048 / 0.283200 (0.139848) | 0.022757 / 0.141683 (-0.118926) | 1.516956 / 1.452155 (0.064801) | 1.581599 / 1.492716 (0.088883) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.214761 / 0.018006 (0.196755) | 0.440921 / 0.000490 (0.440431) | 0.007538 / 0.000200 (0.007338) | 0.000087 / 0.000054 (0.000033) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032313 / 0.037411 (-0.005099) | 0.091365 / 0.014526 (0.076839) | 0.106665 / 0.176557 (-0.069891) | 0.158637 / 0.737135 (-0.578498) | 0.104894 / 0.296338 (-0.191445) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.432995 / 0.215209 (0.217786) | 4.339911 / 2.077655 (2.262256) | 2.313139 / 1.504120 (0.809019) | 2.142552 / 1.541195 (0.601357) | 2.279275 / 1.468490 (0.810785) | 0.501133 / 4.584777 (-4.083644) | 3.696160 / 3.745712 (-0.049552) | 3.341886 / 5.269862 (-1.927976) | 2.105972 / 4.565676 (-2.459705) | 0.059268 / 0.424275 (-0.365008) | 0.007568 / 0.007607 (-0.000039) | 0.512546 / 0.226044 (0.286502) | 5.130219 / 2.268929 (2.861290) | 2.808292 / 55.444624 (-52.636332) | 2.478721 / 6.876477 (-4.397755) | 2.679341 / 2.142072 (0.537269) | 0.599022 / 4.805227 (-4.206206) | 0.143761 / 6.500664 (-6.356903) | 0.062061 / 0.075469 (-0.013409) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.430507 / 1.841788 (-0.411281) | 20.458085 / 8.074308 (12.383777) | 15.268356 / 10.191392 (5.076964) | 0.163359 / 0.680424 (-0.517065) | 0.020908 / 0.534201 (-0.513293) | 0.396870 / 0.579283 (-0.182413) | 0.432630 / 0.434364 (-0.001733) | 0.475909 / 0.540337 (-0.064429) | 0.681031 / 1.386936 (-0.705905) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#fd1dd6aa4c7fa7744c1c1f877573ff59f1529292 \"CML watermark\")\n", "CI failures are unrelated", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005815 / 0.011353 (-0.005538) | 0.003419 / 0.011008 (-0.007589) | 0.080286 / 0.038508 (0.041778) | 0.056487 / 0.023109 (0.033377) | 0.304414 / 0.275898 (0.028516) | 0.341039 / 0.323480 (0.017559) | 0.004392 / 0.007986 (-0.003594) | 0.002852 / 0.004328 (-0.001477) | 0.062339 / 0.004250 (0.058089) | 0.044683 / 0.037052 (0.007630) | 0.311651 / 0.258489 (0.053162) | 0.357249 / 0.293841 (0.063409) | 0.027300 / 0.128546 (-0.101246) | 0.007963 / 0.075646 (-0.067683) | 0.261948 / 0.419271 (-0.157323) | 0.044952 / 0.043533 (0.001419) | 0.309990 / 0.255139 (0.054851) | 0.340735 / 0.283200 (0.057536) | 0.020786 / 0.141683 (-0.120897) | 1.471378 / 1.452155 (0.019224) | 1.517260 / 1.492716 (0.024543) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.245447 / 0.018006 (0.227441) | 0.418967 / 0.000490 (0.418477) | 0.007039 / 0.000200 (0.006840) | 0.000196 / 0.000054 (0.000142) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022880 / 0.037411 (-0.014532) | 0.071862 / 0.014526 (0.057337) | 0.083009 / 0.176557 (-0.093547) | 0.143414 / 0.737135 (-0.593722) | 0.082896 / 0.296338 (-0.213442) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.390645 / 0.215209 (0.175436) | 3.888104 / 2.077655 (1.810450) | 1.859572 / 1.504120 (0.355452) | 1.683803 / 1.541195 (0.142608) | 1.697902 / 1.468490 (0.229412) | 0.499537 / 4.584777 (-4.085239) | 3.015832 / 3.745712 (-0.729881) | 2.805696 / 5.269862 (-2.464166) | 1.830408 / 4.565676 (-2.735268) | 0.058191 / 0.424275 (-0.366085) | 0.006357 / 0.007607 (-0.001250) | 0.462486 / 0.226044 (0.236442) | 4.634951 / 2.268929 (2.366022) | 2.309364 / 55.444624 (-53.135260) | 1.979521 / 6.876477 (-4.896956) | 2.080011 / 2.142072 (-0.062062) | 0.593086 / 4.805227 (-4.212141) | 0.124856 / 6.500664 (-6.375808) | 0.060172 / 0.075469 (-0.015297) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.251439 / 1.841788 (-0.590349) | 17.068999 / 8.074308 (8.994691) | 13.527209 / 10.191392 (3.335817) | 0.146636 / 0.680424 (-0.533788) | 0.016866 / 0.534201 (-0.517335) | 0.333202 / 0.579283 (-0.246081) | 0.360444 / 0.434364 (-0.073920) | 0.388378 / 0.540337 (-0.151959) | 0.530519 / 1.386936 (-0.856417) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006043 / 0.011353 (-0.005310) | 0.003612 / 0.011008 (-0.007396) | 0.062644 / 0.038508 (0.024135) | 0.056104 / 0.023109 (0.032995) | 0.446328 / 0.275898 (0.170430) | 0.478044 / 0.323480 (0.154564) | 0.004641 / 0.007986 (-0.003345) | 0.002896 / 0.004328 (-0.001432) | 0.062344 / 0.004250 (0.058093) | 0.046339 / 0.037052 (0.009287) | 0.454866 / 0.258489 (0.196377) | 0.484242 / 0.293841 (0.190401) | 0.028602 / 0.128546 (-0.099944) | 0.008075 / 0.075646 (-0.067571) | 0.067980 / 0.419271 (-0.351291) | 0.041339 / 0.043533 (-0.002194) | 0.452911 / 0.255139 (0.197772) | 0.474180 / 0.283200 (0.190981) | 0.019395 / 0.141683 (-0.122288) | 1.432161 / 1.452155 (-0.019993) | 1.505800 / 1.492716 (0.013083) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.216983 / 0.018006 (0.198977) | 0.406232 / 0.000490 (0.405743) | 0.005101 / 0.000200 (0.004902) | 0.000077 / 0.000054 (0.000022) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026295 / 0.037411 (-0.011116) | 0.080490 / 0.014526 (0.065964) | 0.088105 / 0.176557 (-0.088451) | 0.143294 / 0.737135 (-0.593841) | 0.089125 / 0.296338 (-0.207213) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.465512 / 0.215209 (0.250302) | 4.648656 / 2.077655 (2.571002) | 2.598225 / 1.504120 (1.094105) | 2.409588 / 1.541195 (0.868393) | 2.513745 / 1.468490 (1.045255) | 0.507425 / 4.584777 (-4.077352) | 3.130164 / 3.745712 (-0.615548) | 2.836817 / 5.269862 (-2.433045) | 1.836029 / 4.565676 (-2.729647) | 0.058829 / 0.424275 (-0.365446) | 0.006551 / 0.007607 (-0.001056) | 0.537892 / 0.226044 (0.311848) | 5.401079 / 2.268929 (3.132150) | 3.019817 / 55.444624 (-52.424807) | 2.695131 / 6.876477 (-4.181346) | 2.805321 / 2.142072 (0.663248) | 0.595681 / 4.805227 (-4.209546) | 0.124368 / 6.500664 (-6.376296) | 0.060712 / 0.075469 (-0.014757) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.361508 / 1.841788 (-0.480279) | 17.811373 / 8.074308 (9.737065) | 14.482705 / 10.191392 (4.291313) | 0.153193 / 0.680424 (-0.527231) | 0.018347 / 0.534201 (-0.515854) | 0.330900 / 0.579283 (-0.248383) | 0.374948 / 0.434364 (-0.059416) | 0.385615 / 0.540337 (-0.154722) | 0.568077 / 1.386936 (-0.818859) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#18ef408c21f8efbb2142f050a691b5c916455af3 \"CML watermark\")\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008410 / 0.011353 (-0.002943) | 0.004888 / 0.011008 (-0.006120) | 0.103342 / 0.038508 (0.064834) | 0.103697 / 0.023109 (0.080587) | 0.416445 / 0.275898 (0.140547) | 0.454604 / 0.323480 (0.131124) | 0.004976 / 0.007986 (-0.003010) | 0.003957 / 0.004328 (-0.000371) | 0.077398 / 0.004250 (0.073148) | 0.069026 / 0.037052 (0.031973) | 0.420484 / 0.258489 (0.161995) | 0.471828 / 0.293841 (0.177987) | 0.037133 / 0.128546 (-0.091413) | 0.010009 / 0.075646 (-0.065637) | 0.349573 / 0.419271 (-0.069698) | 0.063240 / 0.043533 (0.019708) | 0.421554 / 0.255139 (0.166415) | 0.433548 / 0.283200 (0.150348) | 0.029397 / 0.141683 (-0.112286) | 1.716860 / 1.452155 (0.264705) | 1.851264 / 1.492716 (0.358547) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.269733 / 0.018006 (0.251727) | 0.493313 / 0.000490 (0.492823) | 0.010438 / 0.000200 (0.010238) | 0.000401 / 0.000054 (0.000347) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034690 / 0.037411 (-0.002722) | 0.105304 / 0.014526 (0.090778) | 0.115831 / 0.176557 (-0.060726) | 0.185017 / 0.737135 (-0.552118) | 0.117480 / 0.296338 (-0.178859) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.479414 / 0.215209 (0.264205) | 4.785526 / 2.077655 (2.707871) | 2.388412 / 1.504120 (0.884292) | 2.178222 / 1.541195 (0.637027) | 2.248214 / 1.468490 (0.779723) | 0.571723 / 4.584777 (-4.013054) | 4.721250 / 3.745712 (0.975538) | 4.073893 / 5.269862 (-1.195969) | 2.618131 / 4.565676 (-1.947546) | 0.068406 / 0.424275 (-0.355869) | 0.008890 / 0.007607 (0.001283) | 0.564224 / 0.226044 (0.338180) | 5.631412 / 2.268929 (3.362483) | 3.072212 / 55.444624 (-52.372412) | 2.760574 / 6.876477 (-4.115903) | 2.963060 / 2.142072 (0.820987) | 0.708150 / 4.805227 (-4.097077) | 0.160324 / 6.500664 (-6.340340) | 0.075402 / 0.075469 (-0.000067) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.649965 / 1.841788 (-0.191823) | 24.297517 / 8.074308 (16.223209) | 17.658675 / 10.191392 (7.467283) | 0.171399 / 0.680424 (-0.509025) | 0.021172 / 0.534201 (-0.513029) | 0.477196 / 0.579283 (-0.102087) | 0.503900 / 0.434364 (0.069536) | 0.555858 / 0.540337 (0.015520) | 0.824302 / 1.386936 (-0.562634) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008613 / 0.011353 (-0.002740) | 0.004848 / 0.011008 (-0.006160) | 0.078344 / 0.038508 (0.039836) | 0.098976 / 0.023109 (0.075867) | 0.520713 / 0.275898 (0.244815) | 0.566350 / 0.323480 (0.242870) | 0.006658 / 0.007986 (-0.001327) | 0.004043 / 0.004328 (-0.000285) | 0.077881 / 0.004250 (0.073631) | 0.070731 / 0.037052 (0.033678) | 0.519717 / 0.258489 (0.261228) | 0.575623 / 0.293841 (0.281782) | 0.038542 / 0.128546 (-0.090004) | 0.010277 / 0.075646 (-0.065369) | 0.084269 / 0.419271 (-0.335002) | 0.058088 / 0.043533 (0.014555) | 0.541790 / 0.255139 (0.286651) | 0.534915 / 0.283200 (0.251715) | 0.027851 / 0.141683 (-0.113831) | 1.814827 / 1.452155 (0.362672) | 1.898208 / 1.492716 (0.405492) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.244162 / 0.018006 (0.226156) | 0.482895 / 0.000490 (0.482405) | 0.005734 / 0.000200 (0.005534) | 0.000127 / 0.000054 (0.000072) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039328 / 0.037411 (0.001917) | 0.119795 / 0.014526 (0.105269) | 0.128570 / 0.176557 (-0.047986) | 0.191207 / 0.737135 (-0.545929) | 0.127147 / 0.296338 (-0.169192) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.533545 / 0.215209 (0.318336) | 5.320135 / 2.077655 (3.242480) | 2.924573 / 1.504120 (1.420453) | 2.741351 / 1.541195 (1.200156) | 2.824217 / 1.468490 (1.355727) | 0.595842 / 4.584777 (-3.988935) | 4.343499 / 3.745712 (0.597787) | 3.976546 / 5.269862 (-1.293316) | 2.532541 / 4.565676 (-2.033135) | 0.070480 / 0.424275 (-0.353795) | 0.008868 / 0.007607 (0.001260) | 0.634297 / 0.226044 (0.408253) | 6.327314 / 2.268929 (4.058386) | 3.530741 / 55.444624 (-51.913883) | 3.121435 / 6.876477 (-3.755042) | 3.344473 / 2.142072 (1.202401) | 0.719413 / 4.805227 (-4.085814) | 0.162348 / 6.500664 (-6.338316) | 0.074964 / 0.075469 (-0.000505) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.679095 / 1.841788 (-0.162693) | 25.071620 / 8.074308 (16.997312) | 18.422398 / 10.191392 (8.231006) | 0.223981 / 0.680424 (-0.456443) | 0.026537 / 0.534201 (-0.507664) | 0.513867 / 0.579283 (-0.065416) | 0.535874 / 0.434364 (0.101510) | 0.567971 / 0.540337 (0.027634) | 0.842545 / 1.386936 (-0.544391) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d8b871016c25cb3b90ac1ff65a4e54f0454f525e \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006445 / 0.011353 (-0.004908) | 0.003978 / 0.011008 (-0.007030) | 0.084542 / 0.038508 (0.046034) | 0.069231 / 0.023109 (0.046122) | 0.308794 / 0.275898 (0.032896) | 0.339246 / 0.323480 (0.015766) | 0.005269 / 0.007986 (-0.002716) | 0.003285 / 0.004328 (-0.001043) | 0.065336 / 0.004250 (0.061086) | 0.053480 / 0.037052 (0.016428) | 0.316775 / 0.258489 (0.058286) | 0.357885 / 0.293841 (0.064044) | 0.031309 / 0.128546 (-0.097237) | 0.008450 / 0.075646 (-0.067196) | 0.287911 / 0.419271 (-0.131361) | 0.052756 / 0.043533 (0.009223) | 0.321516 / 0.255139 (0.066377) | 0.331998 / 0.283200 (0.048799) | 0.024129 / 0.141683 (-0.117553) | 1.507718 / 1.452155 (0.055563) | 1.571400 / 1.492716 (0.078683) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237536 / 0.018006 (0.219530) | 0.499691 / 0.000490 (0.499201) | 0.007644 / 0.000200 (0.007444) | 0.000284 / 0.000054 (0.000230) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028243 / 0.037411 (-0.009168) | 0.081556 / 0.014526 (0.067030) | 0.096877 / 0.176557 (-0.079680) | 0.149985 / 0.737135 (-0.587150) | 0.095556 / 0.296338 (-0.200783) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383215 / 0.215209 (0.168006) | 3.815800 / 2.077655 (1.738145) | 1.832227 / 1.504120 (0.328107) | 1.664001 / 1.541195 (0.122806) | 1.698786 / 1.468490 (0.230296) | 0.487594 / 4.584777 (-4.097183) | 3.569767 / 3.745712 (-0.175945) | 3.262387 / 5.269862 (-2.007475) | 2.017105 / 4.565676 (-2.548572) | 0.057555 / 0.424275 (-0.366720) | 0.007170 / 0.007607 (-0.000437) | 0.460134 / 0.226044 (0.234090) | 4.629800 / 2.268929 (2.360871) | 2.357126 / 55.444624 (-53.087499) | 1.970144 / 6.876477 (-4.906332) | 2.123520 / 2.142072 (-0.018552) | 0.613058 / 4.805227 (-4.192169) | 0.135869 / 6.500664 (-6.364795) | 0.061292 / 0.075469 (-0.014177) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.311294 / 1.841788 (-0.530494) | 18.640807 / 8.074308 (10.566499) | 13.946834 / 10.191392 (3.755442) | 0.163976 / 0.680424 (-0.516448) | 0.018527 / 0.534201 (-0.515674) | 0.390530 / 0.579283 (-0.188753) | 0.412661 / 0.434364 (-0.021703) | 0.459514 / 0.540337 (-0.080823) | 0.635026 / 1.386936 (-0.751910) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006645 / 0.011353 (-0.004708) | 0.003943 / 0.011008 (-0.007066) | 0.064470 / 0.038508 (0.025962) | 0.069895 / 0.023109 (0.046786) | 0.411091 / 0.275898 (0.135193) | 0.437628 / 0.323480 (0.114148) | 0.005214 / 0.007986 (-0.002772) | 0.003281 / 0.004328 (-0.001047) | 0.064434 / 0.004250 (0.060183) | 0.054294 / 0.037052 (0.017241) | 0.413576 / 0.258489 (0.155087) | 0.448793 / 0.293841 (0.154952) | 0.031754 / 0.128546 (-0.096793) | 0.008530 / 0.075646 (-0.067117) | 0.069950 / 0.419271 (-0.349322) | 0.047747 / 0.043533 (0.004214) | 0.411241 / 0.255139 (0.156102) | 0.430076 / 0.283200 (0.146876) | 0.023462 / 0.141683 (-0.118220) | 1.519501 / 1.452155 (0.067346) | 1.575782 / 1.492716 (0.083066) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.231816 / 0.018006 (0.213810) | 0.442802 / 0.000490 (0.442312) | 0.005738 / 0.000200 (0.005539) | 0.000087 / 0.000054 (0.000032) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031426 / 0.037411 (-0.005985) | 0.090758 / 0.014526 (0.076233) | 0.103414 / 0.176557 (-0.073142) | 0.156409 / 0.737135 (-0.580726) | 0.103900 / 0.296338 (-0.192439) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.438897 / 0.215209 (0.223688) | 4.385318 / 2.077655 (2.307663) | 2.352042 / 1.504120 (0.847923) | 2.182228 / 1.541195 (0.641033) | 2.266256 / 1.468490 (0.797766) | 0.492780 / 4.584777 (-4.091997) | 3.665787 / 3.745712 (-0.079925) | 3.315329 / 5.269862 (-1.954533) | 2.027993 / 4.565676 (-2.537684) | 0.058220 / 0.424275 (-0.366055) | 0.007429 / 0.007607 (-0.000178) | 0.508790 / 0.226044 (0.282746) | 5.107093 / 2.268929 (2.838164) | 2.799789 / 55.444624 (-52.644836) | 2.462828 / 6.876477 (-4.413649) | 2.610193 / 2.142072 (0.468120) | 0.588133 / 4.805227 (-4.217094) | 0.133418 / 6.500664 (-6.367246) | 0.059793 / 0.075469 (-0.015676) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.363358 / 1.841788 (-0.478430) | 19.258372 / 8.074308 (11.184064) | 14.730977 / 10.191392 (4.539584) | 0.169493 / 0.680424 (-0.510931) | 0.020462 / 0.534201 (-0.513739) | 0.397980 / 0.579283 (-0.181303) | 0.426638 / 0.434364 (-0.007726) | 0.474249 / 0.540337 (-0.066088) | 0.677640 / 1.386936 (-0.709296) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#90b3d2619ecb8f01dd12283c30f04dfe6e443795 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006536 / 0.011353 (-0.004817) | 0.003827 / 0.011008 (-0.007181) | 0.084394 / 0.038508 (0.045886) | 0.073166 / 0.023109 (0.050056) | 0.309380 / 0.275898 (0.033482) | 0.338501 / 0.323480 (0.015021) | 0.005346 / 0.007986 (-0.002640) | 0.003273 / 0.004328 (-0.001056) | 0.064606 / 0.004250 (0.060356) | 0.053500 / 0.037052 (0.016447) | 0.313143 / 0.258489 (0.054654) | 0.354364 / 0.293841 (0.060523) | 0.030919 / 0.128546 (-0.097627) | 0.008512 / 0.075646 (-0.067134) | 0.292774 / 0.419271 (-0.126498) | 0.052441 / 0.043533 (0.008908) | 0.310503 / 0.255139 (0.055364) | 0.341211 / 0.283200 (0.058011) | 0.023608 / 0.141683 (-0.118074) | 1.456220 / 1.452155 (0.004065) | 1.540189 / 1.492716 (0.047473) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.234321 / 0.018006 (0.216315) | 0.451809 / 0.000490 (0.451319) | 0.008560 / 0.000200 (0.008360) | 0.000085 / 0.000054 (0.000031) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028165 / 0.037411 (-0.009246) | 0.082548 / 0.014526 (0.068023) | 0.752621 / 0.176557 (0.576065) | 0.263949 / 0.737135 (-0.473187) | 0.097635 / 0.296338 (-0.198704) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.386611 / 0.215209 (0.171402) | 3.847528 / 2.077655 (1.769873) | 1.859173 / 1.504120 (0.355053) | 1.685269 / 1.541195 (0.144074) | 1.715823 / 1.468490 (0.247333) | 0.485272 / 4.584777 (-4.099505) | 3.500724 / 3.745712 (-0.244988) | 3.252149 / 5.269862 (-2.017713) | 2.052914 / 4.565676 (-2.512762) | 0.056794 / 0.424275 (-0.367481) | 0.007317 / 0.007607 (-0.000291) | 0.457924 / 0.226044 (0.231879) | 4.570092 / 2.268929 (2.301163) | 2.328829 / 55.444624 (-53.115796) | 1.986502 / 6.876477 (-4.889975) | 2.164645 / 2.142072 (0.022573) | 0.580455 / 4.805227 (-4.224772) | 0.134415 / 6.500664 (-6.366249) | 0.060506 / 0.075469 (-0.014963) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.267423 / 1.841788 (-0.574364) | 18.653450 / 8.074308 (10.579142) | 13.919682 / 10.191392 (3.728290) | 0.144001 / 0.680424 (-0.536423) | 0.018218 / 0.534201 (-0.515983) | 0.389933 / 0.579283 (-0.189350) | 0.418366 / 0.434364 (-0.015998) | 0.456341 / 0.540337 (-0.083997) | 0.631401 / 1.386936 (-0.755535) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006838 / 0.011353 (-0.004515) | 0.003973 / 0.011008 (-0.007036) | 0.065217 / 0.038508 (0.026709) | 0.068357 / 0.023109 (0.045248) | 0.407960 / 0.275898 (0.132062) | 0.437794 / 0.323480 (0.114314) | 0.005398 / 0.007986 (-0.002587) | 0.003360 / 0.004328 (-0.000969) | 0.065503 / 0.004250 (0.061253) | 0.055676 / 0.037052 (0.018623) | 0.411381 / 0.258489 (0.152892) | 0.446902 / 0.293841 (0.153061) | 0.032156 / 0.128546 (-0.096390) | 0.008702 / 0.075646 (-0.066944) | 0.072295 / 0.419271 (-0.346976) | 0.047722 / 0.043533 (0.004189) | 0.406125 / 0.255139 (0.150986) | 0.428359 / 0.283200 (0.145160) | 0.021901 / 0.141683 (-0.119782) | 1.464186 / 1.452155 (0.012032) | 1.532809 / 1.492716 (0.040093) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.218505 / 0.018006 (0.200499) | 0.447450 / 0.000490 (0.446961) | 0.006509 / 0.000200 (0.006309) | 0.000099 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031789 / 0.037411 (-0.005622) | 0.091100 / 0.014526 (0.076574) | 0.102812 / 0.176557 (-0.073745) | 0.155988 / 0.737135 (-0.581147) | 0.103983 / 0.296338 (-0.192355) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436431 / 0.215209 (0.221222) | 4.336072 / 2.077655 (2.258417) | 2.344613 / 1.504120 (0.840493) | 2.173513 / 1.541195 (0.632319) | 2.313134 / 1.468490 (0.844644) | 0.493651 / 4.584777 (-4.091126) | 3.657541 / 3.745712 (-0.088171) | 3.289933 / 5.269862 (-1.979928) | 2.040271 / 4.565676 (-2.525406) | 0.058092 / 0.424275 (-0.366183) | 0.007348 / 0.007607 (-0.000259) | 0.507506 / 0.226044 (0.281462) | 5.093477 / 2.268929 (2.824548) | 2.770579 / 55.444624 (-52.674046) | 2.449507 / 6.876477 (-4.426970) | 2.645470 / 2.142072 (0.503397) | 0.590799 / 4.805227 (-4.214429) | 0.133411 / 6.500664 (-6.367253) | 0.059507 / 0.075469 (-0.015962) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.381148 / 1.841788 (-0.460639) | 19.188716 / 8.074308 (11.114408) | 14.709111 / 10.191392 (4.517719) | 0.191104 / 0.680424 (-0.489320) | 0.019862 / 0.534201 (-0.514339) | 0.395380 / 0.579283 (-0.183903) | 0.424757 / 0.434364 (-0.009607) | 0.468810 / 0.540337 (-0.071527) | 0.687058 / 1.386936 (-0.699878) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#407169e1ea91ae31f79ff29c4115b04a461279ab \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008872 / 0.011353 (-0.002481) | 0.004824 / 0.011008 (-0.006184) | 0.097012 / 0.038508 (0.058504) | 0.074728 / 0.023109 (0.051619) | 0.400604 / 0.275898 (0.124706) | 0.434316 / 0.323480 (0.110836) | 0.006025 / 0.007986 (-0.001961) | 0.004153 / 0.004328 (-0.000176) | 0.074093 / 0.004250 (0.069842) | 0.057239 / 0.037052 (0.020187) | 0.420611 / 0.258489 (0.162122) | 0.457779 / 0.293841 (0.163938) | 0.047610 / 0.128546 (-0.080936) | 0.014577 / 0.075646 (-0.061069) | 0.414351 / 0.419271 (-0.004921) | 0.063072 / 0.043533 (0.019539) | 0.426141 / 0.255139 (0.171002) | 0.429844 / 0.283200 (0.146644) | 0.034754 / 0.141683 (-0.106929) | 1.620946 / 1.452155 (0.168792) | 1.725831 / 1.492716 (0.233115) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.304712 / 0.018006 (0.286706) | 0.646924 / 0.000490 (0.646434) | 0.014486 / 0.000200 (0.014286) | 0.000626 / 0.000054 (0.000572) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034935 / 0.037411 (-0.002477) | 0.085788 / 0.014526 (0.071262) | 0.107749 / 0.176557 (-0.068807) | 0.170924 / 0.737135 (-0.566211) | 0.134985 / 0.296338 (-0.161354) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.602913 / 0.215209 (0.387704) | 6.041700 / 2.077655 (3.964045) | 2.539970 / 1.504120 (1.035850) | 2.184166 / 1.541195 (0.642972) | 2.241783 / 1.468490 (0.773293) | 0.864601 / 4.584777 (-3.720176) | 5.246955 / 3.745712 (1.501243) | 4.850458 / 5.269862 (-0.419404) | 3.101497 / 4.565676 (-1.464179) | 0.098591 / 0.424275 (-0.325684) | 0.008902 / 0.007607 (0.001295) | 0.732278 / 0.226044 (0.506234) | 7.163557 / 2.268929 (4.894629) | 3.226444 / 55.444624 (-52.218180) | 2.578737 / 6.876477 (-4.297740) | 2.850212 / 2.142072 (0.708140) | 1.026390 / 4.805227 (-3.778837) | 0.217077 / 6.500664 (-6.283587) | 0.080344 / 0.075469 (0.004875) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.687488 / 1.841788 (-0.154300) | 24.686337 / 8.074308 (16.612029) | 21.315989 / 10.191392 (11.124597) | 0.226176 / 0.680424 (-0.454248) | 0.035774 / 0.534201 (-0.498427) | 0.477807 / 0.579283 (-0.101476) | 0.636305 / 0.434364 (0.201941) | 0.553341 / 0.540337 (0.013003) | 0.797267 / 1.386936 (-0.589669) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008955 / 0.011353 (-0.002398) | 0.006099 / 0.011008 (-0.004909) | 0.086306 / 0.038508 (0.047798) | 0.090783 / 0.023109 (0.067674) | 0.554802 / 0.275898 (0.278904) | 0.598778 / 0.323480 (0.275299) | 0.008656 / 0.007986 (0.000670) | 0.004487 / 0.004328 (0.000159) | 0.084194 / 0.004250 (0.079943) | 0.076048 / 0.037052 (0.038996) | 0.533212 / 0.258489 (0.274723) | 0.584029 / 0.293841 (0.290188) | 0.051913 / 0.128546 (-0.076634) | 0.014253 / 0.075646 (-0.061393) | 0.100500 / 0.419271 (-0.318772) | 0.061092 / 0.043533 (0.017560) | 0.516955 / 0.255139 (0.261816) | 0.562754 / 0.283200 (0.279554) | 0.036673 / 0.141683 (-0.105010) | 1.853655 / 1.452155 (0.401501) | 1.968358 / 1.492716 (0.475642) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.308258 / 0.018006 (0.290252) | 0.630492 / 0.000490 (0.630002) | 0.010575 / 0.000200 (0.010375) | 0.000271 / 0.000054 (0.000217) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034762 / 0.037411 (-0.002649) | 0.107314 / 0.014526 (0.092788) | 0.132160 / 0.176557 (-0.044396) | 0.178737 / 0.737135 (-0.558398) | 0.125988 / 0.296338 (-0.170351) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.730738 / 0.215209 (0.515528) | 7.240393 / 2.077655 (5.162738) | 3.557665 / 1.504120 (2.053545) | 3.541425 / 1.541195 (2.000230) | 3.103849 / 1.468490 (1.635359) | 0.926843 / 4.584777 (-3.657934) | 5.818264 / 3.745712 (2.072552) | 5.012984 / 5.269862 (-0.256878) | 3.286085 / 4.565676 (-1.279591) | 0.104879 / 0.424275 (-0.319396) | 0.009010 / 0.007607 (0.001403) | 0.806145 / 0.226044 (0.580101) | 8.263655 / 2.268929 (5.994727) | 4.108932 / 55.444624 (-51.335693) | 3.454613 / 6.876477 (-3.421864) | 3.629045 / 2.142072 (1.486973) | 1.062325 / 4.805227 (-3.742902) | 0.220482 / 6.500664 (-6.280182) | 0.081440 / 0.075469 (0.005970) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.665587 / 1.841788 (-0.176201) | 23.695299 / 8.074308 (15.620991) | 22.917493 / 10.191392 (12.726101) | 0.259033 / 0.680424 (-0.421391) | 0.040118 / 0.534201 (-0.494083) | 0.487329 / 0.579283 (-0.091954) | 0.607482 / 0.434364 (0.173118) | 0.568383 / 0.540337 (0.028045) | 0.824486 / 1.386936 (-0.562450) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#53592bb8f635a1d6ea3e77acc290efdfb28fcbd7 \"CML watermark\")\n", "CI failures are unrelated", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007095 / 0.011353 (-0.004258) | 0.004260 / 0.011008 (-0.006748) | 0.084729 / 0.038508 (0.046221) | 0.076498 / 0.023109 (0.053389) | 0.325981 / 0.275898 (0.050083) | 0.357140 / 0.323480 (0.033661) | 0.004325 / 0.007986 (-0.003660) | 0.003632 / 0.004328 (-0.000696) | 0.065075 / 0.004250 (0.060824) | 0.059058 / 0.037052 (0.022006) | 0.331895 / 0.258489 (0.073406) | 0.370782 / 0.293841 (0.076941) | 0.031886 / 0.128546 (-0.096660) | 0.008782 / 0.075646 (-0.066864) | 0.288159 / 0.419271 (-0.131113) | 0.053012 / 0.043533 (0.009479) | 0.319992 / 0.255139 (0.064853) | 0.347061 / 0.283200 (0.063861) | 0.026365 / 0.141683 (-0.115317) | 1.486112 / 1.452155 (0.033958) | 1.570150 / 1.492716 (0.077434) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.277155 / 0.018006 (0.259149) | 0.573507 / 0.000490 (0.573017) | 0.010122 / 0.000200 (0.009922) | 0.000322 / 0.000054 (0.000268) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029076 / 0.037411 (-0.008335) | 0.082517 / 0.014526 (0.067991) | 0.100710 / 0.176557 (-0.075847) | 0.154529 / 0.737135 (-0.582606) | 0.099531 / 0.296338 (-0.196807) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382058 / 0.215209 (0.166849) | 3.803307 / 2.077655 (1.725652) | 1.834107 / 1.504120 (0.329987) | 1.665703 / 1.541195 (0.124508) | 1.739520 / 1.468490 (0.271030) | 0.490544 / 4.584777 (-4.094233) | 3.577874 / 3.745712 (-0.167838) | 3.327631 / 5.269862 (-1.942231) | 2.056634 / 4.565676 (-2.509043) | 0.057871 / 0.424275 (-0.366404) | 0.007326 / 0.007607 (-0.000281) | 0.453993 / 0.226044 (0.227949) | 4.549179 / 2.268929 (2.280250) | 2.320304 / 55.444624 (-53.124321) | 1.966082 / 6.876477 (-4.910395) | 2.189979 / 2.142072 (0.047907) | 0.586678 / 4.805227 (-4.218549) | 0.134919 / 6.500664 (-6.365745) | 0.061649 / 0.075469 (-0.013820) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.286228 / 1.841788 (-0.555560) | 19.409674 / 8.074308 (11.335366) | 14.290463 / 10.191392 (4.099071) | 0.165766 / 0.680424 (-0.514658) | 0.018200 / 0.534201 (-0.516001) | 0.390526 / 0.579283 (-0.188757) | 0.410953 / 0.434364 (-0.023411) | 0.455921 / 0.540337 (-0.084416) | 0.642271 / 1.386936 (-0.744665) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007288 / 0.011353 (-0.004064) | 0.004348 / 0.011008 (-0.006660) | 0.065935 / 0.038508 (0.027427) | 0.087327 / 0.023109 (0.064218) | 0.413461 / 0.275898 (0.137563) | 0.458904 / 0.323480 (0.135424) | 0.005996 / 0.007986 (-0.001990) | 0.003648 / 0.004328 (-0.000680) | 0.066578 / 0.004250 (0.062328) | 0.062072 / 0.037052 (0.025020) | 0.418469 / 0.258489 (0.159980) | 0.468960 / 0.293841 (0.175119) | 0.032616 / 0.128546 (-0.095930) | 0.008961 / 0.075646 (-0.066686) | 0.072537 / 0.419271 (-0.346734) | 0.048302 / 0.043533 (0.004769) | 0.411845 / 0.255139 (0.156706) | 0.441730 / 0.283200 (0.158530) | 0.025038 / 0.141683 (-0.116645) | 1.519402 / 1.452155 (0.067248) | 1.601791 / 1.492716 (0.109074) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.322494 / 0.018006 (0.304488) | 0.570210 / 0.000490 (0.569720) | 0.025815 / 0.000200 (0.025615) | 0.000166 / 0.000054 (0.000111) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034657 / 0.037411 (-0.002754) | 0.096024 / 0.014526 (0.081498) | 0.109134 / 0.176557 (-0.067422) | 0.162170 / 0.737135 (-0.574965) | 0.110472 / 0.296338 (-0.185866) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.439032 / 0.215209 (0.223823) | 4.385768 / 2.077655 (2.308113) | 2.343261 / 1.504120 (0.839142) | 2.157926 / 1.541195 (0.616731) | 2.299193 / 1.468490 (0.830703) | 0.498961 / 4.584777 (-4.085816) | 3.651909 / 3.745712 (-0.093803) | 3.387587 / 5.269862 (-1.882275) | 2.144553 / 4.565676 (-2.421123) | 0.058242 / 0.424275 (-0.366033) | 0.007416 / 0.007607 (-0.000191) | 0.512714 / 0.226044 (0.286670) | 5.138569 / 2.268929 (2.869641) | 2.778683 / 55.444624 (-52.665941) | 2.532990 / 6.876477 (-4.343487) | 2.782211 / 2.142072 (0.640139) | 0.591881 / 4.805227 (-4.213346) | 0.135005 / 6.500664 (-6.365660) | 0.060965 / 0.075469 (-0.014504) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.356311 / 1.841788 (-0.485477) | 20.029994 / 8.074308 (11.955686) | 14.666570 / 10.191392 (4.475178) | 0.164363 / 0.680424 (-0.516061) | 0.020685 / 0.534201 (-0.513516) | 0.396020 / 0.579283 (-0.183263) | 0.429407 / 0.434364 (-0.004957) | 0.476924 / 0.540337 (-0.063413) | 0.693389 / 1.386936 (-0.693547) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#292d627e398e30a538a616395f3b5ce4e89bb1e8 \"CML watermark\")\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006761 / 0.011353 (-0.004592) | 0.004307 / 0.011008 (-0.006701) | 0.084682 / 0.038508 (0.046174) | 0.083994 / 0.023109 (0.060885) | 0.316612 / 0.275898 (0.040714) | 0.346157 / 0.323480 (0.022678) | 0.004490 / 0.007986 (-0.003495) | 0.003699 / 0.004328 (-0.000629) | 0.066144 / 0.004250 (0.061894) | 0.057958 / 0.037052 (0.020906) | 0.319018 / 0.258489 (0.060529) | 0.367597 / 0.293841 (0.073756) | 0.031146 / 0.128546 (-0.097401) | 0.008814 / 0.075646 (-0.066832) | 0.290971 / 0.419271 (-0.128301) | 0.052769 / 0.043533 (0.009236) | 0.313125 / 0.255139 (0.057986) | 0.330473 / 0.283200 (0.047273) | 0.025922 / 0.141683 (-0.115760) | 1.494989 / 1.452155 (0.042834) | 1.556140 / 1.492716 (0.063423) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.310580 / 0.018006 (0.292574) | 0.563600 / 0.000490 (0.563110) | 0.012344 / 0.000200 (0.012144) | 0.000382 / 0.000054 (0.000328) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031468 / 0.037411 (-0.005943) | 0.084856 / 0.014526 (0.070331) | 0.101371 / 0.176557 (-0.075186) | 0.158735 / 0.737135 (-0.578400) | 0.102451 / 0.296338 (-0.193888) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.402288 / 0.215209 (0.187079) | 4.001351 / 2.077655 (1.923696) | 2.022710 / 1.504120 (0.518590) | 1.850236 / 1.541195 (0.309041) | 1.946779 / 1.468490 (0.478289) | 0.485828 / 4.584777 (-4.098949) | 3.584925 / 3.745712 (-0.160787) | 3.400815 / 5.269862 (-1.869046) | 2.123187 / 4.565676 (-2.442490) | 0.057373 / 0.424275 (-0.366902) | 0.007383 / 0.007607 (-0.000224) | 0.479773 / 0.226044 (0.253729) | 4.805342 / 2.268929 (2.536414) | 2.530151 / 55.444624 (-52.914473) | 2.190136 / 6.876477 (-4.686341) | 2.463666 / 2.142072 (0.321593) | 0.583512 / 4.805227 (-4.221715) | 0.134205 / 6.500664 (-6.366459) | 0.062021 / 0.075469 (-0.013448) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.239532 / 1.841788 (-0.602255) | 20.252941 / 8.074308 (12.178633) | 14.265697 / 10.191392 (4.074305) | 0.158745 / 0.680424 (-0.521679) | 0.018605 / 0.534201 (-0.515596) | 0.394246 / 0.579283 (-0.185037) | 0.415260 / 0.434364 (-0.019104) | 0.462636 / 0.540337 (-0.077701) | 0.645318 / 1.386936 (-0.741618) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007063 / 0.011353 (-0.004290) | 0.004388 / 0.011008 (-0.006621) | 0.064997 / 0.038508 (0.026489) | 0.085135 / 0.023109 (0.062026) | 0.424349 / 0.275898 (0.148451) | 0.456033 / 0.323480 (0.132553) | 0.005745 / 0.007986 (-0.002241) | 0.003705 / 0.004328 (-0.000624) | 0.065835 / 0.004250 (0.061585) | 0.058366 / 0.037052 (0.021314) | 0.421654 / 0.258489 (0.163165) | 0.460334 / 0.293841 (0.166493) | 0.032828 / 0.128546 (-0.095718) | 0.008974 / 0.075646 (-0.066673) | 0.072524 / 0.419271 (-0.346747) | 0.048558 / 0.043533 (0.005025) | 0.413546 / 0.255139 (0.158407) | 0.435765 / 0.283200 (0.152565) | 0.023754 / 0.141683 (-0.117929) | 1.476884 / 1.452155 (0.024730) | 1.560011 / 1.492716 (0.067294) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.318279 / 0.018006 (0.300272) | 0.544990 / 0.000490 (0.544501) | 0.007118 / 0.000200 (0.006918) | 0.000097 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033352 / 0.037411 (-0.004059) | 0.092921 / 0.014526 (0.078395) | 0.109028 / 0.176557 (-0.067528) | 0.161433 / 0.737135 (-0.575703) | 0.108445 / 0.296338 (-0.187893) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.438925 / 0.215209 (0.223716) | 4.400714 / 2.077655 (2.323059) | 2.403727 / 1.504120 (0.899607) | 2.236472 / 1.541195 (0.695277) | 2.319219 / 1.468490 (0.850729) | 0.490159 / 4.584777 (-4.094618) | 3.647474 / 3.745712 (-0.098238) | 3.433144 / 5.269862 (-1.836718) | 2.145367 / 4.565676 (-2.420310) | 0.057994 / 0.424275 (-0.366281) | 0.007452 / 0.007607 (-0.000155) | 0.513808 / 0.226044 (0.287763) | 5.130792 / 2.268929 (2.861863) | 2.861691 / 55.444624 (-52.582934) | 2.473292 / 6.876477 (-4.403185) | 2.756445 / 2.142072 (0.614372) | 0.586783 / 4.805227 (-4.218444) | 0.134170 / 6.500664 (-6.366494) | 0.061149 / 0.075469 (-0.014320) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350144 / 1.841788 (-0.491644) | 21.003528 / 8.074308 (12.929220) | 15.174314 / 10.191392 (4.982922) | 0.186535 / 0.680424 (-0.493888) | 0.020821 / 0.534201 (-0.513380) | 0.399210 / 0.579283 (-0.180073) | 0.431942 / 0.434364 (-0.002422) | 0.475395 / 0.540337 (-0.064942) | 0.677457 / 1.386936 (-0.709479) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6aa5fc278324a253eab43ad1bc048e822e4ae5c7 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007062 / 0.011353 (-0.004291) | 0.004299 / 0.011008 (-0.006710) | 0.086019 / 0.038508 (0.047511) | 0.085166 / 0.023109 (0.062057) | 0.355804 / 0.275898 (0.079906) | 0.381056 / 0.323480 (0.057577) | 0.005500 / 0.007986 (-0.002486) | 0.003496 / 0.004328 (-0.000833) | 0.064866 / 0.004250 (0.060615) | 0.057399 / 0.037052 (0.020346) | 0.357914 / 0.258489 (0.099425) | 0.395387 / 0.293841 (0.101546) | 0.031763 / 0.128546 (-0.096784) | 0.008665 / 0.075646 (-0.066981) | 0.290097 / 0.419271 (-0.129175) | 0.053297 / 0.043533 (0.009765) | 0.355659 / 0.255139 (0.100520) | 0.378232 / 0.283200 (0.095032) | 0.026015 / 0.141683 (-0.115668) | 1.437121 / 1.452155 (-0.015034) | 1.538798 / 1.492716 (0.046082) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.243518 / 0.018006 (0.225511) | 0.461361 / 0.000490 (0.460871) | 0.009529 / 0.000200 (0.009329) | 0.000473 / 0.000054 (0.000419) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030379 / 0.037411 (-0.007032) | 0.089851 / 0.014526 (0.075325) | 0.098278 / 0.176557 (-0.078278) | 0.157077 / 0.737135 (-0.580058) | 0.098997 / 0.296338 (-0.197341) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382415 / 0.215209 (0.167206) | 3.801964 / 2.077655 (1.724309) | 1.887680 / 1.504120 (0.383560) | 1.775903 / 1.541195 (0.234709) | 1.851338 / 1.468490 (0.382848) | 0.483616 / 4.584777 (-4.101161) | 3.612977 / 3.745712 (-0.132736) | 3.397700 / 5.269862 (-1.872162) | 2.114572 / 4.565676 (-2.451105) | 0.057250 / 0.424275 (-0.367025) | 0.007362 / 0.007607 (-0.000245) | 0.456873 / 0.226044 (0.230829) | 4.567319 / 2.268929 (2.298391) | 2.399476 / 55.444624 (-53.045148) | 2.054542 / 6.876477 (-4.821935) | 2.343432 / 2.142072 (0.201359) | 0.582319 / 4.805227 (-4.222908) | 0.134045 / 6.500664 (-6.366619) | 0.062726 / 0.075469 (-0.012743) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.283390 / 1.841788 (-0.558398) | 20.358511 / 8.074308 (12.284202) | 14.933989 / 10.191392 (4.742597) | 0.164960 / 0.680424 (-0.515464) | 0.018625 / 0.534201 (-0.515576) | 0.394087 / 0.579283 (-0.185196) | 0.416761 / 0.434364 (-0.017603) | 0.466669 / 0.540337 (-0.073669) | 0.643161 / 1.386936 (-0.743775) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007141 / 0.011353 (-0.004212) | 0.004185 / 0.011008 (-0.006824) | 0.066097 / 0.038508 (0.027588) | 0.088436 / 0.023109 (0.065327) | 0.401189 / 0.275898 (0.125291) | 0.440402 / 0.323480 (0.116922) | 0.005729 / 0.007986 (-0.002257) | 0.003527 / 0.004328 (-0.000801) | 0.065278 / 0.004250 (0.061027) | 0.060866 / 0.037052 (0.023813) | 0.407035 / 0.258489 (0.148546) | 0.443923 / 0.293841 (0.150083) | 0.032922 / 0.128546 (-0.095625) | 0.008739 / 0.075646 (-0.066907) | 0.071800 / 0.419271 (-0.347472) | 0.048994 / 0.043533 (0.005461) | 0.403736 / 0.255139 (0.148597) | 0.419566 / 0.283200 (0.136366) | 0.025369 / 0.141683 (-0.116314) | 1.474980 / 1.452155 (0.022825) | 1.553500 / 1.492716 (0.060784) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.225224 / 0.018006 (0.207218) | 0.462891 / 0.000490 (0.462401) | 0.006958 / 0.000200 (0.006758) | 0.000163 / 0.000054 (0.000108) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034431 / 0.037411 (-0.002980) | 0.100021 / 0.014526 (0.085495) | 0.108339 / 0.176557 (-0.068217) | 0.162762 / 0.737135 (-0.574374) | 0.108951 / 0.296338 (-0.187388) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.435966 / 0.215209 (0.220757) | 4.351744 / 2.077655 (2.274089) | 2.372307 / 1.504120 (0.868187) | 2.192146 / 1.541195 (0.650951) | 2.326839 / 1.468490 (0.858349) | 0.488292 / 4.584777 (-4.096485) | 3.745227 / 3.745712 (-0.000485) | 3.456306 / 5.269862 (-1.813556) | 2.159771 / 4.565676 (-2.405906) | 0.057953 / 0.424275 (-0.366322) | 0.007469 / 0.007607 (-0.000138) | 0.515116 / 0.226044 (0.289071) | 5.162871 / 2.268929 (2.893942) | 2.850336 / 55.444624 (-52.594288) | 2.514700 / 6.876477 (-4.361777) | 2.748843 / 2.142072 (0.606770) | 0.587687 / 4.805227 (-4.217540) | 0.134333 / 6.500664 (-6.366331) | 0.062097 / 0.075469 (-0.013372) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.377082 / 1.841788 (-0.464705) | 21.103127 / 8.074308 (13.028819) | 15.325275 / 10.191392 (5.133883) | 0.166225 / 0.680424 (-0.514199) | 0.020472 / 0.534201 (-0.513729) | 0.395866 / 0.579283 (-0.183417) | 0.444964 / 0.434364 (0.010600) | 0.475367 / 0.540337 (-0.064970) | 0.693325 / 1.386936 (-0.693611) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#79b5bbbd52ffd90dd958c05b333d7c90a03756cc \"CML watermark\")\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006920 / 0.011353 (-0.004433) | 0.004306 / 0.011008 (-0.006703) | 0.085961 / 0.038508 (0.047453) | 0.087008 / 0.023109 (0.063899) | 0.308953 / 0.275898 (0.033055) | 0.349919 / 0.323480 (0.026440) | 0.005705 / 0.007986 (-0.002281) | 0.003565 / 0.004328 (-0.000763) | 0.066272 / 0.004250 (0.062022) | 0.056438 / 0.037052 (0.019385) | 0.312927 / 0.258489 (0.054437) | 0.363081 / 0.293841 (0.069240) | 0.031947 / 0.128546 (-0.096600) | 0.008801 / 0.075646 (-0.066845) | 0.288657 / 0.419271 (-0.130615) | 0.053746 / 0.043533 (0.010213) | 0.305815 / 0.255139 (0.050676) | 0.327174 / 0.283200 (0.043975) | 0.024863 / 0.141683 (-0.116820) | 1.489718 / 1.452155 (0.037563) | 1.566726 / 1.492716 (0.074009) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.289273 / 0.018006 (0.271266) | 0.555519 / 0.000490 (0.555029) | 0.006522 / 0.000200 (0.006322) | 0.000105 / 0.000054 (0.000051) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031968 / 0.037411 (-0.005443) | 0.085113 / 0.014526 (0.070587) | 0.103931 / 0.176557 (-0.072625) | 0.158471 / 0.737135 (-0.578665) | 0.102633 / 0.296338 (-0.193705) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.399592 / 0.215209 (0.184383) | 4.004453 / 2.077655 (1.926798) | 2.047224 / 1.504120 (0.543104) | 1.896203 / 1.541195 (0.355008) | 1.974056 / 1.468490 (0.505566) | 0.485964 / 4.584777 (-4.098813) | 3.650648 / 3.745712 (-0.095064) | 3.475953 / 5.269862 (-1.793908) | 2.168105 / 4.565676 (-2.397571) | 0.058167 / 0.424275 (-0.366108) | 0.007517 / 0.007607 (-0.000090) | 0.475386 / 0.226044 (0.249342) | 4.758300 / 2.268929 (2.489372) | 2.527540 / 55.444624 (-52.917085) | 2.180544 / 6.876477 (-4.695933) | 2.460148 / 2.142072 (0.318076) | 0.589944 / 4.805227 (-4.215284) | 0.136474 / 6.500664 (-6.364190) | 0.061462 / 0.075469 (-0.014007) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.245816 / 1.841788 (-0.595972) | 20.376958 / 8.074308 (12.302650) | 14.764579 / 10.191392 (4.573187) | 0.152436 / 0.680424 (-0.527988) | 0.018580 / 0.534201 (-0.515621) | 0.394680 / 0.579283 (-0.184603) | 0.424162 / 0.434364 (-0.010202) | 0.465604 / 0.540337 (-0.074733) | 0.658531 / 1.386936 (-0.728405) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007105 / 0.011353 (-0.004248) | 0.004441 / 0.011008 (-0.006567) | 0.068792 / 0.038508 (0.030284) | 0.080371 / 0.023109 (0.057262) | 0.430263 / 0.275898 (0.154365) | 0.451743 / 0.323480 (0.128263) | 0.005987 / 0.007986 (-0.001999) | 0.003639 / 0.004328 (-0.000690) | 0.065462 / 0.004250 (0.061212) | 0.059852 / 0.037052 (0.022800) | 0.438390 / 0.258489 (0.179901) | 0.458679 / 0.293841 (0.164838) | 0.033044 / 0.128546 (-0.095502) | 0.008845 / 0.075646 (-0.066802) | 0.071772 / 0.419271 (-0.347500) | 0.048840 / 0.043533 (0.005307) | 0.415707 / 0.255139 (0.160568) | 0.431216 / 0.283200 (0.148017) | 0.024422 / 0.141683 (-0.117260) | 1.502249 / 1.452155 (0.050094) | 1.566767 / 1.492716 (0.074050) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.311352 / 0.018006 (0.293346) | 0.550395 / 0.000490 (0.549906) | 0.005190 / 0.000200 (0.004990) | 0.000116 / 0.000054 (0.000062) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034264 / 0.037411 (-0.003147) | 0.098712 / 0.014526 (0.084186) | 0.110906 / 0.176557 (-0.065651) | 0.161670 / 0.737135 (-0.575465) | 0.111023 / 0.296338 (-0.185316) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.435296 / 0.215209 (0.220087) | 4.331231 / 2.077655 (2.253576) | 2.305009 / 1.504120 (0.800889) | 2.154492 / 1.541195 (0.613297) | 2.344017 / 1.468490 (0.875527) | 0.496924 / 4.584777 (-4.087853) | 3.750782 / 3.745712 (0.005070) | 3.380193 / 5.269862 (-1.889669) | 2.161239 / 4.565676 (-2.404438) | 0.058456 / 0.424275 (-0.365819) | 0.007395 / 0.007607 (-0.000212) | 0.507824 / 0.226044 (0.281780) | 5.081564 / 2.268929 (2.812635) | 2.824080 / 55.444624 (-52.620544) | 2.458835 / 6.876477 (-4.417642) | 2.747897 / 2.142072 (0.605824) | 0.600727 / 4.805227 (-4.204500) | 0.135085 / 6.500664 (-6.365579) | 0.060506 / 0.075469 (-0.014963) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.376873 / 1.841788 (-0.464915) | 21.211922 / 8.074308 (13.137614) | 15.022845 / 10.191392 (4.831453) | 0.195388 / 0.680424 (-0.485036) | 0.020268 / 0.534201 (-0.513933) | 0.398971 / 0.579283 (-0.180312) | 0.427588 / 0.434364 (-0.006776) | 0.478044 / 0.540337 (-0.062293) | 0.687904 / 1.386936 (-0.699033) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7fb5fae8f79b3db4a94013aa2af7c63796ef2d64 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006134 / 0.011353 (-0.005219) | 0.003655 / 0.011008 (-0.007354) | 0.081295 / 0.038508 (0.042787) | 0.060202 / 0.023109 (0.037093) | 0.330005 / 0.275898 (0.054107) | 0.361219 / 0.323480 (0.037739) | 0.004766 / 0.007986 (-0.003220) | 0.002942 / 0.004328 (-0.001386) | 0.063322 / 0.004250 (0.059072) | 0.047844 / 0.037052 (0.010791) | 0.340375 / 0.258489 (0.081886) | 0.406301 / 0.293841 (0.112460) | 0.027474 / 0.128546 (-0.101072) | 0.007991 / 0.075646 (-0.067655) | 0.262746 / 0.419271 (-0.156526) | 0.045575 / 0.043533 (0.002042) | 0.324123 / 0.255139 (0.068984) | 0.344399 / 0.283200 (0.061199) | 0.021806 / 0.141683 (-0.119877) | 1.425390 / 1.452155 (-0.026765) | 1.487920 / 1.492716 (-0.004796) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.217504 / 0.018006 (0.199498) | 0.420878 / 0.000490 (0.420388) | 0.007312 / 0.000200 (0.007112) | 0.000218 / 0.000054 (0.000163) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023507 / 0.037411 (-0.013905) | 0.073493 / 0.014526 (0.058967) | 0.084857 / 0.176557 (-0.091700) | 0.145130 / 0.737135 (-0.592005) | 0.085204 / 0.296338 (-0.211135) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.388767 / 0.215209 (0.173557) | 3.877998 / 2.077655 (1.800344) | 1.881447 / 1.504120 (0.377327) | 1.714555 / 1.541195 (0.173360) | 1.772551 / 1.468490 (0.304061) | 0.505146 / 4.584777 (-4.079631) | 3.045471 / 3.745712 (-0.700241) | 2.834436 / 5.269862 (-2.435426) | 1.859896 / 4.565676 (-2.705780) | 0.057806 / 0.424275 (-0.366469) | 0.006378 / 0.007607 (-0.001229) | 0.458339 / 0.226044 (0.232294) | 4.588125 / 2.268929 (2.319196) | 2.302215 / 55.444624 (-53.142409) | 1.981297 / 6.876477 (-4.895180) | 2.152967 / 2.142072 (0.010895) | 0.590166 / 4.805227 (-4.215061) | 0.125753 / 6.500664 (-6.374911) | 0.061583 / 0.075469 (-0.013887) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.232195 / 1.841788 (-0.609593) | 17.761159 / 8.074308 (9.686851) | 13.829498 / 10.191392 (3.638106) | 0.131936 / 0.680424 (-0.548488) | 0.016909 / 0.534201 (-0.517292) | 0.332615 / 0.579283 (-0.246668) | 0.358149 / 0.434364 (-0.076215) | 0.384251 / 0.540337 (-0.156087) | 0.536453 / 1.386936 (-0.850483) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006253 / 0.011353 (-0.005100) | 0.003639 / 0.011008 (-0.007370) | 0.062810 / 0.038508 (0.024302) | 0.063761 / 0.023109 (0.040652) | 0.450538 / 0.275898 (0.174640) | 0.483793 / 0.323480 (0.160313) | 0.004973 / 0.007986 (-0.003013) | 0.002918 / 0.004328 (-0.001411) | 0.062140 / 0.004250 (0.057889) | 0.050328 / 0.037052 (0.013275) | 0.455860 / 0.258489 (0.197371) | 0.492399 / 0.293841 (0.198558) | 0.028928 / 0.128546 (-0.099618) | 0.008166 / 0.075646 (-0.067481) | 0.067860 / 0.419271 (-0.351411) | 0.040990 / 0.043533 (-0.002542) | 0.451343 / 0.255139 (0.196204) | 0.473769 / 0.283200 (0.190569) | 0.021585 / 0.141683 (-0.120097) | 1.451040 / 1.452155 (-0.001115) | 1.516065 / 1.492716 (0.023349) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230994 / 0.018006 (0.212988) | 0.428404 / 0.000490 (0.427915) | 0.003777 / 0.000200 (0.003577) | 0.000074 / 0.000054 (0.000020) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027394 / 0.037411 (-0.010018) | 0.081692 / 0.014526 (0.067166) | 0.091568 / 0.176557 (-0.084988) | 0.146149 / 0.737135 (-0.590987) | 0.092200 / 0.296338 (-0.204139) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.467086 / 0.215209 (0.251877) | 4.664862 / 2.077655 (2.587207) | 2.575703 / 1.504120 (1.071583) | 2.396587 / 1.541195 (0.855392) | 2.506064 / 1.468490 (1.037574) | 0.511942 / 4.584777 (-4.072834) | 3.196320 / 3.745712 (-0.549392) | 2.916627 / 5.269862 (-2.353235) | 1.919372 / 4.565676 (-2.646305) | 0.058769 / 0.424275 (-0.365506) | 0.006487 / 0.007607 (-0.001120) | 0.539095 / 0.226044 (0.313051) | 5.404675 / 2.268929 (3.135746) | 2.988962 / 55.444624 (-52.455662) | 2.670134 / 6.876477 (-4.206343) | 2.837414 / 2.142072 (0.695342) | 0.614776 / 4.805227 (-4.190451) | 0.125806 / 6.500664 (-6.374858) | 0.061593 / 0.075469 (-0.013876) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.346171 / 1.841788 (-0.495617) | 18.374626 / 8.074308 (10.300318) | 14.508723 / 10.191392 (4.317331) | 0.146771 / 0.680424 (-0.533652) | 0.018438 / 0.534201 (-0.515763) | 0.336944 / 0.579283 (-0.242339) | 0.385631 / 0.434364 (-0.048733) | 0.391922 / 0.540337 (-0.148416) | 0.568904 / 1.386936 (-0.818032) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3e8d420808718c9a1453a2e7ee3484ca12c9c70d \"CML watermark\")\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006695 / 0.011353 (-0.004658) | 0.004321 / 0.011008 (-0.006687) | 0.084558 / 0.038508 (0.046050) | 0.076290 / 0.023109 (0.053181) | 0.312331 / 0.275898 (0.036433) | 0.349854 / 0.323480 (0.026374) | 0.004267 / 0.007986 (-0.003719) | 0.003595 / 0.004328 (-0.000733) | 0.065077 / 0.004250 (0.060826) | 0.057461 / 0.037052 (0.020409) | 0.314989 / 0.258489 (0.056500) | 0.364767 / 0.293841 (0.070926) | 0.031726 / 0.128546 (-0.096820) | 0.008674 / 0.075646 (-0.066972) | 0.288282 / 0.419271 (-0.130990) | 0.052845 / 0.043533 (0.009312) | 0.317501 / 0.255139 (0.062362) | 0.333241 / 0.283200 (0.050041) | 0.026412 / 0.141683 (-0.115271) | 1.475648 / 1.452155 (0.023493) | 1.551656 / 1.492716 (0.058939) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.276512 / 0.018006 (0.258506) | 0.576350 / 0.000490 (0.575861) | 0.009518 / 0.000200 (0.009318) | 0.000280 / 0.000054 (0.000226) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029332 / 0.037411 (-0.008079) | 0.082904 / 0.014526 (0.068379) | 0.102516 / 0.176557 (-0.074041) | 0.159355 / 0.737135 (-0.577780) | 0.104112 / 0.296338 (-0.192226) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.379144 / 0.215209 (0.163935) | 3.785283 / 2.077655 (1.707629) | 1.833753 / 1.504120 (0.329633) | 1.667906 / 1.541195 (0.126711) | 1.751551 / 1.468490 (0.283061) | 0.480998 / 4.584777 (-4.103779) | 3.533433 / 3.745712 (-0.212279) | 3.343363 / 5.269862 (-1.926498) | 2.094169 / 4.565676 (-2.471508) | 0.056613 / 0.424275 (-0.367662) | 0.007410 / 0.007607 (-0.000197) | 0.455077 / 0.226044 (0.229033) | 4.541380 / 2.268929 (2.272452) | 2.269151 / 55.444624 (-53.175473) | 1.955663 / 6.876477 (-4.920814) | 2.227663 / 2.142072 (0.085591) | 0.580597 / 4.805227 (-4.224630) | 0.135034 / 6.500664 (-6.365630) | 0.062091 / 0.075469 (-0.013378) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.276295 / 1.841788 (-0.565492) | 20.072827 / 8.074308 (11.998519) | 14.296462 / 10.191392 (4.105070) | 0.164936 / 0.680424 (-0.515488) | 0.018415 / 0.534201 (-0.515786) | 0.390894 / 0.579283 (-0.188389) | 0.415515 / 0.434364 (-0.018849) | 0.462798 / 0.540337 (-0.077540) | 0.650099 / 1.386936 (-0.736837) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007218 / 0.011353 (-0.004135) | 0.004246 / 0.011008 (-0.006763) | 0.065818 / 0.038508 (0.027310) | 0.087315 / 0.023109 (0.064206) | 0.406449 / 0.275898 (0.130551) | 0.442008 / 0.323480 (0.118528) | 0.005752 / 0.007986 (-0.002233) | 0.003624 / 0.004328 (-0.000704) | 0.065349 / 0.004250 (0.061099) | 0.062423 / 0.037052 (0.025371) | 0.410099 / 0.258489 (0.151610) | 0.448929 / 0.293841 (0.155088) | 0.032498 / 0.128546 (-0.096048) | 0.008877 / 0.075646 (-0.066770) | 0.071611 / 0.419271 (-0.347661) | 0.048038 / 0.043533 (0.004506) | 0.407957 / 0.255139 (0.152818) | 0.424045 / 0.283200 (0.140846) | 0.025222 / 0.141683 (-0.116461) | 1.496191 / 1.452155 (0.044037) | 1.580765 / 1.492716 (0.088048) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.274798 / 0.018006 (0.256792) | 0.581410 / 0.000490 (0.580920) | 0.007302 / 0.000200 (0.007102) | 0.000160 / 0.000054 (0.000106) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034068 / 0.037411 (-0.003343) | 0.096116 / 0.014526 (0.081590) | 0.110234 / 0.176557 (-0.066323) | 0.163246 / 0.737135 (-0.573889) | 0.110250 / 0.296338 (-0.186089) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.442381 / 0.215209 (0.227172) | 4.427061 / 2.077655 (2.349406) | 2.361013 / 1.504120 (0.856893) | 2.185048 / 1.541195 (0.643853) | 2.312544 / 1.468490 (0.844054) | 0.498347 / 4.584777 (-4.086430) | 3.640839 / 3.745712 (-0.104873) | 3.353405 / 5.269862 (-1.916457) | 2.082038 / 4.565676 (-2.483638) | 0.058786 / 0.424275 (-0.365489) | 0.007403 / 0.007607 (-0.000205) | 0.517894 / 0.226044 (0.291850) | 5.184257 / 2.268929 (2.915329) | 2.838467 / 55.444624 (-52.606157) | 2.511116 / 6.876477 (-4.365361) | 2.757816 / 2.142072 (0.615743) | 0.644050 / 4.805227 (-4.161177) | 0.136446 / 6.500664 (-6.364218) | 0.062219 / 0.075469 (-0.013250) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350916 / 1.841788 (-0.490872) | 20.549280 / 8.074308 (12.474972) | 14.697569 / 10.191392 (4.506177) | 0.149818 / 0.680424 (-0.530606) | 0.020187 / 0.534201 (-0.514014) | 0.396008 / 0.579283 (-0.183275) | 0.427535 / 0.434364 (-0.006829) | 0.484544 / 0.540337 (-0.055794) | 0.687076 / 1.386936 (-0.699860) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#02a0d7cc9bdbc745c355c0bf8a210d8bf0b90327 \"CML watermark\")\n", "I'd rather be consistent with `huggingface_hub` and have this module in `utils/` with the exceptions exposed in `utils/__init__.py` ...", "Ok, I'll close this PR.\r\n\r\n> Maybe we could ask huggingface_hub to align with the rest of open-source libraries and expose the errors/exceptions at the root of the library...\r\n\r\ncc @Wauplin \r\n\r\nIt would be nice to have an HF style guide to ensure consistency across our libraries 🙂. ", "I can expose exceptions at root level yes.\r\n\r\nAbout having guidelines and consistency, let's try to do our best but it's not really in the essence of HF to formalize stuff in libraries :unamused: " ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008112 / 0.011353 (-0.003241) | 0.004762 / 0.011008 (-0.006247) | 0.101349 / 0.038508 (0.062841) | 0.092361 / 0.023109 (0.069252) | 0.418429 / 0.275898 (0.142531) | 0.427332 / 0.323480 (0.103852) | 0.006112 / 0.007986 (-0.001874) | 0.003920 / 0.004328 (-0.000408) | 0.076813 / 0.004250 (0.072563) | 0.064361 / 0.037052 (0.027309) | 0.420526 / 0.258489 (0.162037) | 0.441576 / 0.293841 (0.147735) | 0.044760 / 0.128546 (-0.083787) | 0.010054 / 0.075646 (-0.065592) | 0.346063 / 0.419271 (-0.073209) | 0.077453 / 0.043533 (0.033920) | 0.412871 / 0.255139 (0.157732) | 0.408307 / 0.283200 (0.125107) | 0.033398 / 0.141683 (-0.108285) | 1.755825 / 1.452155 (0.303671) | 1.852347 / 1.492716 (0.359630) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.274201 / 0.018006 (0.256194) | 0.536375 / 0.000490 (0.535885) | 0.008076 / 0.000200 (0.007876) | 0.000159 / 0.000054 (0.000105) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033567 / 0.037411 (-0.003845) | 0.102378 / 0.014526 (0.087852) | 0.114176 / 0.176557 (-0.062381) | 0.180576 / 0.737135 (-0.556560) | 0.114801 / 0.296338 (-0.181538) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.450300 / 0.215209 (0.235091) | 4.490940 / 2.077655 (2.413285) | 2.172412 / 1.504120 (0.668292) | 1.978746 / 1.541195 (0.437551) | 2.065602 / 1.468490 (0.597112) | 0.571260 / 4.584777 (-4.013517) | 4.185485 / 3.745712 (0.439773) | 3.885594 / 5.269862 (-1.384268) | 2.532942 / 4.565676 (-2.032735) | 0.067612 / 0.424275 (-0.356663) | 0.008694 / 0.007607 (0.001087) | 0.533375 / 0.226044 (0.307331) | 5.321261 / 2.268929 (3.052333) | 2.697788 / 55.444624 (-52.746836) | 2.331328 / 6.876477 (-4.545149) | 2.585168 / 2.142072 (0.443096) | 0.681760 / 4.805227 (-4.123467) | 0.157687 / 6.500664 (-6.342977) | 0.071014 / 0.075469 (-0.004455) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.525689 / 1.841788 (-0.316098) | 23.162280 / 8.074308 (15.087972) | 16.644941 / 10.191392 (6.453548) | 0.182588 / 0.680424 (-0.497836) | 0.021653 / 0.534201 (-0.512548) | 0.466556 / 0.579283 (-0.112727) | 0.511902 / 0.434364 (0.077538) | 0.553707 / 0.540337 (0.013370) | 0.777830 / 1.386936 (-0.609106) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007954 / 0.011353 (-0.003399) | 0.004645 / 0.011008 (-0.006363) | 0.079096 / 0.038508 (0.040587) | 0.088200 / 0.023109 (0.065090) | 0.508882 / 0.275898 (0.232984) | 0.545986 / 0.323480 (0.222506) | 0.006233 / 0.007986 (-0.001752) | 0.004016 / 0.004328 (-0.000312) | 0.078103 / 0.004250 (0.073853) | 0.066354 / 0.037052 (0.029302) | 0.504132 / 0.258489 (0.245643) | 0.543714 / 0.293841 (0.249873) | 0.038140 / 0.128546 (-0.090407) | 0.011201 / 0.075646 (-0.064446) | 0.085713 / 0.419271 (-0.333559) | 0.057169 / 0.043533 (0.013637) | 0.488161 / 0.255139 (0.233022) | 0.516231 / 0.283200 (0.233031) | 0.027868 / 0.141683 (-0.113814) | 1.794084 / 1.452155 (0.341930) | 1.884993 / 1.492716 (0.392276) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.263108 / 0.018006 (0.245102) | 0.495761 / 0.000490 (0.495272) | 0.007056 / 0.000200 (0.006856) | 0.000117 / 0.000054 (0.000062) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039089 / 0.037411 (0.001678) | 0.113332 / 0.014526 (0.098806) | 0.130137 / 0.176557 (-0.046419) | 0.189330 / 0.737135 (-0.547805) | 0.125860 / 0.296338 (-0.170479) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.530496 / 0.215209 (0.315287) | 5.349235 / 2.077655 (3.271581) | 2.975886 / 1.504120 (1.471766) | 2.786368 / 1.541195 (1.245173) | 2.920448 / 1.468490 (1.451958) | 0.575677 / 4.584777 (-4.009100) | 4.215535 / 3.745712 (0.469823) | 3.879984 / 5.269862 (-1.389878) | 2.420193 / 4.565676 (-2.145484) | 0.068506 / 0.424275 (-0.355769) | 0.008785 / 0.007607 (0.001178) | 0.611471 / 0.226044 (0.385427) | 6.118399 / 2.268929 (3.849471) | 3.509376 / 55.444624 (-51.935248) | 3.149219 / 6.876477 (-3.727257) | 3.413861 / 2.142072 (1.271788) | 0.697586 / 4.805227 (-4.107641) | 0.157767 / 6.500664 (-6.342897) | 0.071539 / 0.075469 (-0.003930) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.625196 / 1.841788 (-0.216591) | 24.347319 / 8.074308 (16.273011) | 17.365789 / 10.191392 (7.174397) | 0.217590 / 0.680424 (-0.462834) | 0.023885 / 0.534201 (-0.510316) | 0.477226 / 0.579283 (-0.102057) | 0.529319 / 0.434364 (0.094955) | 0.622299 / 0.540337 (0.081962) | 0.835295 / 1.386936 (-0.551641) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3de42c8fae86c602fc71ac6d166e5c77f4149446 \"CML watermark\")\n", "CI errors are unrelated or due to flaky tests", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006288 / 0.011353 (-0.005065) | 0.003836 / 0.011008 (-0.007172) | 0.080958 / 0.038508 (0.042450) | 0.065934 / 0.023109 (0.042825) | 0.312597 / 0.275898 (0.036699) | 0.351216 / 0.323480 (0.027736) | 0.004864 / 0.007986 (-0.003121) | 0.002961 / 0.004328 (-0.001368) | 0.063142 / 0.004250 (0.058892) | 0.049822 / 0.037052 (0.012770) | 0.320305 / 0.258489 (0.061816) | 0.363151 / 0.293841 (0.069310) | 0.027561 / 0.128546 (-0.100985) | 0.008176 / 0.075646 (-0.067470) | 0.261290 / 0.419271 (-0.157982) | 0.045517 / 0.043533 (0.001984) | 0.309218 / 0.255139 (0.054079) | 0.340140 / 0.283200 (0.056940) | 0.021000 / 0.141683 (-0.120683) | 1.448699 / 1.452155 (-0.003456) | 1.523904 / 1.492716 (0.031188) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224294 / 0.018006 (0.206288) | 0.434928 / 0.000490 (0.434439) | 0.007541 / 0.000200 (0.007341) | 0.000286 / 0.000054 (0.000232) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025257 / 0.037411 (-0.012154) | 0.077364 / 0.014526 (0.062838) | 0.085825 / 0.176557 (-0.090732) | 0.148121 / 0.737135 (-0.589014) | 0.086838 / 0.296338 (-0.209500) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.396900 / 0.215209 (0.181691) | 3.953381 / 2.077655 (1.875727) | 1.933561 / 1.504120 (0.429441) | 1.760549 / 1.541195 (0.219354) | 1.824014 / 1.468490 (0.355523) | 0.495385 / 4.584777 (-4.089392) | 3.005558 / 3.745712 (-0.740154) | 2.931022 / 5.269862 (-2.338840) | 1.905113 / 4.565676 (-2.660563) | 0.057232 / 0.424275 (-0.367043) | 0.006472 / 0.007607 (-0.001135) | 0.464261 / 0.226044 (0.238216) | 4.629388 / 2.268929 (2.360459) | 2.342004 / 55.444624 (-53.102620) | 1.977295 / 6.876477 (-4.899181) | 2.167151 / 2.142072 (0.025079) | 0.582483 / 4.805227 (-4.222744) | 0.129444 / 6.500664 (-6.371220) | 0.061057 / 0.075469 (-0.014412) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.259444 / 1.841788 (-0.582344) | 18.189338 / 8.074308 (10.115030) | 14.313174 / 10.191392 (4.121782) | 0.146209 / 0.680424 (-0.534215) | 0.017115 / 0.534201 (-0.517086) | 0.336643 / 0.579283 (-0.242640) | 0.370824 / 0.434364 (-0.063540) | 0.387032 / 0.540337 (-0.153306) | 0.546688 / 1.386936 (-0.840248) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006371 / 0.011353 (-0.004982) | 0.003693 / 0.011008 (-0.007315) | 0.062499 / 0.038508 (0.023991) | 0.066367 / 0.023109 (0.043257) | 0.451481 / 0.275898 (0.175583) | 0.482495 / 0.323480 (0.159015) | 0.005676 / 0.007986 (-0.002310) | 0.002940 / 0.004328 (-0.001389) | 0.063011 / 0.004250 (0.058760) | 0.051500 / 0.037052 (0.014447) | 0.455482 / 0.258489 (0.196993) | 0.488888 / 0.293841 (0.195047) | 0.028714 / 0.128546 (-0.099832) | 0.008178 / 0.075646 (-0.067468) | 0.067218 / 0.419271 (-0.352053) | 0.041323 / 0.043533 (-0.002210) | 0.454007 / 0.255139 (0.198868) | 0.476241 / 0.283200 (0.193041) | 0.021530 / 0.141683 (-0.120153) | 1.457859 / 1.452155 (0.005705) | 1.506437 / 1.492716 (0.013721) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228280 / 0.018006 (0.210274) | 0.427574 / 0.000490 (0.427084) | 0.003793 / 0.000200 (0.003593) | 0.000076 / 0.000054 (0.000022) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028420 / 0.037411 (-0.008992) | 0.087935 / 0.014526 (0.073409) | 0.092761 / 0.176557 (-0.083796) | 0.148084 / 0.737135 (-0.589051) | 0.095301 / 0.296338 (-0.201037) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.462457 / 0.215209 (0.247248) | 4.618016 / 2.077655 (2.540361) | 2.540531 / 1.504120 (1.036412) | 2.384696 / 1.541195 (0.843501) | 2.493108 / 1.468490 (1.024618) | 0.511689 / 4.584777 (-4.073088) | 3.173701 / 3.745712 (-0.572011) | 2.917046 / 5.269862 (-2.352816) | 1.916294 / 4.565676 (-2.649382) | 0.058969 / 0.424275 (-0.365306) | 0.006461 / 0.007607 (-0.001147) | 0.540997 / 0.226044 (0.314952) | 5.406596 / 2.268929 (3.137667) | 3.071189 / 55.444624 (-52.373435) | 2.701982 / 6.876477 (-4.174494) | 2.860194 / 2.142072 (0.718121) | 0.602684 / 4.805227 (-4.202543) | 0.127384 / 6.500664 (-6.373280) | 0.061718 / 0.075469 (-0.013751) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.340587 / 1.841788 (-0.501201) | 18.543831 / 8.074308 (10.469523) | 14.847319 / 10.191392 (4.655927) | 0.146523 / 0.680424 (-0.533901) | 0.018172 / 0.534201 (-0.516029) | 0.333276 / 0.579283 (-0.246007) | 0.375874 / 0.434364 (-0.058490) | 0.396766 / 0.540337 (-0.143572) | 0.572562 / 1.386936 (-0.814374) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f2d9fcc0840f9d94f63635e9b40a1a7f11b34ea2 \"CML watermark\")\n" ]

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[ "It looks to be the same issue as the one reported in https://discuss.huggingface.co/t/indexerror-invalid-key-16-is-out-of-bounds-for-size-0.\r\n\r\nCan you check the length of `train_dataset` before the `train_sampler = self._get_train_sampler()` (and after `_remove_unused_columns`) line?" ]

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[ "Hi! Can you provide a code that reproduces the issue?\r\n\r\nAlso, which version of `datasets` are you using? You can check this by running `python -c \"import datasets; print(datasets.__version__)\"` inside the env. We added support for \"float images\" in `datasets 2.9`." ]

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[ "Thanks for reporting! I've opened a PR with a fix" ]

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[ "Yea I think waiting for #6269 would be best, or branching from it. For reference, this [PR](https://github.com/LAION-AI/Discord-Scrapers/pull/2) is progressing pretty well which will do similar using the hf hub for our LAION dataset bot https://github.com/LAION-AI/Discord-Scrapers/pull/2. " ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006424 / 0.011353 (-0.004929) | 0.003960 / 0.011008 (-0.007048) | 0.084022 / 0.038508 (0.045514) | 0.070770 / 0.023109 (0.047661) | 0.320525 / 0.275898 (0.044627) | 0.354507 / 0.323480 (0.031027) | 0.003939 / 0.007986 (-0.004047) | 0.004161 / 0.004328 (-0.000168) | 0.064754 / 0.004250 (0.060503) | 0.053630 / 0.037052 (0.016578) | 0.323948 / 0.258489 (0.065459) | 0.376908 / 0.293841 (0.083067) | 0.031063 / 0.128546 (-0.097483) | 0.008470 / 0.075646 (-0.067177) | 0.288110 / 0.419271 (-0.131161) | 0.053062 / 0.043533 (0.009529) | 0.328176 / 0.255139 (0.073037) | 0.345203 / 0.283200 (0.062003) | 0.024579 / 0.141683 (-0.117104) | 1.471649 / 1.452155 (0.019495) | 1.561458 / 1.492716 (0.068742) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223591 / 0.018006 (0.205585) | 0.450758 / 0.000490 (0.450269) | 0.003751 / 0.000200 (0.003552) | 0.000079 / 0.000054 (0.000025) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027859 / 0.037411 (-0.009552) | 0.080607 / 0.014526 (0.066081) | 0.093835 / 0.176557 (-0.082722) | 0.150466 / 0.737135 (-0.586669) | 0.094381 / 0.296338 (-0.201957) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.394011 / 0.215209 (0.178802) | 3.918318 / 2.077655 (1.840664) | 1.928684 / 1.504120 (0.424564) | 1.765944 / 1.541195 (0.224749) | 1.784716 / 1.468490 (0.316226) | 0.487189 / 4.584777 (-4.097588) | 3.537705 / 3.745712 (-0.208008) | 3.312162 / 5.269862 (-1.957699) | 2.024520 / 4.565676 (-2.541156) | 0.057571 / 0.424275 (-0.366704) | 0.007203 / 0.007607 (-0.000404) | 0.467253 / 0.226044 (0.241208) | 4.659934 / 2.268929 (2.391005) | 2.377764 / 55.444624 (-53.066860) | 2.021984 / 6.876477 (-4.854492) | 2.197468 / 2.142072 (0.055395) | 0.586415 / 4.805227 (-4.218812) | 0.136636 / 6.500664 (-6.364028) | 0.060885 / 0.075469 (-0.014584) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.241879 / 1.841788 (-0.599908) | 18.719327 / 8.074308 (10.645019) | 14.408689 / 10.191392 (4.217297) | 0.155778 / 0.680424 (-0.524646) | 0.018475 / 0.534201 (-0.515726) | 0.392316 / 0.579283 (-0.186967) | 0.409803 / 0.434364 (-0.024561) | 0.458701 / 0.540337 (-0.081637) | 0.630561 / 1.386936 (-0.756375) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006541 / 0.011353 (-0.004812) | 0.003915 / 0.011008 (-0.007094) | 0.064292 / 0.038508 (0.025784) | 0.069174 / 0.023109 (0.046065) | 0.402048 / 0.275898 (0.126150) | 0.423960 / 0.323480 (0.100480) | 0.005355 / 0.007986 (-0.002631) | 0.003295 / 0.004328 (-0.001033) | 0.065212 / 0.004250 (0.060962) | 0.054292 / 0.037052 (0.017240) | 0.402930 / 0.258489 (0.144441) | 0.441840 / 0.293841 (0.147999) | 0.032732 / 0.128546 (-0.095814) | 0.008565 / 0.075646 (-0.067081) | 0.070705 / 0.419271 (-0.348567) | 0.047908 / 0.043533 (0.004375) | 0.401400 / 0.255139 (0.146261) | 0.422682 / 0.283200 (0.139483) | 0.022244 / 0.141683 (-0.119439) | 1.532018 / 1.452155 (0.079864) | 1.597955 / 1.492716 (0.105239) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226277 / 0.018006 (0.208271) | 0.475578 / 0.000490 (0.475088) | 0.005456 / 0.000200 (0.005256) | 0.000140 / 0.000054 (0.000085) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033111 / 0.037411 (-0.004300) | 0.093138 / 0.014526 (0.078613) | 0.104619 / 0.176557 (-0.071937) | 0.157972 / 0.737135 (-0.579164) | 0.105017 / 0.296338 (-0.191321) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.441771 / 0.215209 (0.226562) | 4.396981 / 2.077655 (2.319326) | 2.410745 / 1.504120 (0.906625) | 2.258359 / 1.541195 (0.717164) | 2.372628 / 1.468490 (0.904138) | 0.491411 / 4.584777 (-4.093366) | 3.650084 / 3.745712 (-0.095628) | 3.279557 / 5.269862 (-1.990304) | 2.011377 / 4.565676 (-2.554300) | 0.058283 / 0.424275 (-0.365992) | 0.007435 / 0.007607 (-0.000172) | 0.507212 / 0.226044 (0.281167) | 5.080104 / 2.268929 (2.811176) | 2.822680 / 55.444624 (-52.621945) | 2.507608 / 6.876477 (-4.368869) | 2.719349 / 2.142072 (0.577277) | 0.586157 / 4.805227 (-4.219071) | 0.132851 / 6.500664 (-6.367813) | 0.059944 / 0.075469 (-0.015525) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.374801 / 1.841788 (-0.466987) | 19.089359 / 8.074308 (11.015051) | 14.525861 / 10.191392 (4.334469) | 0.184758 / 0.680424 (-0.495666) | 0.020206 / 0.534201 (-0.513995) | 0.397309 / 0.579283 (-0.181975) | 0.418120 / 0.434364 (-0.016244) | 0.471817 / 0.540337 (-0.068520) | 0.681691 / 1.386936 (-0.705245) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#2076cb857e90cf7a6050bba230f586993c5e034a \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "A duplicate of https://github.com/huggingface/datasets/issues/4796.\r\n\r\nWe could get this for free by implementing the `Image` feature as an extension type, as shown in [this](https://colab.research.google.com/drive/1Uzm_tXVpGTwbzleDConWcNjacwO1yxE4?usp=sharing) Colab (example with UUIDs).\r\n" ]

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[ "There is no \"text\" column in the `amazon_reviews_multi`, hence the `KeyError`. You can get the column names by running `dataset.column_names`." ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009157 / 0.011353 (-0.002195) | 0.004275 / 0.011008 (-0.006734) | 0.099341 / 0.038508 (0.060833) | 0.080634 / 0.023109 (0.057525) | 0.373598 / 0.275898 (0.097700) | 0.445048 / 0.323480 (0.121568) | 0.006541 / 0.007986 (-0.001444) | 0.003550 / 0.004328 (-0.000779) | 0.071034 / 0.004250 (0.066784) | 0.062637 / 0.037052 (0.025585) | 0.379110 / 0.258489 (0.120621) | 0.447896 / 0.293841 (0.154055) | 0.047739 / 0.128546 (-0.080807) | 0.012575 / 0.075646 (-0.063071) | 0.332314 / 0.419271 (-0.086957) | 0.065500 / 0.043533 (0.021967) | 0.365919 / 0.255139 (0.110780) | 0.438611 / 0.283200 (0.155412) | 0.034243 / 0.141683 (-0.107440) | 1.628034 / 1.452155 (0.175880) | 1.802970 / 1.492716 (0.310253) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224528 / 0.018006 (0.206522) | 0.482094 / 0.000490 (0.481604) | 0.012752 / 0.000200 (0.012552) | 0.000570 / 0.000054 (0.000515) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025456 / 0.037411 (-0.011956) | 0.082281 / 0.014526 (0.067756) | 0.100050 / 0.176557 (-0.076506) | 0.156931 / 0.737135 (-0.580204) | 0.108229 / 0.296338 (-0.188110) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.560688 / 0.215209 (0.345479) | 5.171711 / 2.077655 (3.094056) | 2.273178 / 1.504120 (0.769058) | 1.948158 / 1.541195 (0.406963) | 1.879744 / 1.468490 (0.411254) | 0.789216 / 4.584777 (-3.795561) | 4.529370 / 3.745712 (0.783658) | 4.008743 / 5.269862 (-1.261118) | 2.633555 / 4.565676 (-1.932121) | 0.085411 / 0.424275 (-0.338864) | 0.007256 / 0.007607 (-0.000351) | 0.623254 / 0.226044 (0.397209) | 6.327256 / 2.268929 (4.058327) | 2.911787 / 55.444624 (-52.532837) | 2.240610 / 6.876477 (-4.635867) | 2.352811 / 2.142072 (0.210738) | 0.930114 / 4.805227 (-3.875114) | 0.185028 / 6.500664 (-6.315636) | 0.062115 / 0.075469 (-0.013354) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.394261 / 1.841788 (-0.447527) | 19.689376 / 8.074308 (11.615067) | 17.242289 / 10.191392 (7.050897) | 0.209122 / 0.680424 (-0.471302) | 0.027205 / 0.534201 (-0.506996) | 0.408613 / 0.579283 (-0.170670) | 0.503836 / 0.434364 (0.069472) | 0.485179 / 0.540337 (-0.055158) | 0.674333 / 1.386936 (-0.712603) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007506 / 0.011353 (-0.003847) | 0.004683 / 0.011008 (-0.006325) | 0.067584 / 0.038508 (0.029076) | 0.065635 / 0.023109 (0.042525) | 0.458814 / 0.275898 (0.182916) | 0.477549 / 0.323480 (0.154069) | 0.005212 / 0.007986 (-0.002774) | 0.003393 / 0.004328 (-0.000936) | 0.075307 / 0.004250 (0.071057) | 0.051989 / 0.037052 (0.014937) | 0.484229 / 0.258489 (0.225740) | 0.470889 / 0.293841 (0.177048) | 0.043528 / 0.128546 (-0.085018) | 0.014685 / 0.075646 (-0.060962) | 0.084199 / 0.419271 (-0.335073) | 0.053970 / 0.043533 (0.010437) | 0.432362 / 0.255139 (0.177223) | 0.467472 / 0.283200 (0.184272) | 0.031109 / 0.141683 (-0.110574) | 1.525938 / 1.452155 (0.073784) | 1.631993 / 1.492716 (0.139276) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.200196 / 0.018006 (0.182190) | 0.479316 / 0.000490 (0.478827) | 0.010146 / 0.000200 (0.009947) | 0.000118 / 0.000054 (0.000063) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027911 / 0.037411 (-0.009500) | 0.089720 / 0.014526 (0.075194) | 0.097000 / 0.176557 (-0.079557) | 0.157549 / 0.737135 (-0.579587) | 0.098247 / 0.296338 (-0.198092) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.581401 / 0.215209 (0.366192) | 5.703829 / 2.077655 (3.626174) | 2.688272 / 1.504120 (1.184152) | 2.321691 / 1.541195 (0.780496) | 2.355987 / 1.468490 (0.887497) | 0.759109 / 4.584777 (-3.825668) | 4.711288 / 3.745712 (0.965576) | 4.093019 / 5.269862 (-1.176843) | 2.648240 / 4.565676 (-1.917437) | 0.087839 / 0.424275 (-0.336436) | 0.007060 / 0.007607 (-0.000547) | 0.702783 / 0.226044 (0.476739) | 6.986924 / 2.268929 (4.717996) | 3.365970 / 55.444624 (-52.078654) | 2.670876 / 6.876477 (-4.205600) | 2.776431 / 2.142072 (0.634358) | 0.920005 / 4.805227 (-3.885222) | 0.197521 / 6.500664 (-6.303143) | 0.069974 / 0.075469 (-0.005495) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.596947 / 1.841788 (-0.244841) | 20.606007 / 8.074308 (12.531699) | 18.437425 / 10.191392 (8.246033) | 0.222445 / 0.680424 (-0.457978) | 0.028610 / 0.534201 (-0.505591) | 0.419748 / 0.579283 (-0.159535) | 0.513409 / 0.434364 (0.079045) | 0.487517 / 0.540337 (-0.052820) | 0.706637 / 1.386936 (-0.680299) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d664439eb82d62889c21c5236a5869dae75ae779 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007744 / 0.011353 (-0.003609) | 0.004678 / 0.011008 (-0.006330) | 0.101243 / 0.038508 (0.062735) | 0.085653 / 0.023109 (0.062543) | 0.383772 / 0.275898 (0.107874) | 0.422151 / 0.323480 (0.098671) | 0.004566 / 0.007986 (-0.003419) | 0.003900 / 0.004328 (-0.000429) | 0.077778 / 0.004250 (0.073528) | 0.063761 / 0.037052 (0.026709) | 0.385505 / 0.258489 (0.127016) | 0.436186 / 0.293841 (0.142345) | 0.036172 / 0.128546 (-0.092374) | 0.009935 / 0.075646 (-0.065711) | 0.341434 / 0.419271 (-0.077837) | 0.061866 / 0.043533 (0.018333) | 0.385020 / 0.255139 (0.129881) | 0.399455 / 0.283200 (0.116256) | 0.029324 / 0.141683 (-0.112358) | 1.784749 / 1.452155 (0.332594) | 1.845926 / 1.492716 (0.353209) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.266322 / 0.018006 (0.248316) | 0.508708 / 0.000490 (0.508218) | 0.013680 / 0.000200 (0.013480) | 0.000868 / 0.000054 (0.000814) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033887 / 0.037411 (-0.003525) | 0.096709 / 0.014526 (0.082183) | 0.109472 / 0.176557 (-0.067084) | 0.174422 / 0.737135 (-0.562713) | 0.110830 / 0.296338 (-0.185509) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.457533 / 0.215209 (0.242324) | 4.615229 / 2.077655 (2.537575) | 2.418820 / 1.504120 (0.914700) | 2.181079 / 1.541195 (0.639884) | 2.229164 / 1.468490 (0.760674) | 0.554861 / 4.584777 (-4.029916) | 4.323787 / 3.745712 (0.578075) | 3.769396 / 5.269862 (-1.500466) | 2.376850 / 4.565676 (-2.188826) | 0.065030 / 0.424275 (-0.359245) | 0.008397 / 0.007607 (0.000790) | 0.541109 / 0.226044 (0.315065) | 5.477540 / 2.268929 (3.208612) | 2.957049 / 55.444624 (-52.487576) | 2.511732 / 6.876477 (-4.364744) | 2.703953 / 2.142072 (0.561881) | 0.660822 / 4.805227 (-4.144405) | 0.147035 / 6.500664 (-6.353630) | 0.066045 / 0.075469 (-0.009424) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.526481 / 1.841788 (-0.315307) | 22.020256 / 8.074308 (13.945948) | 16.854566 / 10.191392 (6.663174) | 0.192958 / 0.680424 (-0.487466) | 0.021505 / 0.534201 (-0.512696) | 0.462867 / 0.579283 (-0.116416) | 0.514813 / 0.434364 (0.080449) | 0.546147 / 0.540337 (0.005809) | 0.767853 / 1.386936 (-0.619083) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007770 / 0.011353 (-0.003583) | 0.004671 / 0.011008 (-0.006337) | 0.080862 / 0.038508 (0.042354) | 0.087049 / 0.023109 (0.063940) | 0.479497 / 0.275898 (0.203599) | 0.559787 / 0.323480 (0.236307) | 0.007168 / 0.007986 (-0.000818) | 0.003829 / 0.004328 (-0.000500) | 0.079018 / 0.004250 (0.074768) | 0.067359 / 0.037052 (0.030307) | 0.516140 / 0.258489 (0.257651) | 0.547000 / 0.293841 (0.253159) | 0.037955 / 0.128546 (-0.090591) | 0.010007 / 0.075646 (-0.065639) | 0.087673 / 0.419271 (-0.331598) | 0.059309 / 0.043533 (0.015777) | 0.473920 / 0.255139 (0.218781) | 0.529216 / 0.283200 (0.246017) | 0.028236 / 0.141683 (-0.113447) | 1.771127 / 1.452155 (0.318972) | 1.918878 / 1.492716 (0.426162) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.242010 / 0.018006 (0.224004) | 0.494944 / 0.000490 (0.494454) | 0.006319 / 0.000200 (0.006119) | 0.000111 / 0.000054 (0.000056) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039220 / 0.037411 (0.001809) | 0.113805 / 0.014526 (0.099279) | 0.125704 / 0.176557 (-0.050853) | 0.189198 / 0.737135 (-0.547937) | 0.126334 / 0.296338 (-0.170004) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.502226 / 0.215209 (0.287017) | 5.039133 / 2.077655 (2.961478) | 2.782352 / 1.504120 (1.278232) | 2.587654 / 1.541195 (1.046460) | 2.692588 / 1.468490 (1.224098) | 0.585672 / 4.584777 (-3.999105) | 4.553078 / 3.745712 (0.807366) | 3.864739 / 5.269862 (-1.405123) | 2.536109 / 4.565676 (-2.029567) | 0.069567 / 0.424275 (-0.354708) | 0.008749 / 0.007607 (0.001142) | 0.620645 / 0.226044 (0.394601) | 6.247286 / 2.268929 (3.978357) | 3.345293 / 55.444624 (-52.099332) | 2.873970 / 6.876477 (-4.002507) | 3.123190 / 2.142072 (0.981118) | 0.687391 / 4.805227 (-4.117837) | 0.159046 / 6.500664 (-6.341618) | 0.071019 / 0.075469 (-0.004450) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.728724 / 1.841788 (-0.113064) | 22.828390 / 8.074308 (14.754082) | 17.305225 / 10.191392 (7.113833) | 0.176571 / 0.680424 (-0.503853) | 0.023837 / 0.534201 (-0.510364) | 0.467935 / 0.579283 (-0.111348) | 0.503701 / 0.434364 (0.069337) | 0.558140 / 0.540337 (0.017803) | 0.789326 / 1.386936 (-0.597610) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7d357eb4b499cd530c3f4e626f2825a50ee6c8aa \"CML watermark\")\n" ]

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[ "You should be able to load the images by modifying the `load_dataset` call like this:\r\n```python\r\ndataset = load_dataset(\"imagefolder\", data_dir=\"/content/datasets/PotholeDetectionYOLOv8-1\")\r\n```\r\n\r\nThe `imagefolder` builder expects the image files to be in `path/label/image_file` (e.g. .`.../train/dog/image_1.jpg`), so the solution for the labels in your case is to create metadata files (one for each split; as explained [here](https://huggingface.co/docs/datasets/image_dataset#imagefolder)) that map the images to their labels.", "> You should be able to load the images by modifying the `load_dataset` call like this:\r\n> \r\n> ```python\r\n> dataset = load_dataset(\"imagefolder\", data_dir=\"/content/datasets/PotholeDetectionYOLOv8-1\")\r\n> ```\r\n> \r\n> The `imagefolder` builder expects the image files to be in `path/label/image_file` (e.g. .`.../train/dog/image_1.jpg`), so the solution for the labels in your case is to create metadata files (one for each split; as explained [here](https://huggingface.co/docs/datasets/image_dataset#imagefolder)) that map the images to their labels.\r\n\r\nI tried like this but only uploads images and not labels, Andyrasika/potholes-dataset", "As explained in my previous comment, you need to define metadata files to load the labels or update the paths to be in the format `train/label/image` (`train- image /n -labels` is not supported by the loader).", "I downloaded my file after annotating using roboflow . It gives train-\r\nimages, labels , test- images, labels , valid- images, labels . I hope it\r\ngives you an idea of the dataset . Please advise on this dataset\r\n\r\nOn Tue, Oct 10, 2023 at 18:12 Mario Šaško ***@***.***> wrote:\r\n\r\n> As explained in my previous comment, you need to define metadata files to\r\n> load the labels or update the paths to be in the format train/label/image\r\n> (train- image /n -labels is not supported by the loader).\r\n>\r\n> —\r\n> Reply to this email directly, view it on GitHub\r\n> <https://github.com/huggingface/datasets/issues/6285#issuecomment-1755335215>,\r\n> or unsubscribe\r\n> <https://github.com/notifications/unsubscribe-auth/AE4LJNN56FWWTSBYTSTUWHLX6U7CVAVCNFSM6AAAAAA5YHCSTGVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTONJVGMZTKMRRGU>\r\n> .\r\n> You are receiving this because you authored the thread.Message ID:\r\n> ***@***.***>\r\n>\r\n" ]

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[ "This dataset is already available on the Hub: https://huggingface.co/datasets/facebook/belebele.\r\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006278 / 0.011353 (-0.005075) | 0.003692 / 0.011008 (-0.007316) | 0.080464 / 0.038508 (0.041956) | 0.064751 / 0.023109 (0.041642) | 0.318586 / 0.275898 (0.042688) | 0.351435 / 0.323480 (0.027955) | 0.005044 / 0.007986 (-0.002942) | 0.003034 / 0.004328 (-0.001295) | 0.063710 / 0.004250 (0.059460) | 0.050607 / 0.037052 (0.013555) | 0.318491 / 0.258489 (0.060001) | 0.365688 / 0.293841 (0.071847) | 0.027818 / 0.128546 (-0.100729) | 0.008119 / 0.075646 (-0.067527) | 0.262141 / 0.419271 (-0.157131) | 0.044710 / 0.043533 (0.001177) | 0.318875 / 0.255139 (0.063736) | 0.344559 / 0.283200 (0.061360) | 0.022861 / 0.141683 (-0.118822) | 1.452402 / 1.452155 (0.000247) | 1.502340 / 1.492716 (0.009624) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.219355 / 0.018006 (0.201349) | 0.433311 / 0.000490 (0.432822) | 0.006545 / 0.000200 (0.006345) | 0.000078 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024538 / 0.037411 (-0.012874) | 0.073346 / 0.014526 (0.058821) | 0.083824 / 0.176557 (-0.092733) | 0.145176 / 0.737135 (-0.591959) | 0.085941 / 0.296338 (-0.210397) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.395153 / 0.215209 (0.179944) | 3.944734 / 2.077655 (1.867080) | 1.883910 / 1.504120 (0.379790) | 1.690560 / 1.541195 (0.149365) | 1.775180 / 1.468490 (0.306690) | 0.506873 / 4.584777 (-4.077904) | 3.111095 / 3.745712 (-0.634617) | 2.915358 / 5.269862 (-2.354504) | 1.892886 / 4.565676 (-2.672791) | 0.058690 / 0.424275 (-0.365585) | 0.006550 / 0.007607 (-0.001057) | 0.463372 / 0.226044 (0.237328) | 4.640511 / 2.268929 (2.371583) | 2.321051 / 55.444624 (-53.123573) | 1.986330 / 6.876477 (-4.890147) | 2.160046 / 2.142072 (0.017973) | 0.597833 / 4.805227 (-4.207394) | 0.127946 / 6.500664 (-6.372718) | 0.059709 / 0.075469 (-0.015760) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.278966 / 1.841788 (-0.562822) | 17.863102 / 8.074308 (9.788794) | 13.896057 / 10.191392 (3.704665) | 0.147512 / 0.680424 (-0.532912) | 0.016771 / 0.534201 (-0.517430) | 0.335260 / 0.579283 (-0.244024) | 0.383019 / 0.434364 (-0.051345) | 0.384821 / 0.540337 (-0.155516) | 0.550143 / 1.386936 (-0.836793) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006234 / 0.011353 (-0.005118) | 0.003695 / 0.011008 (-0.007313) | 0.062654 / 0.038508 (0.024146) | 0.059397 / 0.023109 (0.036287) | 0.458375 / 0.275898 (0.182477) | 0.488951 / 0.323480 (0.165471) | 0.004971 / 0.007986 (-0.003014) | 0.002914 / 0.004328 (-0.001415) | 0.061184 / 0.004250 (0.056934) | 0.051246 / 0.037052 (0.014194) | 0.458035 / 0.258489 (0.199546) | 0.490838 / 0.293841 (0.196997) | 0.028746 / 0.128546 (-0.099800) | 0.008167 / 0.075646 (-0.067480) | 0.068006 / 0.419271 (-0.351265) | 0.041809 / 0.043533 (-0.001724) | 0.453896 / 0.255139 (0.198757) | 0.477583 / 0.283200 (0.194383) | 0.020906 / 0.141683 (-0.120777) | 1.443275 / 1.452155 (-0.008879) | 1.493431 / 1.492716 (0.000714) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.219903 / 0.018006 (0.201896) | 0.410275 / 0.000490 (0.409785) | 0.003919 / 0.000200 (0.003719) | 0.000078 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027850 / 0.037411 (-0.009561) | 0.080444 / 0.014526 (0.065918) | 0.089943 / 0.176557 (-0.086614) | 0.145810 / 0.737135 (-0.591326) | 0.090908 / 0.296338 (-0.205430) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.464386 / 0.215209 (0.249177) | 4.633787 / 2.077655 (2.556133) | 2.581658 / 1.504120 (1.077538) | 2.408486 / 1.541195 (0.867291) | 2.460491 / 1.468490 (0.992001) | 0.507512 / 4.584777 (-4.077265) | 3.190363 / 3.745712 (-0.555349) | 2.895581 / 5.269862 (-2.374280) | 1.871506 / 4.565676 (-2.694171) | 0.058469 / 0.424275 (-0.365806) | 0.006526 / 0.007607 (-0.001082) | 0.537641 / 0.226044 (0.311596) | 5.396660 / 2.268929 (3.127731) | 3.027028 / 55.444624 (-52.417596) | 2.703771 / 6.876477 (-4.172705) | 2.865576 / 2.142072 (0.723503) | 0.600103 / 4.805227 (-4.205124) | 0.127109 / 6.500664 (-6.373555) | 0.060985 / 0.075469 (-0.014484) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.365030 / 1.841788 (-0.476758) | 17.988218 / 8.074308 (9.913909) | 14.900796 / 10.191392 (4.709404) | 0.158211 / 0.680424 (-0.522213) | 0.018291 / 0.534201 (-0.515910) | 0.337437 / 0.579283 (-0.241846) | 0.383710 / 0.434364 (-0.050654) | 0.392341 / 0.540337 (-0.147997) | 0.561584 / 1.386936 (-0.825352) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b7571ab4b0d9b67b767c55db400b4ffac0f752f1 \"CML watermark\")\n", "CI failures are unrelated", "I also plan to address https://github.com/huggingface/datasets/issues/6280#issuecomment-1749310065 in this PR :).", "Oh ok, ping me again whenever you want another review :)" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006934 / 0.011353 (-0.004419) | 0.004097 / 0.011008 (-0.006911) | 0.084662 / 0.038508 (0.046154) | 0.077106 / 0.023109 (0.053996) | 0.355035 / 0.275898 (0.079137) | 0.381466 / 0.323480 (0.057986) | 0.004182 / 0.007986 (-0.003803) | 0.003411 / 0.004328 (-0.000917) | 0.065279 / 0.004250 (0.061029) | 0.058192 / 0.037052 (0.021140) | 0.372363 / 0.258489 (0.113874) | 0.401621 / 0.293841 (0.107780) | 0.031719 / 0.128546 (-0.096827) | 0.008753 / 0.075646 (-0.066893) | 0.287125 / 0.419271 (-0.132146) | 0.052943 / 0.043533 (0.009410) | 0.349680 / 0.255139 (0.094541) | 0.364004 / 0.283200 (0.080805) | 0.026705 / 0.141683 (-0.114977) | 1.472708 / 1.452155 (0.020553) | 1.556559 / 1.492716 (0.063842) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224868 / 0.018006 (0.206862) | 0.458793 / 0.000490 (0.458304) | 0.009434 / 0.000200 (0.009234) | 0.000356 / 0.000054 (0.000301) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029670 / 0.037411 (-0.007741) | 0.086517 / 0.014526 (0.071991) | 0.097342 / 0.176557 (-0.079215) | 0.153722 / 0.737135 (-0.583413) | 0.098465 / 0.296338 (-0.197874) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.400739 / 0.215209 (0.185530) | 3.998087 / 2.077655 (1.920432) | 2.025772 / 1.504120 (0.521652) | 1.858679 / 1.541195 (0.317485) | 1.951573 / 1.468490 (0.483083) | 0.483028 / 4.584777 (-4.101749) | 3.554085 / 3.745712 (-0.191627) | 3.306983 / 5.269862 (-1.962879) | 2.087043 / 4.565676 (-2.478633) | 0.057127 / 0.424275 (-0.367148) | 0.007252 / 0.007607 (-0.000355) | 0.480180 / 0.226044 (0.254136) | 4.787183 / 2.268929 (2.518255) | 2.489667 / 55.444624 (-52.954957) | 2.150774 / 6.876477 (-4.725703) | 2.403197 / 2.142072 (0.261124) | 0.581843 / 4.805227 (-4.223384) | 0.134915 / 6.500664 (-6.365749) | 0.061283 / 0.075469 (-0.014186) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.285700 / 1.841788 (-0.556088) | 19.474093 / 8.074308 (11.399785) | 14.336349 / 10.191392 (4.144957) | 0.170932 / 0.680424 (-0.509492) | 0.018348 / 0.534201 (-0.515853) | 0.391909 / 0.579283 (-0.187374) | 0.414706 / 0.434364 (-0.019658) | 0.458156 / 0.540337 (-0.082182) | 0.656303 / 1.386936 (-0.730633) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006738 / 0.011353 (-0.004615) | 0.004029 / 0.011008 (-0.006979) | 0.064411 / 0.038508 (0.025903) | 0.078225 / 0.023109 (0.055116) | 0.408468 / 0.275898 (0.132569) | 0.445585 / 0.323480 (0.122105) | 0.005490 / 0.007986 (-0.002495) | 0.003419 / 0.004328 (-0.000910) | 0.063966 / 0.004250 (0.059715) | 0.056779 / 0.037052 (0.019727) | 0.415258 / 0.258489 (0.156769) | 0.461258 / 0.293841 (0.167418) | 0.032051 / 0.128546 (-0.096495) | 0.008471 / 0.075646 (-0.067176) | 0.071004 / 0.419271 (-0.348267) | 0.049068 / 0.043533 (0.005536) | 0.409575 / 0.255139 (0.154436) | 0.430748 / 0.283200 (0.147548) | 0.023784 / 0.141683 (-0.117899) | 1.507894 / 1.452155 (0.055739) | 1.586575 / 1.492716 (0.093859) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228574 / 0.018006 (0.210568) | 0.451389 / 0.000490 (0.450900) | 0.006312 / 0.000200 (0.006112) | 0.000100 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033391 / 0.037411 (-0.004020) | 0.096816 / 0.014526 (0.082290) | 0.107269 / 0.176557 (-0.069288) | 0.159749 / 0.737135 (-0.577387) | 0.108240 / 0.296338 (-0.188098) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.437643 / 0.215209 (0.222434) | 4.378173 / 2.077655 (2.300518) | 2.367218 / 1.504120 (0.863098) | 2.229493 / 1.541195 (0.688298) | 2.329849 / 1.468490 (0.861359) | 0.494985 / 4.584777 (-4.089792) | 3.578540 / 3.745712 (-0.167172) | 3.338220 / 5.269862 (-1.931642) | 2.092482 / 4.565676 (-2.473194) | 0.058495 / 0.424275 (-0.365780) | 0.007396 / 0.007607 (-0.000211) | 0.511001 / 0.226044 (0.284957) | 5.113497 / 2.268929 (2.844568) | 2.806215 / 55.444624 (-52.638409) | 2.485428 / 6.876477 (-4.391048) | 2.764907 / 2.142072 (0.622835) | 0.598824 / 4.805227 (-4.206404) | 0.134988 / 6.500664 (-6.365676) | 0.061752 / 0.075469 (-0.013717) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.365583 / 1.841788 (-0.476205) | 20.270297 / 8.074308 (12.195989) | 15.331673 / 10.191392 (5.140281) | 0.166152 / 0.680424 (-0.514272) | 0.020678 / 0.534201 (-0.513523) | 0.394821 / 0.579283 (-0.184462) | 0.420493 / 0.434364 (-0.013871) | 0.468551 / 0.540337 (-0.071787) | 0.654903 / 1.386936 (-0.732033) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5f268dd4ad4fb6dada15937d57fb367cb2810162 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007803 / 0.011353 (-0.003550) | 0.004664 / 0.011008 (-0.006344) | 0.099908 / 0.038508 (0.061400) | 0.090674 / 0.023109 (0.067565) | 0.406009 / 0.275898 (0.130111) | 0.465098 / 0.323480 (0.141618) | 0.004667 / 0.007986 (-0.003319) | 0.003880 / 0.004328 (-0.000449) | 0.076552 / 0.004250 (0.072301) | 0.066345 / 0.037052 (0.029292) | 0.419195 / 0.258489 (0.160706) | 0.478581 / 0.293841 (0.184741) | 0.036967 / 0.128546 (-0.091579) | 0.010000 / 0.075646 (-0.065647) | 0.347126 / 0.419271 (-0.072145) | 0.062265 / 0.043533 (0.018733) | 0.406653 / 0.255139 (0.151514) | 0.439044 / 0.283200 (0.155845) | 0.031289 / 0.141683 (-0.110394) | 1.797674 / 1.452155 (0.345520) | 1.835183 / 1.492716 (0.342467) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.268194 / 0.018006 (0.250187) | 0.493614 / 0.000490 (0.493124) | 0.015636 / 0.000200 (0.015436) | 0.000417 / 0.000054 (0.000362) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034188 / 0.037411 (-0.003223) | 0.099127 / 0.014526 (0.084601) | 0.113949 / 0.176557 (-0.062607) | 0.181209 / 0.737135 (-0.555926) | 0.114943 / 0.296338 (-0.181395) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.455767 / 0.215209 (0.240558) | 4.542947 / 2.077655 (2.465293) | 2.214605 / 1.504120 (0.710485) | 2.015163 / 1.541195 (0.473969) | 2.084945 / 1.468490 (0.616455) | 0.583827 / 4.584777 (-4.000950) | 4.187009 / 3.745712 (0.441297) | 3.920841 / 5.269862 (-1.349020) | 2.447260 / 4.565676 (-2.118417) | 0.069139 / 0.424275 (-0.355137) | 0.008734 / 0.007607 (0.001127) | 0.544673 / 0.226044 (0.318629) | 5.445094 / 2.268929 (3.176165) | 2.788284 / 55.444624 (-52.656340) | 2.395863 / 6.876477 (-4.480614) | 2.622632 / 2.142072 (0.480560) | 0.703931 / 4.805227 (-4.101297) | 0.160502 / 6.500664 (-6.340162) | 0.073734 / 0.075469 (-0.001735) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.498992 / 1.841788 (-0.342795) | 22.761476 / 8.074308 (14.687168) | 17.123919 / 10.191392 (6.932527) | 0.170272 / 0.680424 (-0.510151) | 0.021307 / 0.534201 (-0.512894) | 0.467548 / 0.579283 (-0.111735) | 0.480777 / 0.434364 (0.046413) | 0.542168 / 0.540337 (0.001830) | 0.771092 / 1.386936 (-0.615844) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007923 / 0.011353 (-0.003430) | 0.004664 / 0.011008 (-0.006344) | 0.077795 / 0.038508 (0.039286) | 0.090293 / 0.023109 (0.067184) | 0.494682 / 0.275898 (0.218784) | 0.539973 / 0.323480 (0.216494) | 0.006302 / 0.007986 (-0.001684) | 0.003794 / 0.004328 (-0.000535) | 0.076567 / 0.004250 (0.072317) | 0.067141 / 0.037052 (0.030089) | 0.501279 / 0.258489 (0.242790) | 0.555670 / 0.293841 (0.261829) | 0.037773 / 0.128546 (-0.090773) | 0.009930 / 0.075646 (-0.065716) | 0.084839 / 0.419271 (-0.334433) | 0.056876 / 0.043533 (0.013344) | 0.499329 / 0.255139 (0.244190) | 0.518449 / 0.283200 (0.235249) | 0.026041 / 0.141683 (-0.115642) | 1.787259 / 1.452155 (0.335105) | 1.853505 / 1.492716 (0.360788) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.238413 / 0.018006 (0.220407) | 0.488889 / 0.000490 (0.488399) | 0.007476 / 0.000200 (0.007277) | 0.000141 / 0.000054 (0.000087) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038701 / 0.037411 (0.001290) | 0.115391 / 0.014526 (0.100865) | 0.125553 / 0.176557 (-0.051004) | 0.190267 / 0.737135 (-0.546868) | 0.126401 / 0.296338 (-0.169937) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.509270 / 0.215209 (0.294061) | 5.087631 / 2.077655 (3.009976) | 2.745863 / 1.504120 (1.241743) | 2.560259 / 1.541195 (1.019064) | 2.653124 / 1.468490 (1.184634) | 0.582118 / 4.584777 (-4.002659) | 4.181144 / 3.745712 (0.435431) | 3.871179 / 5.269862 (-1.398683) | 2.459849 / 4.565676 (-2.105827) | 0.068844 / 0.424275 (-0.355431) | 0.008672 / 0.007607 (0.001065) | 0.604898 / 0.226044 (0.378854) | 6.073263 / 2.268929 (3.804334) | 3.366638 / 55.444624 (-52.077986) | 2.937261 / 6.876477 (-3.939215) | 3.181173 / 2.142072 (1.039100) | 0.700478 / 4.805227 (-4.104750) | 0.158361 / 6.500664 (-6.342303) | 0.072860 / 0.075469 (-0.002609) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.621363 / 1.841788 (-0.220425) | 23.614315 / 8.074308 (15.540007) | 17.607213 / 10.191392 (7.415821) | 0.198031 / 0.680424 (-0.482393) | 0.023859 / 0.534201 (-0.510342) | 0.474674 / 0.579283 (-0.104609) | 0.491173 / 0.434364 (0.056809) | 0.581995 / 0.540337 (0.041658) | 0.792168 / 1.386936 (-0.594768) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#56fa9645fd24e083adee3cfd0f7d972fce391f0e \"CML watermark\")\n" ]

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[ "I have looked at the doc failures, and I do not think that my change caused the doc build failure, but I'm not 100% sure about that.\r\nI have high confidence that the integration test failures are not something I introduced:-)", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008557 / 0.011353 (-0.002796) | 0.005224 / 0.011008 (-0.005784) | 0.109402 / 0.038508 (0.070893) | 0.075008 / 0.023109 (0.051899) | 0.388910 / 0.275898 (0.113012) | 0.425481 / 0.323480 (0.102002) | 0.005046 / 0.007986 (-0.002939) | 0.004166 / 0.004328 (-0.000162) | 0.079890 / 0.004250 (0.075639) | 0.061992 / 0.037052 (0.024940) | 0.409933 / 0.258489 (0.151444) | 0.444096 / 0.293841 (0.150255) | 0.043958 / 0.128546 (-0.084588) | 0.013655 / 0.075646 (-0.061991) | 0.402620 / 0.419271 (-0.016651) | 0.062784 / 0.043533 (0.019251) | 0.399653 / 0.255139 (0.144514) | 0.432926 / 0.283200 (0.149727) | 0.034631 / 0.141683 (-0.107052) | 1.801450 / 1.452155 (0.349296) | 1.965007 / 1.492716 (0.472290) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.305744 / 0.018006 (0.287738) | 0.590825 / 0.000490 (0.590335) | 0.014561 / 0.000200 (0.014361) | 0.000430 / 0.000054 (0.000375) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030449 / 0.037411 (-0.006962) | 0.091753 / 0.014526 (0.077227) | 0.106259 / 0.176557 (-0.070298) | 0.174599 / 0.737135 (-0.562537) | 0.107069 / 0.296338 (-0.189269) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.607544 / 0.215209 (0.392335) | 6.182592 / 2.077655 (4.104937) | 2.699782 / 1.504120 (1.195663) | 2.386915 / 1.541195 (0.845720) | 2.441763 / 1.468490 (0.973273) | 0.811360 / 4.584777 (-3.773417) | 5.253799 / 3.745712 (1.508087) | 4.762054 / 5.269862 (-0.507807) | 3.045161 / 4.565676 (-1.520515) | 0.095983 / 0.424275 (-0.328292) | 0.008653 / 0.007607 (0.001046) | 0.714218 / 0.226044 (0.488174) | 7.279325 / 2.268929 (5.010397) | 3.356107 / 55.444624 (-52.088517) | 2.765867 / 6.876477 (-4.110610) | 2.997756 / 2.142072 (0.855684) | 1.008740 / 4.805227 (-3.796487) | 0.201462 / 6.500664 (-6.299202) | 0.075780 / 0.075469 (0.000311) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.677034 / 1.841788 (-0.164754) | 23.546919 / 8.074308 (15.472610) | 21.576985 / 10.191392 (11.385593) | 0.239253 / 0.680424 (-0.441171) | 0.028740 / 0.534201 (-0.505460) | 0.468519 / 0.579283 (-0.110765) | 0.593935 / 0.434364 (0.159571) | 0.536830 / 0.540337 (-0.003507) | 0.779925 / 1.386936 (-0.607011) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009582 / 0.011353 (-0.001771) | 0.004971 / 0.011008 (-0.006037) | 0.081304 / 0.038508 (0.042796) | 0.077588 / 0.023109 (0.054478) | 0.486610 / 0.275898 (0.210712) | 0.580228 / 0.323480 (0.256748) | 0.006707 / 0.007986 (-0.001279) | 0.004325 / 0.004328 (-0.000004) | 0.086170 / 0.004250 (0.081920) | 0.060591 / 0.037052 (0.023539) | 0.501723 / 0.258489 (0.243234) | 0.548633 / 0.293841 (0.254793) | 0.050306 / 0.128546 (-0.078240) | 0.017458 / 0.075646 (-0.058188) | 0.093295 / 0.419271 (-0.325977) | 0.064588 / 0.043533 (0.021056) | 0.519395 / 0.255139 (0.264256) | 0.526021 / 0.283200 (0.242821) | 0.035795 / 0.141683 (-0.105888) | 1.792927 / 1.452155 (0.340772) | 1.956499 / 1.492716 (0.463783) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.296249 / 0.018006 (0.278243) | 0.594482 / 0.000490 (0.593992) | 0.007318 / 0.000200 (0.007118) | 0.000182 / 0.000054 (0.000128) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036110 / 0.037411 (-0.001301) | 0.107924 / 0.014526 (0.093399) | 0.119975 / 0.176557 (-0.056582) | 0.177499 / 0.737135 (-0.559636) | 0.123299 / 0.296338 (-0.173039) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.632994 / 0.215209 (0.417785) | 6.481663 / 2.077655 (4.404008) | 3.231259 / 1.504120 (1.727139) | 2.768298 / 1.541195 (1.227103) | 2.694543 / 1.468490 (1.226053) | 0.837384 / 4.584777 (-3.747393) | 5.405278 / 3.745712 (1.659566) | 4.639424 / 5.269862 (-0.630437) | 2.944251 / 4.565676 (-1.621426) | 0.094978 / 0.424275 (-0.329297) | 0.008716 / 0.007607 (0.001108) | 0.795820 / 0.226044 (0.569776) | 8.514233 / 2.268929 (6.245304) | 3.800463 / 55.444624 (-51.644161) | 3.000005 / 6.876477 (-3.876472) | 3.298853 / 2.142072 (1.156781) | 0.994112 / 4.805227 (-3.811115) | 0.209435 / 6.500664 (-6.291229) | 0.075610 / 0.075469 (0.000141) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.681127 / 1.841788 (-0.160661) | 23.874465 / 8.074308 (15.800156) | 21.638567 / 10.191392 (11.447175) | 0.233303 / 0.680424 (-0.447121) | 0.032504 / 0.534201 (-0.501697) | 0.460462 / 0.579283 (-0.118821) | 0.560043 / 0.434364 (0.125679) | 0.555059 / 0.540337 (0.014721) | 0.831444 / 1.386936 (-0.555492) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#faada1742e1f25fce9cc5691ec11d3f91d4aa120 \"CML watermark\")\n" ]

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[ "Thanks for reporting! I've opened a PR with a fix.", "Thanks for the quick response @mariosasko! I just installed your branch via `poetry add 'git+https://github.com/huggingface/datasets#fix-array_values'` and I can confirm it works on the example provided.\r\n\r\nFollow up question for you, should `None`s be supported in these types of features as they are in others?\r\n\r\nFor example, the following script:\r\n\r\n```\r\nfrom datasets import Features, Value, Sequence, ClassLabel, Dataset\r\n\r\ndataset_features = Features({\r\n 'text': Value('string'),\r\n 'embedding': Sequence(Value('double'), length=2),\r\n 'categories': Sequence(ClassLabel(names=sorted([\r\n 'one',\r\n 'two',\r\n 'three'\r\n ]))),\r\n})\r\n\r\ndataset = Dataset.from_dict(\r\n {\r\n 'text': ['A'] * 10000,\r\n \"embedding\": [None] * 10000, # THIS LINE CHANGED\r\n 'categories': [[0]] * 10000,\r\n },\r\n features=dataset_features\r\n)\r\n\r\ndef test_mapper(r):\r\n r['text'] = list(map(lambda t: t + ' b', r['text']))\r\n return r\r\n\r\n\r\ndataset = dataset.map(test_mapper, batched=True, batch_size=10, features=dataset_features, num_proc=2)\r\n```\r\n\r\nfails with\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"/home/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/multiprocess/pool.py\", line 125, in worker\r\n result = (True, func(*args, **kwds))\r\n File \"/home/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/utils/py_utils.py\", line 1354, in _write_generator_to_queue\r\n for i, result in enumerate(func(**kwargs)):\r\n File \"/home/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/arrow_dataset.py\", line 3493, in _map_single\r\n writer.write_batch(batch)\r\n File \"/home/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/arrow_writer.py\", line 549, in write_batch\r\n array = cast_array_to_feature(col_values, col_type) if col_type is not None else col_values\r\n File \"/home/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/table.py\", line 1831, in wrapper\r\n return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])\r\n File \"/home/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/table.py\", line 1831, in <listcomp>\r\n return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])\r\n File \"/home/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/table.py\", line 2160, in cast_array_to_feature\r\n raise TypeError(f\"Couldn't cast array of type\\n{array.type}\\nto\\n{feature}\")\r\nTypeError: Couldn't cast array of type\r\nfixed_size_list<item: double>[2]\r\nto\r\nSequence(feature=Value(dtype='float64', id=None), length=2, id=None)\r\n```\r\n\r\nIdeally we can have empty embedding columns as well!", "This part of PyArrow is buggy and inconsistent regarding features implemented across the types, so the only option is to operate on the Arrow buffer level to fix issues such as the above one.", "Ok - can you take the POC I did [here](https://github.com/huggingface/datasets/commit/15443098e9ce053943172f7ec6fce3769d7dff6e)? Happy to turn this into an actual PR but would appreciate feedback on the implementation before I take another pass!" ]

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[ "This is exactly what I was looking for. It would also be very useful for me :-)" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009624 / 0.011353 (-0.001729) | 0.005121 / 0.011008 (-0.005887) | 0.105560 / 0.038508 (0.067052) | 0.090749 / 0.023109 (0.067640) | 0.430274 / 0.275898 (0.154376) | 0.443399 / 0.323480 (0.119919) | 0.006575 / 0.007986 (-0.001411) | 0.004396 / 0.004328 (0.000068) | 0.080900 / 0.004250 (0.076649) | 0.064921 / 0.037052 (0.027868) | 0.410092 / 0.258489 (0.151603) | 0.470058 / 0.293841 (0.176217) | 0.054160 / 0.128546 (-0.074386) | 0.014367 / 0.075646 (-0.061279) | 0.384844 / 0.419271 (-0.034428) | 0.072818 / 0.043533 (0.029285) | 0.429341 / 0.255139 (0.174202) | 0.430968 / 0.283200 (0.147769) | 0.038437 / 0.141683 (-0.103246) | 1.814456 / 1.452155 (0.362301) | 1.832122 / 1.492716 (0.339406) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.329266 / 0.018006 (0.311260) | 0.596848 / 0.000490 (0.596358) | 0.018291 / 0.000200 (0.018091) | 0.000113 / 0.000054 (0.000058) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030505 / 0.037411 (-0.006907) | 0.097394 / 0.014526 (0.082869) | 0.127144 / 0.176557 (-0.049412) | 0.190251 / 0.737135 (-0.546884) | 0.116543 / 0.296338 (-0.179795) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.592124 / 0.215209 (0.376915) | 5.979801 / 2.077655 (3.902146) | 2.837753 / 1.504120 (1.333633) | 2.492942 / 1.541195 (0.951747) | 2.548083 / 1.468490 (1.079593) | 0.870446 / 4.584777 (-3.714330) | 5.493718 / 3.745712 (1.748006) | 4.945135 / 5.269862 (-0.324727) | 3.133994 / 4.565676 (-1.431683) | 0.097742 / 0.424275 (-0.326533) | 0.008750 / 0.007607 (0.001143) | 0.723304 / 0.226044 (0.497260) | 7.353766 / 2.268929 (5.084838) | 3.504808 / 55.444624 (-51.939816) | 2.872490 / 6.876477 (-4.003987) | 3.186628 / 2.142072 (1.044556) | 1.035470 / 4.805227 (-3.769758) | 0.211980 / 6.500664 (-6.288684) | 0.080356 / 0.075469 (0.004887) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.623389 / 1.841788 (-0.218399) | 23.492350 / 8.074308 (15.418042) | 21.053525 / 10.191392 (10.862133) | 0.225668 / 0.680424 (-0.454756) | 0.028311 / 0.534201 (-0.505890) | 0.472672 / 0.579283 (-0.106611) | 0.581536 / 0.434364 (0.147172) | 0.525180 / 0.540337 (-0.015158) | 0.790420 / 1.386936 (-0.596516) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009091 / 0.011353 (-0.002262) | 0.004978 / 0.011008 (-0.006030) | 0.077633 / 0.038508 (0.039125) | 0.103189 / 0.023109 (0.080080) | 0.500194 / 0.275898 (0.224296) | 0.524310 / 0.323480 (0.200831) | 0.006656 / 0.007986 (-0.001329) | 0.004586 / 0.004328 (0.000257) | 0.075535 / 0.004250 (0.071284) | 0.065100 / 0.037052 (0.028048) | 0.513776 / 0.258489 (0.255287) | 0.528483 / 0.293841 (0.234642) | 0.049877 / 0.128546 (-0.078669) | 0.012494 / 0.075646 (-0.063152) | 0.090225 / 0.419271 (-0.329046) | 0.054648 / 0.043533 (0.011116) | 0.510369 / 0.255139 (0.255230) | 0.540042 / 0.283200 (0.256842) | 0.035966 / 0.141683 (-0.105717) | 1.825965 / 1.452155 (0.373810) | 1.965647 / 1.492716 (0.472931) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.295921 / 0.018006 (0.277914) | 0.605751 / 0.000490 (0.605262) | 0.007243 / 0.000200 (0.007043) | 0.000134 / 0.000054 (0.000079) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032954 / 0.037411 (-0.004457) | 0.093613 / 0.014526 (0.079087) | 0.120010 / 0.176557 (-0.056546) | 0.176168 / 0.737135 (-0.560967) | 0.113978 / 0.296338 (-0.182360) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.682904 / 0.215209 (0.467695) | 6.674640 / 2.077655 (4.596986) | 3.360660 / 1.504120 (1.856540) | 3.227246 / 1.541195 (1.686051) | 3.188852 / 1.468490 (1.720362) | 0.862293 / 4.584777 (-3.722484) | 5.518455 / 3.745712 (1.772743) | 4.881904 / 5.269862 (-0.387957) | 3.066964 / 4.565676 (-1.498712) | 0.099284 / 0.424275 (-0.324991) | 0.008644 / 0.007607 (0.001037) | 0.789231 / 0.226044 (0.563186) | 7.872017 / 2.268929 (5.603089) | 4.037105 / 55.444624 (-51.407519) | 3.318921 / 6.876477 (-3.557555) | 3.621953 / 2.142072 (1.479881) | 1.012049 / 4.805227 (-3.793178) | 0.204541 / 6.500664 (-6.296123) | 0.074509 / 0.075469 (-0.000960) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.748215 / 1.841788 (-0.093573) | 24.274974 / 8.074308 (16.200665) | 20.582389 / 10.191392 (10.390997) | 0.251001 / 0.680424 (-0.429423) | 0.032390 / 0.534201 (-0.501811) | 0.479211 / 0.579283 (-0.100072) | 0.607482 / 0.434364 (0.173118) | 0.587867 / 0.540337 (0.047530) | 0.822399 / 1.386936 (-0.564537) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f2b6b2fd90ba47f19e9ab125f6f7656903dd065f \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009715 / 0.011353 (-0.001638) | 0.005449 / 0.011008 (-0.005559) | 0.108556 / 0.038508 (0.070048) | 0.080512 / 0.023109 (0.057403) | 0.450736 / 0.275898 (0.174838) | 0.487771 / 0.323480 (0.164291) | 0.005155 / 0.007986 (-0.002830) | 0.004213 / 0.004328 (-0.000115) | 0.087247 / 0.004250 (0.082997) | 0.063962 / 0.037052 (0.026909) | 0.454153 / 0.258489 (0.195664) | 0.499917 / 0.293841 (0.206076) | 0.052605 / 0.128546 (-0.075942) | 0.013019 / 0.075646 (-0.062627) | 0.379716 / 0.419271 (-0.039555) | 0.073241 / 0.043533 (0.029708) | 0.473488 / 0.255139 (0.218349) | 0.482944 / 0.283200 (0.199745) | 0.041541 / 0.141683 (-0.100142) | 1.829415 / 1.452155 (0.377261) | 1.953280 / 1.492716 (0.460564) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.313725 / 0.018006 (0.295719) | 0.591336 / 0.000490 (0.590847) | 0.021224 / 0.000200 (0.021025) | 0.000969 / 0.000054 (0.000914) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031874 / 0.037411 (-0.005537) | 0.099786 / 0.014526 (0.085260) | 0.116987 / 0.176557 (-0.059569) | 0.205538 / 0.737135 (-0.531597) | 0.118716 / 0.296338 (-0.177622) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.617145 / 0.215209 (0.401936) | 6.079144 / 2.077655 (4.001489) | 2.567233 / 1.504120 (1.063113) | 2.265301 / 1.541195 (0.724107) | 2.314001 / 1.468490 (0.845511) | 0.871561 / 4.584777 (-3.713216) | 5.477049 / 3.745712 (1.731337) | 4.720552 / 5.269862 (-0.549309) | 3.107515 / 4.565676 (-1.458162) | 0.100438 / 0.424275 (-0.323838) | 0.008586 / 0.007607 (0.000979) | 0.716913 / 0.226044 (0.490869) | 7.108417 / 2.268929 (4.839489) | 3.391336 / 55.444624 (-52.053288) | 2.734052 / 6.876477 (-4.142425) | 2.857226 / 2.142072 (0.715153) | 1.024121 / 4.805227 (-3.781106) | 0.216735 / 6.500664 (-6.283929) | 0.081605 / 0.075469 (0.006136) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.678176 / 1.841788 (-0.163611) | 23.606037 / 8.074308 (15.531729) | 21.485331 / 10.191392 (11.293939) | 0.218312 / 0.680424 (-0.462112) | 0.027061 / 0.534201 (-0.507140) | 0.481188 / 0.579283 (-0.098096) | 0.620592 / 0.434364 (0.186228) | 0.574778 / 0.540337 (0.034441) | 0.831529 / 1.386936 (-0.555407) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011666 / 0.011353 (0.000313) | 0.005187 / 0.011008 (-0.005821) | 0.080692 / 0.038508 (0.042184) | 0.079159 / 0.023109 (0.056049) | 0.530823 / 0.275898 (0.254925) | 0.577807 / 0.323480 (0.254327) | 0.006246 / 0.007986 (-0.001740) | 0.004355 / 0.004328 (0.000026) | 0.080702 / 0.004250 (0.076452) | 0.062279 / 0.037052 (0.025226) | 0.553712 / 0.258489 (0.295223) | 0.579112 / 0.293841 (0.285271) | 0.056374 / 0.128546 (-0.072172) | 0.014681 / 0.075646 (-0.060966) | 0.097110 / 0.419271 (-0.322161) | 0.061040 / 0.043533 (0.017507) | 0.524718 / 0.255139 (0.269579) | 0.568586 / 0.283200 (0.285386) | 0.035774 / 0.141683 (-0.105909) | 1.864590 / 1.452155 (0.412435) | 1.953715 / 1.492716 (0.460998) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.271315 / 0.018006 (0.253309) | 0.571343 / 0.000490 (0.570854) | 0.015812 / 0.000200 (0.015612) | 0.000115 / 0.000054 (0.000060) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038582 / 0.037411 (0.001170) | 0.117523 / 0.014526 (0.102997) | 0.128864 / 0.176557 (-0.047693) | 0.191164 / 0.737135 (-0.545971) | 0.133161 / 0.296338 (-0.163178) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.679305 / 0.215209 (0.464096) | 6.814451 / 2.077655 (4.736796) | 3.377431 / 1.504120 (1.873311) | 3.011008 / 1.541195 (1.469813) | 3.093200 / 1.468490 (1.624710) | 0.905827 / 4.584777 (-3.678950) | 5.456094 / 3.745712 (1.710382) | 4.848511 / 5.269862 (-0.421351) | 3.064230 / 4.565676 (-1.501447) | 0.107478 / 0.424275 (-0.316798) | 0.009234 / 0.007607 (0.001627) | 0.833944 / 0.226044 (0.607899) | 8.286100 / 2.268929 (6.017171) | 4.241455 / 55.444624 (-51.203169) | 3.405460 / 6.876477 (-3.471017) | 3.660618 / 2.142072 (1.518546) | 1.046310 / 4.805227 (-3.758917) | 0.210891 / 6.500664 (-6.289773) | 0.079413 / 0.075469 (0.003944) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.825448 / 1.841788 (-0.016340) | 24.639059 / 8.074308 (16.564750) | 21.970417 / 10.191392 (11.779025) | 0.247708 / 0.680424 (-0.432715) | 0.033810 / 0.534201 (-0.500391) | 0.495517 / 0.579283 (-0.083766) | 0.601820 / 0.434364 (0.167456) | 0.585618 / 0.540337 (0.045280) | 0.858722 / 1.386936 (-0.528214) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0477e20dccb77b68f0add77fd5c9b4cb05473235 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006137 / 0.011353 (-0.005216) | 0.003685 / 0.011008 (-0.007324) | 0.079985 / 0.038508 (0.041476) | 0.060937 / 0.023109 (0.037828) | 0.390583 / 0.275898 (0.114685) | 0.425307 / 0.323480 (0.101827) | 0.003433 / 0.007986 (-0.004552) | 0.002868 / 0.004328 (-0.001461) | 0.062572 / 0.004250 (0.058322) | 0.048642 / 0.037052 (0.011590) | 0.401096 / 0.258489 (0.142607) | 0.436988 / 0.293841 (0.143147) | 0.027645 / 0.128546 (-0.100901) | 0.007973 / 0.075646 (-0.067673) | 0.261997 / 0.419271 (-0.157275) | 0.045393 / 0.043533 (0.001860) | 0.394266 / 0.255139 (0.139127) | 0.414448 / 0.283200 (0.131248) | 0.022551 / 0.141683 (-0.119131) | 1.438458 / 1.452155 (-0.013697) | 1.501568 / 1.492716 (0.008852) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224335 / 0.018006 (0.206329) | 0.421918 / 0.000490 (0.421428) | 0.006883 / 0.000200 (0.006683) | 0.000210 / 0.000054 (0.000155) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023505 / 0.037411 (-0.013906) | 0.072438 / 0.014526 (0.057912) | 0.083576 / 0.176557 (-0.092981) | 0.142906 / 0.737135 (-0.594229) | 0.083910 / 0.296338 (-0.212428) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.396004 / 0.215209 (0.180795) | 3.969852 / 2.077655 (1.892197) | 1.966000 / 1.504120 (0.461880) | 1.786453 / 1.541195 (0.245258) | 1.866082 / 1.468490 (0.397592) | 0.502633 / 4.584777 (-4.082144) | 3.114331 / 3.745712 (-0.631382) | 2.940003 / 5.269862 (-2.329859) | 1.901844 / 4.565676 (-2.663832) | 0.058109 / 0.424275 (-0.366166) | 0.006502 / 0.007607 (-0.001105) | 0.463465 / 0.226044 (0.237420) | 4.641531 / 2.268929 (2.372603) | 2.315759 / 55.444624 (-53.128865) | 2.253088 / 6.876477 (-4.623389) | 2.151399 / 2.142072 (0.009326) | 0.592225 / 4.805227 (-4.213002) | 0.125072 / 6.500664 (-6.375592) | 0.059966 / 0.075469 (-0.015503) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.231392 / 1.841788 (-0.610396) | 17.533893 / 8.074308 (9.459585) | 13.710478 / 10.191392 (3.519086) | 0.147389 / 0.680424 (-0.533035) | 0.017932 / 0.534201 (-0.516269) | 0.334144 / 0.579283 (-0.245139) | 0.368817 / 0.434364 (-0.065547) | 0.383790 / 0.540337 (-0.156547) | 0.540262 / 1.386936 (-0.846674) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006066 / 0.011353 (-0.005287) | 0.003804 / 0.011008 (-0.007205) | 0.062474 / 0.038508 (0.023966) | 0.060547 / 0.023109 (0.037437) | 0.448643 / 0.275898 (0.172745) | 0.487005 / 0.323480 (0.163525) | 0.004884 / 0.007986 (-0.003102) | 0.002911 / 0.004328 (-0.001418) | 0.062950 / 0.004250 (0.058700) | 0.049672 / 0.037052 (0.012620) | 0.477491 / 0.258489 (0.219002) | 0.488234 / 0.293841 (0.194393) | 0.028711 / 0.128546 (-0.099835) | 0.008101 / 0.075646 (-0.067545) | 0.068333 / 0.419271 (-0.350939) | 0.040959 / 0.043533 (-0.002574) | 0.450716 / 0.255139 (0.195577) | 0.471089 / 0.283200 (0.187890) | 0.020710 / 0.141683 (-0.120973) | 1.474850 / 1.452155 (0.022695) | 1.540115 / 1.492716 (0.047399) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229811 / 0.018006 (0.211805) | 0.419526 / 0.000490 (0.419036) | 0.003818 / 0.000200 (0.003618) | 0.000084 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026045 / 0.037411 (-0.011366) | 0.080325 / 0.014526 (0.065799) | 0.091549 / 0.176557 (-0.085007) | 0.145253 / 0.737135 (-0.591882) | 0.091849 / 0.296338 (-0.204489) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.463047 / 0.215209 (0.247838) | 4.598727 / 2.077655 (2.521072) | 2.558996 / 1.504120 (1.054877) | 2.405896 / 1.541195 (0.864701) | 2.447291 / 1.468490 (0.978801) | 0.510393 / 4.584777 (-4.074384) | 3.173344 / 3.745712 (-0.572368) | 2.901201 / 5.269862 (-2.368661) | 1.896440 / 4.565676 (-2.669236) | 0.058374 / 0.424275 (-0.365901) | 0.006449 / 0.007607 (-0.001158) | 0.539653 / 0.226044 (0.313608) | 5.408217 / 2.268929 (3.139289) | 3.042453 / 55.444624 (-52.402172) | 2.656724 / 6.876477 (-4.219753) | 2.838165 / 2.142072 (0.696092) | 0.598663 / 4.805227 (-4.206565) | 0.126211 / 6.500664 (-6.374453) | 0.062830 / 0.075469 (-0.012639) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.392412 / 1.841788 (-0.449376) | 18.195170 / 8.074308 (10.120862) | 14.788251 / 10.191392 (4.596859) | 0.132579 / 0.680424 (-0.547845) | 0.017867 / 0.534201 (-0.516334) | 0.340020 / 0.579283 (-0.239263) | 0.386719 / 0.434364 (-0.047645) | 0.398863 / 0.540337 (-0.141475) | 0.579320 / 1.386936 (-0.807617) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a2569fdfcf387f8885974a35fafa409fbc6dd059 \"CML watermark\")\n", "closing in favor of https://github.com/huggingface/datasets/pull/6282" ]

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[ "`evaluate.load(\"paws-x\", \"es\")` throws the error because there is no such metric in the `evaluate` lib.\r\n\r\nSo, this is unrelated to our lib." ]

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[ "Since you are using Windows, maybe moving the `map` call inside `if __name__ == \"__main__\"` can fix the issue:\r\n```python\r\nif __name__ == \"__main__\":\r\n common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names[\"train\"], num_proc=4)\r\n```\r\n\r\nOtherwise, the only solution is to set `num_proc=1`.", "> Since you are using Windows, maybe moving the `map` call inside `if __name__ == \"__main__\"` can fix the issue:\r\n> \r\n> ```python\r\n> if __name__ == \"__main__\":\r\n> common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names[\"train\"], num_proc=4)\r\n> ```\r\n> \r\n> Otherwise, the only solution is to set `num_proc=1`.\r\n\r\nThank you very much for the response, i eventually tried setting `num_proc=1` and now the jupyter notebook kernel keers dying after running the command, what do you think the issue could be, could it be that my system is not capable of running the command \"i'm using a Lenovo Thinkpad T440 with no GPU\"" ]

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[ "Hi! The process of contributing a dataset is explained here: https://huggingface.co/docs/datasets/upload_dataset. Also, check https://huggingface.co/docs/datasets/image_dataset for a more detailed explanation of how to share an image dataset." ]

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[ "Please tell me if the above info is not enough for solving the problem. I will then make my dataset public temporarily so that you can really reproduce the bug. " ]

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[ "This has already been reported in the HF Course repo (https://github.com/huggingface/course/issues/623).", "@lhoestq @albertvillanova @lewtun I don't think we are allowed to host these data files on the Hub (due to DMCA), which means the only option is to use a different dataset in the course (and to re-record the video 🙂), no?", "Keeping the video is maybe fine, we can add a note on youtube to suggest to load a dataset with a different name. Maybe C4 ? And update the code snippets on the website ?" ]

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[ "Also reported in https://github.com/huggingface/datasets/issues/6259", "I think it's best to drop duplicates with a `set` (as a temporary fix) and improve the patterns when/if https://github.com/fsspec/filesystem_spec/pull/1382 gets merged. @lhoestq Do you have some other ideas?", "Alternatively we could just use this no ?\r\n\r\n```python\r\nif config.FSSPEC_VERSION < version.parse(\"2023.9.0\"):\r\n KEYWORDS_IN_PATH_NAME_BASE_PATTERNS = [\r\n \"{keyword}[{sep}/]**\",\r\n \"**[{sep}]{keyword}[{sep}/]**\",\r\n \"**/{keyword}[{sep}/]**\",\r\n ]\r\nelse:\r\n KEYWORDS_IN_PATH_NAME_BASE_PATTERNS = [\r\n \"{keyword}[{sep}/]**\",\r\n \"**/*[{sep}]{keyword}[{sep}/]**\",\r\n \"**/*/{keyword}[{sep}/]**\",\r\n ]\r\n```\r\n\r\nThis way no need to implement sets, which would require a bit of work since we've always considered a list of pattern to be resolved as the concatenated list of resolved files for each pattern (including duplicates)\r\n", "Arf `\"**/*/{keyword}[{sep}/]**\"` does return `data/keyword.txt` in latest `fsspec` but not in `glob.glob`\r\n\r\nEDIT: actually forgot to set `recursive=True`", "Actually `glob.glob` does return it with `recursive=True` ! my bad", "Pff just tested and my idea sucks, pattern 1 and 3 obviously give duplicates ", "> I think it's best to drop duplicates with a set (as a temporary fix)\r\n\r\nI started https://github.com/huggingface/datasets/pull/6278 to use DataFilesSet objects instead of DataFilesList" ]

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[ "`gen_kwargs` should be a `dict`, as stated in the docstring, but you are passing a `list`.\r\n\r\nSo, to fix the error, replace the list of dicts with a dict of lists (and slightly modify the generator function):\r\n```python\r\nfrom pathlib import Path\r\nimport datasets\r\n\r\ndef process_yaml(files):\r\n for f in files:\r\n # process\r\n yield dict(...)\r\n\r\n\r\nif __name__ == '__main__':\r\n import sys\r\n dir = Path(sys.argv[0]).parent\r\n ds = datasets.Dataset.from_generator(process_yaml, gen_kwargs={'files': [f for f in dir.glob('*.yml')]})\r\n ds.to_json('training.jsonl')\r\n```", "That runs, and because my dataset is small, it's what I did to get past the problem.\r\nHowever, it does not produce a sharded dataset. From the doc string I expect there ought to be a way to call from_generator such that num_shards in the resulting data set is equal to the number of items in the list.\r\nThe part of the doc string that your suggestion is not responsive to is:\r\n` You can define a sharded dataset by passing the list of shards in *g\r\nen_kwargs*.\r\n`\r\n\r\nWhat your suggestion does is calls the generator once, with the list argument, and produces a single shard dataset.\r\n", "The sharding mentioned here refers to using this function with `num_proc` (multiprocessing splits the `kwargs` into shards and passes them to the generator function)\r\n\r\n> That runs, and because my dataset is small, it's what I did to get past the problem.\r\n\r\n`from_generator` generates a memory-mapped dataset (can be larger than RAM), so the dataset size should not be an issue unless the generator function's implementation does not properly free the memory.\r\n", "It sounds like you are saying that num_proc affects the form of gen_kwargs.\r\nAre you saying that for non-zero num_proc gen_kwargs should be a list whose length is the same as num_proc?\r\nOr are you saying that for non-zero num_proc, gen_kwargs should be a dict whose elements are lists the length of num_proc?\r\n", "I ran some tests. So, it looks like with num_proc greater than 1, gen_kwargs is expected to be a dict of lists. It calls the generator also with a dict of lists, but the lists are split.\r\nI.E. if my original has `gen_kwargs=dict(a=[0,1,2])`, then my generator might get called with `gen_kwalrgs=dict([0])`.\r\nThat all makes sense, but I definitely think there is room for improvement in the doc string here.\r\nIn order to suggest improvements to the doc string, I need to look at how the gen_kwargs are split, and figure out if:\r\n* num_proc needs to exactly equal the length of the lists\r\n* num_proc needs to evenly divide the length of the lists\r\n* Or there's no required relationship.\r\nI'll look into that and then propose an improved doc string if no one else gets to it first.", "Okay, that was fun; I took a dive through the dataset code and feel like I have a much better understanding.\r\nHere is my understanding of the behavior:\r\n* max_proc is an upper limit on the number of shards that `from_generator` produces\r\n* If `max_proc` is greater than 1, then all lists in *gen_kwargs* must be the same length\r\n* If the lists in *gen_kwargs* are shorter than *num_proc* elements, *num_proc* will be reduced and a warning produced. Put another way, `min(list_length, num_shards)` shards will be produced\r\n* The members of the lists in *gen_kwargs* will be partitioned among the created jobs.\r\nTo validate the above, take a look at\r\n`_number_of_shards_in_gen_kwargs` and `_distribute_shards` and `_split_gen_kwargs` in utils/sharding.py.\r\nI've also chased down starting at *from_generator* all the way through to GeneratorBuilder and the calls to the functions in sharding.py.\r\nTomorrow I'll take a look at the contributing guidelines and see what's involved in putting together a PR to improve the doc string." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005864 / 0.011353 (-0.005489) | 0.003535 / 0.011008 (-0.007474) | 0.080732 / 0.038508 (0.042224) | 0.057072 / 0.023109 (0.033963) | 0.334342 / 0.275898 (0.058444) | 0.361345 / 0.323480 (0.037865) | 0.003290 / 0.007986 (-0.004696) | 0.003794 / 0.004328 (-0.000534) | 0.063414 / 0.004250 (0.059163) | 0.046901 / 0.037052 (0.009848) | 0.335973 / 0.258489 (0.077484) | 0.377929 / 0.293841 (0.084088) | 0.027199 / 0.128546 (-0.101348) | 0.008049 / 0.075646 (-0.067597) | 0.261810 / 0.419271 (-0.157462) | 0.044669 / 0.043533 (0.001136) | 0.333600 / 0.255139 (0.078461) | 0.356362 / 0.283200 (0.073162) | 0.020325 / 0.141683 (-0.121358) | 1.458138 / 1.452155 (0.005984) | 1.505923 / 1.492716 (0.013207) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.216456 / 0.018006 (0.198450) | 0.421750 / 0.000490 (0.421261) | 0.007359 / 0.000200 (0.007159) | 0.000246 / 0.000054 (0.000191) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023400 / 0.037411 (-0.014012) | 0.073363 / 0.014526 (0.058838) | 0.083533 / 0.176557 (-0.093023) | 0.144045 / 0.737135 (-0.593090) | 0.084050 / 0.296338 (-0.212288) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.398354 / 0.215209 (0.183145) | 3.982875 / 2.077655 (1.905220) | 2.047299 / 1.504120 (0.543180) | 1.873780 / 1.541195 (0.332585) | 1.977044 / 1.468490 (0.508554) | 0.497038 / 4.584777 (-4.087739) | 3.039743 / 3.745712 (-0.705969) | 2.832885 / 5.269862 (-2.436977) | 1.827300 / 4.565676 (-2.738377) | 0.057503 / 0.424275 (-0.366772) | 0.006272 / 0.007607 (-0.001335) | 0.468681 / 0.226044 (0.242637) | 4.696551 / 2.268929 (2.427622) | 2.413805 / 55.444624 (-53.030819) | 2.157199 / 6.876477 (-4.719278) | 2.345986 / 2.142072 (0.203914) | 0.584632 / 4.805227 (-4.220595) | 0.124684 / 6.500664 (-6.375980) | 0.060090 / 0.075469 (-0.015379) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.293551 / 1.841788 (-0.548236) | 17.198292 / 8.074308 (9.123984) | 13.677910 / 10.191392 (3.486518) | 0.146633 / 0.680424 (-0.533791) | 0.016711 / 0.534201 (-0.517490) | 0.331644 / 0.579283 (-0.247639) | 0.360148 / 0.434364 (-0.074215) | 0.381194 / 0.540337 (-0.159143) | 0.537952 / 1.386936 (-0.848984) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006020 / 0.011353 (-0.005333) | 0.003557 / 0.011008 (-0.007451) | 0.061926 / 0.038508 (0.023418) | 0.056246 / 0.023109 (0.033137) | 0.446679 / 0.275898 (0.170781) | 0.479843 / 0.323480 (0.156363) | 0.004656 / 0.007986 (-0.003330) | 0.002823 / 0.004328 (-0.001505) | 0.061366 / 0.004250 (0.057115) | 0.045793 / 0.037052 (0.008740) | 0.460807 / 0.258489 (0.202318) | 0.485467 / 0.293841 (0.191626) | 0.028555 / 0.128546 (-0.099991) | 0.007973 / 0.075646 (-0.067674) | 0.068305 / 0.419271 (-0.350966) | 0.040844 / 0.043533 (-0.002689) | 0.463715 / 0.255139 (0.208576) | 0.474553 / 0.283200 (0.191354) | 0.019959 / 0.141683 (-0.121723) | 1.432527 / 1.452155 (-0.019628) | 1.485410 / 1.492716 (-0.007307) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.205555 / 0.018006 (0.187549) | 0.408271 / 0.000490 (0.407781) | 0.004325 / 0.000200 (0.004125) | 0.000076 / 0.000054 (0.000022) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026338 / 0.037411 (-0.011074) | 0.080534 / 0.014526 (0.066008) | 0.093935 / 0.176557 (-0.082622) | 0.146446 / 0.737135 (-0.590689) | 0.092890 / 0.296338 (-0.203448) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.463879 / 0.215209 (0.248670) | 4.646411 / 2.077655 (2.568756) | 2.567320 / 1.504120 (1.063200) | 2.384376 / 1.541195 (0.843181) | 2.412738 / 1.468490 (0.944248) | 0.510240 / 4.584777 (-4.074537) | 3.094988 / 3.745712 (-0.650724) | 2.837700 / 5.269862 (-2.432161) | 1.850163 / 4.565676 (-2.715513) | 0.059320 / 0.424275 (-0.364955) | 0.006330 / 0.007607 (-0.001277) | 0.537770 / 0.226044 (0.311726) | 5.385556 / 2.268929 (3.116627) | 3.036088 / 55.444624 (-52.408536) | 2.650464 / 6.876477 (-4.226013) | 2.755676 / 2.142072 (0.613603) | 0.607353 / 4.805227 (-4.197875) | 0.124589 / 6.500664 (-6.376075) | 0.060778 / 0.075469 (-0.014691) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.343243 / 1.841788 (-0.498545) | 17.630281 / 8.074308 (9.555973) | 14.401219 / 10.191392 (4.209827) | 0.143252 / 0.680424 (-0.537172) | 0.017880 / 0.534201 (-0.516321) | 0.337391 / 0.579283 (-0.241892) | 0.373531 / 0.434364 (-0.060833) | 0.398408 / 0.540337 (-0.141929) | 0.558925 / 1.386936 (-0.828011) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a8f511638b486b9f83b17fd69a505fe606ad257b \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006552 / 0.011353 (-0.004801) | 0.003853 / 0.011008 (-0.007155) | 0.077673 / 0.038508 (0.039165) | 0.066043 / 0.023109 (0.042934) | 0.289858 / 0.275898 (0.013960) | 0.299009 / 0.323480 (-0.024471) | 0.004806 / 0.007986 (-0.003179) | 0.003517 / 0.004328 (-0.000811) | 0.058227 / 0.004250 (0.053977) | 0.052134 / 0.037052 (0.015082) | 0.328800 / 0.258489 (0.070311) | 0.317616 / 0.293841 (0.023776) | 0.028344 / 0.128546 (-0.100202) | 0.007853 / 0.075646 (-0.067794) | 0.291207 / 0.419271 (-0.128065) | 0.052977 / 0.043533 (0.009444) | 0.287548 / 0.255139 (0.032409) | 0.307647 / 0.283200 (0.024448) | 0.023899 / 0.141683 (-0.117784) | 1.382267 / 1.452155 (-0.069888) | 1.589915 / 1.492716 (0.097199) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.246244 / 0.018006 (0.228238) | 0.478255 / 0.000490 (0.477766) | 0.014115 / 0.000200 (0.013915) | 0.000305 / 0.000054 (0.000250) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027033 / 0.037411 (-0.010378) | 0.073988 / 0.014526 (0.059462) | 0.088337 / 0.176557 (-0.088219) | 0.144067 / 0.737135 (-0.593069) | 0.091295 / 0.296338 (-0.205043) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.365904 / 0.215209 (0.150695) | 3.537330 / 2.077655 (1.459675) | 1.678341 / 1.504120 (0.174221) | 1.530297 / 1.541195 (-0.010898) | 1.605634 / 1.468490 (0.137144) | 0.437461 / 4.584777 (-4.147316) | 3.419040 / 3.745712 (-0.326672) | 3.203549 / 5.269862 (-2.066312) | 1.913214 / 4.565676 (-2.652463) | 0.052675 / 0.424275 (-0.371600) | 0.006681 / 0.007607 (-0.000926) | 0.429269 / 0.226044 (0.203225) | 4.214051 / 2.268929 (1.945122) | 2.217928 / 55.444624 (-53.226696) | 1.842679 / 6.876477 (-5.033798) | 1.867961 / 2.142072 (-0.274111) | 0.550566 / 4.805227 (-4.254661) | 0.118015 / 6.500664 (-6.382649) | 0.054749 / 0.075469 (-0.020720) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.170547 / 1.841788 (-0.671241) | 18.410567 / 8.074308 (10.336259) | 12.729992 / 10.191392 (2.538600) | 0.160426 / 0.680424 (-0.519998) | 0.021259 / 0.534201 (-0.512942) | 0.369573 / 0.579283 (-0.209710) | 0.440350 / 0.434364 (0.005986) | 0.443755 / 0.540337 (-0.096582) | 0.645614 / 1.386936 (-0.741322) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005913 / 0.011353 (-0.005440) | 0.003542 / 0.011008 (-0.007466) | 0.057621 / 0.038508 (0.019113) | 0.065822 / 0.023109 (0.042713) | 0.390847 / 0.275898 (0.114949) | 0.393127 / 0.323480 (0.069647) | 0.005040 / 0.007986 (-0.002945) | 0.002944 / 0.004328 (-0.001384) | 0.069058 / 0.004250 (0.064808) | 0.051594 / 0.037052 (0.014542) | 0.383745 / 0.258489 (0.125256) | 0.414372 / 0.293841 (0.120531) | 0.030038 / 0.128546 (-0.098508) | 0.008109 / 0.075646 (-0.067538) | 0.065444 / 0.419271 (-0.353828) | 0.045974 / 0.043533 (0.002441) | 0.401695 / 0.255139 (0.146556) | 0.417834 / 0.283200 (0.134635) | 0.020137 / 0.141683 (-0.121546) | 1.452130 / 1.452155 (-0.000025) | 1.455259 / 1.492716 (-0.037458) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228262 / 0.018006 (0.210255) | 0.455155 / 0.000490 (0.454665) | 0.006667 / 0.000200 (0.006467) | 0.000207 / 0.000054 (0.000153) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030159 / 0.037411 (-0.007252) | 0.098478 / 0.014526 (0.083952) | 0.101409 / 0.176557 (-0.075147) | 0.148689 / 0.737135 (-0.588446) | 0.103067 / 0.296338 (-0.193272) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.444095 / 0.215209 (0.228886) | 3.991588 / 2.077655 (1.913934) | 2.147845 / 1.504120 (0.643725) | 2.007871 / 1.541195 (0.466676) | 2.042074 / 1.468490 (0.573584) | 0.451592 / 4.584777 (-4.133185) | 3.439400 / 3.745712 (-0.306312) | 3.107756 / 5.269862 (-2.162106) | 1.909785 / 4.565676 (-2.655891) | 0.051718 / 0.424275 (-0.372558) | 0.006597 / 0.007607 (-0.001010) | 0.480822 / 0.226044 (0.254777) | 4.913235 / 2.268929 (2.644307) | 2.631882 / 55.444624 (-52.812742) | 2.397209 / 6.876477 (-4.479267) | 2.487191 / 2.142072 (0.345119) | 0.566321 / 4.805227 (-4.238906) | 0.121741 / 6.500664 (-6.378924) | 0.053399 / 0.075469 (-0.022070) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.256599 / 1.841788 (-0.585189) | 18.891127 / 8.074308 (10.816819) | 13.219662 / 10.191392 (3.028270) | 0.154570 / 0.680424 (-0.525854) | 0.022599 / 0.534201 (-0.511602) | 0.361998 / 0.579283 (-0.217286) | 0.413287 / 0.434364 (-0.021077) | 0.464867 / 0.540337 (-0.075470) | 0.638880 / 1.386936 (-0.748056) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#869e6bc775cf4dff1b92834426e1a286b104432b \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010625 / 0.011353 (-0.000728) | 0.005129 / 0.011008 (-0.005879) | 0.119975 / 0.038508 (0.081467) | 0.100128 / 0.023109 (0.077019) | 0.448678 / 0.275898 (0.172780) | 0.533150 / 0.323480 (0.209670) | 0.005881 / 0.007986 (-0.002105) | 0.007451 / 0.004328 (0.003123) | 0.090792 / 0.004250 (0.086542) | 0.073416 / 0.037052 (0.036363) | 0.455395 / 0.258489 (0.196906) | 0.497572 / 0.293841 (0.203731) | 0.053112 / 0.128546 (-0.075434) | 0.014619 / 0.075646 (-0.061027) | 0.388023 / 0.419271 (-0.031248) | 0.074004 / 0.043533 (0.030471) | 0.435319 / 0.255139 (0.180180) | 0.465985 / 0.283200 (0.182785) | 0.046991 / 0.141683 (-0.094692) | 1.895717 / 1.452155 (0.443563) | 2.086600 / 1.492716 (0.593884) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.334412 / 0.018006 (0.316406) | 0.645510 / 0.000490 (0.645020) | 0.019175 / 0.000200 (0.018975) | 0.000429 / 0.000054 (0.000374) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034385 / 0.037411 (-0.003026) | 0.108939 / 0.014526 (0.094413) | 0.125937 / 0.176557 (-0.050619) | 0.205643 / 0.737135 (-0.531493) | 0.127662 / 0.296338 (-0.168676) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.674093 / 0.215209 (0.458884) | 6.646554 / 2.077655 (4.568900) | 2.837698 / 1.504120 (1.333578) | 2.397199 / 1.541195 (0.856004) | 2.485856 / 1.468490 (1.017366) | 0.955142 / 4.584777 (-3.629635) | 5.667462 / 3.745712 (1.921750) | 5.354129 / 5.269862 (0.084268) | 3.301609 / 4.565676 (-1.264068) | 0.106051 / 0.424275 (-0.318224) | 0.009287 / 0.007607 (0.001680) | 0.766678 / 0.226044 (0.540634) | 7.786701 / 2.268929 (5.517772) | 3.665463 / 55.444624 (-51.779161) | 2.982912 / 6.876477 (-3.893564) | 3.053363 / 2.142072 (0.911290) | 1.141090 / 4.805227 (-3.664137) | 0.223975 / 6.500664 (-6.276689) | 0.093024 / 0.075469 (0.017555) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.728175 / 1.841788 (-0.113613) | 25.640134 / 8.074308 (17.565826) | 22.124769 / 10.191392 (11.933377) | 0.237489 / 0.680424 (-0.442935) | 0.030353 / 0.534201 (-0.503848) | 0.509371 / 0.579283 (-0.069913) | 0.642320 / 0.434364 (0.207956) | 0.576889 / 0.540337 (0.036552) | 0.899377 / 1.386936 (-0.487559) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010846 / 0.011353 (-0.000507) | 0.005876 / 0.011008 (-0.005132) | 0.090810 / 0.038508 (0.052302) | 0.106651 / 0.023109 (0.083542) | 0.551064 / 0.275898 (0.275166) | 0.608328 / 0.323480 (0.284848) | 0.007563 / 0.007986 (-0.000423) | 0.004595 / 0.004328 (0.000267) | 0.089125 / 0.004250 (0.084874) | 0.076577 / 0.037052 (0.039525) | 0.579970 / 0.258489 (0.321481) | 0.620214 / 0.293841 (0.326373) | 0.052577 / 0.128546 (-0.075970) | 0.013734 / 0.075646 (-0.061912) | 0.099825 / 0.419271 (-0.319447) | 0.068391 / 0.043533 (0.024858) | 0.564733 / 0.255139 (0.309594) | 0.593925 / 0.283200 (0.310726) | 0.037201 / 0.141683 (-0.104482) | 1.880969 / 1.452155 (0.428815) | 2.065094 / 1.492716 (0.572377) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.426148 / 0.018006 (0.408141) | 0.673935 / 0.000490 (0.673445) | 0.124190 / 0.000200 (0.123990) | 0.001219 / 0.000054 (0.001164) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.040280 / 0.037411 (0.002868) | 0.122042 / 0.014526 (0.107516) | 0.131333 / 0.176557 (-0.045223) | 0.203039 / 0.737135 (-0.534096) | 0.134851 / 0.296338 (-0.161487) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.684599 / 0.215209 (0.469390) | 6.727529 / 2.077655 (4.649874) | 3.255228 / 1.504120 (1.751108) | 2.925865 / 1.541195 (1.384670) | 2.978762 / 1.468490 (1.510272) | 0.931769 / 4.584777 (-3.653008) | 5.988956 / 3.745712 (2.243244) | 5.228049 / 5.269862 (-0.041812) | 3.341470 / 4.565676 (-1.224206) | 0.106737 / 0.424275 (-0.317539) | 0.009847 / 0.007607 (0.002240) | 0.813954 / 0.226044 (0.587909) | 8.137071 / 2.268929 (5.868143) | 4.140725 / 55.444624 (-51.303899) | 3.500579 / 6.876477 (-3.375898) | 3.623120 / 2.142072 (1.481047) | 1.096634 / 4.805227 (-3.708593) | 0.236938 / 6.500664 (-6.263726) | 0.083099 / 0.075469 (0.007630) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.856112 / 1.841788 (0.014324) | 26.531325 / 8.074308 (18.457017) | 24.435866 / 10.191392 (14.244474) | 0.264093 / 0.680424 (-0.416331) | 0.034872 / 0.534201 (-0.499329) | 0.520682 / 0.579283 (-0.058601) | 0.635010 / 0.434364 (0.200646) | 0.645451 / 0.540337 (0.105113) | 0.914616 / 1.386936 (-0.472320) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d8c29b9416371283e8aaabee235a91b2f45a05ee \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005928 / 0.011353 (-0.005425) | 0.003633 / 0.011008 (-0.007375) | 0.079554 / 0.038508 (0.041046) | 0.057093 / 0.023109 (0.033984) | 0.311374 / 0.275898 (0.035476) | 0.343778 / 0.323480 (0.020298) | 0.004634 / 0.007986 (-0.003352) | 0.002886 / 0.004328 (-0.001443) | 0.061888 / 0.004250 (0.057637) | 0.045895 / 0.037052 (0.008843) | 0.316447 / 0.258489 (0.057958) | 0.358141 / 0.293841 (0.064300) | 0.027247 / 0.128546 (-0.101300) | 0.007947 / 0.075646 (-0.067699) | 0.259070 / 0.419271 (-0.160201) | 0.043802 / 0.043533 (0.000269) | 0.315453 / 0.255139 (0.060314) | 0.335282 / 0.283200 (0.052082) | 0.021096 / 0.141683 (-0.120587) | 1.443219 / 1.452155 (-0.008936) | 1.523140 / 1.492716 (0.030423) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.222957 / 0.018006 (0.204951) | 0.414611 / 0.000490 (0.414122) | 0.008354 / 0.000200 (0.008154) | 0.000249 / 0.000054 (0.000195) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023880 / 0.037411 (-0.013532) | 0.074523 / 0.014526 (0.059997) | 0.084803 / 0.176557 (-0.091754) | 0.146701 / 0.737135 (-0.590435) | 0.084990 / 0.296338 (-0.211348) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.397736 / 0.215209 (0.182527) | 3.961740 / 2.077655 (1.884086) | 1.909014 / 1.504120 (0.404894) | 1.823026 / 1.541195 (0.281831) | 1.966235 / 1.468490 (0.497745) | 0.498056 / 4.584777 (-4.086721) | 3.041408 / 3.745712 (-0.704304) | 2.998010 / 5.269862 (-2.271852) | 1.887293 / 4.565676 (-2.678384) | 0.057096 / 0.424275 (-0.367179) | 0.006338 / 0.007607 (-0.001269) | 0.465166 / 0.226044 (0.239122) | 4.667710 / 2.268929 (2.398781) | 2.480798 / 55.444624 (-52.963826) | 2.270701 / 6.876477 (-4.605776) | 2.376470 / 2.142072 (0.234397) | 0.579873 / 4.805227 (-4.225355) | 0.125032 / 6.500664 (-6.375632) | 0.061057 / 0.075469 (-0.014412) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.229916 / 1.841788 (-0.611872) | 17.829628 / 8.074308 (9.755320) | 13.860184 / 10.191392 (3.668792) | 0.143507 / 0.680424 (-0.536917) | 0.016943 / 0.534201 (-0.517258) | 0.350106 / 0.579283 (-0.229178) | 0.364547 / 0.434364 (-0.069817) | 0.398889 / 0.540337 (-0.141448) | 0.557948 / 1.386936 (-0.828988) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006052 / 0.011353 (-0.005301) | 0.003636 / 0.011008 (-0.007372) | 0.062705 / 0.038508 (0.024197) | 0.057753 / 0.023109 (0.034644) | 0.453219 / 0.275898 (0.177321) | 0.485179 / 0.323480 (0.161699) | 0.004886 / 0.007986 (-0.003100) | 0.002838 / 0.004328 (-0.001490) | 0.062593 / 0.004250 (0.058343) | 0.047476 / 0.037052 (0.010423) | 0.454266 / 0.258489 (0.195777) | 0.487939 / 0.293841 (0.194098) | 0.028124 / 0.128546 (-0.100422) | 0.008000 / 0.075646 (-0.067647) | 0.068335 / 0.419271 (-0.350937) | 0.040491 / 0.043533 (-0.003042) | 0.457868 / 0.255139 (0.202729) | 0.476355 / 0.283200 (0.193155) | 0.019557 / 0.141683 (-0.122126) | 1.507111 / 1.452155 (0.054956) | 1.569720 / 1.492716 (0.077003) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.209205 / 0.018006 (0.191199) | 0.411782 / 0.000490 (0.411292) | 0.003544 / 0.000200 (0.003344) | 0.000072 / 0.000054 (0.000018) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026569 / 0.037411 (-0.010842) | 0.081213 / 0.014526 (0.066687) | 0.090971 / 0.176557 (-0.085585) | 0.145287 / 0.737135 (-0.591849) | 0.091792 / 0.296338 (-0.204546) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.458329 / 0.215209 (0.243120) | 4.574463 / 2.077655 (2.496808) | 2.516693 / 1.504120 (1.012573) | 2.329463 / 1.541195 (0.788269) | 2.386704 / 1.468490 (0.918214) | 0.503526 / 4.584777 (-4.081251) | 3.113382 / 3.745712 (-0.632331) | 2.872538 / 5.269862 (-2.397323) | 1.865483 / 4.565676 (-2.700194) | 0.058292 / 0.424275 (-0.365983) | 0.006434 / 0.007607 (-0.001173) | 0.530804 / 0.226044 (0.304760) | 5.312666 / 2.268929 (3.043738) | 2.992569 / 55.444624 (-52.452055) | 2.611524 / 6.876477 (-4.264953) | 2.779569 / 2.142072 (0.637497) | 0.595200 / 4.805227 (-4.210028) | 0.123957 / 6.500664 (-6.376707) | 0.060601 / 0.075469 (-0.014868) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.345536 / 1.841788 (-0.496252) | 18.183827 / 8.074308 (10.109519) | 14.814084 / 10.191392 (4.622692) | 0.145305 / 0.680424 (-0.535119) | 0.018812 / 0.534201 (-0.515389) | 0.334793 / 0.579283 (-0.244490) | 0.375331 / 0.434364 (-0.059033) | 0.392499 / 0.540337 (-0.147839) | 0.563286 / 1.386936 (-0.823650) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1e186f0b7fe851f1f474020f0d6b1dc35114f994 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008922 / 0.011353 (-0.002431) | 0.005169 / 0.011008 (-0.005840) | 0.106275 / 0.038508 (0.067767) | 0.076446 / 0.023109 (0.053337) | 0.400207 / 0.275898 (0.124309) | 0.476262 / 0.323480 (0.152782) | 0.006032 / 0.007986 (-0.001954) | 0.004266 / 0.004328 (-0.000063) | 0.083518 / 0.004250 (0.079267) | 0.059644 / 0.037052 (0.022592) | 0.409094 / 0.258489 (0.150605) | 0.470400 / 0.293841 (0.176559) | 0.050161 / 0.128546 (-0.078385) | 0.013580 / 0.075646 (-0.062066) | 0.375047 / 0.419271 (-0.044224) | 0.068319 / 0.043533 (0.024786) | 0.433765 / 0.255139 (0.178626) | 0.449221 / 0.283200 (0.166021) | 0.037636 / 0.141683 (-0.104047) | 1.825855 / 1.452155 (0.373700) | 1.889665 / 1.492716 (0.396948) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.319622 / 0.018006 (0.301616) | 0.588878 / 0.000490 (0.588388) | 0.017790 / 0.000200 (0.017590) | 0.000532 / 0.000054 (0.000477) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031152 / 0.037411 (-0.006259) | 0.093808 / 0.014526 (0.079282) | 0.119296 / 0.176557 (-0.057261) | 0.181845 / 0.737135 (-0.555291) | 0.108527 / 0.296338 (-0.187811) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.575106 / 0.215209 (0.359896) | 5.776322 / 2.077655 (3.698668) | 2.592913 / 1.504120 (1.088793) | 2.389481 / 1.541195 (0.848286) | 2.390117 / 1.468490 (0.921627) | 0.852420 / 4.584777 (-3.732357) | 5.474171 / 3.745712 (1.728459) | 4.967188 / 5.269862 (-0.302674) | 3.053712 / 4.565676 (-1.511965) | 0.098128 / 0.424275 (-0.326147) | 0.008722 / 0.007607 (0.001115) | 0.699838 / 0.226044 (0.473794) | 7.103622 / 2.268929 (4.834693) | 3.359326 / 55.444624 (-52.085299) | 2.733943 / 6.876477 (-4.142534) | 2.770001 / 2.142072 (0.627929) | 1.058217 / 4.805227 (-3.747011) | 0.215845 / 6.500664 (-6.284820) | 0.078532 / 0.075469 (0.003063) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.633173 / 1.841788 (-0.208614) | 23.795045 / 8.074308 (15.720737) | 21.094433 / 10.191392 (10.903041) | 0.234522 / 0.680424 (-0.445902) | 0.033632 / 0.534201 (-0.500569) | 0.496701 / 0.579283 (-0.082582) | 0.626861 / 0.434364 (0.192497) | 0.558267 / 0.540337 (0.017930) | 0.807461 / 1.386936 (-0.579475) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009136 / 0.011353 (-0.002217) | 0.005425 / 0.011008 (-0.005584) | 0.081478 / 0.038508 (0.042970) | 0.077240 / 0.023109 (0.054130) | 0.512156 / 0.275898 (0.236258) | 0.561593 / 0.323480 (0.238113) | 0.006499 / 0.007986 (-0.001486) | 0.004080 / 0.004328 (-0.000248) | 0.082121 / 0.004250 (0.077870) | 0.063774 / 0.037052 (0.026722) | 0.509801 / 0.258489 (0.251312) | 0.572826 / 0.293841 (0.278985) | 0.050969 / 0.128546 (-0.077578) | 0.014876 / 0.075646 (-0.060771) | 0.094815 / 0.419271 (-0.324456) | 0.063904 / 0.043533 (0.020371) | 0.530572 / 0.255139 (0.275433) | 0.545940 / 0.283200 (0.262741) | 0.036729 / 0.141683 (-0.104954) | 1.799493 / 1.452155 (0.347339) | 1.931955 / 1.492716 (0.439239) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.291405 / 0.018006 (0.273398) | 0.590257 / 0.000490 (0.589767) | 0.008394 / 0.000200 (0.008194) | 0.000112 / 0.000054 (0.000058) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037613 / 0.037411 (0.000201) | 0.103136 / 0.014526 (0.088610) | 0.121744 / 0.176557 (-0.054813) | 0.198503 / 0.737135 (-0.538632) | 0.120183 / 0.296338 (-0.176156) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.659872 / 0.215209 (0.444663) | 6.616775 / 2.077655 (4.539120) | 3.031679 / 1.504120 (1.527559) | 2.743489 / 1.541195 (1.202294) | 2.786786 / 1.468490 (1.318296) | 0.866625 / 4.584777 (-3.718152) | 5.637705 / 3.745712 (1.891993) | 4.702563 / 5.269862 (-0.567298) | 3.017797 / 4.565676 (-1.547879) | 0.100107 / 0.424275 (-0.324169) | 0.008443 / 0.007607 (0.000836) | 0.791385 / 0.226044 (0.565341) | 7.869504 / 2.268929 (5.600576) | 3.856634 / 55.444624 (-51.587991) | 3.140089 / 6.876477 (-3.736388) | 3.489339 / 2.142072 (1.347267) | 1.132170 / 4.805227 (-3.673058) | 0.219630 / 6.500664 (-6.281034) | 0.082289 / 0.075469 (0.006820) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.781902 / 1.841788 (-0.059885) | 24.912604 / 8.074308 (16.838296) | 21.626512 / 10.191392 (11.435120) | 0.228194 / 0.680424 (-0.452230) | 0.032799 / 0.534201 (-0.501402) | 0.483683 / 0.579283 (-0.095600) | 0.604966 / 0.434364 (0.170602) | 0.617278 / 0.540337 (0.076940) | 0.887337 / 1.386936 (-0.499599) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#579c31fda7182ca6fc33ab1e95db9e3a21fb5518 \"CML watermark\")\n", "I used [this](https://colab.research.google.com/drive/1q2FYnkJFDMM3OZbhnYeZkfzmBa6ksofQ?usp=sharing) Colab to test the new `push_to_hub` on a large dataset (55 GB). It works great. \r\n\r\nOne thing that could be improved is the performance of `dataset.data.nbytes` - it takes ≈ 3 minutes to compute for the dataset in question (50k array chunks per column). It probably makes sense to store larger chunks locally. But this can be addressed in a subsequent PR.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007190 / 0.011353 (-0.004163) | 0.004394 / 0.011008 (-0.006614) | 0.085506 / 0.038508 (0.046998) | 0.092177 / 0.023109 (0.069068) | 0.351636 / 0.275898 (0.075738) | 0.389716 / 0.323480 (0.066236) | 0.004443 / 0.007986 (-0.003543) | 0.003641 / 0.004328 (-0.000687) | 0.066578 / 0.004250 (0.062328) | 0.061399 / 0.037052 (0.024346) | 0.356008 / 0.258489 (0.097519) | 0.398677 / 0.293841 (0.104836) | 0.031958 / 0.128546 (-0.096588) | 0.008857 / 0.075646 (-0.066789) | 0.289613 / 0.419271 (-0.129659) | 0.053555 / 0.043533 (0.010022) | 0.349268 / 0.255139 (0.094129) | 0.368666 / 0.283200 (0.085466) | 0.028267 / 0.141683 (-0.113416) | 1.502857 / 1.452155 (0.050702) | 1.598422 / 1.492716 (0.105705) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.319938 / 0.018006 (0.301931) | 0.566925 / 0.000490 (0.566435) | 0.014625 / 0.000200 (0.014425) | 0.000372 / 0.000054 (0.000318) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030156 / 0.037411 (-0.007255) | 0.083128 / 0.014526 (0.068602) | 0.101435 / 0.176557 (-0.075122) | 0.158971 / 0.737135 (-0.578165) | 0.101488 / 0.296338 (-0.194851) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383904 / 0.215209 (0.168695) | 3.829201 / 2.077655 (1.751546) | 1.815224 / 1.504120 (0.311104) | 1.647865 / 1.541195 (0.106670) | 1.738411 / 1.468490 (0.269921) | 0.484963 / 4.584777 (-4.099814) | 3.494811 / 3.745712 (-0.250901) | 3.505811 / 5.269862 (-1.764051) | 2.115467 / 4.565676 (-2.450210) | 0.057271 / 0.424275 (-0.367004) | 0.007285 / 0.007607 (-0.000322) | 0.467162 / 0.226044 (0.241118) | 4.661572 / 2.268929 (2.392643) | 2.330443 / 55.444624 (-53.114182) | 1.986116 / 6.876477 (-4.890361) | 2.055350 / 2.142072 (-0.086723) | 0.580369 / 4.805227 (-4.224858) | 0.132700 / 6.500664 (-6.367964) | 0.061219 / 0.075469 (-0.014251) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.270843 / 1.841788 (-0.570945) | 19.870723 / 8.074308 (11.796415) | 14.368932 / 10.191392 (4.177540) | 0.167345 / 0.680424 (-0.513079) | 0.018358 / 0.534201 (-0.515843) | 0.390833 / 0.579283 (-0.188450) | 0.419884 / 0.434364 (-0.014480) | 0.465683 / 0.540337 (-0.074655) | 0.646101 / 1.386936 (-0.740835) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007027 / 0.011353 (-0.004326) | 0.004578 / 0.011008 (-0.006430) | 0.066468 / 0.038508 (0.027960) | 0.081576 / 0.023109 (0.058466) | 0.414928 / 0.275898 (0.139030) | 0.452130 / 0.323480 (0.128651) | 0.005861 / 0.007986 (-0.002124) | 0.003740 / 0.004328 (-0.000588) | 0.066943 / 0.004250 (0.062692) | 0.060100 / 0.037052 (0.023048) | 0.418697 / 0.258489 (0.160208) | 0.466604 / 0.293841 (0.172764) | 0.031887 / 0.128546 (-0.096660) | 0.009119 / 0.075646 (-0.066527) | 0.072285 / 0.419271 (-0.346986) | 0.047599 / 0.043533 (0.004066) | 0.410791 / 0.255139 (0.155652) | 0.434182 / 0.283200 (0.150982) | 0.024799 / 0.141683 (-0.116884) | 1.500310 / 1.452155 (0.048155) | 1.567151 / 1.492716 (0.074434) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.322482 / 0.018006 (0.304476) | 0.550234 / 0.000490 (0.549744) | 0.007796 / 0.000200 (0.007596) | 0.000088 / 0.000054 (0.000033) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036013 / 0.037411 (-0.001398) | 0.098482 / 0.014526 (0.083956) | 0.111641 / 0.176557 (-0.064916) | 0.166251 / 0.737135 (-0.570884) | 0.112426 / 0.296338 (-0.183912) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.429181 / 0.215209 (0.213972) | 4.273126 / 2.077655 (2.195472) | 2.277440 / 1.504120 (0.773321) | 2.112567 / 1.541195 (0.571372) | 2.224118 / 1.468490 (0.755628) | 0.488876 / 4.584777 (-4.095901) | 3.711638 / 3.745712 (-0.034074) | 3.480995 / 5.269862 (-1.788867) | 2.122114 / 4.565676 (-2.443563) | 0.057538 / 0.424275 (-0.366737) | 0.007416 / 0.007607 (-0.000191) | 0.506881 / 0.226044 (0.280836) | 5.067601 / 2.268929 (2.798672) | 2.769216 / 55.444624 (-52.675408) | 2.420448 / 6.876477 (-4.456029) | 2.694225 / 2.142072 (0.552153) | 0.588911 / 4.805227 (-4.216316) | 0.133542 / 6.500664 (-6.367122) | 0.061135 / 0.075469 (-0.014334) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.378029 / 1.841788 (-0.463758) | 20.660942 / 8.074308 (12.586634) | 15.725969 / 10.191392 (5.534577) | 0.169078 / 0.680424 (-0.511346) | 0.020540 / 0.534201 (-0.513661) | 0.399409 / 0.579283 (-0.179874) | 0.432572 / 0.434364 (-0.001792) | 0.477106 / 0.540337 (-0.063231) | 0.675593 / 1.386936 (-0.711343) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9764c49d8bfdad5439e16faa6c52e510feabf6fa \"CML watermark\")\n", "@lhoestq \r\n\r\n> single commit can fail (time out) if there are too many operations so we might have to do multi commits anyway in that case\r\n\r\nMultiple commits complicate the logic significantly. Maybe, let's keep things simple and emit a warning if there are more than 100 additions (we can suggest increasing `max_shard_size` in that case). Additionally, we can set the default `max_shard_size` to a higher value, e.g., 5GB. I think handling up to 500GB of data in the default case seems reasonable. In rare cases where this is a problem, one could increase the default `max_shard_size` even further (if RAM is not a limiting factor) or use `to_parquet` + `huggingface_hub` (we could have a docstring or a doc note that explains this).\r\n\r\nNote that we split the dataset based on the Arrow data size, which means Parquet shards will be considerably smaller unless there are binary fields such as image JPEGs in the dataset, which are hard to compress efficiently.\r\n\r\n> how to let users resume a push_to_hub that failed mid-way because of a connection error for example\r\n\r\nThey can resume by rerunning the failed `push_to_hub`.\r\n\r\n`preupload_lfs_files` will be instant in that scenario, as explained in https://github.com/huggingface/huggingface_hub/pull/1699#discussion_r1342446406", "> Multiple commits complicate the logic significantly. Maybe, let's keep things simple and emit a warning if there are more than 100 additions (we can suggest increasing max_shard_size in that case)\r\n\r\nI don't think we can do that, many people are uploading files with 100+ files and it would break their workflow", "Indeed, we should not break this, considering the number of datasets with more than 100 shards on the Hub (over 1k)", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006834 / 0.011353 (-0.004519) | 0.004424 / 0.011008 (-0.006584) | 0.085199 / 0.038508 (0.046691) | 0.080237 / 0.023109 (0.057128) | 0.308800 / 0.275898 (0.032902) | 0.346314 / 0.323480 (0.022835) | 0.004399 / 0.007986 (-0.003586) | 0.003773 / 0.004328 (-0.000556) | 0.065886 / 0.004250 (0.061636) | 0.057830 / 0.037052 (0.020777) | 0.312035 / 0.258489 (0.053546) | 0.362646 / 0.293841 (0.068805) | 0.031223 / 0.128546 (-0.097323) | 0.008851 / 0.075646 (-0.066795) | 0.288264 / 0.419271 (-0.131007) | 0.052600 / 0.043533 (0.009067) | 0.316127 / 0.255139 (0.060988) | 0.328539 / 0.283200 (0.045340) | 0.026068 / 0.141683 (-0.115615) | 1.458928 / 1.452155 (0.006773) | 1.547619 / 1.492716 (0.054902) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.274382 / 0.018006 (0.256375) | 0.591192 / 0.000490 (0.590703) | 0.009290 / 0.000200 (0.009090) | 0.000327 / 0.000054 (0.000273) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031428 / 0.037411 (-0.005983) | 0.087523 / 0.014526 (0.072997) | 0.101427 / 0.176557 (-0.075130) | 0.159228 / 0.737135 (-0.577907) | 0.101430 / 0.296338 (-0.194909) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.393914 / 0.215209 (0.178705) | 3.917323 / 2.077655 (1.839668) | 1.940577 / 1.504120 (0.436457) | 1.760996 / 1.541195 (0.219801) | 1.865858 / 1.468490 (0.397368) | 0.488920 / 4.584777 (-4.095857) | 3.513465 / 3.745712 (-0.232248) | 3.506600 / 5.269862 (-1.763261) | 2.072583 / 4.565676 (-2.493093) | 0.058256 / 0.424275 (-0.366019) | 0.007420 / 0.007607 (-0.000187) | 0.467241 / 0.226044 (0.241197) | 4.671470 / 2.268929 (2.402542) | 2.422717 / 55.444624 (-53.021908) | 2.069501 / 6.876477 (-4.806975) | 2.159257 / 2.142072 (0.017184) | 0.583808 / 4.805227 (-4.221419) | 0.134160 / 6.500664 (-6.366504) | 0.068855 / 0.075469 (-0.006614) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.305299 / 1.841788 (-0.536488) | 19.913902 / 8.074308 (11.839593) | 14.708057 / 10.191392 (4.516665) | 0.160113 / 0.680424 (-0.520311) | 0.018431 / 0.534201 (-0.515770) | 0.396147 / 0.579283 (-0.183136) | 0.411738 / 0.434364 (-0.022626) | 0.459297 / 0.540337 (-0.081041) | 0.636599 / 1.386936 (-0.750337) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006936 / 0.011353 (-0.004417) | 0.004290 / 0.011008 (-0.006718) | 0.065754 / 0.038508 (0.027246) | 0.080655 / 0.023109 (0.057546) | 0.399701 / 0.275898 (0.123803) | 0.435999 / 0.323480 (0.112519) | 0.005690 / 0.007986 (-0.002295) | 0.003580 / 0.004328 (-0.000748) | 0.065685 / 0.004250 (0.061434) | 0.059299 / 0.037052 (0.022246) | 0.404295 / 0.258489 (0.145806) | 0.438745 / 0.293841 (0.144904) | 0.032241 / 0.128546 (-0.096305) | 0.008699 / 0.075646 (-0.066947) | 0.072053 / 0.419271 (-0.347218) | 0.047489 / 0.043533 (0.003956) | 0.395638 / 0.255139 (0.140499) | 0.417224 / 0.283200 (0.134025) | 0.022734 / 0.141683 (-0.118949) | 1.507519 / 1.452155 (0.055364) | 1.570459 / 1.492716 (0.077743) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.260442 / 0.018006 (0.242435) | 0.551933 / 0.000490 (0.551444) | 0.005240 / 0.000200 (0.005040) | 0.000097 / 0.000054 (0.000042) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033718 / 0.037411 (-0.003694) | 0.095710 / 0.014526 (0.081184) | 0.109970 / 0.176557 (-0.066586) | 0.167930 / 0.737135 (-0.569205) | 0.109977 / 0.296338 (-0.186362) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.430067 / 0.215209 (0.214857) | 4.292564 / 2.077655 (2.214910) | 2.313511 / 1.504120 (0.809391) | 2.158153 / 1.541195 (0.616959) | 2.262486 / 1.468490 (0.793996) | 0.492376 / 4.584777 (-4.092401) | 3.622287 / 3.745712 (-0.123425) | 3.380162 / 5.269862 (-1.889699) | 2.111874 / 4.565676 (-2.453803) | 0.057882 / 0.424275 (-0.366393) | 0.007317 / 0.007607 (-0.000290) | 0.504722 / 0.226044 (0.278678) | 5.039009 / 2.268929 (2.770080) | 2.772162 / 55.444624 (-52.672463) | 2.430928 / 6.876477 (-4.445549) | 2.666556 / 2.142072 (0.524484) | 0.586722 / 4.805227 (-4.218505) | 0.133780 / 6.500664 (-6.366884) | 0.060269 / 0.075469 (-0.015200) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.339064 / 1.841788 (-0.502724) | 20.743931 / 8.074308 (12.669623) | 15.491066 / 10.191392 (5.299674) | 0.159236 / 0.680424 (-0.521188) | 0.020722 / 0.534201 (-0.513479) | 0.399440 / 0.579283 (-0.179843) | 0.424501 / 0.434364 (-0.009863) | 0.474026 / 0.540337 (-0.066311) | 0.685239 / 1.386936 (-0.701697) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#58406f61c52e7ff064ac6c19ebdb3e5247c70862 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005930 / 0.011353 (-0.005422) | 0.003496 / 0.011008 (-0.007512) | 0.079631 / 0.038508 (0.041123) | 0.058250 / 0.023109 (0.035141) | 0.310108 / 0.275898 (0.034210) | 0.352747 / 0.323480 (0.029267) | 0.005367 / 0.007986 (-0.002619) | 0.002943 / 0.004328 (-0.001386) | 0.062449 / 0.004250 (0.058199) | 0.046433 / 0.037052 (0.009381) | 0.311020 / 0.258489 (0.052531) | 0.361033 / 0.293841 (0.067192) | 0.027419 / 0.128546 (-0.101128) | 0.008073 / 0.075646 (-0.067574) | 0.261403 / 0.419271 (-0.157869) | 0.045059 / 0.043533 (0.001527) | 0.310622 / 0.255139 (0.055483) | 0.344361 / 0.283200 (0.061161) | 0.020561 / 0.141683 (-0.121122) | 1.427409 / 1.452155 (-0.024746) | 1.506612 / 1.492716 (0.013896) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.234095 / 0.018006 (0.216089) | 0.432603 / 0.000490 (0.432113) | 0.010283 / 0.000200 (0.010083) | 0.000289 / 0.000054 (0.000235) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024263 / 0.037411 (-0.013148) | 0.073672 / 0.014526 (0.059146) | 0.084080 / 0.176557 (-0.092476) | 0.146679 / 0.737135 (-0.590457) | 0.084337 / 0.296338 (-0.212001) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434297 / 0.215209 (0.219088) | 4.358287 / 2.077655 (2.280633) | 2.268461 / 1.504120 (0.764341) | 2.107924 / 1.541195 (0.566729) | 2.165136 / 1.468490 (0.696646) | 0.498421 / 4.584777 (-4.086356) | 3.094414 / 3.745712 (-0.651298) | 2.991511 / 5.269862 (-2.278351) | 1.998052 / 4.565676 (-2.567624) | 0.057363 / 0.424275 (-0.366912) | 0.006405 / 0.007607 (-0.001203) | 0.508396 / 0.226044 (0.282351) | 5.104756 / 2.268929 (2.835828) | 2.720462 / 55.444624 (-52.724163) | 2.391840 / 6.876477 (-4.484637) | 2.443063 / 2.142072 (0.300991) | 0.590015 / 4.805227 (-4.215212) | 0.125414 / 6.500664 (-6.375250) | 0.061122 / 0.075469 (-0.014347) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.221883 / 1.841788 (-0.619904) | 17.788248 / 8.074308 (9.713940) | 13.753315 / 10.191392 (3.561923) | 0.146388 / 0.680424 (-0.534036) | 0.017038 / 0.534201 (-0.517163) | 0.339162 / 0.579283 (-0.240121) | 0.372054 / 0.434364 (-0.062309) | 0.381507 / 0.540337 (-0.158830) | 0.538603 / 1.386936 (-0.848333) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006044 / 0.011353 (-0.005309) | 0.003654 / 0.011008 (-0.007354) | 0.062956 / 0.038508 (0.024448) | 0.061325 / 0.023109 (0.038216) | 0.450006 / 0.275898 (0.174108) | 0.474560 / 0.323480 (0.151080) | 0.004846 / 0.007986 (-0.003140) | 0.002904 / 0.004328 (-0.001425) | 0.064206 / 0.004250 (0.059956) | 0.047850 / 0.037052 (0.010798) | 0.448431 / 0.258489 (0.189942) | 0.481363 / 0.293841 (0.187523) | 0.028622 / 0.128546 (-0.099925) | 0.008255 / 0.075646 (-0.067391) | 0.068461 / 0.419271 (-0.350810) | 0.040234 / 0.043533 (-0.003299) | 0.447396 / 0.255139 (0.192257) | 0.465383 / 0.283200 (0.182184) | 0.021864 / 0.141683 (-0.119819) | 1.402197 / 1.452155 (-0.049957) | 1.475337 / 1.492716 (-0.017379) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227093 / 0.018006 (0.209087) | 0.407908 / 0.000490 (0.407419) | 0.006709 / 0.000200 (0.006509) | 0.000076 / 0.000054 (0.000022) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026560 / 0.037411 (-0.010851) | 0.080926 / 0.014526 (0.066400) | 0.091531 / 0.176557 (-0.085026) | 0.145742 / 0.737135 (-0.591393) | 0.092203 / 0.296338 (-0.204135) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.473029 / 0.215209 (0.257820) | 4.703613 / 2.077655 (2.625958) | 2.642622 / 1.504120 (1.138502) | 2.465376 / 1.541195 (0.924181) | 2.510125 / 1.468490 (1.041635) | 0.512606 / 4.584777 (-4.072171) | 3.132127 / 3.745712 (-0.613585) | 2.890098 / 5.269862 (-2.379763) | 1.908140 / 4.565676 (-2.657537) | 0.058938 / 0.424275 (-0.365337) | 0.006486 / 0.007607 (-0.001121) | 0.542279 / 0.226044 (0.316235) | 5.435621 / 2.268929 (3.166693) | 3.083943 / 55.444624 (-52.360681) | 2.761575 / 6.876477 (-4.114901) | 2.919672 / 2.142072 (0.777599) | 0.608022 / 4.805227 (-4.197205) | 0.126821 / 6.500664 (-6.373843) | 0.061374 / 0.075469 (-0.014095) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.348848 / 1.841788 (-0.492940) | 18.323507 / 8.074308 (10.249199) | 14.713411 / 10.191392 (4.522019) | 0.155277 / 0.680424 (-0.525146) | 0.017739 / 0.534201 (-0.516462) | 0.337357 / 0.579283 (-0.241926) | 0.376519 / 0.434364 (-0.057844) | 0.398011 / 0.540337 (-0.142327) | 0.589797 / 1.386936 (-0.797139) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#26d8bfca337e01bd78d5590d5e49c6d8d022a3ff \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007823 / 0.011353 (-0.003530) | 0.004136 / 0.011008 (-0.006872) | 0.087282 / 0.038508 (0.048774) | 0.086352 / 0.023109 (0.063243) | 0.328107 / 0.275898 (0.052209) | 0.368717 / 0.323480 (0.045237) | 0.005452 / 0.007986 (-0.002533) | 0.003460 / 0.004328 (-0.000868) | 0.064360 / 0.004250 (0.060110) | 0.062215 / 0.037052 (0.025162) | 0.334666 / 0.258489 (0.076177) | 0.388688 / 0.293841 (0.094847) | 0.031093 / 0.128546 (-0.097454) | 0.008510 / 0.075646 (-0.067137) | 0.295965 / 0.419271 (-0.123306) | 0.052858 / 0.043533 (0.009325) | 0.320104 / 0.255139 (0.064965) | 0.346761 / 0.283200 (0.063562) | 0.024864 / 0.141683 (-0.116819) | 1.483164 / 1.452155 (0.031010) | 1.580363 / 1.492716 (0.087647) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.243523 / 0.018006 (0.225516) | 0.459741 / 0.000490 (0.459251) | 0.010508 / 0.000200 (0.010308) | 0.000384 / 0.000054 (0.000330) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029896 / 0.037411 (-0.007515) | 0.089150 / 0.014526 (0.074624) | 0.098855 / 0.176557 (-0.077702) | 0.154469 / 0.737135 (-0.582667) | 0.099546 / 0.296338 (-0.196792) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.403547 / 0.215209 (0.188338) | 4.036711 / 2.077655 (1.959056) | 2.030882 / 1.504120 (0.526762) | 1.850432 / 1.541195 (0.309238) | 1.924248 / 1.468490 (0.455758) | 0.493153 / 4.584777 (-4.091624) | 3.634074 / 3.745712 (-0.111638) | 3.546145 / 5.269862 (-1.723717) | 2.120819 / 4.565676 (-2.444858) | 0.057137 / 0.424275 (-0.367138) | 0.007454 / 0.007607 (-0.000153) | 0.481687 / 0.226044 (0.255642) | 4.813203 / 2.268929 (2.544275) | 2.481260 / 55.444624 (-52.963364) | 2.194185 / 6.876477 (-4.682292) | 2.255381 / 2.142072 (0.113308) | 0.575160 / 4.805227 (-4.230068) | 0.132310 / 6.500664 (-6.368355) | 0.061917 / 0.075469 (-0.013553) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.265722 / 1.841788 (-0.576066) | 19.949624 / 8.074308 (11.875315) | 14.804356 / 10.191392 (4.612964) | 0.170485 / 0.680424 (-0.509939) | 0.018831 / 0.534201 (-0.515370) | 0.407051 / 0.579283 (-0.172233) | 0.420560 / 0.434364 (-0.013804) | 0.470721 / 0.540337 (-0.069616) | 0.651665 / 1.386936 (-0.735271) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007113 / 0.011353 (-0.004240) | 0.004186 / 0.011008 (-0.006822) | 0.065082 / 0.038508 (0.026574) | 0.080275 / 0.023109 (0.057166) | 0.393460 / 0.275898 (0.117562) | 0.426702 / 0.323480 (0.103223) | 0.005639 / 0.007986 (-0.002347) | 0.003492 / 0.004328 (-0.000836) | 0.065774 / 0.004250 (0.061523) | 0.059708 / 0.037052 (0.022656) | 0.395598 / 0.258489 (0.137109) | 0.437088 / 0.293841 (0.143247) | 0.033165 / 0.128546 (-0.095381) | 0.008559 / 0.075646 (-0.067087) | 0.071782 / 0.419271 (-0.347490) | 0.048672 / 0.043533 (0.005139) | 0.393883 / 0.255139 (0.138744) | 0.412817 / 0.283200 (0.129617) | 0.024115 / 0.141683 (-0.117568) | 1.522752 / 1.452155 (0.070597) | 1.577311 / 1.492716 (0.084595) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.225569 / 0.018006 (0.207563) | 0.460310 / 0.000490 (0.459820) | 0.004733 / 0.000200 (0.004533) | 0.000115 / 0.000054 (0.000060) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035241 / 0.037411 (-0.002170) | 0.098092 / 0.014526 (0.083566) | 0.108025 / 0.176557 (-0.068531) | 0.162910 / 0.737135 (-0.574225) | 0.108649 / 0.296338 (-0.187689) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.441723 / 0.215209 (0.226514) | 4.400656 / 2.077655 (2.323001) | 2.413588 / 1.504120 (0.909468) | 2.261890 / 1.541195 (0.720696) | 2.420878 / 1.468490 (0.952388) | 0.496456 / 4.584777 (-4.088321) | 3.679930 / 3.745712 (-0.065782) | 3.390539 / 5.269862 (-1.879322) | 2.109599 / 4.565676 (-2.456078) | 0.058896 / 0.424275 (-0.365379) | 0.007483 / 0.007607 (-0.000125) | 0.521108 / 0.226044 (0.295064) | 5.209468 / 2.268929 (2.940540) | 2.948595 / 55.444624 (-52.496029) | 2.658864 / 6.876477 (-4.217613) | 2.913653 / 2.142072 (0.771580) | 0.602776 / 4.805227 (-4.202451) | 0.136166 / 6.500664 (-6.364498) | 0.063812 / 0.075469 (-0.011657) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350306 / 1.841788 (-0.491482) | 20.453980 / 8.074308 (12.379672) | 15.758719 / 10.191392 (5.567327) | 0.165847 / 0.680424 (-0.514577) | 0.020254 / 0.534201 (-0.513947) | 0.400006 / 0.579283 (-0.179277) | 0.440336 / 0.434364 (0.005972) | 0.480122 / 0.540337 (-0.060215) | 0.688994 / 1.386936 (-0.697942) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#997082a2a3c599ea1b23a70759d3af98a78f7f33 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008633 / 0.011353 (-0.002720) | 0.004851 / 0.011008 (-0.006157) | 0.100647 / 0.038508 (0.062139) | 0.084701 / 0.023109 (0.061592) | 0.410489 / 0.275898 (0.134590) | 0.440231 / 0.323480 (0.116751) | 0.004679 / 0.007986 (-0.003307) | 0.004172 / 0.004328 (-0.000157) | 0.079911 / 0.004250 (0.075661) | 0.069537 / 0.037052 (0.032485) | 0.423506 / 0.258489 (0.165017) | 0.466098 / 0.293841 (0.172257) | 0.048773 / 0.128546 (-0.079773) | 0.014446 / 0.075646 (-0.061200) | 0.342776 / 0.419271 (-0.076495) | 0.065672 / 0.043533 (0.022139) | 0.411845 / 0.255139 (0.156706) | 0.466662 / 0.283200 (0.183462) | 0.035752 / 0.141683 (-0.105931) | 1.684956 / 1.452155 (0.232801) | 1.832173 / 1.492716 (0.339456) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.250744 / 0.018006 (0.232738) | 0.528860 / 0.000490 (0.528371) | 0.013301 / 0.000200 (0.013101) | 0.000413 / 0.000054 (0.000359) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032376 / 0.037411 (-0.005035) | 0.094630 / 0.014526 (0.080104) | 0.107163 / 0.176557 (-0.069394) | 0.172503 / 0.737135 (-0.564633) | 0.108407 / 0.296338 (-0.187932) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.671251 / 0.215209 (0.456042) | 6.235361 / 2.077655 (4.157706) | 2.650328 / 1.504120 (1.146208) | 2.341199 / 1.541195 (0.800004) | 2.368803 / 1.468490 (0.900313) | 0.841347 / 4.584777 (-3.743430) | 5.042508 / 3.745712 (1.296796) | 4.807565 / 5.269862 (-0.462296) | 3.007420 / 4.565676 (-1.558257) | 0.099953 / 0.424275 (-0.324322) | 0.008412 / 0.007607 (0.000805) | 0.747803 / 0.226044 (0.521759) | 7.481245 / 2.268929 (5.212316) | 3.416157 / 55.444624 (-52.028467) | 2.724608 / 6.876477 (-4.151869) | 2.832982 / 2.142072 (0.690910) | 1.072423 / 4.805227 (-3.732804) | 0.211314 / 6.500664 (-6.289351) | 0.074098 / 0.075469 (-0.001371) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.566010 / 1.841788 (-0.275778) | 23.137708 / 8.074308 (15.063400) | 21.440132 / 10.191392 (11.248740) | 0.230713 / 0.680424 (-0.449711) | 0.028271 / 0.534201 (-0.505930) | 0.450821 / 0.579283 (-0.128463) | 0.548399 / 0.434364 (0.114035) | 0.543588 / 0.540337 (0.003250) | 0.805522 / 1.386936 (-0.581414) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008969 / 0.011353 (-0.002384) | 0.004793 / 0.011008 (-0.006216) | 0.075804 / 0.038508 (0.037296) | 0.079893 / 0.023109 (0.056783) | 0.464358 / 0.275898 (0.188460) | 0.507243 / 0.323480 (0.183763) | 0.005945 / 0.007986 (-0.002040) | 0.005341 / 0.004328 (0.001012) | 0.077952 / 0.004250 (0.073701) | 0.059965 / 0.037052 (0.022913) | 0.478947 / 0.258489 (0.220458) | 0.528444 / 0.293841 (0.234603) | 0.052878 / 0.128546 (-0.075668) | 0.013939 / 0.075646 (-0.061707) | 0.087351 / 0.419271 (-0.331920) | 0.058448 / 0.043533 (0.014916) | 0.478664 / 0.255139 (0.223525) | 0.491239 / 0.283200 (0.208039) | 0.032674 / 0.141683 (-0.109008) | 1.753911 / 1.452155 (0.301756) | 1.858923 / 1.492716 (0.366206) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.239278 / 0.018006 (0.221271) | 0.507372 / 0.000490 (0.506882) | 0.005489 / 0.000200 (0.005289) | 0.000142 / 0.000054 (0.000087) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032919 / 0.037411 (-0.004493) | 0.097726 / 0.014526 (0.083200) | 0.119159 / 0.176557 (-0.057398) | 0.174545 / 0.737135 (-0.562590) | 0.115319 / 0.296338 (-0.181020) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.627107 / 0.215209 (0.411898) | 6.211925 / 2.077655 (4.134270) | 2.731484 / 1.504120 (1.227365) | 2.488847 / 1.541195 (0.947652) | 2.372445 / 1.468490 (0.903955) | 0.822663 / 4.584777 (-3.762114) | 4.924001 / 3.745712 (1.178289) | 4.371161 / 5.269862 (-0.898700) | 2.850314 / 4.565676 (-1.715363) | 0.099156 / 0.424275 (-0.325119) | 0.007941 / 0.007607 (0.000334) | 0.721539 / 0.226044 (0.495495) | 7.260874 / 2.268929 (4.991946) | 3.351072 / 55.444624 (-52.093552) | 2.757115 / 6.876477 (-4.119362) | 2.858899 / 2.142072 (0.716827) | 0.994054 / 4.805227 (-3.811173) | 0.209186 / 6.500664 (-6.291478) | 0.072070 / 0.075469 (-0.003399) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.748073 / 1.841788 (-0.093714) | 23.514638 / 8.074308 (15.440330) | 20.372037 / 10.191392 (10.180645) | 0.220020 / 0.680424 (-0.460404) | 0.057130 / 0.534201 (-0.477071) | 0.458204 / 0.579283 (-0.121079) | 0.600509 / 0.434364 (0.166145) | 0.557100 / 0.540337 (0.016762) | 0.814360 / 1.386936 (-0.572576) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#072f0ceafde60c16516fe1297e4aba981fc56052 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007341 / 0.011353 (-0.004012) | 0.004606 / 0.011008 (-0.006402) | 0.087903 / 0.038508 (0.049395) | 0.094090 / 0.023109 (0.070981) | 0.322278 / 0.275898 (0.046380) | 0.356770 / 0.323480 (0.033290) | 0.005988 / 0.007986 (-0.001997) | 0.003667 / 0.004328 (-0.000662) | 0.066105 / 0.004250 (0.061854) | 0.061220 / 0.037052 (0.024167) | 0.331190 / 0.258489 (0.072701) | 0.381402 / 0.293841 (0.087561) | 0.032261 / 0.128546 (-0.096285) | 0.009281 / 0.075646 (-0.066366) | 0.293694 / 0.419271 (-0.125577) | 0.055041 / 0.043533 (0.011508) | 0.318080 / 0.255139 (0.062941) | 0.348763 / 0.283200 (0.065563) | 0.027379 / 0.141683 (-0.114304) | 1.496294 / 1.452155 (0.044139) | 1.581942 / 1.492716 (0.089226) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.307592 / 0.018006 (0.289586) | 0.591805 / 0.000490 (0.591316) | 0.017082 / 0.000200 (0.016882) | 0.000721 / 0.000054 (0.000666) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032157 / 0.037411 (-0.005254) | 0.096249 / 0.014526 (0.081724) | 0.106656 / 0.176557 (-0.069901) | 0.162966 / 0.737135 (-0.574169) | 0.107068 / 0.296338 (-0.189271) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.409083 / 0.215209 (0.193874) | 4.044307 / 2.077655 (1.966652) | 2.062887 / 1.504120 (0.558767) | 1.900568 / 1.541195 (0.359373) | 2.011862 / 1.468490 (0.543372) | 0.489250 / 4.584777 (-4.095527) | 3.519531 / 3.745712 (-0.226182) | 3.631713 / 5.269862 (-1.638149) | 2.163967 / 4.565676 (-2.401709) | 0.057723 / 0.424275 (-0.366552) | 0.007474 / 0.007607 (-0.000133) | 0.479562 / 0.226044 (0.253517) | 4.799825 / 2.268929 (2.530897) | 2.530036 / 55.444624 (-52.914588) | 2.195344 / 6.876477 (-4.681133) | 2.341046 / 2.142072 (0.198974) | 0.625105 / 4.805227 (-4.180122) | 0.132823 / 6.500664 (-6.367841) | 0.061721 / 0.075469 (-0.013748) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.301313 / 1.841788 (-0.540475) | 21.218468 / 8.074308 (13.144159) | 15.466347 / 10.191392 (5.274955) | 0.166115 / 0.680424 (-0.514309) | 0.018866 / 0.534201 (-0.515335) | 0.399307 / 0.579283 (-0.179976) | 0.430537 / 0.434364 (-0.003827) | 0.467110 / 0.540337 (-0.073228) | 0.645686 / 1.386936 (-0.741250) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007288 / 0.011353 (-0.004065) | 0.004298 / 0.011008 (-0.006710) | 0.065515 / 0.038508 (0.027007) | 0.089948 / 0.023109 (0.066839) | 0.410121 / 0.275898 (0.134223) | 0.449312 / 0.323480 (0.125832) | 0.006749 / 0.007986 (-0.001237) | 0.003927 / 0.004328 (-0.000401) | 0.065321 / 0.004250 (0.061071) | 0.062480 / 0.037052 (0.025428) | 0.410796 / 0.258489 (0.152307) | 0.457356 / 0.293841 (0.163515) | 0.032632 / 0.128546 (-0.095914) | 0.008798 / 0.075646 (-0.066849) | 0.075936 / 0.419271 (-0.343335) | 0.048402 / 0.043533 (0.004869) | 0.403385 / 0.255139 (0.148246) | 0.426094 / 0.283200 (0.142895) | 0.025326 / 0.141683 (-0.116357) | 1.551550 / 1.452155 (0.099395) | 1.628622 / 1.492716 (0.135905) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.279689 / 0.018006 (0.261682) | 0.583754 / 0.000490 (0.583265) | 0.006579 / 0.000200 (0.006379) | 0.000096 / 0.000054 (0.000042) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034906 / 0.037411 (-0.002505) | 0.099232 / 0.014526 (0.084706) | 0.113093 / 0.176557 (-0.063464) | 0.165499 / 0.737135 (-0.571636) | 0.113398 / 0.296338 (-0.182941) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.439154 / 0.215209 (0.223945) | 4.377041 / 2.077655 (2.299387) | 2.395058 / 1.504120 (0.890938) | 2.233359 / 1.541195 (0.692164) | 2.357281 / 1.468490 (0.888791) | 0.486036 / 4.584777 (-4.098741) | 3.568794 / 3.745712 (-0.176918) | 3.485421 / 5.269862 (-1.784440) | 2.174325 / 4.565676 (-2.391351) | 0.057855 / 0.424275 (-0.366420) | 0.007545 / 0.007607 (-0.000062) | 0.516853 / 0.226044 (0.290808) | 5.173340 / 2.268929 (2.904412) | 2.931475 / 55.444624 (-52.513149) | 2.566814 / 6.876477 (-4.309663) | 2.873304 / 2.142072 (0.731232) | 0.597072 / 4.805227 (-4.208155) | 0.133589 / 6.500664 (-6.367075) | 0.061882 / 0.075469 (-0.013587) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.382845 / 1.841788 (-0.458943) | 21.608316 / 8.074308 (13.534008) | 15.702152 / 10.191392 (5.510759) | 0.190629 / 0.680424 (-0.489795) | 0.020572 / 0.534201 (-0.513629) | 0.396207 / 0.579283 (-0.183076) | 0.421184 / 0.434364 (-0.013180) | 0.477700 / 0.540337 (-0.062638) | 0.690828 / 1.386936 (-0.696108) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5e7374b453911cda5e0f866ad45b51c3fbe267c9 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008450 / 0.011353 (-0.002903) | 0.004958 / 0.011008 (-0.006051) | 0.105397 / 0.038508 (0.066889) | 0.079508 / 0.023109 (0.056399) | 0.403050 / 0.275898 (0.127152) | 0.443679 / 0.323480 (0.120199) | 0.004654 / 0.007986 (-0.003332) | 0.005629 / 0.004328 (0.001301) | 0.078755 / 0.004250 (0.074505) | 0.055694 / 0.037052 (0.018642) | 0.409952 / 0.258489 (0.151463) | 0.454931 / 0.293841 (0.161090) | 0.045124 / 0.128546 (-0.083422) | 0.014031 / 0.075646 (-0.061616) | 0.347340 / 0.419271 (-0.071931) | 0.064359 / 0.043533 (0.020826) | 0.414158 / 0.255139 (0.159019) | 0.428442 / 0.283200 (0.145243) | 0.033726 / 0.141683 (-0.107957) | 1.770483 / 1.452155 (0.318328) | 1.795267 / 1.492716 (0.302551) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.251020 / 0.018006 (0.233014) | 0.507066 / 0.000490 (0.506576) | 0.015751 / 0.000200 (0.015551) | 0.000531 / 0.000054 (0.000477) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028897 / 0.037411 (-0.008515) | 0.087393 / 0.014526 (0.072867) | 0.097365 / 0.176557 (-0.079192) | 0.164833 / 0.737135 (-0.572303) | 0.101281 / 0.296338 (-0.195058) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.610806 / 0.215209 (0.395597) | 6.011697 / 2.077655 (3.934042) | 2.544268 / 1.504120 (1.040148) | 2.127103 / 1.541195 (0.585908) | 2.133330 / 1.468490 (0.664839) | 0.860964 / 4.584777 (-3.723813) | 4.982374 / 3.745712 (1.236662) | 5.073026 / 5.269862 (-0.196836) | 3.033056 / 4.565676 (-1.532621) | 0.118835 / 0.424275 (-0.305440) | 0.010122 / 0.007607 (0.002515) | 0.805807 / 0.226044 (0.579763) | 7.839166 / 2.268929 (5.570238) | 3.512405 / 55.444624 (-51.932219) | 2.767578 / 6.876477 (-4.108898) | 2.936885 / 2.142072 (0.794813) | 1.058533 / 4.805227 (-3.746695) | 0.222260 / 6.500664 (-6.278404) | 0.073890 / 0.075469 (-0.001580) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.628307 / 1.841788 (-0.213480) | 22.827116 / 8.074308 (14.752808) | 21.809759 / 10.191392 (11.618367) | 0.220637 / 0.680424 (-0.459786) | 0.028030 / 0.534201 (-0.506171) | 0.448620 / 0.579283 (-0.130663) | 0.540442 / 0.434364 (0.106078) | 0.548601 / 0.540337 (0.008264) | 0.770387 / 1.386936 (-0.616549) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009198 / 0.011353 (-0.002155) | 0.004935 / 0.011008 (-0.006073) | 0.079095 / 0.038508 (0.040587) | 0.090490 / 0.023109 (0.067381) | 0.453374 / 0.275898 (0.177476) | 0.519483 / 0.323480 (0.196003) | 0.006539 / 0.007986 (-0.001447) | 0.004160 / 0.004328 (-0.000169) | 0.078433 / 0.004250 (0.074182) | 0.068022 / 0.037052 (0.030969) | 0.467686 / 0.258489 (0.209197) | 0.523863 / 0.293841 (0.230022) | 0.050926 / 0.128546 (-0.077620) | 0.013664 / 0.075646 (-0.061982) | 0.088787 / 0.419271 (-0.330485) | 0.060503 / 0.043533 (0.016971) | 0.474692 / 0.255139 (0.219553) | 0.516461 / 0.283200 (0.233261) | 0.034482 / 0.141683 (-0.107200) | 1.747939 / 1.452155 (0.295784) | 1.915212 / 1.492716 (0.422496) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.247400 / 0.018006 (0.229394) | 0.516829 / 0.000490 (0.516339) | 0.005770 / 0.000200 (0.005570) | 0.000121 / 0.000054 (0.000067) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034334 / 0.037411 (-0.003077) | 0.102397 / 0.014526 (0.087871) | 0.114187 / 0.176557 (-0.062370) | 0.171093 / 0.737135 (-0.566043) | 0.117281 / 0.296338 (-0.179058) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.635710 / 0.215209 (0.420501) | 6.400656 / 2.077655 (4.323002) | 2.896896 / 1.504120 (1.392776) | 2.682890 / 1.541195 (1.141696) | 2.656445 / 1.468490 (1.187955) | 1.044244 / 4.584777 (-3.540533) | 5.393212 / 3.745712 (1.647500) | 4.592928 / 5.269862 (-0.676934) | 2.798525 / 4.565676 (-1.767151) | 0.103720 / 0.424275 (-0.320555) | 0.010196 / 0.007607 (0.002589) | 0.762756 / 0.226044 (0.536711) | 7.232939 / 2.268929 (4.964011) | 3.714015 / 55.444624 (-51.730609) | 3.050766 / 6.876477 (-3.825711) | 3.149715 / 2.142072 (1.007643) | 1.058827 / 4.805227 (-3.746400) | 0.214079 / 6.500664 (-6.286585) | 0.076712 / 0.075469 (0.001243) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.701032 / 1.841788 (-0.140755) | 23.742023 / 8.074308 (15.667715) | 22.486043 / 10.191392 (12.294651) | 0.249757 / 0.680424 (-0.430667) | 0.031714 / 0.534201 (-0.502486) | 0.479914 / 0.579283 (-0.099369) | 0.593315 / 0.434364 (0.158951) | 0.562897 / 0.540337 (0.022560) | 0.826636 / 1.386936 (-0.560300) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#429f9c69d1813ec643c316313b69ff23aaf208f6 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007816 / 0.011353 (-0.003537) | 0.004541 / 0.011008 (-0.006467) | 0.097256 / 0.038508 (0.058748) | 0.081376 / 0.023109 (0.058267) | 0.356635 / 0.275898 (0.080737) | 0.394969 / 0.323480 (0.071489) | 0.004670 / 0.007986 (-0.003316) | 0.003537 / 0.004328 (-0.000791) | 0.075564 / 0.004250 (0.071314) | 0.063459 / 0.037052 (0.026407) | 0.363846 / 0.258489 (0.105357) | 0.416337 / 0.293841 (0.122496) | 0.036690 / 0.128546 (-0.091857) | 0.009653 / 0.075646 (-0.065993) | 0.337265 / 0.419271 (-0.082007) | 0.061446 / 0.043533 (0.017913) | 0.359190 / 0.255139 (0.104051) | 0.385866 / 0.283200 (0.102666) | 0.030474 / 0.141683 (-0.111209) | 1.796903 / 1.452155 (0.344748) | 1.852332 / 1.492716 (0.359616) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.264008 / 0.018006 (0.246002) | 0.507387 / 0.000490 (0.506897) | 0.012309 / 0.000200 (0.012109) | 0.000377 / 0.000054 (0.000323) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033224 / 0.037411 (-0.004188) | 0.097136 / 0.014526 (0.082610) | 0.113035 / 0.176557 (-0.063522) | 0.181778 / 0.737135 (-0.555357) | 0.130511 / 0.296338 (-0.165827) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.444512 / 0.215209 (0.229303) | 4.453285 / 2.077655 (2.375631) | 2.154123 / 1.504120 (0.650003) | 1.955451 / 1.541195 (0.414256) | 2.015089 / 1.468490 (0.546599) | 0.567824 / 4.584777 (-4.016953) | 4.083084 / 3.745712 (0.337371) | 3.912417 / 5.269862 (-1.357445) | 2.366197 / 4.565676 (-2.199480) | 0.066468 / 0.424275 (-0.357807) | 0.008478 / 0.007607 (0.000870) | 0.531196 / 0.226044 (0.305152) | 5.311285 / 2.268929 (3.042356) | 2.743252 / 55.444624 (-52.701372) | 2.322353 / 6.876477 (-4.554124) | 2.368168 / 2.142072 (0.226095) | 0.679223 / 4.805227 (-4.126004) | 0.152401 / 6.500664 (-6.348263) | 0.071954 / 0.075469 (-0.003515) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.489114 / 1.841788 (-0.352674) | 22.114956 / 8.074308 (14.040648) | 16.072564 / 10.191392 (5.881172) | 0.164303 / 0.680424 (-0.516121) | 0.021317 / 0.534201 (-0.512884) | 0.460250 / 0.579283 (-0.119033) | 0.467554 / 0.434364 (0.033190) | 0.539773 / 0.540337 (-0.000564) | 0.751904 / 1.386936 (-0.635032) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007520 / 0.011353 (-0.003833) | 0.004487 / 0.011008 (-0.006521) | 0.075074 / 0.038508 (0.036566) | 0.083135 / 0.023109 (0.060026) | 0.474052 / 0.275898 (0.198154) | 0.524051 / 0.323480 (0.200571) | 0.006192 / 0.007986 (-0.001793) | 0.003835 / 0.004328 (-0.000494) | 0.074643 / 0.004250 (0.070392) | 0.065334 / 0.037052 (0.028282) | 0.507033 / 0.258489 (0.248544) | 0.519846 / 0.293841 (0.226005) | 0.036985 / 0.128546 (-0.091561) | 0.009828 / 0.075646 (-0.065818) | 0.082992 / 0.419271 (-0.336279) | 0.055942 / 0.043533 (0.012409) | 0.480652 / 0.255139 (0.225513) | 0.503683 / 0.283200 (0.220483) | 0.025560 / 0.141683 (-0.116123) | 1.801390 / 1.452155 (0.349235) | 1.892929 / 1.492716 (0.400213) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.246771 / 0.018006 (0.228765) | 0.498901 / 0.000490 (0.498411) | 0.008186 / 0.000200 (0.007986) | 0.000166 / 0.000054 (0.000112) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038666 / 0.037411 (0.001254) | 0.110317 / 0.014526 (0.095791) | 0.122995 / 0.176557 (-0.053562) | 0.185355 / 0.737135 (-0.551781) | 0.123720 / 0.296338 (-0.172619) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.508421 / 0.215209 (0.293212) | 5.046464 / 2.077655 (2.968809) | 2.660004 / 1.504120 (1.155884) | 2.482841 / 1.541195 (0.941646) | 2.573941 / 1.468490 (1.105451) | 0.565702 / 4.584777 (-4.019075) | 4.197895 / 3.745712 (0.452183) | 3.755480 / 5.269862 (-1.514381) | 2.308066 / 4.565676 (-2.257610) | 0.066559 / 0.424275 (-0.357716) | 0.008436 / 0.007607 (0.000829) | 0.589858 / 0.226044 (0.363814) | 5.873488 / 2.268929 (3.604559) | 3.241810 / 55.444624 (-52.202814) | 2.789831 / 6.876477 (-4.086645) | 3.008989 / 2.142072 (0.866917) | 0.679624 / 4.805227 (-4.125603) | 0.150868 / 6.500664 (-6.349796) | 0.068581 / 0.075469 (-0.006889) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.582955 / 1.841788 (-0.258833) | 22.684969 / 8.074308 (14.610661) | 16.829855 / 10.191392 (6.638463) | 0.201599 / 0.680424 (-0.478825) | 0.023261 / 0.534201 (-0.510940) | 0.465009 / 0.579283 (-0.114274) | 0.497701 / 0.434364 (0.063337) | 0.557822 / 0.540337 (0.017485) | 0.803234 / 1.386936 (-0.583702) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9241c1070b5c9021705c17b12548b6fea75782d8 \"CML watermark\")\n", "Well done! :clap: :fire: ", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008866 / 0.011353 (-0.002487) | 0.005910 / 0.011008 (-0.005098) | 0.099916 / 0.038508 (0.061408) | 0.085787 / 0.023109 (0.062678) | 0.391028 / 0.275898 (0.115130) | 0.412689 / 0.323480 (0.089209) | 0.006527 / 0.007986 (-0.001459) | 0.004629 / 0.004328 (0.000301) | 0.084627 / 0.004250 (0.080377) | 0.063404 / 0.037052 (0.026352) | 0.408923 / 0.258489 (0.150434) | 0.437130 / 0.293841 (0.143289) | 0.050256 / 0.128546 (-0.078290) | 0.013914 / 0.075646 (-0.061732) | 0.350893 / 0.419271 (-0.068379) | 0.067931 / 0.043533 (0.024398) | 0.383807 / 0.255139 (0.128668) | 0.424150 / 0.283200 (0.140950) | 0.039978 / 0.141683 (-0.101705) | 1.697631 / 1.452155 (0.245476) | 1.925568 / 1.492716 (0.432851) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.315417 / 0.018006 (0.297410) | 0.607050 / 0.000490 (0.606560) | 0.017314 / 0.000200 (0.017114) | 0.000514 / 0.000054 (0.000459) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032994 / 0.037411 (-0.004417) | 0.103993 / 0.014526 (0.089467) | 0.125369 / 0.176557 (-0.051187) | 0.185984 / 0.737135 (-0.551151) | 0.139192 / 0.296338 (-0.157146) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.639769 / 0.215209 (0.424560) | 6.236187 / 2.077655 (4.158532) | 2.775777 / 1.504120 (1.271657) | 2.599683 / 1.541195 (1.058488) | 2.780064 / 1.468490 (1.311574) | 1.107247 / 4.584777 (-3.477530) | 5.724223 / 3.745712 (1.978511) | 5.284786 / 5.269862 (0.014925) | 3.342465 / 4.565676 (-1.223211) | 0.107685 / 0.424275 (-0.316590) | 0.009237 / 0.007607 (0.001630) | 0.760282 / 0.226044 (0.534238) | 7.570859 / 2.268929 (5.301930) | 3.572498 / 55.444624 (-51.872126) | 2.997482 / 6.876477 (-3.878995) | 2.910001 / 2.142072 (0.767929) | 1.249272 / 4.805227 (-3.555955) | 0.229425 / 6.500664 (-6.271239) | 0.091974 / 0.075469 (0.016505) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.663859 / 1.841788 (-0.177929) | 25.283961 / 8.074308 (17.209653) | 20.793389 / 10.191392 (10.601997) | 0.239263 / 0.680424 (-0.441161) | 0.028808 / 0.534201 (-0.505393) | 0.521045 / 0.579283 (-0.058238) | 0.602451 / 0.434364 (0.168087) | 0.544536 / 0.540337 (0.004198) | 0.819732 / 1.386936 (-0.567204) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008970 / 0.011353 (-0.002383) | 0.009663 / 0.011008 (-0.001345) | 0.083471 / 0.038508 (0.044963) | 0.090695 / 0.023109 (0.067585) | 0.562539 / 0.275898 (0.286641) | 0.572092 / 0.323480 (0.248612) | 0.007269 / 0.007986 (-0.000717) | 0.004664 / 0.004328 (0.000335) | 0.084212 / 0.004250 (0.079961) | 0.072716 / 0.037052 (0.035664) | 0.559810 / 0.258489 (0.301320) | 0.574296 / 0.293841 (0.280455) | 0.048555 / 0.128546 (-0.079991) | 0.015901 / 0.075646 (-0.059746) | 0.107815 / 0.419271 (-0.311456) | 0.065404 / 0.043533 (0.021871) | 0.544787 / 0.255139 (0.289648) | 0.586993 / 0.283200 (0.303794) | 0.042613 / 0.141683 (-0.099069) | 1.919266 / 1.452155 (0.467111) | 2.095189 / 1.492716 (0.602473) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.298512 / 0.018006 (0.280506) | 0.597745 / 0.000490 (0.597256) | 0.008806 / 0.000200 (0.008606) | 0.000119 / 0.000054 (0.000064) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039420 / 0.037411 (0.002009) | 0.111378 / 0.014526 (0.096852) | 0.136421 / 0.176557 (-0.040135) | 0.192006 / 0.737135 (-0.545129) | 0.130037 / 0.296338 (-0.166301) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.679169 / 0.215209 (0.463960) | 6.750881 / 2.077655 (4.673226) | 3.220411 / 1.504120 (1.716291) | 2.851988 / 1.541195 (1.310794) | 2.974247 / 1.468490 (1.505757) | 0.892593 / 4.584777 (-3.692184) | 5.659975 / 3.745712 (1.914263) | 5.172641 / 5.269862 (-0.097220) | 3.308429 / 4.565676 (-1.257248) | 0.100580 / 0.424275 (-0.323695) | 0.009320 / 0.007607 (0.001713) | 0.833290 / 0.226044 (0.607245) | 8.091847 / 2.268929 (5.822918) | 4.023734 / 55.444624 (-51.420890) | 3.441583 / 6.876477 (-3.434894) | 3.763562 / 2.142072 (1.621489) | 1.055105 / 4.805227 (-3.750122) | 0.239218 / 6.500664 (-6.261446) | 0.081922 / 0.075469 (0.006453) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.796495 / 1.841788 (-0.045293) | 25.942492 / 8.074308 (17.868184) | 23.211617 / 10.191392 (13.020225) | 0.256054 / 0.680424 (-0.424370) | 0.030491 / 0.534201 (-0.503710) | 0.520474 / 0.579283 (-0.058809) | 0.626331 / 0.434364 (0.191967) | 0.619897 / 0.540337 (0.079560) | 0.900833 / 1.386936 (-0.486103) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e74f80255700c4b8cde383a426c4b2def6db1253 \"CML watermark\")\n", "Congrats on merging this! 👏 " ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6268). All of your documentation changes will be reflected on that endpoint.", "In https://github.com/huggingface/datasets/issues/4129 we want to track the origin of a dataset, e.g. if it comes from multiple datasets.\r\n\r\nI think it's out of scope of DatasetInfo alone, which has info for one dataset only.\r\nTherefore it makes sense to add repo_id, which is for one dataset only.\r\n\r\nIMO if we want to track multiple origins we will need a new DatasetInfo that would have fields relevant to a mix of datasets (out of scope of this PR)\r\n\r\ncc @mariosasko I'd like your opinion on this", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009009 / 0.011353 (-0.002344) | 0.004169 / 0.011008 (-0.006840) | 0.098634 / 0.038508 (0.060126) | 0.069526 / 0.023109 (0.046417) | 0.337963 / 0.275898 (0.062065) | 0.379737 / 0.323480 (0.056257) | 0.004318 / 0.007986 (-0.003668) | 0.005347 / 0.004328 (0.001019) | 0.069875 / 0.004250 (0.065624) | 0.055964 / 0.037052 (0.018912) | 0.340305 / 0.258489 (0.081816) | 0.429718 / 0.293841 (0.135877) | 0.045101 / 0.128546 (-0.083445) | 0.012610 / 0.075646 (-0.063036) | 0.312366 / 0.419271 (-0.106905) | 0.064711 / 0.043533 (0.021178) | 0.345216 / 0.255139 (0.090077) | 0.367245 / 0.283200 (0.084046) | 0.034638 / 0.141683 (-0.107045) | 1.541947 / 1.452155 (0.089793) | 1.645268 / 1.492716 (0.152551) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.233501 / 0.018006 (0.215495) | 0.514207 / 0.000490 (0.513717) | 0.014271 / 0.000200 (0.014072) | 0.000366 / 0.000054 (0.000311) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026288 / 0.037411 (-0.011124) | 0.083206 / 0.014526 (0.068680) | 0.098172 / 0.176557 (-0.078385) | 0.158529 / 0.737135 (-0.578606) | 0.095183 / 0.296338 (-0.201155) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.538300 / 0.215209 (0.323091) | 5.486939 / 2.077655 (3.409285) | 2.321812 / 1.504120 (0.817692) | 2.002124 / 1.541195 (0.460929) | 2.045043 / 1.468490 (0.576553) | 0.852772 / 4.584777 (-3.732005) | 5.014897 / 3.745712 (1.269185) | 4.428115 / 5.269862 (-0.841746) | 2.750126 / 4.565676 (-1.815550) | 0.099028 / 0.424275 (-0.325247) | 0.007678 / 0.007607 (0.000070) | 0.664463 / 0.226044 (0.438418) | 6.617811 / 2.268929 (4.348883) | 2.888382 / 55.444624 (-52.556242) | 2.190753 / 6.876477 (-4.685724) | 2.414586 / 2.142072 (0.272513) | 1.010302 / 4.805227 (-3.794925) | 0.194925 / 6.500664 (-6.305739) | 0.063490 / 0.075469 (-0.011979) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.543464 / 1.841788 (-0.298323) | 20.566666 / 8.074308 (12.492358) | 19.410745 / 10.191392 (9.219353) | 0.207077 / 0.680424 (-0.473347) | 0.028895 / 0.534201 (-0.505306) | 0.427525 / 0.579283 (-0.151758) | 0.535450 / 0.434364 (0.101086) | 0.494632 / 0.540337 (-0.045705) | 0.723705 / 1.386936 (-0.663231) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008209 / 0.011353 (-0.003144) | 0.004184 / 0.011008 (-0.006824) | 0.072420 / 0.038508 (0.033912) | 0.066851 / 0.023109 (0.043742) | 0.424137 / 0.275898 (0.148239) | 0.473156 / 0.323480 (0.149676) | 0.005394 / 0.007986 (-0.002591) | 0.003898 / 0.004328 (-0.000430) | 0.069996 / 0.004250 (0.065746) | 0.053113 / 0.037052 (0.016061) | 0.453214 / 0.258489 (0.194725) | 0.495921 / 0.293841 (0.202080) | 0.043028 / 0.128546 (-0.085519) | 0.012320 / 0.075646 (-0.063326) | 0.080270 / 0.419271 (-0.339002) | 0.053337 / 0.043533 (0.009804) | 0.436604 / 0.255139 (0.181465) | 0.463422 / 0.283200 (0.180223) | 0.030277 / 0.141683 (-0.111406) | 1.560261 / 1.452155 (0.108106) | 1.647209 / 1.492716 (0.154493) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.232556 / 0.018006 (0.214550) | 0.502387 / 0.000490 (0.501897) | 0.006688 / 0.000200 (0.006488) | 0.000118 / 0.000054 (0.000064) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030204 / 0.037411 (-0.007207) | 0.089438 / 0.014526 (0.074912) | 0.118939 / 0.176557 (-0.057617) | 0.160537 / 0.737135 (-0.576598) | 0.113432 / 0.296338 (-0.182906) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.586469 / 0.215209 (0.371260) | 5.916156 / 2.077655 (3.838502) | 2.904960 / 1.504120 (1.400840) | 2.346838 / 1.541195 (0.805644) | 2.373688 / 1.468490 (0.905198) | 0.829917 / 4.584777 (-3.754860) | 4.851283 / 3.745712 (1.105571) | 4.220103 / 5.269862 (-1.049758) | 2.706139 / 4.565676 (-1.859538) | 0.094095 / 0.424275 (-0.330180) | 0.008201 / 0.007607 (0.000594) | 0.699099 / 0.226044 (0.473054) | 7.046940 / 2.268929 (4.778011) | 3.374837 / 55.444624 (-52.069788) | 2.690839 / 6.876477 (-4.185638) | 2.845717 / 2.142072 (0.703645) | 0.989698 / 4.805227 (-3.815529) | 0.190413 / 6.500664 (-6.310251) | 0.066233 / 0.075469 (-0.009236) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.513607 / 1.841788 (-0.328180) | 21.544200 / 8.074308 (13.469892) | 20.297337 / 10.191392 (10.105945) | 0.216390 / 0.680424 (-0.464034) | 0.029962 / 0.534201 (-0.504239) | 0.451531 / 0.579283 (-0.127752) | 0.530147 / 0.434364 (0.095783) | 0.520739 / 0.540337 (-0.019598) | 0.716431 / 1.386936 (-0.670505) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#fcaa9f218ad1505bb5474060889b4b9578e24423 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006509 / 0.011353 (-0.004844) | 0.003987 / 0.011008 (-0.007022) | 0.085233 / 0.038508 (0.046725) | 0.077765 / 0.023109 (0.054656) | 0.310467 / 0.275898 (0.034569) | 0.343363 / 0.323480 (0.019883) | 0.005557 / 0.007986 (-0.002429) | 0.003430 / 0.004328 (-0.000898) | 0.064948 / 0.004250 (0.060697) | 0.056864 / 0.037052 (0.019812) | 0.314005 / 0.258489 (0.055516) | 0.360638 / 0.293841 (0.066798) | 0.031134 / 0.128546 (-0.097412) | 0.008869 / 0.075646 (-0.066777) | 0.286409 / 0.419271 (-0.132862) | 0.051338 / 0.043533 (0.007805) | 0.311329 / 0.255139 (0.056190) | 0.334373 / 0.283200 (0.051174) | 0.024816 / 0.141683 (-0.116867) | 1.502872 / 1.452155 (0.050718) | 1.569941 / 1.492716 (0.077224) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.269639 / 0.018006 (0.251633) | 0.558510 / 0.000490 (0.558020) | 0.011748 / 0.000200 (0.011548) | 0.000234 / 0.000054 (0.000180) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029139 / 0.037411 (-0.008272) | 0.083586 / 0.014526 (0.069060) | 0.102426 / 0.176557 (-0.074131) | 0.162398 / 0.737135 (-0.574737) | 0.101364 / 0.296338 (-0.194975) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382281 / 0.215209 (0.167072) | 3.826412 / 2.077655 (1.748758) | 1.815911 / 1.504120 (0.311791) | 1.644539 / 1.541195 (0.103344) | 1.688487 / 1.468490 (0.219996) | 0.482115 / 4.584777 (-4.102662) | 3.574773 / 3.745712 (-0.170939) | 3.262733 / 5.269862 (-2.007129) | 2.058115 / 4.565676 (-2.507562) | 0.056367 / 0.424275 (-0.367908) | 0.007233 / 0.007607 (-0.000374) | 0.456859 / 0.226044 (0.230815) | 4.565935 / 2.268929 (2.297006) | 2.311802 / 55.444624 (-53.132823) | 1.943936 / 6.876477 (-4.932541) | 2.129811 / 2.142072 (-0.012261) | 0.575098 / 4.805227 (-4.230129) | 0.130495 / 6.500664 (-6.370169) | 0.059757 / 0.075469 (-0.015712) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.238495 / 1.841788 (-0.603293) | 18.940000 / 8.074308 (10.865692) | 14.034240 / 10.191392 (3.842848) | 0.166418 / 0.680424 (-0.514006) | 0.018420 / 0.534201 (-0.515781) | 0.395330 / 0.579283 (-0.183953) | 0.413518 / 0.434364 (-0.020846) | 0.461499 / 0.540337 (-0.078838) | 0.661371 / 1.386936 (-0.725565) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006673 / 0.011353 (-0.004680) | 0.004335 / 0.011008 (-0.006673) | 0.064568 / 0.038508 (0.026060) | 0.072763 / 0.023109 (0.049653) | 0.429488 / 0.275898 (0.153590) | 0.456900 / 0.323480 (0.133420) | 0.005481 / 0.007986 (-0.002505) | 0.003649 / 0.004328 (-0.000680) | 0.064975 / 0.004250 (0.060724) | 0.056839 / 0.037052 (0.019786) | 0.439451 / 0.258489 (0.180962) | 0.461691 / 0.293841 (0.167850) | 0.031455 / 0.128546 (-0.097092) | 0.008848 / 0.075646 (-0.066798) | 0.071719 / 0.419271 (-0.347553) | 0.047116 / 0.043533 (0.003583) | 0.429055 / 0.255139 (0.173916) | 0.434204 / 0.283200 (0.151004) | 0.022594 / 0.141683 (-0.119089) | 1.539231 / 1.452155 (0.087077) | 1.568111 / 1.492716 (0.075394) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.267374 / 0.018006 (0.249368) | 0.553202 / 0.000490 (0.552712) | 0.005410 / 0.000200 (0.005210) | 0.000101 / 0.000054 (0.000046) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031478 / 0.037411 (-0.005933) | 0.092438 / 0.014526 (0.077912) | 0.103874 / 0.176557 (-0.072682) | 0.158428 / 0.737135 (-0.578708) | 0.111617 / 0.296338 (-0.184721) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434783 / 0.215209 (0.219574) | 4.332536 / 2.077655 (2.254881) | 2.354522 / 1.504120 (0.850402) | 2.220271 / 1.541195 (0.679076) | 2.338524 / 1.468490 (0.870034) | 0.494508 / 4.584777 (-4.090269) | 3.619592 / 3.745712 (-0.126120) | 3.320897 / 5.269862 (-1.948964) | 2.107475 / 4.565676 (-2.458202) | 0.058479 / 0.424275 (-0.365796) | 0.007427 / 0.007607 (-0.000180) | 0.509298 / 0.226044 (0.283254) | 5.067940 / 2.268929 (2.799012) | 2.815336 / 55.444624 (-52.629288) | 2.470958 / 6.876477 (-4.405519) | 2.672801 / 2.142072 (0.530728) | 0.588199 / 4.805227 (-4.217028) | 0.134062 / 6.500664 (-6.366602) | 0.060951 / 0.075469 (-0.014518) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.353955 / 1.841788 (-0.487832) | 20.386012 / 8.074308 (12.311704) | 15.032463 / 10.191392 (4.841071) | 0.167243 / 0.680424 (-0.513181) | 0.020426 / 0.534201 (-0.513775) | 0.396815 / 0.579283 (-0.182469) | 0.421806 / 0.434364 (-0.012558) | 0.471866 / 0.540337 (-0.068471) | 0.667206 / 1.386936 (-0.719730) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#aade5a0c79398c84632a3ff253111e694c7b598b \"CML watermark\")\n", "Really happy to see this! It could also be helpful to track some other metadata about how the dataset was built in the future. i.e. for the Stack loaded like this:\r\n\r\n```\r\nds = load_dataset(\"bigcode/the-stack\", data_dir=\"data/dockerfile\", split=\"train\")\r\n```\r\nIt could be helpful to have easy access to the `data_dir` argument used during loading since that changes the training data quite a bit vs. loading the full dataset. You can also recover this from `download_checksums`, which seems a bit hacky. That is not necessary for this PR, though.\r\n", "Perhaps it is also interesting to track the revision? I suppose the version also kind of covers that.\r\n\r\nThat said, this is looking great already! I'm quite excited about this. Losing the `repo_id` after merging (different) datasets also makes sense to me, well done.", "One other thought. Is it worth tracking if a `token` was passed during loading? \r\n\r\nThe Hub ID for private datasets could in some cases contain information someone wouldn't want to make public i.e. `davanstrien/super_secret_dataset_using_GPT_created_data`. \r\n\r\nAdding a bool like `is_private` could then be used by another library to determine if the dataset ID should be shared or not (or default to not sharing the ID for private datasets). i.e. in SpanMarker @tomaarsen might do a check like \r\n\r\n```python\r\nif ds.is_private and not push_hub_id_for_private_ds:\r\n\tds_name = None\r\n```\r\nPotentially this is overkill but could be useful for downstream libraries who might use this information for creating automatic model cards. \r\n\r\n\r\n", "We should probably find a way to remove `DatasetInfo`, as (most of) its attributes are outdated (homepage, description, etc.), not introduce new ones :). But I guess storing `repo_id` there is the simplest solution for now, so I'm OK with it.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007757 / 0.011353 (-0.003595) | 0.004543 / 0.011008 (-0.006465) | 0.100193 / 0.038508 (0.061685) | 0.082333 / 0.023109 (0.059224) | 0.374586 / 0.275898 (0.098688) | 0.412617 / 0.323480 (0.089137) | 0.006148 / 0.007986 (-0.001838) | 0.003826 / 0.004328 (-0.000503) | 0.077077 / 0.004250 (0.072827) | 0.064057 / 0.037052 (0.027005) | 0.391435 / 0.258489 (0.132946) | 0.436439 / 0.293841 (0.142599) | 0.036534 / 0.128546 (-0.092012) | 0.009986 / 0.075646 (-0.065660) | 0.344243 / 0.419271 (-0.075028) | 0.062013 / 0.043533 (0.018480) | 0.378113 / 0.255139 (0.122974) | 0.398476 / 0.283200 (0.115276) | 0.026552 / 0.141683 (-0.115131) | 1.740505 / 1.452155 (0.288350) | 1.835684 / 1.492716 (0.342968) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.267917 / 0.018006 (0.249911) | 0.510676 / 0.000490 (0.510186) | 0.010810 / 0.000200 (0.010610) | 0.000383 / 0.000054 (0.000328) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032113 / 0.037411 (-0.005299) | 0.097679 / 0.014526 (0.083153) | 0.113213 / 0.176557 (-0.063344) | 0.177897 / 0.737135 (-0.559238) | 0.111761 / 0.296338 (-0.184577) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.450544 / 0.215209 (0.235335) | 4.476746 / 2.077655 (2.399091) | 2.205391 / 1.504120 (0.701271) | 2.006457 / 1.541195 (0.465262) | 2.058859 / 1.468490 (0.590369) | 0.571549 / 4.584777 (-4.013228) | 4.175039 / 3.745712 (0.429327) | 3.815445 / 5.269862 (-1.454416) | 2.376673 / 4.565676 (-2.189004) | 0.067048 / 0.424275 (-0.357227) | 0.008544 / 0.007607 (0.000937) | 0.536384 / 0.226044 (0.310340) | 5.386232 / 2.268929 (3.117304) | 2.825620 / 55.444624 (-52.619004) | 2.339821 / 6.876477 (-4.536656) | 2.535736 / 2.142072 (0.393663) | 0.679572 / 4.805227 (-4.125655) | 0.156799 / 6.500664 (-6.343865) | 0.071667 / 0.075469 (-0.003802) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.512198 / 1.841788 (-0.329590) | 21.786760 / 8.074308 (13.712452) | 16.386274 / 10.191392 (6.194882) | 0.169108 / 0.680424 (-0.511316) | 0.021312 / 0.534201 (-0.512889) | 0.466153 / 0.579283 (-0.113130) | 0.496192 / 0.434364 (0.061829) | 0.549420 / 0.540337 (0.009082) | 0.780974 / 1.386936 (-0.605962) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007644 / 0.011353 (-0.003709) | 0.004654 / 0.011008 (-0.006354) | 0.075280 / 0.038508 (0.036772) | 0.083044 / 0.023109 (0.059935) | 0.481704 / 0.275898 (0.205805) | 0.514828 / 0.323480 (0.191348) | 0.006245 / 0.007986 (-0.001740) | 0.003715 / 0.004328 (-0.000614) | 0.074498 / 0.004250 (0.070248) | 0.064406 / 0.037052 (0.027353) | 0.481874 / 0.258489 (0.223385) | 0.518527 / 0.293841 (0.224686) | 0.037549 / 0.128546 (-0.090997) | 0.010106 / 0.075646 (-0.065541) | 0.084266 / 0.419271 (-0.335006) | 0.056659 / 0.043533 (0.013126) | 0.497707 / 0.255139 (0.242568) | 0.503201 / 0.283200 (0.220001) | 0.027086 / 0.141683 (-0.114597) | 1.834715 / 1.452155 (0.382560) | 1.919927 / 1.492716 (0.427210) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.249288 / 0.018006 (0.231282) | 0.500950 / 0.000490 (0.500460) | 0.005856 / 0.000200 (0.005656) | 0.000120 / 0.000054 (0.000065) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037674 / 0.037411 (0.000263) | 0.111141 / 0.014526 (0.096615) | 0.123408 / 0.176557 (-0.053149) | 0.186604 / 0.737135 (-0.550531) | 0.125360 / 0.296338 (-0.170979) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.520480 / 0.215209 (0.305271) | 5.171108 / 2.077655 (3.093453) | 2.812746 / 1.504120 (1.308626) | 2.602941 / 1.541195 (1.061746) | 2.666196 / 1.468490 (1.197706) | 0.578684 / 4.584777 (-4.006092) | 4.238722 / 3.745712 (0.493010) | 3.844361 / 5.269862 (-1.425501) | 2.369214 / 4.565676 (-2.196462) | 0.068543 / 0.424275 (-0.355732) | 0.008695 / 0.007607 (0.001088) | 0.621869 / 0.226044 (0.395825) | 6.200566 / 2.268929 (3.931637) | 3.340846 / 55.444624 (-52.103779) | 2.920691 / 6.876477 (-3.955786) | 3.132438 / 2.142072 (0.990366) | 0.697394 / 4.805227 (-4.107834) | 0.158385 / 6.500664 (-6.342280) | 0.072566 / 0.075469 (-0.002903) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.599070 / 1.841788 (-0.242717) | 22.767139 / 8.074308 (14.692831) | 17.053988 / 10.191392 (6.862596) | 0.188414 / 0.680424 (-0.492009) | 0.023409 / 0.534201 (-0.510792) | 0.472092 / 0.579283 (-0.107191) | 0.486107 / 0.434364 (0.051743) | 0.562190 / 0.540337 (0.021852) | 0.791606 / 1.386936 (-0.595330) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#aacbaf45c93f88e8c95924f6224153fb37c3064a \"CML watermark\")\n" ]

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[ "You can use a `Sequence(ClassLabel(...))` feature type to represent a list of labels, and `cast_column`/`cast` to perform the \"string to label\" conversion (`class_encode_column` does support nested fields), e.g., in your case:\r\n```python\r\nfrom datasets import Dataset, Sequence, ClassLabel\r\ndata = {\r\n 'text': ['one', 'two', 'three', 'four'],\r\n 'labels': [['a', 'b'], ['b'], ['b', 'c'], ['a', 'd']]\r\n}\r\n\r\ndataset = Dataset.from_dict(data)\r\ndataset = dataset.cast_column('labels', Sequence(ClassLabel(names=[\"a\", \"b\", \"c\", \"d\"])))\r\n```", "Great! Can you elaborate on \"class_encode_column does support nested fields\"? Do you mean that there is a way to `class_encode_column` on a Sequence?", "Yes, exactly! This would be a nice contribution, though.", "Sorry, I'm still not following. Are you saying that there currently exists a way to call `class_encode_column` on a `Sequence(ClassLabel)` type? Or that the underlying data structures support it and a contribution of a method to do that would be welcome?", "`class_encode_column ` currently does not support `Sequence(ClassLabel)`. Implementing support for this would be a nice contribution.\r\n\r\nIn the meantime, this limitation can be circumvented by fetching (unique) labels and calling `.cast_column(col, Sequence(ClassLabel(names=labels)))`.", "Ok makes sense, can you take a look at the POC implementation I did [here](https://github.com/huggingface/datasets/commit/15443098e9ce053943172f7ec6fce3769d7dff6e)? Happy to take another pass / submit as a PR but would be helpful if I got a thumbs up that this was directionally correct with respect to implementation / architecture. " ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6266). All of your documentation changes will be reflected on that endpoint.", "On Ubuntu, if `libyaml-dev` is installed, you can install PyYAML 6.0.1 with LibYAML with the following command (as it's automatically detected):\r\n\r\n```bash\r\npip install git+https://github.com/yaml/[email protected]\r\n```", "Are the failing tests flaky?", "We use `huggingface_hub`'s RepoCard API instead of these modules to parse the YAML block (notice the deprecations), so the `huggingface_hub` repo is the right place to suggest these changes.\r\n\r\nPersonally, I'm not a fan of these changes, as a single non-standard usage of the `ClassLabel` type is not a sufficient reason to merge them. Also, the dataset in question stores data in a single Parquet file, with the features info embedded in its (schema) metadata, which means the YAML parsing can be skipped while preserving the features by directly loading the Parquet file:\r\n```python\r\nfrom datasets import load_dataset\r\nds = load_dataset(\"parquet\", data_files=\"https://huggingface.co/datasets/HuggingFaceM4/SugarCrepe_swap_obj/resolve/main/data/test-00000-of-00001-ca2ae6017a2336d7.parquet\")\r\n```\r\n\r\nPS: Yes, these tests are flaky. We are working on fixing them.", "Oh, I didn't realize they were deprecated. Thanks for the tip on how to work around this issue!\r\n\r\nFor future reference, the places to change the code in `huggingface_hub` would be:\r\n\r\nhttps://github.com/huggingface/huggingface_hub/blob/89cc69105074f1d071e0471144605f3cdfe1dab3/src/huggingface_hub/repocard.py#L506\r\n\r\nhttps://github.com/huggingface/huggingface_hub/blob/89cc69105074f1d071e0471144605f3cdfe1dab3/src/huggingface_hub/utils/_fixes.py#L34" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005896 / 0.011353 (-0.005457) | 0.003642 / 0.011008 (-0.007366) | 0.081917 / 0.038508 (0.043409) | 0.059513 / 0.023109 (0.036404) | 0.341422 / 0.275898 (0.065524) | 0.359278 / 0.323480 (0.035798) | 0.004707 / 0.007986 (-0.003279) | 0.002938 / 0.004328 (-0.001390) | 0.063095 / 0.004250 (0.058845) | 0.051777 / 0.037052 (0.014725) | 0.321114 / 0.258489 (0.062625) | 0.363823 / 0.293841 (0.069982) | 0.027590 / 0.128546 (-0.100957) | 0.007846 / 0.075646 (-0.067800) | 0.261197 / 0.419271 (-0.158074) | 0.045812 / 0.043533 (0.002279) | 0.319787 / 0.255139 (0.064648) | 0.341839 / 0.283200 (0.058640) | 0.021913 / 0.141683 (-0.119770) | 1.397525 / 1.452155 (-0.054630) | 1.495902 / 1.492716 (0.003186) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224815 / 0.018006 (0.206809) | 0.425780 / 0.000490 (0.425290) | 0.006934 / 0.000200 (0.006734) | 0.000225 / 0.000054 (0.000171) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024342 / 0.037411 (-0.013070) | 0.073923 / 0.014526 (0.059398) | 0.082108 / 0.176557 (-0.094448) | 0.143017 / 0.737135 (-0.594119) | 0.083163 / 0.296338 (-0.213175) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.398244 / 0.215209 (0.183035) | 3.957688 / 2.077655 (1.880033) | 1.904615 / 1.504120 (0.400495) | 1.710353 / 1.541195 (0.169158) | 1.798980 / 1.468490 (0.330490) | 0.499307 / 4.584777 (-4.085470) | 3.026734 / 3.745712 (-0.718978) | 2.923940 / 5.269862 (-2.345922) | 1.831870 / 4.565676 (-2.733807) | 0.058551 / 0.424275 (-0.365724) | 0.006403 / 0.007607 (-0.001204) | 0.464164 / 0.226044 (0.238119) | 4.644556 / 2.268929 (2.375628) | 2.341455 / 55.444624 (-53.103169) | 2.004385 / 6.876477 (-4.872092) | 2.051819 / 2.142072 (-0.090253) | 0.585610 / 4.805227 (-4.219617) | 0.124735 / 6.500664 (-6.375929) | 0.061150 / 0.075469 (-0.014319) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.224665 / 1.841788 (-0.617122) | 17.476227 / 8.074308 (9.401919) | 13.867617 / 10.191392 (3.676225) | 0.144177 / 0.680424 (-0.536247) | 0.017045 / 0.534201 (-0.517156) | 0.337468 / 0.579283 (-0.241815) | 0.374476 / 0.434364 (-0.059888) | 0.393428 / 0.540337 (-0.146910) | 0.535335 / 1.386936 (-0.851601) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006208 / 0.011353 (-0.005145) | 0.003650 / 0.011008 (-0.007359) | 0.062843 / 0.038508 (0.024335) | 0.062272 / 0.023109 (0.039162) | 0.446336 / 0.275898 (0.170438) | 0.477476 / 0.323480 (0.153996) | 0.004862 / 0.007986 (-0.003124) | 0.002822 / 0.004328 (-0.001506) | 0.063427 / 0.004250 (0.059177) | 0.049023 / 0.037052 (0.011971) | 0.453633 / 0.258489 (0.195144) | 0.486494 / 0.293841 (0.192653) | 0.028634 / 0.128546 (-0.099912) | 0.008187 / 0.075646 (-0.067460) | 0.068846 / 0.419271 (-0.350425) | 0.041104 / 0.043533 (-0.002429) | 0.446646 / 0.255139 (0.191507) | 0.468860 / 0.283200 (0.185660) | 0.020980 / 0.141683 (-0.120703) | 1.455565 / 1.452155 (0.003410) | 1.511142 / 1.492716 (0.018426) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224242 / 0.018006 (0.206236) | 0.408483 / 0.000490 (0.407993) | 0.003495 / 0.000200 (0.003296) | 0.000076 / 0.000054 (0.000022) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027286 / 0.037411 (-0.010125) | 0.081151 / 0.014526 (0.066625) | 0.096598 / 0.176557 (-0.079959) | 0.146193 / 0.737135 (-0.590942) | 0.092213 / 0.296338 (-0.204125) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.463837 / 0.215209 (0.248628) | 4.636820 / 2.077655 (2.559165) | 2.576100 / 1.504120 (1.071980) | 2.396974 / 1.541195 (0.855779) | 2.461526 / 1.468490 (0.993036) | 0.502360 / 4.584777 (-4.082417) | 3.099973 / 3.745712 (-0.645739) | 2.937260 / 5.269862 (-2.332602) | 1.871274 / 4.565676 (-2.694402) | 0.057913 / 0.424275 (-0.366362) | 0.006511 / 0.007607 (-0.001096) | 0.536917 / 0.226044 (0.310873) | 5.396966 / 2.268929 (3.128038) | 3.015646 / 55.444624 (-52.428978) | 2.673793 / 6.876477 (-4.202684) | 2.712376 / 2.142072 (0.570304) | 0.591632 / 4.805227 (-4.213595) | 0.124872 / 6.500664 (-6.375792) | 0.061820 / 0.075469 (-0.013649) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.356828 / 1.841788 (-0.484960) | 18.076995 / 8.074308 (10.002687) | 15.116482 / 10.191392 (4.925090) | 0.151375 / 0.680424 (-0.529049) | 0.017867 / 0.534201 (-0.516334) | 0.335012 / 0.579283 (-0.244271) | 0.384137 / 0.434364 (-0.050226) | 0.397792 / 0.540337 (-0.142546) | 0.551521 / 1.386936 (-0.835415) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#46a0506765d0f92916ed5c37eb19e5fa1a77736a \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009418 / 0.011353 (-0.001935) | 0.005186 / 0.011008 (-0.005822) | 0.112270 / 0.038508 (0.073761) | 0.114856 / 0.023109 (0.091747) | 0.402267 / 0.275898 (0.126369) | 0.445213 / 0.323480 (0.121733) | 0.005588 / 0.007986 (-0.002398) | 0.004315 / 0.004328 (-0.000013) | 0.083561 / 0.004250 (0.079311) | 0.087319 / 0.037052 (0.050267) | 0.400989 / 0.258489 (0.142500) | 0.455636 / 0.293841 (0.161795) | 0.045168 / 0.128546 (-0.083378) | 0.010939 / 0.075646 (-0.064707) | 0.400120 / 0.419271 (-0.019151) | 0.071599 / 0.043533 (0.028066) | 0.418112 / 0.255139 (0.162973) | 0.443889 / 0.283200 (0.160690) | 0.032433 / 0.141683 (-0.109250) | 1.886313 / 1.452155 (0.434159) | 2.012909 / 1.492716 (0.520193) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.306991 / 0.018006 (0.288985) | 0.590426 / 0.000490 (0.589937) | 0.011811 / 0.000200 (0.011611) | 0.000596 / 0.000054 (0.000542) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.042520 / 0.037411 (0.005108) | 0.129808 / 0.014526 (0.115283) | 0.125481 / 0.176557 (-0.051075) | 0.199181 / 0.737135 (-0.537954) | 0.130426 / 0.296338 (-0.165913) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.526455 / 0.215209 (0.311246) | 5.213304 / 2.077655 (3.135649) | 2.643406 / 1.504120 (1.139286) | 2.611214 / 1.541195 (1.070019) | 2.586730 / 1.468490 (1.118240) | 0.639103 / 4.584777 (-3.945674) | 5.197421 / 3.745712 (1.451709) | 4.634642 / 5.269862 (-0.635220) | 2.741079 / 4.565676 (-1.824598) | 0.073064 / 0.424275 (-0.351211) | 0.009441 / 0.007607 (0.001834) | 0.635984 / 0.226044 (0.409940) | 6.283268 / 2.268929 (4.014339) | 3.337205 / 55.444624 (-52.107419) | 3.192362 / 6.876477 (-3.684114) | 2.910367 / 2.142072 (0.768294) | 0.767937 / 4.805227 (-4.037290) | 0.177467 / 6.500664 (-6.323198) | 0.081162 / 0.075469 (0.005693) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.803717 / 1.841788 (-0.038071) | 26.823235 / 8.074308 (18.748927) | 19.714471 / 10.191392 (9.523079) | 0.204048 / 0.680424 (-0.476376) | 0.025992 / 0.534201 (-0.508209) | 0.521438 / 0.579283 (-0.057845) | 0.596524 / 0.434364 (0.162160) | 0.600763 / 0.540337 (0.060425) | 0.945971 / 1.386936 (-0.440965) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009126 / 0.011353 (-0.002226) | 0.005109 / 0.011008 (-0.005899) | 0.083046 / 0.038508 (0.044538) | 0.115930 / 0.023109 (0.092821) | 0.534311 / 0.275898 (0.258413) | 0.552846 / 0.323480 (0.229366) | 0.007240 / 0.007986 (-0.000746) | 0.004617 / 0.004328 (0.000289) | 0.083927 / 0.004250 (0.079676) | 0.075926 / 0.037052 (0.038873) | 0.534750 / 0.258489 (0.276261) | 0.575122 / 0.293841 (0.281281) | 0.041001 / 0.128546 (-0.087545) | 0.010851 / 0.075646 (-0.064795) | 0.096574 / 0.419271 (-0.322697) | 0.063533 / 0.043533 (0.020001) | 0.546850 / 0.255139 (0.291711) | 0.547122 / 0.283200 (0.263922) | 0.032437 / 0.141683 (-0.109245) | 1.926191 / 1.452155 (0.474036) | 2.029841 / 1.492716 (0.537125) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.275582 / 0.018006 (0.257576) | 0.574212 / 0.000490 (0.573722) | 0.006863 / 0.000200 (0.006663) | 0.000236 / 0.000054 (0.000181) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.045340 / 0.037411 (0.007928) | 0.129196 / 0.014526 (0.114670) | 0.136637 / 0.176557 (-0.039920) | 0.200040 / 0.737135 (-0.537096) | 0.136328 / 0.296338 (-0.160011) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.612379 / 0.215209 (0.397170) | 5.874664 / 2.077655 (3.797010) | 3.070626 / 1.504120 (1.566506) | 2.999319 / 1.541195 (1.458124) | 3.000571 / 1.468490 (1.532081) | 0.732119 / 4.584777 (-3.852658) | 5.193226 / 3.745712 (1.447514) | 4.714571 / 5.269862 (-0.555291) | 2.870438 / 4.565676 (-1.695239) | 0.075793 / 0.424275 (-0.348482) | 0.009238 / 0.007607 (0.001631) | 0.695192 / 0.226044 (0.469148) | 6.897996 / 2.268929 (4.629067) | 3.923474 / 55.444624 (-51.521150) | 3.458326 / 6.876477 (-3.418151) | 3.331652 / 2.142072 (1.189579) | 0.821132 / 4.805227 (-3.984095) | 0.182252 / 6.500664 (-6.318412) | 0.084730 / 0.075469 (0.009260) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.919861 / 1.841788 (0.078073) | 27.437228 / 8.074308 (19.362920) | 21.109899 / 10.191392 (10.918507) | 0.245998 / 0.680424 (-0.434426) | 0.025817 / 0.534201 (-0.508384) | 0.517757 / 0.579283 (-0.061526) | 0.576375 / 0.434364 (0.142011) | 0.625283 / 0.540337 (0.084945) | 0.956877 / 1.386936 (-0.430059) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8ddee15a8650a0ea52073477036d8c973da50f11 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008099 / 0.011353 (-0.003254) | 0.004815 / 0.011008 (-0.006194) | 0.099657 / 0.038508 (0.061149) | 0.064737 / 0.023109 (0.041628) | 0.461773 / 0.275898 (0.185875) | 0.444810 / 0.323480 (0.121330) | 0.004247 / 0.007986 (-0.003739) | 0.004956 / 0.004328 (0.000628) | 0.068664 / 0.004250 (0.064414) | 0.052039 / 0.037052 (0.014986) | 0.406750 / 0.258489 (0.148261) | 0.452832 / 0.293841 (0.158991) | 0.044518 / 0.128546 (-0.084028) | 0.013220 / 0.075646 (-0.062426) | 0.317713 / 0.419271 (-0.101558) | 0.061897 / 0.043533 (0.018364) | 0.398664 / 0.255139 (0.143525) | 0.531494 / 0.283200 (0.248294) | 0.064033 / 0.141683 (-0.077650) | 1.590385 / 1.452155 (0.138231) | 1.769918 / 1.492716 (0.277202) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230795 / 0.018006 (0.212789) | 0.568797 / 0.000490 (0.568308) | 0.013498 / 0.000200 (0.013298) | 0.000448 / 0.000054 (0.000393) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028394 / 0.037411 (-0.009017) | 0.081973 / 0.014526 (0.067447) | 0.097623 / 0.176557 (-0.078934) | 0.158691 / 0.737135 (-0.578445) | 0.101548 / 0.296338 (-0.194791) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.574459 / 0.215209 (0.359249) | 5.709871 / 2.077655 (3.632217) | 2.521460 / 1.504120 (1.017340) | 2.239463 / 1.541195 (0.698268) | 2.195067 / 1.468490 (0.726577) | 0.792390 / 4.584777 (-3.792387) | 4.841665 / 3.745712 (1.095952) | 4.201620 / 5.269862 (-1.068241) | 2.664081 / 4.565676 (-1.901595) | 0.097661 / 0.424275 (-0.326614) | 0.008428 / 0.007607 (0.000821) | 0.698729 / 0.226044 (0.472684) | 6.908867 / 2.268929 (4.639939) | 3.247480 / 55.444624 (-52.197145) | 2.563921 / 6.876477 (-4.312556) | 2.738249 / 2.142072 (0.596177) | 0.972066 / 4.805227 (-3.833161) | 0.191196 / 6.500664 (-6.309468) | 0.064732 / 0.075469 (-0.010737) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.421910 / 1.841788 (-0.419877) | 20.633538 / 8.074308 (12.559230) | 18.054562 / 10.191392 (7.863170) | 0.194125 / 0.680424 (-0.486299) | 0.028097 / 0.534201 (-0.506104) | 0.417857 / 0.579283 (-0.161426) | 0.518758 / 0.434364 (0.084394) | 0.500199 / 0.540337 (-0.040138) | 0.754662 / 1.386936 (-0.632274) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008452 / 0.011353 (-0.002901) | 0.004646 / 0.011008 (-0.006362) | 0.077286 / 0.038508 (0.038778) | 0.072507 / 0.023109 (0.049398) | 0.439580 / 0.275898 (0.163682) | 0.506166 / 0.323480 (0.182686) | 0.006035 / 0.007986 (-0.001950) | 0.003886 / 0.004328 (-0.000442) | 0.075091 / 0.004250 (0.070841) | 0.063163 / 0.037052 (0.026110) | 0.468550 / 0.258489 (0.210061) | 0.523273 / 0.293841 (0.229432) | 0.048728 / 0.128546 (-0.079818) | 0.012991 / 0.075646 (-0.062655) | 0.087964 / 0.419271 (-0.331308) | 0.058920 / 0.043533 (0.015387) | 0.451247 / 0.255139 (0.196108) | 0.489827 / 0.283200 (0.206628) | 0.031164 / 0.141683 (-0.110519) | 1.675504 / 1.452155 (0.223349) | 1.806098 / 1.492716 (0.313382) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.253567 / 0.018006 (0.235561) | 0.508971 / 0.000490 (0.508481) | 0.010882 / 0.000200 (0.010682) | 0.000111 / 0.000054 (0.000057) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029490 / 0.037411 (-0.007921) | 0.090255 / 0.014526 (0.075729) | 0.110075 / 0.176557 (-0.066482) | 0.159375 / 0.737135 (-0.577760) | 0.109313 / 0.296338 (-0.187025) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.580252 / 0.215209 (0.365043) | 5.911741 / 2.077655 (3.834086) | 2.659405 / 1.504120 (1.155285) | 2.344943 / 1.541195 (0.803749) | 2.390748 / 1.468490 (0.922258) | 0.827823 / 4.584777 (-3.756954) | 4.973544 / 3.745712 (1.227832) | 4.300220 / 5.269862 (-0.969642) | 2.826181 / 4.565676 (-1.739495) | 0.101013 / 0.424275 (-0.323263) | 0.008025 / 0.007607 (0.000418) | 0.728414 / 0.226044 (0.502369) | 7.508045 / 2.268929 (5.239117) | 3.687627 / 55.444624 (-51.756997) | 2.902953 / 6.876477 (-3.973524) | 3.094624 / 2.142072 (0.952551) | 1.054696 / 4.805227 (-3.750531) | 0.212297 / 6.500664 (-6.288367) | 0.070211 / 0.075469 (-0.005258) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.567117 / 1.841788 (-0.274670) | 21.420746 / 8.074308 (13.346438) | 19.857467 / 10.191392 (9.666075) | 0.228554 / 0.680424 (-0.451870) | 0.032278 / 0.534201 (-0.501923) | 0.459966 / 0.579283 (-0.119317) | 0.541219 / 0.434364 (0.106855) | 0.549599 / 0.540337 (0.009261) | 0.731476 / 1.386936 (-0.655460) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0cc77d7f45c73698c31eab4f8cfff901044d0020 \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008356 / 0.011353 (-0.002997) | 0.004553 / 0.011008 (-0.006455) | 0.101025 / 0.038508 (0.062517) | 0.090194 / 0.023109 (0.067085) | 0.427127 / 0.275898 (0.151229) | 0.469116 / 0.323480 (0.145636) | 0.007593 / 0.007986 (-0.000393) | 0.003751 / 0.004328 (-0.000578) | 0.077432 / 0.004250 (0.073182) | 0.082744 / 0.037052 (0.045692) | 0.433638 / 0.258489 (0.175149) | 0.482387 / 0.293841 (0.188546) | 0.040658 / 0.128546 (-0.087888) | 0.009799 / 0.075646 (-0.065848) | 0.345274 / 0.419271 (-0.073998) | 0.076642 / 0.043533 (0.033109) | 0.424417 / 0.255139 (0.169278) | 0.457045 / 0.283200 (0.173846) | 0.033642 / 0.141683 (-0.108041) | 1.765446 / 1.452155 (0.313291) | 1.859279 / 1.492716 (0.366562) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.273629 / 0.018006 (0.255623) | 0.505743 / 0.000490 (0.505253) | 0.009300 / 0.000200 (0.009100) | 0.000359 / 0.000054 (0.000305) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032510 / 0.037411 (-0.004901) | 0.099628 / 0.014526 (0.085103) | 0.112904 / 0.176557 (-0.063652) | 0.179118 / 0.737135 (-0.558018) | 0.115946 / 0.296338 (-0.180393) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.456431 / 0.215209 (0.241222) | 4.556559 / 2.077655 (2.478904) | 2.207893 / 1.504120 (0.703773) | 2.024706 / 1.541195 (0.483512) | 2.165424 / 1.468490 (0.696934) | 0.571745 / 4.584777 (-4.013031) | 4.341017 / 3.745712 (0.595305) | 3.980520 / 5.269862 (-1.289342) | 2.333077 / 4.565676 (-2.232599) | 0.067200 / 0.424275 (-0.357075) | 0.008563 / 0.007607 (0.000956) | 0.545294 / 0.226044 (0.319250) | 5.445152 / 2.268929 (3.176224) | 2.740657 / 55.444624 (-52.703968) | 2.370635 / 6.876477 (-4.505842) | 2.451642 / 2.142072 (0.309570) | 0.679385 / 4.805227 (-4.125842) | 0.155967 / 6.500664 (-6.344697) | 0.072812 / 0.075469 (-0.002657) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.494483 / 1.841788 (-0.347305) | 23.673700 / 8.074308 (15.599392) | 16.608529 / 10.191392 (6.417137) | 0.170220 / 0.680424 (-0.510204) | 0.021630 / 0.534201 (-0.512571) | 0.470771 / 0.579283 (-0.108512) | 0.535874 / 0.434364 (0.101510) | 0.550376 / 0.540337 (0.010039) | 0.776633 / 1.386936 (-0.610303) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007899 / 0.011353 (-0.003454) | 0.004581 / 0.011008 (-0.006427) | 0.076520 / 0.038508 (0.038012) | 0.090374 / 0.023109 (0.067265) | 0.495016 / 0.275898 (0.219118) | 0.532384 / 0.323480 (0.208904) | 0.006160 / 0.007986 (-0.001825) | 0.003780 / 0.004328 (-0.000548) | 0.077164 / 0.004250 (0.072914) | 0.064444 / 0.037052 (0.027391) | 0.501642 / 0.258489 (0.243153) | 0.549170 / 0.293841 (0.255329) | 0.038051 / 0.128546 (-0.090495) | 0.010081 / 0.075646 (-0.065565) | 0.083752 / 0.419271 (-0.335520) | 0.061334 / 0.043533 (0.017801) | 0.493502 / 0.255139 (0.238363) | 0.518018 / 0.283200 (0.234818) | 0.029534 / 0.141683 (-0.112149) | 1.929432 / 1.452155 (0.477277) | 1.889985 / 1.492716 (0.397268) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.254802 / 0.018006 (0.236795) | 0.494463 / 0.000490 (0.493974) | 0.005040 / 0.000200 (0.004840) | 0.000120 / 0.000054 (0.000065) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038372 / 0.037411 (0.000960) | 0.112247 / 0.014526 (0.097721) | 0.124365 / 0.176557 (-0.052191) | 0.187142 / 0.737135 (-0.549993) | 0.126070 / 0.296338 (-0.170269) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.513418 / 0.215209 (0.298209) | 5.132267 / 2.077655 (3.054613) | 2.773676 / 1.504120 (1.269556) | 2.576840 / 1.541195 (1.035645) | 2.681729 / 1.468490 (1.213238) | 0.581809 / 4.584777 (-4.002968) | 4.327075 / 3.745712 (0.581363) | 4.040264 / 5.269862 (-1.229598) | 2.436192 / 4.565676 (-2.129484) | 0.067819 / 0.424275 (-0.356456) | 0.008760 / 0.007607 (0.001153) | 0.610765 / 0.226044 (0.384720) | 6.105679 / 2.268929 (3.836750) | 3.341341 / 55.444624 (-52.103284) | 2.926695 / 6.876477 (-3.949781) | 3.017269 / 2.142072 (0.875196) | 0.707289 / 4.805227 (-4.097938) | 0.157379 / 6.500664 (-6.343285) | 0.072549 / 0.075469 (-0.002920) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.666738 / 1.841788 (-0.175050) | 23.698567 / 8.074308 (15.624259) | 17.806437 / 10.191392 (7.615045) | 0.172103 / 0.680424 (-0.508321) | 0.023508 / 0.534201 (-0.510693) | 0.473171 / 0.579283 (-0.106112) | 0.524834 / 0.434364 (0.090470) | 0.562562 / 0.540337 (0.022224) | 0.788667 / 1.386936 (-0.598269) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1e7338259b26b32a095d251d5cdbc779c3573307 \"CML watermark\")\n", "CI 404 errors are unrelated. See:\r\n- #6262 ", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006657 / 0.011353 (-0.004696) | 0.003975 / 0.011008 (-0.007033) | 0.084614 / 0.038508 (0.046106) | 0.074557 / 0.023109 (0.051448) | 0.309213 / 0.275898 (0.033315) | 0.338245 / 0.323480 (0.014765) | 0.005375 / 0.007986 (-0.002610) | 0.003355 / 0.004328 (-0.000973) | 0.064406 / 0.004250 (0.060156) | 0.061763 / 0.037052 (0.024711) | 0.313405 / 0.258489 (0.054916) | 0.352149 / 0.293841 (0.058308) | 0.031597 / 0.128546 (-0.096949) | 0.008499 / 0.075646 (-0.067147) | 0.289098 / 0.419271 (-0.130174) | 0.054415 / 0.043533 (0.010882) | 0.313210 / 0.255139 (0.058071) | 0.326728 / 0.283200 (0.043528) | 0.024597 / 0.141683 (-0.117086) | 1.449916 / 1.452155 (-0.002239) | 1.526314 / 1.492716 (0.033598) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.231435 / 0.018006 (0.213429) | 0.537224 / 0.000490 (0.536734) | 0.007287 / 0.000200 (0.007088) | 0.000227 / 0.000054 (0.000172) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028340 / 0.037411 (-0.009071) | 0.084085 / 0.014526 (0.069560) | 0.428211 / 0.176557 (0.251655) | 0.157360 / 0.737135 (-0.579775) | 0.139470 / 0.296338 (-0.156868) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.389311 / 0.215209 (0.174102) | 3.871329 / 2.077655 (1.793674) | 1.861533 / 1.504120 (0.357413) | 1.688082 / 1.541195 (0.146887) | 1.804036 / 1.468490 (0.335546) | 0.489154 / 4.584777 (-4.095623) | 3.603843 / 3.745712 (-0.141869) | 3.424868 / 5.269862 (-1.844994) | 2.013525 / 4.565676 (-2.552152) | 0.057387 / 0.424275 (-0.366888) | 0.007274 / 0.007607 (-0.000333) | 0.462340 / 0.226044 (0.236295) | 4.620095 / 2.268929 (2.351167) | 2.326641 / 55.444624 (-53.117984) | 1.990082 / 6.876477 (-4.886395) | 2.037841 / 2.142072 (-0.104232) | 0.581973 / 4.805227 (-4.223254) | 0.135932 / 6.500664 (-6.364732) | 0.061092 / 0.075469 (-0.014377) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.249586 / 1.841788 (-0.592202) | 19.036233 / 8.074308 (10.961925) | 14.083365 / 10.191392 (3.891973) | 0.169802 / 0.680424 (-0.510622) | 0.018547 / 0.534201 (-0.515654) | 0.392926 / 0.579283 (-0.186357) | 0.409993 / 0.434364 (-0.024371) | 0.460081 / 0.540337 (-0.080257) | 0.643836 / 1.386936 (-0.743100) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006889 / 0.011353 (-0.004464) | 0.004060 / 0.011008 (-0.006948) | 0.064332 / 0.038508 (0.025824) | 0.077067 / 0.023109 (0.053958) | 0.401235 / 0.275898 (0.125337) | 0.437139 / 0.323480 (0.113659) | 0.005510 / 0.007986 (-0.002476) | 0.003338 / 0.004328 (-0.000991) | 0.064446 / 0.004250 (0.060195) | 0.055537 / 0.037052 (0.018485) | 0.432689 / 0.258489 (0.174200) | 0.460005 / 0.293841 (0.166164) | 0.033122 / 0.128546 (-0.095424) | 0.008637 / 0.075646 (-0.067010) | 0.071088 / 0.419271 (-0.348183) | 0.049024 / 0.043533 (0.005491) | 0.400258 / 0.255139 (0.145119) | 0.419324 / 0.283200 (0.136124) | 0.022050 / 0.141683 (-0.119632) | 1.475744 / 1.452155 (0.023589) | 1.546565 / 1.492716 (0.053848) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226241 / 0.018006 (0.208235) | 0.448574 / 0.000490 (0.448085) | 0.004732 / 0.000200 (0.004533) | 0.000097 / 0.000054 (0.000042) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033260 / 0.037411 (-0.004151) | 0.092622 / 0.014526 (0.078096) | 0.105501 / 0.176557 (-0.071056) | 0.157981 / 0.737135 (-0.579155) | 0.105993 / 0.296338 (-0.190345) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.445716 / 0.215209 (0.230507) | 4.451848 / 2.077655 (2.374194) | 2.404769 / 1.504120 (0.900649) | 2.232594 / 1.541195 (0.691399) | 2.312735 / 1.468490 (0.844245) | 0.491208 / 4.584777 (-4.093569) | 3.561629 / 3.745712 (-0.184083) | 3.444269 / 5.269862 (-1.825592) | 2.060365 / 4.565676 (-2.505311) | 0.057723 / 0.424275 (-0.366552) | 0.007392 / 0.007607 (-0.000215) | 0.526447 / 0.226044 (0.300403) | 5.264307 / 2.268929 (2.995379) | 2.951481 / 55.444624 (-52.493143) | 2.593178 / 6.876477 (-4.283299) | 2.689780 / 2.142072 (0.547707) | 0.588649 / 4.805227 (-4.216579) | 0.133566 / 6.500664 (-6.367098) | 0.060462 / 0.075469 (-0.015008) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.381008 / 1.841788 (-0.460780) | 19.452394 / 8.074308 (11.378086) | 15.255912 / 10.191392 (5.064520) | 0.171043 / 0.680424 (-0.509381) | 0.020395 / 0.534201 (-0.513806) | 0.396429 / 0.579283 (-0.182854) | 0.422820 / 0.434364 (-0.011544) | 0.477305 / 0.540337 (-0.063032) | 0.658274 / 1.386936 (-0.728663) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#faedc670ca896584d0f8edcb1fd9c13d1d6cc903 \"CML watermark\")\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008220 / 0.011353 (-0.003133) | 0.005560 / 0.011008 (-0.005448) | 0.100147 / 0.038508 (0.061639) | 0.070106 / 0.023109 (0.046996) | 0.411906 / 0.275898 (0.136008) | 0.432825 / 0.323480 (0.109345) | 0.004795 / 0.007986 (-0.003190) | 0.004094 / 0.004328 (-0.000235) | 0.075719 / 0.004250 (0.071468) | 0.067426 / 0.037052 (0.030374) | 0.428531 / 0.258489 (0.170042) | 0.437114 / 0.293841 (0.143273) | 0.045603 / 0.128546 (-0.082943) | 0.013333 / 0.075646 (-0.062313) | 0.353137 / 0.419271 (-0.066134) | 0.067902 / 0.043533 (0.024369) | 0.396633 / 0.255139 (0.141494) | 0.399185 / 0.283200 (0.115985) | 0.036377 / 0.141683 (-0.105306) | 1.624249 / 1.452155 (0.172094) | 1.792575 / 1.492716 (0.299859) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.315847 / 0.018006 (0.297840) | 0.595009 / 0.000490 (0.594519) | 0.018876 / 0.000200 (0.018676) | 0.000613 / 0.000054 (0.000558) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029886 / 0.037411 (-0.007526) | 0.085765 / 0.014526 (0.071239) | 0.108680 / 0.176557 (-0.067877) | 0.174588 / 0.737135 (-0.562548) | 0.104494 / 0.296338 (-0.191844) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.594429 / 0.215209 (0.379220) | 5.912352 / 2.077655 (3.834698) | 2.408501 / 1.504120 (0.904381) | 2.050914 / 1.541195 (0.509720) | 2.199349 / 1.468490 (0.730859) | 0.813797 / 4.584777 (-3.770980) | 5.169577 / 3.745712 (1.423864) | 4.653951 / 5.269862 (-0.615911) | 2.805423 / 4.565676 (-1.760253) | 0.092278 / 0.424275 (-0.331997) | 0.007394 / 0.007607 (-0.000213) | 0.684029 / 0.226044 (0.457985) | 6.964260 / 2.268929 (4.695331) | 3.108408 / 55.444624 (-52.336217) | 2.470907 / 6.876477 (-4.405569) | 2.460153 / 2.142072 (0.318081) | 0.986445 / 4.805227 (-3.818782) | 0.213069 / 6.500664 (-6.287596) | 0.074061 / 0.075469 (-0.001408) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.590732 / 1.841788 (-0.251056) | 23.736918 / 8.074308 (15.662609) | 21.223910 / 10.191392 (11.032518) | 0.236173 / 0.680424 (-0.444251) | 0.030056 / 0.534201 (-0.504145) | 0.489461 / 0.579283 (-0.089822) | 0.607582 / 0.434364 (0.173218) | 0.539889 / 0.540337 (-0.000449) | 0.817942 / 1.386936 (-0.568994) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008042 / 0.011353 (-0.003311) | 0.004836 / 0.011008 (-0.006173) | 0.075434 / 0.038508 (0.036926) | 0.080818 / 0.023109 (0.057709) | 0.474797 / 0.275898 (0.198899) | 0.526168 / 0.323480 (0.202689) | 0.006463 / 0.007986 (-0.001522) | 0.004031 / 0.004328 (-0.000297) | 0.074141 / 0.004250 (0.069891) | 0.068265 / 0.037052 (0.031212) | 0.562550 / 0.258489 (0.304061) | 0.544820 / 0.293841 (0.250979) | 0.047263 / 0.128546 (-0.081283) | 0.014113 / 0.075646 (-0.061534) | 0.086061 / 0.419271 (-0.333210) | 0.062475 / 0.043533 (0.018942) | 0.479912 / 0.255139 (0.224773) | 0.494784 / 0.283200 (0.211584) | 0.035847 / 0.141683 (-0.105836) | 1.726452 / 1.452155 (0.274297) | 1.770113 / 1.492716 (0.277396) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.286713 / 0.018006 (0.268707) | 0.609704 / 0.000490 (0.609214) | 0.009342 / 0.000200 (0.009143) | 0.000134 / 0.000054 (0.000080) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035137 / 0.037411 (-0.002275) | 0.099331 / 0.014526 (0.084805) | 0.108971 / 0.176557 (-0.067586) | 0.170952 / 0.737135 (-0.566183) | 0.111736 / 0.296338 (-0.184603) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.617434 / 0.215209 (0.402225) | 6.204351 / 2.077655 (4.126697) | 2.854347 / 1.504120 (1.350227) | 2.557424 / 1.541195 (1.016229) | 2.638173 / 1.468490 (1.169683) | 0.854234 / 4.584777 (-3.730543) | 5.383288 / 3.745712 (1.637576) | 4.698098 / 5.269862 (-0.571763) | 2.903860 / 4.565676 (-1.661817) | 0.094689 / 0.424275 (-0.329586) | 0.007892 / 0.007607 (0.000285) | 0.729420 / 0.226044 (0.503376) | 7.356691 / 2.268929 (5.087763) | 3.708039 / 55.444624 (-51.736585) | 2.979734 / 6.876477 (-3.896743) | 2.978983 / 2.142072 (0.836911) | 1.040554 / 4.805227 (-3.764673) | 0.211246 / 6.500664 (-6.289418) | 0.079880 / 0.075469 (0.004411) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.676057 / 1.841788 (-0.165731) | 23.428443 / 8.074308 (15.354135) | 21.016293 / 10.191392 (10.824901) | 0.260927 / 0.680424 (-0.419497) | 0.030689 / 0.534201 (-0.503512) | 0.495652 / 0.579283 (-0.083632) | 0.622976 / 0.434364 (0.188612) | 0.561175 / 0.540337 (0.020837) | 0.786733 / 1.386936 (-0.600203) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#fb621b9630a69643255d25f192fdb011935122b1 \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005942 / 0.011353 (-0.005410) | 0.003706 / 0.011008 (-0.007302) | 0.081002 / 0.038508 (0.042493) | 0.056854 / 0.023109 (0.033745) | 0.358668 / 0.275898 (0.082770) | 0.369718 / 0.323480 (0.046238) | 0.005202 / 0.007986 (-0.002784) | 0.002841 / 0.004328 (-0.001487) | 0.062976 / 0.004250 (0.058726) | 0.051308 / 0.037052 (0.014255) | 0.373636 / 0.258489 (0.115147) | 0.390480 / 0.293841 (0.096639) | 0.027480 / 0.128546 (-0.101067) | 0.007960 / 0.075646 (-0.067686) | 0.262719 / 0.419271 (-0.156552) | 0.046488 / 0.043533 (0.002955) | 0.347299 / 0.255139 (0.092160) | 0.393448 / 0.283200 (0.110249) | 0.019445 / 0.141683 (-0.122238) | 1.431314 / 1.452155 (-0.020841) | 1.495578 / 1.492716 (0.002862) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223724 / 0.018006 (0.205718) | 0.416929 / 0.000490 (0.416440) | 0.005253 / 0.000200 (0.005053) | 0.000217 / 0.000054 (0.000163) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023571 / 0.037411 (-0.013841) | 0.073503 / 0.014526 (0.058978) | 0.081366 / 0.176557 (-0.095190) | 0.142716 / 0.737135 (-0.594420) | 0.082612 / 0.296338 (-0.213727) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.407319 / 0.215209 (0.192109) | 4.141404 / 2.077655 (2.063749) | 1.910842 / 1.504120 (0.406722) | 1.731694 / 1.541195 (0.190499) | 1.805228 / 1.468490 (0.336738) | 0.497109 / 4.584777 (-4.087668) | 3.107624 / 3.745712 (-0.638088) | 2.890687 / 5.269862 (-2.379174) | 1.795913 / 4.565676 (-2.769763) | 0.057099 / 0.424275 (-0.367176) | 0.006414 / 0.007607 (-0.001194) | 0.482127 / 0.226044 (0.256083) | 4.835158 / 2.268929 (2.566229) | 2.368909 / 55.444624 (-53.075715) | 2.001608 / 6.876477 (-4.874868) | 2.004492 / 2.142072 (-0.137580) | 0.579910 / 4.805227 (-4.225317) | 0.123541 / 6.500664 (-6.377123) | 0.059651 / 0.075469 (-0.015818) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.242364 / 1.841788 (-0.599424) | 16.982676 / 8.074308 (8.908368) | 13.718885 / 10.191392 (3.527493) | 0.132759 / 0.680424 (-0.547665) | 0.017012 / 0.534201 (-0.517189) | 0.333447 / 0.579283 (-0.245836) | 0.360149 / 0.434364 (-0.074215) | 0.385526 / 0.540337 (-0.154811) | 0.536915 / 1.386936 (-0.850021) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005946 / 0.011353 (-0.005407) | 0.003442 / 0.011008 (-0.007566) | 0.062595 / 0.038508 (0.024087) | 0.058699 / 0.023109 (0.035590) | 0.442626 / 0.275898 (0.166728) | 0.473773 / 0.323480 (0.150293) | 0.004622 / 0.007986 (-0.003364) | 0.002812 / 0.004328 (-0.001516) | 0.064099 / 0.004250 (0.059849) | 0.046784 / 0.037052 (0.009731) | 0.466049 / 0.258489 (0.207560) | 0.487912 / 0.293841 (0.194071) | 0.028372 / 0.128546 (-0.100174) | 0.007992 / 0.075646 (-0.067654) | 0.068151 / 0.419271 (-0.351120) | 0.041010 / 0.043533 (-0.002523) | 0.442331 / 0.255139 (0.187192) | 0.469686 / 0.283200 (0.186487) | 0.019694 / 0.141683 (-0.121989) | 1.467928 / 1.452155 (0.015774) | 1.525635 / 1.492716 (0.032918) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.204459 / 0.018006 (0.186453) | 0.407766 / 0.000490 (0.407276) | 0.003898 / 0.000200 (0.003698) | 0.000077 / 0.000054 (0.000023) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025909 / 0.037411 (-0.011503) | 0.080341 / 0.014526 (0.065816) | 0.088231 / 0.176557 (-0.088325) | 0.144056 / 0.737135 (-0.593079) | 0.089769 / 0.296338 (-0.206569) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.462876 / 0.215209 (0.247667) | 4.625983 / 2.077655 (2.548329) | 2.580079 / 1.504120 (1.075959) | 2.402792 / 1.541195 (0.861597) | 2.424982 / 1.468490 (0.956491) | 0.503654 / 4.584777 (-4.081123) | 3.178995 / 3.745712 (-0.566717) | 2.956126 / 5.269862 (-2.313735) | 1.847837 / 4.565676 (-2.717840) | 0.057964 / 0.424275 (-0.366311) | 0.006405 / 0.007607 (-0.001202) | 0.536036 / 0.226044 (0.309992) | 5.374416 / 2.268929 (3.105487) | 3.036440 / 55.444624 (-52.408184) | 2.682054 / 6.876477 (-4.194422) | 2.683462 / 2.142072 (0.541390) | 0.592751 / 4.805227 (-4.212477) | 0.124313 / 6.500664 (-6.376351) | 0.061127 / 0.075469 (-0.014342) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.383539 / 1.841788 (-0.458249) | 17.766221 / 8.074308 (9.691913) | 15.306600 / 10.191392 (5.115208) | 0.145035 / 0.680424 (-0.535389) | 0.018078 / 0.534201 (-0.516123) | 0.330102 / 0.579283 (-0.249181) | 0.375380 / 0.434364 (-0.058984) | 0.388531 / 0.540337 (-0.151807) | 0.548720 / 1.386936 (-0.838216) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0082342ac792a05f4a615e4985d1c791e155115a \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006757 / 0.011353 (-0.004596) | 0.004110 / 0.011008 (-0.006898) | 0.084727 / 0.038508 (0.046219) | 0.074328 / 0.023109 (0.051219) | 0.310467 / 0.275898 (0.034569) | 0.343209 / 0.323480 (0.019729) | 0.004228 / 0.007986 (-0.003757) | 0.003400 / 0.004328 (-0.000929) | 0.065546 / 0.004250 (0.061296) | 0.063057 / 0.037052 (0.026005) | 0.315023 / 0.258489 (0.056534) | 0.356395 / 0.293841 (0.062554) | 0.031959 / 0.128546 (-0.096588) | 0.008577 / 0.075646 (-0.067069) | 0.289075 / 0.419271 (-0.130196) | 0.055011 / 0.043533 (0.011478) | 0.308861 / 0.255139 (0.053722) | 0.328691 / 0.283200 (0.045491) | 0.027037 / 0.141683 (-0.114646) | 1.464314 / 1.452155 (0.012159) | 1.549644 / 1.492716 (0.056927) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.238330 / 0.018006 (0.220324) | 0.451570 / 0.000490 (0.451080) | 0.010873 / 0.000200 (0.010673) | 0.000341 / 0.000054 (0.000286) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029909 / 0.037411 (-0.007503) | 0.085222 / 0.014526 (0.070696) | 0.100180 / 0.176557 (-0.076377) | 0.154842 / 0.737135 (-0.582293) | 0.099253 / 0.296338 (-0.197086) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.401603 / 0.215209 (0.186394) | 4.009781 / 2.077655 (1.932126) | 2.021807 / 1.504120 (0.517687) | 1.861017 / 1.541195 (0.319822) | 2.009072 / 1.468490 (0.540582) | 0.483798 / 4.584777 (-4.100979) | 3.580394 / 3.745712 (-0.165318) | 3.464587 / 5.269862 (-1.805275) | 2.018400 / 4.565676 (-2.547276) | 0.057134 / 0.424275 (-0.367141) | 0.007303 / 0.007607 (-0.000304) | 0.473627 / 0.226044 (0.247582) | 4.722634 / 2.268929 (2.453706) | 2.490884 / 55.444624 (-52.953741) | 2.121568 / 6.876477 (-4.754909) | 2.200699 / 2.142072 (0.058626) | 0.576728 / 4.805227 (-4.228499) | 0.135633 / 6.500664 (-6.365032) | 0.061625 / 0.075469 (-0.013844) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.250545 / 1.841788 (-0.591243) | 19.167642 / 8.074308 (11.093334) | 14.189891 / 10.191392 (3.998499) | 0.164552 / 0.680424 (-0.515872) | 0.018215 / 0.534201 (-0.515986) | 0.389962 / 0.579283 (-0.189321) | 0.413972 / 0.434364 (-0.020392) | 0.460253 / 0.540337 (-0.080085) | 0.647897 / 1.386936 (-0.739039) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006714 / 0.011353 (-0.004639) | 0.004081 / 0.011008 (-0.006927) | 0.065627 / 0.038508 (0.027119) | 0.077644 / 0.023109 (0.054535) | 0.409950 / 0.275898 (0.134052) | 0.442940 / 0.323480 (0.119460) | 0.005523 / 0.007986 (-0.002463) | 0.003366 / 0.004328 (-0.000962) | 0.065425 / 0.004250 (0.061174) | 0.056222 / 0.037052 (0.019169) | 0.429928 / 0.258489 (0.171439) | 0.457136 / 0.293841 (0.163296) | 0.032356 / 0.128546 (-0.096190) | 0.008676 / 0.075646 (-0.066970) | 0.071785 / 0.419271 (-0.347486) | 0.048458 / 0.043533 (0.004925) | 0.408003 / 0.255139 (0.152864) | 0.433529 / 0.283200 (0.150330) | 0.023232 / 0.141683 (-0.118450) | 1.483640 / 1.452155 (0.031485) | 1.552425 / 1.492716 (0.059709) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.282347 / 0.018006 (0.264341) | 0.448742 / 0.000490 (0.448253) | 0.039590 / 0.000200 (0.039390) | 0.000407 / 0.000054 (0.000353) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032516 / 0.037411 (-0.004896) | 0.095269 / 0.014526 (0.080744) | 0.106363 / 0.176557 (-0.070193) | 0.157945 / 0.737135 (-0.579191) | 0.106783 / 0.296338 (-0.189556) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436334 / 0.215209 (0.221125) | 4.348147 / 2.077655 (2.270492) | 2.326830 / 1.504120 (0.822710) | 2.162586 / 1.541195 (0.621391) | 2.257769 / 1.468490 (0.789279) | 0.491677 / 4.584777 (-4.093099) | 3.707385 / 3.745712 (-0.038328) | 3.567147 / 5.269862 (-1.702715) | 2.099451 / 4.565676 (-2.466226) | 0.058486 / 0.424275 (-0.365789) | 0.007324 / 0.007607 (-0.000283) | 0.510962 / 0.226044 (0.284917) | 5.106550 / 2.268929 (2.837622) | 2.785723 / 55.444624 (-52.658901) | 2.452928 / 6.876477 (-4.423548) | 2.545034 / 2.142072 (0.402961) | 0.611124 / 4.805227 (-4.194103) | 0.133503 / 6.500664 (-6.367161) | 0.061118 / 0.075469 (-0.014351) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.386640 / 1.841788 (-0.455148) | 20.485670 / 8.074308 (12.411362) | 15.332223 / 10.191392 (5.140831) | 0.164070 / 0.680424 (-0.516354) | 0.019962 / 0.534201 (-0.514239) | 0.394217 / 0.579283 (-0.185066) | 0.428442 / 0.434364 (-0.005922) | 0.473784 / 0.540337 (-0.066553) | 0.665141 / 1.386936 (-0.721795) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c722eb75a6cc56eac530c44a17ff679ca805aa89 \"CML watermark\")\n", "The CI errors seem unrelated to this PR but I think they need further investigation in another PR.\r\n```\r\nFAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_multiple_files - KeyError: 'url'\r\n```", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008766 / 0.011353 (-0.002587) | 0.005289 / 0.011008 (-0.005720) | 0.097220 / 0.038508 (0.058712) | 0.072246 / 0.023109 (0.049137) | 0.369359 / 0.275898 (0.093461) | 0.422571 / 0.323480 (0.099091) | 0.004941 / 0.007986 (-0.003044) | 0.006103 / 0.004328 (0.001774) | 0.075828 / 0.004250 (0.071578) | 0.065795 / 0.037052 (0.028743) | 0.412835 / 0.258489 (0.154346) | 0.430062 / 0.293841 (0.136221) | 0.045806 / 0.128546 (-0.082741) | 0.013760 / 0.075646 (-0.061887) | 0.351542 / 0.419271 (-0.067729) | 0.064836 / 0.043533 (0.021304) | 0.370162 / 0.255139 (0.115023) | 0.434949 / 0.283200 (0.151749) | 0.039198 / 0.141683 (-0.102485) | 1.670940 / 1.452155 (0.218785) | 1.809677 / 1.492716 (0.316961) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.295104 / 0.018006 (0.277097) | 0.594584 / 0.000490 (0.594095) | 0.010923 / 0.000200 (0.010723) | 0.000479 / 0.000054 (0.000425) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029174 / 0.037411 (-0.008237) | 0.094637 / 0.014526 (0.080111) | 0.102948 / 0.176557 (-0.073608) | 0.171048 / 0.737135 (-0.566087) | 0.111465 / 0.296338 (-0.184873) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.582017 / 0.215209 (0.366808) | 5.727008 / 2.077655 (3.649354) | 2.563211 / 1.504120 (1.059091) | 2.308912 / 1.541195 (0.767717) | 2.301258 / 1.468490 (0.832768) | 0.819594 / 4.584777 (-3.765183) | 5.177536 / 3.745712 (1.431824) | 4.473602 / 5.269862 (-0.796260) | 2.743819 / 4.565676 (-1.821857) | 0.090052 / 0.424275 (-0.334223) | 0.007903 / 0.007607 (0.000295) | 0.679142 / 0.226044 (0.453097) | 6.887891 / 2.268929 (4.618962) | 3.337926 / 55.444624 (-52.106699) | 2.659228 / 6.876477 (-4.217249) | 2.641289 / 2.142072 (0.499216) | 0.974829 / 4.805227 (-3.830398) | 0.205775 / 6.500664 (-6.294890) | 0.075268 / 0.075469 (-0.000201) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.500562 / 1.841788 (-0.341226) | 22.688483 / 8.074308 (14.614175) | 19.634878 / 10.191392 (9.443486) | 0.227409 / 0.680424 (-0.453015) | 0.029794 / 0.534201 (-0.504407) | 0.475204 / 0.579283 (-0.104079) | 0.579379 / 0.434364 (0.145016) | 0.541244 / 0.540337 (0.000907) | 0.739187 / 1.386936 (-0.647749) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008641 / 0.011353 (-0.002712) | 0.006139 / 0.011008 (-0.004870) | 0.075048 / 0.038508 (0.036540) | 0.074070 / 0.023109 (0.050961) | 0.508288 / 0.275898 (0.232390) | 0.539770 / 0.323480 (0.216290) | 0.006092 / 0.007986 (-0.001894) | 0.003748 / 0.004328 (-0.000581) | 0.077945 / 0.004250 (0.073695) | 0.056989 / 0.037052 (0.019936) | 0.526889 / 0.258489 (0.268400) | 0.560862 / 0.293841 (0.267021) | 0.046507 / 0.128546 (-0.082040) | 0.013249 / 0.075646 (-0.062397) | 0.088363 / 0.419271 (-0.330908) | 0.058776 / 0.043533 (0.015243) | 0.495869 / 0.255139 (0.240730) | 0.538615 / 0.283200 (0.255415) | 0.034055 / 0.141683 (-0.107628) | 1.658713 / 1.452155 (0.206558) | 1.736599 / 1.492716 (0.243883) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.288355 / 0.018006 (0.270349) | 0.571481 / 0.000490 (0.570991) | 0.006765 / 0.000200 (0.006565) | 0.000101 / 0.000054 (0.000047) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031836 / 0.037411 (-0.005575) | 0.101312 / 0.014526 (0.086786) | 0.111433 / 0.176557 (-0.065124) | 0.169599 / 0.737135 (-0.567536) | 0.114595 / 0.296338 (-0.181743) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.645258 / 0.215209 (0.430049) | 6.446653 / 2.077655 (4.368998) | 2.983498 / 1.504120 (1.479379) | 2.573820 / 1.541195 (1.032625) | 2.624286 / 1.468490 (1.155796) | 0.815997 / 4.584777 (-3.768780) | 5.140248 / 3.745712 (1.394536) | 4.636915 / 5.269862 (-0.632947) | 2.866313 / 4.565676 (-1.699364) | 0.096643 / 0.424275 (-0.327633) | 0.008452 / 0.007607 (0.000845) | 0.765837 / 0.226044 (0.539793) | 7.622897 / 2.268929 (5.353968) | 3.796247 / 55.444624 (-51.648378) | 3.019349 / 6.876477 (-3.857128) | 3.034187 / 2.142072 (0.892115) | 1.001682 / 4.805227 (-3.803546) | 0.211841 / 6.500664 (-6.288823) | 0.073351 / 0.075469 (-0.002119) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.740254 / 1.841788 (-0.101534) | 23.465619 / 8.074308 (15.391311) | 21.651670 / 10.191392 (11.460278) | 0.226129 / 0.680424 (-0.454294) | 0.029611 / 0.534201 (-0.504590) | 0.441140 / 0.579283 (-0.138143) | 0.605591 / 0.434364 (0.171227) | 0.552427 / 0.540337 (0.012090) | 0.771975 / 1.386936 (-0.614961) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ef5751522c424c758df0647ff9a449b8b0404b6a \"CML watermark\")\n", "> The CI errors seem unrelated to this PR but I think they need further investigation in another PR.\r\n> \r\n> ```\r\n> FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_multiple_files - KeyError: 'url'\r\n> ```\r\n\r\nWe need to wait for `huggingface_hub`'s next release to fix this (see https://github.com/huggingface/huggingface_hub/pull/1675; 409 error is currently ignored, hence the `KeyError`)\r\n\r\nAlso, we should be able to fix `test_push_dataset_dict_to_hub_overwrite_files` by inserting `gc.collect()` (to drop the \"reference\" to an Arrow file) between the `load_dataset` calls to avoid the `PermissionError` (also reported in https://github.com/huggingface/datasets/issues/3139)\r\n\r\n(Indeed, this can be addressed in subsequent PRs.)\r\n\r\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008988 / 0.011353 (-0.002365) | 0.005270 / 0.011008 (-0.005738) | 0.114577 / 0.038508 (0.076068) | 0.091630 / 0.023109 (0.068521) | 0.409217 / 0.275898 (0.133319) | 0.440903 / 0.323480 (0.117424) | 0.005226 / 0.007986 (-0.002760) | 0.004289 / 0.004328 (-0.000040) | 0.082246 / 0.004250 (0.077995) | 0.084926 / 0.037052 (0.047873) | 0.407822 / 0.258489 (0.149333) | 0.440891 / 0.293841 (0.147051) | 0.052225 / 0.128546 (-0.076321) | 0.014218 / 0.075646 (-0.061429) | 0.436994 / 0.419271 (0.017722) | 0.066433 / 0.043533 (0.022901) | 0.413909 / 0.255139 (0.158770) | 0.425729 / 0.283200 (0.142530) | 0.039576 / 0.141683 (-0.102107) | 1.905604 / 1.452155 (0.453449) | 1.907032 / 1.492716 (0.414315) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.313662 / 0.018006 (0.295655) | 0.614541 / 0.000490 (0.614051) | 0.015631 / 0.000200 (0.015431) | 0.000507 / 0.000054 (0.000453) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029049 / 0.037411 (-0.008362) | 0.094626 / 0.014526 (0.080100) | 0.104718 / 0.176557 (-0.071838) | 0.187346 / 0.737135 (-0.549790) | 0.108001 / 0.296338 (-0.188337) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.578997 / 0.215209 (0.363788) | 5.815546 / 2.077655 (3.737892) | 2.411301 / 1.504120 (0.907181) | 2.110088 / 1.541195 (0.568893) | 2.147839 / 1.468490 (0.679349) | 0.861285 / 4.584777 (-3.723492) | 5.264245 / 3.745712 (1.518533) | 4.695786 / 5.269862 (-0.574076) | 2.867522 / 4.565676 (-1.698154) | 0.096523 / 0.424275 (-0.327752) | 0.008777 / 0.007607 (0.001170) | 0.716316 / 0.226044 (0.490272) | 7.257574 / 2.268929 (4.988645) | 3.141502 / 55.444624 (-52.303123) | 2.480604 / 6.876477 (-4.395872) | 2.530031 / 2.142072 (0.387958) | 1.054274 / 4.805227 (-3.750953) | 0.210781 / 6.500664 (-6.289883) | 0.073837 / 0.075469 (-0.001632) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.607689 / 1.841788 (-0.234099) | 23.856780 / 8.074308 (15.782472) | 19.507196 / 10.191392 (9.315804) | 0.232712 / 0.680424 (-0.447712) | 0.027037 / 0.534201 (-0.507164) | 0.466613 / 0.579283 (-0.112670) | 0.571139 / 0.434364 (0.136775) | 0.543109 / 0.540337 (0.002771) | 0.785558 / 1.386936 (-0.601378) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008104 / 0.011353 (-0.003249) | 0.004923 / 0.011008 (-0.006086) | 0.075093 / 0.038508 (0.036585) | 0.075218 / 0.023109 (0.052109) | 0.476615 / 0.275898 (0.200717) | 0.506984 / 0.323480 (0.183504) | 0.006371 / 0.007986 (-0.001614) | 0.004818 / 0.004328 (0.000489) | 0.075634 / 0.004250 (0.071383) | 0.059513 / 0.037052 (0.022461) | 0.523763 / 0.258489 (0.265274) | 0.531858 / 0.293841 (0.238017) | 0.048168 / 0.128546 (-0.080379) | 0.014110 / 0.075646 (-0.061537) | 0.086052 / 0.419271 (-0.333219) | 0.058369 / 0.043533 (0.014836) | 0.475537 / 0.255139 (0.220398) | 0.509429 / 0.283200 (0.226229) | 0.033924 / 0.141683 (-0.107758) | 1.657490 / 1.452155 (0.205336) | 1.762544 / 1.492716 (0.269828) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.263863 / 0.018006 (0.245857) | 0.584468 / 0.000490 (0.583978) | 0.007063 / 0.000200 (0.006863) | 0.000181 / 0.000054 (0.000126) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032229 / 0.037411 (-0.005183) | 0.096750 / 0.014526 (0.082224) | 0.117798 / 0.176557 (-0.058758) | 0.173376 / 0.737135 (-0.563760) | 0.117241 / 0.296338 (-0.179098) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.701935 / 0.215209 (0.486726) | 6.544655 / 2.077655 (4.467001) | 3.055531 / 1.504120 (1.551411) | 2.896339 / 1.541195 (1.355144) | 3.013157 / 1.468490 (1.544667) | 0.852989 / 4.584777 (-3.731788) | 5.399355 / 3.745712 (1.653643) | 5.119811 / 5.269862 (-0.150051) | 3.167269 / 4.565676 (-1.398407) | 0.096962 / 0.424275 (-0.327313) | 0.008843 / 0.007607 (0.001236) | 0.776170 / 0.226044 (0.550125) | 7.735093 / 2.268929 (5.466164) | 3.792629 / 55.444624 (-51.651996) | 3.249911 / 6.876477 (-3.626565) | 3.235590 / 2.142072 (1.093517) | 1.046426 / 4.805227 (-3.758801) | 0.239854 / 6.500664 (-6.260810) | 0.100648 / 0.075469 (0.025179) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.774488 / 1.841788 (-0.067300) | 25.646958 / 8.074308 (17.572650) | 23.181577 / 10.191392 (12.990185) | 0.231948 / 0.680424 (-0.448476) | 0.030147 / 0.534201 (-0.504054) | 0.464161 / 0.579283 (-0.115122) | 0.598980 / 0.434364 (0.164616) | 0.571156 / 0.540337 (0.030819) | 0.833221 / 1.386936 (-0.553715) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ad876e8908188dcd56759a35c4da182bf121535a \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006010 / 0.011353 (-0.005343) | 0.003662 / 0.011008 (-0.007346) | 0.079971 / 0.038508 (0.041463) | 0.066790 / 0.023109 (0.043681) | 0.311387 / 0.275898 (0.035489) | 0.346781 / 0.323480 (0.023301) | 0.003500 / 0.007986 (-0.004485) | 0.002831 / 0.004328 (-0.001498) | 0.063238 / 0.004250 (0.058988) | 0.056163 / 0.037052 (0.019110) | 0.317456 / 0.258489 (0.058967) | 0.356106 / 0.293841 (0.062265) | 0.027358 / 0.128546 (-0.101188) | 0.007906 / 0.075646 (-0.067741) | 0.261779 / 0.419271 (-0.157492) | 0.046385 / 0.043533 (0.002852) | 0.312587 / 0.255139 (0.057448) | 0.339513 / 0.283200 (0.056314) | 0.021474 / 0.141683 (-0.120209) | 1.418637 / 1.452155 (-0.033518) | 1.510257 / 1.492716 (0.017540) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.211761 / 0.018006 (0.193755) | 0.424387 / 0.000490 (0.423898) | 0.002579 / 0.000200 (0.002379) | 0.000065 / 0.000054 (0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024038 / 0.037411 (-0.013374) | 0.072524 / 0.014526 (0.057998) | 0.083443 / 0.176557 (-0.093113) | 0.144835 / 0.737135 (-0.592300) | 0.084754 / 0.296338 (-0.211585) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.392423 / 0.215209 (0.177214) | 3.927220 / 2.077655 (1.849565) | 1.877853 / 1.504120 (0.373733) | 1.699275 / 1.541195 (0.158081) | 1.793144 / 1.468490 (0.324654) | 0.503809 / 4.584777 (-4.080968) | 3.052569 / 3.745712 (-0.693143) | 2.907432 / 5.269862 (-2.362429) | 1.811220 / 4.565676 (-2.754457) | 0.057249 / 0.424275 (-0.367026) | 0.006433 / 0.007607 (-0.001174) | 0.463257 / 0.226044 (0.237213) | 4.631038 / 2.268929 (2.362109) | 2.315870 / 55.444624 (-53.128754) | 2.000476 / 6.876477 (-4.876001) | 2.043581 / 2.142072 (-0.098492) | 0.588911 / 4.805227 (-4.216317) | 0.125370 / 6.500664 (-6.375295) | 0.061721 / 0.075469 (-0.013748) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.244486 / 1.841788 (-0.597301) | 17.862422 / 8.074308 (9.788114) | 13.890205 / 10.191392 (3.698813) | 0.145467 / 0.680424 (-0.534957) | 0.016856 / 0.534201 (-0.517345) | 0.329357 / 0.579283 (-0.249926) | 0.367550 / 0.434364 (-0.066814) | 0.377541 / 0.540337 (-0.162796) | 0.534087 / 1.386936 (-0.852849) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006030 / 0.011353 (-0.005323) | 0.003650 / 0.011008 (-0.007359) | 0.063300 / 0.038508 (0.024792) | 0.058877 / 0.023109 (0.035767) | 0.454662 / 0.275898 (0.178764) | 0.489362 / 0.323480 (0.165882) | 0.004856 / 0.007986 (-0.003130) | 0.002909 / 0.004328 (-0.001420) | 0.063356 / 0.004250 (0.059105) | 0.047867 / 0.037052 (0.010814) | 0.465461 / 0.258489 (0.206972) | 0.506684 / 0.293841 (0.212843) | 0.028599 / 0.128546 (-0.099947) | 0.008076 / 0.075646 (-0.067570) | 0.068695 / 0.419271 (-0.350576) | 0.041487 / 0.043533 (-0.002045) | 0.448676 / 0.255139 (0.193537) | 0.471206 / 0.283200 (0.188007) | 0.020401 / 0.141683 (-0.121282) | 1.461181 / 1.452155 (0.009026) | 1.517079 / 1.492716 (0.024363) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.222827 / 0.018006 (0.204821) | 0.425074 / 0.000490 (0.424585) | 0.004153 / 0.000200 (0.003953) | 0.000081 / 0.000054 (0.000026) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026980 / 0.037411 (-0.010431) | 0.080786 / 0.014526 (0.066260) | 0.092040 / 0.176557 (-0.084517) | 0.146082 / 0.737135 (-0.591053) | 0.092739 / 0.296338 (-0.203600) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.461663 / 0.215209 (0.246454) | 4.604828 / 2.077655 (2.527173) | 2.566926 / 1.504120 (1.062806) | 2.394419 / 1.541195 (0.853224) | 2.458375 / 1.468490 (0.989885) | 0.505140 / 4.584777 (-4.079637) | 3.155916 / 3.745712 (-0.589796) | 3.014474 / 5.269862 (-2.255388) | 1.900296 / 4.565676 (-2.665380) | 0.058063 / 0.424275 (-0.366212) | 0.006409 / 0.007607 (-0.001198) | 0.541165 / 0.226044 (0.315120) | 5.410700 / 2.268929 (3.141772) | 3.010239 / 55.444624 (-52.434386) | 2.668103 / 6.876477 (-4.208373) | 2.730418 / 2.142072 (0.588346) | 0.603471 / 4.805227 (-4.201756) | 0.129852 / 6.500664 (-6.370812) | 0.061507 / 0.075469 (-0.013962) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.355272 / 1.841788 (-0.486516) | 18.170088 / 8.074308 (10.095780) | 15.583855 / 10.191392 (5.392463) | 0.146246 / 0.680424 (-0.534178) | 0.018093 / 0.534201 (-0.516108) | 0.331695 / 0.579283 (-0.247588) | 0.380845 / 0.434364 (-0.053519) | 0.388564 / 0.540337 (-0.151774) | 0.551465 / 1.386936 (-0.835471) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#afc3c2b034481a3502f5476186a110cf8613a248 \"CML watermark\")\n" ]

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[ "I believe is due to the fact that doesn't work with .tgz files.", "`JourneyDB/JourneyDB` is a gated dataset, so this error means you are not authenticated to access it, either by using an invalid token or by not agreeing to the terms in the dialog on the dataset page.\r\n\r\n> I believe is due to the fact that doesn't work with .tgz files.\r\n\r\nIndeed, the dataset's data files structure is not supported natively by `datasets`. To load it, one option is to clone the repo (or download it with `huggingface_hub.snapshot_download`) and use `Dataset.from_generator` to process the files.", "> JourneyDB/JourneyDB is a gated dataset, so this error means you are not authenticated to access it, either by using an invalid token or by not agreeing to the terms in the dialog on the dataset page.´\r\n\r\nI did authentication with:\r\n\r\n```\r\nfrom huggingface_hub import notebook_login\r\nnotebook_login()\r\n```\r\n\r\nIsn't that the correct way to do it?\r\n\r\n> Indeed, the dataset's data files structure is not supported natively by datasets. To load it, one option is to clone the repo (or download it with huggingface_hub.snapshot_download) and use Dataset.from_generator to process the files.\r\n\r\nGreat suggestion I will give it a try.", "Have you accepted the terms in the dialog [here](https://huggingface.co/datasets/JourneyDB/JourneyDB)?\r\n\r\nIIRC Kaggle preinstalls an outdated `datasets` version, so it's also a good idea to update it before importing `datasets` (and do the same for `huggingface_hub`)", "Sorry for the late reply. Yes, I did. Thanks for the tip!" ]

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[ "Hi! Unfortunately, the current behavior is to delete the downloaded data when this error happens. So, I've opened a PR that removes the problematic import to avoid losing data due to `apache_beam` not being installed (we host the preprocessed version of `natual_questions` on the HF GCS, so requiring `apache_beam` in that case doesn't make sense)", "Thanks for your reply. I met another question that I set `export HF_DATASETS_CACHE=/data/lxy/.cache` , but each time I run load_datasets, the datasets module still looking for NQ in the wrong default cache dir '/home/lxy/.cache' 。How to avoid this incorrect behavior. I am sure HF_DATASETS_CACHE was set correctly since I use echo & to check it.\r\n\r\nby the way I delete the file in '/home/lxy/.cache' since I found there has some kb size file seems useless.", "You need to set this variable before the `datasets` import. Then, you can use `import datasets; datasets.config.HF_DATASETS_CACHE` to verify the cache location." ]

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[ "Thanks for reporting this issue! We should be able to avoid this by making our `glob` patterns more precise. In the meantime, you can load the dataset by directly assigning splits to the data files: \r\n```python\r\nfrom datasets import load_dataset\r\nds = load_dataset(\"parquet\", data_files={\"train\": \"testing123/train/output_train.parquet\", \"validation\": \"testing123/val/output_val.parquet\"})\r\n```" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006131 / 0.011353 (-0.005222) | 0.003682 / 0.011008 (-0.007327) | 0.081108 / 0.038508 (0.042600) | 0.061580 / 0.023109 (0.038471) | 0.395880 / 0.275898 (0.119982) | 0.427429 / 0.323480 (0.103949) | 0.003570 / 0.007986 (-0.004416) | 0.003874 / 0.004328 (-0.000455) | 0.063322 / 0.004250 (0.059072) | 0.049742 / 0.037052 (0.012690) | 0.396547 / 0.258489 (0.138058) | 0.434759 / 0.293841 (0.140918) | 0.028137 / 0.128546 (-0.100409) | 0.008103 / 0.075646 (-0.067544) | 0.262504 / 0.419271 (-0.156767) | 0.045944 / 0.043533 (0.002411) | 0.397659 / 0.255139 (0.142520) | 0.416479 / 0.283200 (0.133280) | 0.022870 / 0.141683 (-0.118813) | 1.478280 / 1.452155 (0.026126) | 1.543748 / 1.492716 (0.051031) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228851 / 0.018006 (0.210845) | 0.432845 / 0.000490 (0.432355) | 0.005922 / 0.000200 (0.005722) | 0.000227 / 0.000054 (0.000172) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025545 / 0.037411 (-0.011867) | 0.073506 / 0.014526 (0.058980) | 0.087622 / 0.176557 (-0.088935) | 0.145455 / 0.737135 (-0.591680) | 0.085236 / 0.296338 (-0.211102) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.433083 / 0.215209 (0.217874) | 4.323121 / 2.077655 (2.245466) | 2.297947 / 1.504120 (0.793827) | 2.126405 / 1.541195 (0.585211) | 2.201635 / 1.468490 (0.733145) | 0.509902 / 4.584777 (-4.074875) | 3.116877 / 3.745712 (-0.628835) | 2.892949 / 5.269862 (-2.376912) | 1.866833 / 4.565676 (-2.698844) | 0.058087 / 0.424275 (-0.366189) | 0.006464 / 0.007607 (-0.001143) | 0.503594 / 0.226044 (0.277550) | 5.027634 / 2.268929 (2.758705) | 2.718030 / 55.444624 (-52.726595) | 2.373876 / 6.876477 (-4.502600) | 2.515496 / 2.142072 (0.373423) | 0.602648 / 4.805227 (-4.202579) | 0.126119 / 6.500664 (-6.374545) | 0.060623 / 0.075469 (-0.014846) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.236429 / 1.841788 (-0.605359) | 17.760532 / 8.074308 (9.686224) | 13.970093 / 10.191392 (3.778701) | 0.145455 / 0.680424 (-0.534969) | 0.017110 / 0.534201 (-0.517091) | 0.329649 / 0.579283 (-0.249634) | 0.366942 / 0.434364 (-0.067421) | 0.384418 / 0.540337 (-0.155920) | 0.552330 / 1.386936 (-0.834606) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006302 / 0.011353 (-0.005051) | 0.003677 / 0.011008 (-0.007331) | 0.062836 / 0.038508 (0.024328) | 0.063317 / 0.023109 (0.040207) | 0.449970 / 0.275898 (0.174072) | 0.480903 / 0.323480 (0.157423) | 0.005013 / 0.007986 (-0.002972) | 0.002934 / 0.004328 (-0.001394) | 0.062975 / 0.004250 (0.058724) | 0.051285 / 0.037052 (0.014233) | 0.448417 / 0.258489 (0.189928) | 0.486022 / 0.293841 (0.192181) | 0.029215 / 0.128546 (-0.099332) | 0.008189 / 0.075646 (-0.067457) | 0.068203 / 0.419271 (-0.351068) | 0.041942 / 0.043533 (-0.001591) | 0.445749 / 0.255139 (0.190610) | 0.465442 / 0.283200 (0.182243) | 0.020681 / 0.141683 (-0.121002) | 1.500704 / 1.452155 (0.048549) | 1.550511 / 1.492716 (0.057795) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224922 / 0.018006 (0.206915) | 0.419714 / 0.000490 (0.419224) | 0.003804 / 0.000200 (0.003604) | 0.000082 / 0.000054 (0.000028) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026924 / 0.037411 (-0.010487) | 0.082400 / 0.014526 (0.067874) | 0.092193 / 0.176557 (-0.084363) | 0.147045 / 0.737135 (-0.590090) | 0.093173 / 0.296338 (-0.203166) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.462510 / 0.215209 (0.247300) | 4.635249 / 2.077655 (2.557594) | 2.627127 / 1.504120 (1.123007) | 2.442879 / 1.541195 (0.901684) | 2.502456 / 1.468490 (1.033966) | 0.506607 / 4.584777 (-4.078170) | 3.127348 / 3.745712 (-0.618364) | 2.901818 / 5.269862 (-2.368044) | 1.906876 / 4.565676 (-2.658801) | 0.058025 / 0.424275 (-0.366250) | 0.006442 / 0.007607 (-0.001165) | 0.534438 / 0.226044 (0.308394) | 5.352481 / 2.268929 (3.083553) | 3.058068 / 55.444624 (-52.386556) | 2.697310 / 6.876477 (-4.179167) | 2.873141 / 2.142072 (0.731069) | 0.594517 / 4.805227 (-4.210710) | 0.125369 / 6.500664 (-6.375295) | 0.061411 / 0.075469 (-0.014058) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.369549 / 1.841788 (-0.472238) | 17.933507 / 8.074308 (9.859199) | 14.890107 / 10.191392 (4.698715) | 0.154398 / 0.680424 (-0.526026) | 0.018021 / 0.534201 (-0.516180) | 0.335163 / 0.579283 (-0.244120) | 0.350396 / 0.434364 (-0.083968) | 0.397694 / 0.540337 (-0.142643) | 0.554853 / 1.386936 (-0.832083) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f56fd9d6c877ffa6fb44fb832c13b61227c9cc5b \"CML watermark\")\n" ]

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[ "how is your dataset structured? (file types, how many commits and files are you trying to push, etc)", "I succeeded in uploading it after several attempts with an hour gap between each attempt (inconvenient but worked). The final dataset is [here](https://huggingface.co/datasets/yuvalkirstain/pickapic_v2), code and context to the dataset can be found [here](https://github.com/yuvalkirstain/PickScore/).\r\nI can close the issue if this behavior is intended, as most users probably do not need to upload large-scale datasets.", "We could fix this by creating a single commit for all the (Parquet) shards in `push_to_hub` instead of one commit per shard, as we currently do. \r\n\r\n@Wauplin Any updates on the 2-step commit process suggested by you that we need to implement this?", "> Any updates on the 2-step commit process suggested by you that we need to implement this?\r\n\r\nRe-prioritizing this, sorry. Will let you know but probably can be done this week." ]

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[ "Can you share the error message?\r\n\r\nAlso, it would help if you could check whether `huggingface_hub`'s download behaves the same:\r\n```python\r\nfrom huggingface_hub import snapshot_download\r\nsnapshot_download(\"trec\", repo_type=\"dataset\", cache_dir='/path/to/my/dir)\r\n```\r\n\r\nIn the next major release, we aim to switch to `huggingface_hub` for file download/caching, but we could align the `cache_dir`'s `umask` behavior earlier than this if their solution works for your use case." ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005905 / 0.011353 (-0.005448) | 0.003623 / 0.011008 (-0.007385) | 0.079616 / 0.038508 (0.041108) | 0.059840 / 0.023109 (0.036730) | 0.392281 / 0.275898 (0.116383) | 0.434539 / 0.323480 (0.111059) | 0.004746 / 0.007986 (-0.003239) | 0.002935 / 0.004328 (-0.001394) | 0.062907 / 0.004250 (0.058657) | 0.048233 / 0.037052 (0.011181) | 0.394170 / 0.258489 (0.135681) | 0.427430 / 0.293841 (0.133589) | 0.027382 / 0.128546 (-0.101164) | 0.007890 / 0.075646 (-0.067756) | 0.259681 / 0.419271 (-0.159591) | 0.044085 / 0.043533 (0.000552) | 0.388640 / 0.255139 (0.133501) | 0.412665 / 0.283200 (0.129465) | 0.021256 / 0.141683 (-0.120427) | 1.485672 / 1.452155 (0.033518) | 1.531410 / 1.492716 (0.038694) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.220346 / 0.018006 (0.202340) | 0.425329 / 0.000490 (0.424840) | 0.006224 / 0.000200 (0.006024) | 0.000208 / 0.000054 (0.000153) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024864 / 0.037411 (-0.012547) | 0.072925 / 0.014526 (0.058399) | 0.083711 / 0.176557 (-0.092845) | 0.144213 / 0.737135 (-0.592923) | 0.084201 / 0.296338 (-0.212137) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.399467 / 0.215209 (0.184258) | 3.978979 / 2.077655 (1.901325) | 1.916994 / 1.504120 (0.412874) | 1.753098 / 1.541195 (0.211903) | 1.809866 / 1.468490 (0.341376) | 0.506806 / 4.584777 (-4.077971) | 3.051044 / 3.745712 (-0.694668) | 2.857624 / 5.269862 (-2.412237) | 1.872033 / 4.565676 (-2.693644) | 0.058543 / 0.424275 (-0.365732) | 0.006569 / 0.007607 (-0.001038) | 0.472630 / 0.226044 (0.246586) | 4.724862 / 2.268929 (2.455934) | 2.413068 / 55.444624 (-53.031556) | 2.046910 / 6.876477 (-4.829567) | 2.190455 / 2.142072 (0.048383) | 0.595228 / 4.805227 (-4.210000) | 0.125942 / 6.500664 (-6.374722) | 0.059474 / 0.075469 (-0.015995) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.235927 / 1.841788 (-0.605861) | 17.367803 / 8.074308 (9.293495) | 13.550362 / 10.191392 (3.358970) | 0.131664 / 0.680424 (-0.548760) | 0.016331 / 0.534201 (-0.517870) | 0.331295 / 0.579283 (-0.247988) | 0.367641 / 0.434364 (-0.066723) | 0.382595 / 0.540337 (-0.157742) | 0.540361 / 1.386936 (-0.846575) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006120 / 0.011353 (-0.005233) | 0.003691 / 0.011008 (-0.007318) | 0.062768 / 0.038508 (0.024259) | 0.058045 / 0.023109 (0.034936) | 0.443616 / 0.275898 (0.167718) | 0.473854 / 0.323480 (0.150374) | 0.004710 / 0.007986 (-0.003275) | 0.002915 / 0.004328 (-0.001414) | 0.062922 / 0.004250 (0.058672) | 0.048557 / 0.037052 (0.011505) | 0.446136 / 0.258489 (0.187647) | 0.479235 / 0.293841 (0.185394) | 0.028704 / 0.128546 (-0.099842) | 0.008170 / 0.075646 (-0.067477) | 0.068853 / 0.419271 (-0.350419) | 0.041393 / 0.043533 (-0.002140) | 0.444683 / 0.255139 (0.189544) | 0.466607 / 0.283200 (0.183407) | 0.020890 / 0.141683 (-0.120793) | 1.473745 / 1.452155 (0.021590) | 1.498772 / 1.492716 (0.006055) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.216875 / 0.018006 (0.198868) | 0.411700 / 0.000490 (0.411211) | 0.003337 / 0.000200 (0.003137) | 0.000079 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027054 / 0.037411 (-0.010357) | 0.080617 / 0.014526 (0.066092) | 0.091052 / 0.176557 (-0.085505) | 0.144126 / 0.737135 (-0.593009) | 0.090123 / 0.296338 (-0.206216) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.461132 / 0.215209 (0.245922) | 4.598662 / 2.077655 (2.521008) | 2.539213 / 1.504120 (1.035093) | 2.362782 / 1.541195 (0.821587) | 2.428648 / 1.468490 (0.960157) | 0.506305 / 4.584777 (-4.078472) | 3.091132 / 3.745712 (-0.654581) | 2.884870 / 5.269862 (-2.384992) | 1.880806 / 4.565676 (-2.684870) | 0.058727 / 0.424275 (-0.365548) | 0.006452 / 0.007607 (-0.001155) | 0.533519 / 0.226044 (0.307474) | 5.346406 / 2.268929 (3.077478) | 2.987920 / 55.444624 (-52.456704) | 2.667591 / 6.876477 (-4.208885) | 2.848696 / 2.142072 (0.706623) | 0.601018 / 4.805227 (-4.204209) | 0.124929 / 6.500664 (-6.375735) | 0.061583 / 0.075469 (-0.013886) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.356825 / 1.841788 (-0.484962) | 17.964503 / 8.074308 (9.890195) | 14.691471 / 10.191392 (4.500079) | 0.132525 / 0.680424 (-0.547899) | 0.018061 / 0.534201 (-0.516140) | 0.335459 / 0.579283 (-0.243824) | 0.378260 / 0.434364 (-0.056104) | 0.390681 / 0.540337 (-0.149657) | 0.547030 / 1.386936 (-0.839906) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8c55213a6c5fcff9b3dacce491caa68eacebe10d \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006624 / 0.011353 (-0.004729) | 0.004039 / 0.011008 (-0.006970) | 0.085862 / 0.038508 (0.047354) | 0.077183 / 0.023109 (0.054074) | 0.319132 / 0.275898 (0.043234) | 0.350818 / 0.323480 (0.027338) | 0.004122 / 0.007986 (-0.003864) | 0.003395 / 0.004328 (-0.000934) | 0.065237 / 0.004250 (0.060987) | 0.056675 / 0.037052 (0.019623) | 0.321040 / 0.258489 (0.062551) | 0.362011 / 0.293841 (0.068170) | 0.030988 / 0.128546 (-0.097559) | 0.008623 / 0.075646 (-0.067023) | 0.289433 / 0.419271 (-0.129839) | 0.052755 / 0.043533 (0.009222) | 0.323291 / 0.255139 (0.068152) | 0.340110 / 0.283200 (0.056911) | 0.026299 / 0.141683 (-0.115383) | 1.509405 / 1.452155 (0.057250) | 1.559993 / 1.492716 (0.067277) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.233285 / 0.018006 (0.215279) | 0.451633 / 0.000490 (0.451143) | 0.009954 / 0.000200 (0.009754) | 0.000098 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029623 / 0.037411 (-0.007788) | 0.083942 / 0.014526 (0.069416) | 0.097378 / 0.176557 (-0.079178) | 0.152630 / 0.737135 (-0.584506) | 0.098379 / 0.296338 (-0.197959) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.386237 / 0.215209 (0.171028) | 3.850805 / 2.077655 (1.773150) | 1.896032 / 1.504120 (0.391912) | 1.729746 / 1.541195 (0.188551) | 1.867831 / 1.468490 (0.399341) | 0.481496 / 4.584777 (-4.103281) | 3.564432 / 3.745712 (-0.181280) | 3.336084 / 5.269862 (-1.933777) | 2.040944 / 4.565676 (-2.524732) | 0.057247 / 0.424275 (-0.367028) | 0.007275 / 0.007607 (-0.000332) | 0.464600 / 0.226044 (0.238556) | 4.648562 / 2.268929 (2.379634) | 2.394430 / 55.444624 (-53.050195) | 2.029748 / 6.876477 (-4.846728) | 2.280975 / 2.142072 (0.138902) | 0.619073 / 4.805227 (-4.186154) | 0.150504 / 6.500664 (-6.350160) | 0.061206 / 0.075469 (-0.014263) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.267309 / 1.841788 (-0.574479) | 19.062725 / 8.074308 (10.988417) | 14.192565 / 10.191392 (4.001173) | 0.162908 / 0.680424 (-0.517515) | 0.018445 / 0.534201 (-0.515756) | 0.392110 / 0.579283 (-0.187173) | 0.415340 / 0.434364 (-0.019024) | 0.456783 / 0.540337 (-0.083554) | 0.653019 / 1.386936 (-0.733917) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006995 / 0.011353 (-0.004358) | 0.004027 / 0.011008 (-0.006981) | 0.064124 / 0.038508 (0.025616) | 0.076004 / 0.023109 (0.052895) | 0.401760 / 0.275898 (0.125862) | 0.432339 / 0.323480 (0.108859) | 0.005471 / 0.007986 (-0.002515) | 0.003335 / 0.004328 (-0.000993) | 0.064164 / 0.004250 (0.059913) | 0.058101 / 0.037052 (0.021048) | 0.401698 / 0.258489 (0.143209) | 0.436033 / 0.293841 (0.142192) | 0.032789 / 0.128546 (-0.095757) | 0.008482 / 0.075646 (-0.067165) | 0.070707 / 0.419271 (-0.348565) | 0.048287 / 0.043533 (0.004755) | 0.395501 / 0.255139 (0.140362) | 0.419385 / 0.283200 (0.136186) | 0.024043 / 0.141683 (-0.117640) | 1.503310 / 1.452155 (0.051156) | 1.562160 / 1.492716 (0.069444) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227629 / 0.018006 (0.209623) | 0.457306 / 0.000490 (0.456816) | 0.005835 / 0.000200 (0.005635) | 0.000109 / 0.000054 (0.000054) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032991 / 0.037411 (-0.004420) | 0.093265 / 0.014526 (0.078739) | 0.106595 / 0.176557 (-0.069961) | 0.158557 / 0.737135 (-0.578578) | 0.106805 / 0.296338 (-0.189533) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436573 / 0.215209 (0.221364) | 4.355777 / 2.077655 (2.278122) | 2.323151 / 1.504120 (0.819031) | 2.164101 / 1.541195 (0.622906) | 2.252808 / 1.468490 (0.784318) | 0.494902 / 4.584777 (-4.089875) | 3.615073 / 3.745712 (-0.130639) | 3.329738 / 5.269862 (-1.940124) | 2.059137 / 4.565676 (-2.506539) | 0.058384 / 0.424275 (-0.365891) | 0.007330 / 0.007607 (-0.000277) | 0.512326 / 0.226044 (0.286281) | 5.125652 / 2.268929 (2.856724) | 2.861981 / 55.444624 (-52.582644) | 2.500172 / 6.876477 (-4.376305) | 2.715862 / 2.142072 (0.573789) | 0.597299 / 4.805227 (-4.207928) | 0.134346 / 6.500664 (-6.366318) | 0.060396 / 0.075469 (-0.015074) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.353771 / 1.841788 (-0.488017) | 19.334801 / 8.074308 (11.260493) | 14.669875 / 10.191392 (4.478483) | 0.167607 / 0.680424 (-0.512817) | 0.019839 / 0.534201 (-0.514362) | 0.395473 / 0.579283 (-0.183810) | 0.419822 / 0.434364 (-0.014542) | 0.471400 / 0.540337 (-0.068938) | 0.648297 / 1.386936 (-0.738639) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d5a112e7f1ce1635725773d911c825adca7bcfe0 \"CML watermark\")\n", "@mariosasko let me know what you think or if you have better ideas to make it faster", "Yea lazy data files resolution seems a better approach actually" ]

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[ "Answered on the forum: https://discuss.huggingface.co/t/dataset-from-generator-cost-much-more-time-in-vscode-debugging-mode-then-running-mode/56005/2" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006591 / 0.011353 (-0.004762) | 0.003991 / 0.011008 (-0.007017) | 0.085197 / 0.038508 (0.046689) | 0.080312 / 0.023109 (0.057202) | 0.342026 / 0.275898 (0.066128) | 0.370749 / 0.323480 (0.047269) | 0.004124 / 0.007986 (-0.003861) | 0.003413 / 0.004328 (-0.000916) | 0.064363 / 0.004250 (0.060113) | 0.055920 / 0.037052 (0.018868) | 0.340667 / 0.258489 (0.082178) | 0.380138 / 0.293841 (0.086297) | 0.031115 / 0.128546 (-0.097431) | 0.008511 / 0.075646 (-0.067135) | 0.289065 / 0.419271 (-0.130207) | 0.052266 / 0.043533 (0.008734) | 0.343808 / 0.255139 (0.088669) | 0.353578 / 0.283200 (0.070378) | 0.024006 / 0.141683 (-0.117676) | 1.490322 / 1.452155 (0.038168) | 1.591133 / 1.492716 (0.098417) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.234718 / 0.018006 (0.216712) | 0.447023 / 0.000490 (0.446533) | 0.009343 / 0.000200 (0.009143) | 0.000259 / 0.000054 (0.000204) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030466 / 0.037411 (-0.006945) | 0.083367 / 0.014526 (0.068841) | 0.100532 / 0.176557 (-0.076024) | 0.158018 / 0.737135 (-0.579117) | 0.098280 / 0.296338 (-0.198059) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.408501 / 0.215209 (0.193292) | 4.066937 / 2.077655 (1.989282) | 2.034029 / 1.504120 (0.529909) | 1.842982 / 1.541195 (0.301788) | 1.987319 / 1.468490 (0.518829) | 0.492126 / 4.584777 (-4.092651) | 3.554027 / 3.745712 (-0.191685) | 3.289023 / 5.269862 (-1.980839) | 2.069796 / 4.565676 (-2.495880) | 0.057930 / 0.424275 (-0.366346) | 0.007308 / 0.007607 (-0.000299) | 0.482596 / 0.226044 (0.256552) | 4.830714 / 2.268929 (2.561785) | 2.506787 / 55.444624 (-52.937838) | 2.163498 / 6.876477 (-4.712979) | 2.389135 / 2.142072 (0.247062) | 0.597538 / 4.805227 (-4.207689) | 0.134268 / 6.500664 (-6.366396) | 0.061189 / 0.075469 (-0.014280) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.245328 / 1.841788 (-0.596460) | 19.145151 / 8.074308 (11.070843) | 14.742121 / 10.191392 (4.550729) | 0.144749 / 0.680424 (-0.535675) | 0.018433 / 0.534201 (-0.515768) | 0.391867 / 0.579283 (-0.187416) | 0.416555 / 0.434364 (-0.017809) | 0.454341 / 0.540337 (-0.085997) | 0.646833 / 1.386936 (-0.740103) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006669 / 0.011353 (-0.004684) | 0.004031 / 0.011008 (-0.006978) | 0.064347 / 0.038508 (0.025839) | 0.076857 / 0.023109 (0.053748) | 0.415864 / 0.275898 (0.139966) | 0.468615 / 0.323480 (0.145135) | 0.005383 / 0.007986 (-0.002603) | 0.003314 / 0.004328 (-0.001015) | 0.064829 / 0.004250 (0.060578) | 0.057182 / 0.037052 (0.020129) | 0.417055 / 0.258489 (0.158566) | 0.472725 / 0.293841 (0.178884) | 0.031938 / 0.128546 (-0.096608) | 0.008564 / 0.075646 (-0.067082) | 0.070649 / 0.419271 (-0.348623) | 0.047439 / 0.043533 (0.003906) | 0.409589 / 0.255139 (0.154450) | 0.433700 / 0.283200 (0.150500) | 0.024132 / 0.141683 (-0.117551) | 1.500825 / 1.452155 (0.048670) | 1.592059 / 1.492716 (0.099343) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.225652 / 0.018006 (0.207646) | 0.444188 / 0.000490 (0.443698) | 0.004581 / 0.000200 (0.004381) | 0.000104 / 0.000054 (0.000050) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033272 / 0.037411 (-0.004139) | 0.096833 / 0.014526 (0.082307) | 0.107134 / 0.176557 (-0.069422) | 0.159299 / 0.737135 (-0.577836) | 0.107533 / 0.296338 (-0.188806) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.429100 / 0.215209 (0.213890) | 4.281051 / 2.077655 (2.203396) | 2.318713 / 1.504120 (0.814593) | 2.165645 / 1.541195 (0.624451) | 2.250224 / 1.468490 (0.781734) | 0.495791 / 4.584777 (-4.088986) | 3.591953 / 3.745712 (-0.153760) | 3.303426 / 5.269862 (-1.966436) | 2.076861 / 4.565676 (-2.488816) | 0.058369 / 0.424275 (-0.365906) | 0.007387 / 0.007607 (-0.000220) | 0.501270 / 0.226044 (0.275225) | 5.014987 / 2.268929 (2.746059) | 2.800951 / 55.444624 (-52.643673) | 2.464316 / 6.876477 (-4.412161) | 2.685259 / 2.142072 (0.543187) | 0.584797 / 4.805227 (-4.220430) | 0.131889 / 6.500664 (-6.368775) | 0.061021 / 0.075469 (-0.014448) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.366982 / 1.841788 (-0.474806) | 19.820376 / 8.074308 (11.746068) | 14.968664 / 10.191392 (4.777272) | 0.165344 / 0.680424 (-0.515080) | 0.019956 / 0.534201 (-0.514245) | 0.395843 / 0.579283 (-0.183441) | 0.420854 / 0.434364 (-0.013510) | 0.465065 / 0.540337 (-0.075272) | 0.651531 / 1.386936 (-0.735405) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#980ca0e13300f5392cd87189d5afd5942927afc7 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005974 / 0.011353 (-0.005379) | 0.003714 / 0.011008 (-0.007294) | 0.080049 / 0.038508 (0.041541) | 0.061233 / 0.023109 (0.038124) | 0.317187 / 0.275898 (0.041289) | 0.352725 / 0.323480 (0.029245) | 0.004867 / 0.007986 (-0.003119) | 0.002953 / 0.004328 (-0.001376) | 0.063156 / 0.004250 (0.058905) | 0.046752 / 0.037052 (0.009700) | 0.320171 / 0.258489 (0.061682) | 0.367572 / 0.293841 (0.073731) | 0.027253 / 0.128546 (-0.101293) | 0.008100 / 0.075646 (-0.067546) | 0.261206 / 0.419271 (-0.158066) | 0.044581 / 0.043533 (0.001048) | 0.331169 / 0.255139 (0.076030) | 0.348719 / 0.283200 (0.065519) | 0.021397 / 0.141683 (-0.120286) | 1.528315 / 1.452155 (0.076160) | 1.533789 / 1.492716 (0.041073) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.233336 / 0.018006 (0.215329) | 0.416866 / 0.000490 (0.416376) | 0.008805 / 0.000200 (0.008605) | 0.000240 / 0.000054 (0.000186) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024754 / 0.037411 (-0.012657) | 0.073311 / 0.014526 (0.058785) | 0.085419 / 0.176557 (-0.091138) | 0.146380 / 0.737135 (-0.590756) | 0.085545 / 0.296338 (-0.210793) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.431426 / 0.215209 (0.216217) | 4.315899 / 2.077655 (2.238244) | 2.232492 / 1.504120 (0.728372) | 2.064174 / 1.541195 (0.522979) | 2.158982 / 1.468490 (0.690492) | 0.499375 / 4.584777 (-4.085402) | 3.093259 / 3.745712 (-0.652454) | 2.848260 / 5.269862 (-2.421601) | 1.853097 / 4.565676 (-2.712579) | 0.057143 / 0.424275 (-0.367132) | 0.006349 / 0.007607 (-0.001258) | 0.507747 / 0.226044 (0.281702) | 5.078872 / 2.268929 (2.809944) | 2.717697 / 55.444624 (-52.726927) | 2.363564 / 6.876477 (-4.512913) | 2.485756 / 2.142072 (0.343684) | 0.595888 / 4.805227 (-4.209340) | 0.127285 / 6.500664 (-6.373379) | 0.060639 / 0.075469 (-0.014830) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.219287 / 1.841788 (-0.622501) | 17.300038 / 8.074308 (9.225730) | 13.747230 / 10.191392 (3.555838) | 0.144841 / 0.680424 (-0.535583) | 0.016587 / 0.534201 (-0.517614) | 0.336891 / 0.579283 (-0.242392) | 0.376128 / 0.434364 (-0.058236) | 0.385749 / 0.540337 (-0.154588) | 0.552218 / 1.386936 (-0.834718) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006477 / 0.011353 (-0.004876) | 0.003709 / 0.011008 (-0.007299) | 0.064708 / 0.038508 (0.026200) | 0.062627 / 0.023109 (0.039518) | 0.444721 / 0.275898 (0.168823) | 0.477825 / 0.323480 (0.154345) | 0.004890 / 0.007986 (-0.003096) | 0.002896 / 0.004328 (-0.001432) | 0.063781 / 0.004250 (0.059530) | 0.050488 / 0.037052 (0.013436) | 0.453466 / 0.258489 (0.194977) | 0.483303 / 0.293841 (0.189462) | 0.028814 / 0.128546 (-0.099732) | 0.008207 / 0.075646 (-0.067440) | 0.070140 / 0.419271 (-0.349131) | 0.041487 / 0.043533 (-0.002045) | 0.454599 / 0.255139 (0.199460) | 0.468374 / 0.283200 (0.185174) | 0.019758 / 0.141683 (-0.121925) | 1.437542 / 1.452155 (-0.014613) | 1.507965 / 1.492716 (0.015249) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223358 / 0.018006 (0.205352) | 0.413824 / 0.000490 (0.413334) | 0.004593 / 0.000200 (0.004393) | 0.000089 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026278 / 0.037411 (-0.011134) | 0.081992 / 0.014526 (0.067466) | 0.089969 / 0.176557 (-0.086587) | 0.143668 / 0.737135 (-0.593467) | 0.091273 / 0.296338 (-0.205066) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.461198 / 0.215209 (0.245989) | 4.615398 / 2.077655 (2.537743) | 2.552291 / 1.504120 (1.048171) | 2.373789 / 1.541195 (0.832595) | 2.431591 / 1.468490 (0.963101) | 0.507683 / 4.584777 (-4.077094) | 3.148771 / 3.745712 (-0.596941) | 2.849118 / 5.269862 (-2.420744) | 1.883001 / 4.565676 (-2.682675) | 0.059423 / 0.424275 (-0.364852) | 0.006463 / 0.007607 (-0.001144) | 0.535129 / 0.226044 (0.309085) | 5.362870 / 2.268929 (3.093941) | 3.016548 / 55.444624 (-52.428076) | 2.666205 / 6.876477 (-4.210271) | 2.821396 / 2.142072 (0.679324) | 0.606596 / 4.805227 (-4.198631) | 0.125991 / 6.500664 (-6.374673) | 0.063566 / 0.075469 (-0.011903) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.364771 / 1.841788 (-0.477017) | 18.000713 / 8.074308 (9.926404) | 14.840330 / 10.191392 (4.648937) | 0.144770 / 0.680424 (-0.535653) | 0.018060 / 0.534201 (-0.516141) | 0.334470 / 0.579283 (-0.244813) | 0.387386 / 0.434364 (-0.046978) | 0.398743 / 0.540337 (-0.141595) | 0.555437 / 1.386936 (-0.831499) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5b974c9af6b45b6ebdbbf4b3418f25506c1c0618 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006491 / 0.011353 (-0.004862) | 0.004058 / 0.011008 (-0.006950) | 0.084462 / 0.038508 (0.045954) | 0.072310 / 0.023109 (0.049201) | 0.352458 / 0.275898 (0.076560) | 0.385829 / 0.323480 (0.062350) | 0.003978 / 0.007986 (-0.004007) | 0.003455 / 0.004328 (-0.000873) | 0.064070 / 0.004250 (0.059819) | 0.055577 / 0.037052 (0.018525) | 0.361288 / 0.258489 (0.102799) | 0.400147 / 0.293841 (0.106306) | 0.030785 / 0.128546 (-0.097761) | 0.008676 / 0.075646 (-0.066971) | 0.287481 / 0.419271 (-0.131791) | 0.052643 / 0.043533 (0.009110) | 0.354670 / 0.255139 (0.099531) | 0.382322 / 0.283200 (0.099122) | 0.025657 / 0.141683 (-0.116026) | 1.486798 / 1.452155 (0.034643) | 1.588439 / 1.492716 (0.095723) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.240881 / 0.018006 (0.222875) | 0.463997 / 0.000490 (0.463507) | 0.009688 / 0.000200 (0.009488) | 0.000601 / 0.000054 (0.000546) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029071 / 0.037411 (-0.008340) | 0.083077 / 0.014526 (0.068551) | 0.119857 / 0.176557 (-0.056699) | 0.153387 / 0.737135 (-0.583749) | 0.132162 / 0.296338 (-0.164177) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383822 / 0.215209 (0.168613) | 3.828572 / 2.077655 (1.750918) | 1.877629 / 1.504120 (0.373509) | 1.708757 / 1.541195 (0.167562) | 1.771658 / 1.468490 (0.303168) | 0.482439 / 4.584777 (-4.102338) | 3.496247 / 3.745712 (-0.249466) | 3.282055 / 5.269862 (-1.987807) | 2.053069 / 4.565676 (-2.512607) | 0.056626 / 0.424275 (-0.367649) | 0.007338 / 0.007607 (-0.000269) | 0.461257 / 0.226044 (0.235213) | 4.605326 / 2.268929 (2.336397) | 2.408365 / 55.444624 (-53.036260) | 1.986550 / 6.876477 (-4.889926) | 2.225220 / 2.142072 (0.083148) | 0.601301 / 4.805227 (-4.203927) | 0.132217 / 6.500664 (-6.368447) | 0.061217 / 0.075469 (-0.014252) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.268706 / 1.841788 (-0.573081) | 18.892026 / 8.074308 (10.817717) | 14.093892 / 10.191392 (3.902500) | 0.162483 / 0.680424 (-0.517941) | 0.018372 / 0.534201 (-0.515829) | 0.391901 / 0.579283 (-0.187382) | 0.401578 / 0.434364 (-0.032786) | 0.456741 / 0.540337 (-0.083596) | 0.646760 / 1.386936 (-0.740176) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006657 / 0.011353 (-0.004696) | 0.003981 / 0.011008 (-0.007027) | 0.066126 / 0.038508 (0.027617) | 0.072673 / 0.023109 (0.049564) | 0.409970 / 0.275898 (0.134072) | 0.430797 / 0.323480 (0.107317) | 0.005477 / 0.007986 (-0.002508) | 0.003362 / 0.004328 (-0.000966) | 0.065532 / 0.004250 (0.061282) | 0.056018 / 0.037052 (0.018966) | 0.406676 / 0.258489 (0.148187) | 0.438516 / 0.293841 (0.144675) | 0.032795 / 0.128546 (-0.095751) | 0.008580 / 0.075646 (-0.067066) | 0.072692 / 0.419271 (-0.346579) | 0.048110 / 0.043533 (0.004577) | 0.396826 / 0.255139 (0.141687) | 0.418442 / 0.283200 (0.135242) | 0.023269 / 0.141683 (-0.118414) | 1.499438 / 1.452155 (0.047283) | 1.568842 / 1.492716 (0.076126) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.218729 / 0.018006 (0.200723) | 0.450771 / 0.000490 (0.450281) | 0.004996 / 0.000200 (0.004796) | 0.000086 / 0.000054 (0.000031) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031484 / 0.037411 (-0.005928) | 0.092927 / 0.014526 (0.078401) | 0.107849 / 0.176557 (-0.068707) | 0.156658 / 0.737135 (-0.580478) | 0.106373 / 0.296338 (-0.189965) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434658 / 0.215209 (0.219449) | 4.336386 / 2.077655 (2.258731) | 2.322577 / 1.504120 (0.818457) | 2.149505 / 1.541195 (0.608310) | 2.201967 / 1.468490 (0.733476) | 0.496994 / 4.584777 (-4.087783) | 3.533065 / 3.745712 (-0.212647) | 3.235750 / 5.269862 (-2.034112) | 2.034854 / 4.565676 (-2.530823) | 0.058258 / 0.424275 (-0.366017) | 0.007260 / 0.007607 (-0.000347) | 0.509115 / 0.226044 (0.283071) | 5.088427 / 2.268929 (2.819499) | 2.793551 / 55.444624 (-52.651073) | 2.430588 / 6.876477 (-4.445889) | 2.625998 / 2.142072 (0.483926) | 0.611676 / 4.805227 (-4.193552) | 0.133343 / 6.500664 (-6.367321) | 0.059888 / 0.075469 (-0.015581) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.377292 / 1.841788 (-0.464496) | 19.214299 / 8.074308 (11.139991) | 14.629146 / 10.191392 (4.437754) | 0.171283 / 0.680424 (-0.509141) | 0.020348 / 0.534201 (-0.513853) | 0.397823 / 0.579283 (-0.181461) | 0.411590 / 0.434364 (-0.022774) | 0.470850 / 0.540337 (-0.069487) | 0.658667 / 1.386936 (-0.728269) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a1e1867e932f14233244fb25713f3c94c46ff50a \"CML watermark\")\n" ]

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[ "Indeed, it makes sense to do this by default. \r\n\r\nIn the meantime, you can use `.with_transform` to transpose the images when accessing them:\r\n\r\n```python\r\nimport PIL.ImageOps\r\n\r\ndef exif_transpose_transform(batch):\r\n batch[\"image\"] = [PIL.ImageOps.exif_transpose(image) for image in batch[\"image\"]]\r\n return batch\r\n\r\ndataset = dataset.with_transform(exif_transpose_transform)\r\n```", "This operation sets some `Image` attributes to `None` (`.format`, `.filename`, etc.), causing our tests to fail, so I think we should wait for Datasets 3.0 to make this change. In version 3.0, storing image paths will be replaced by embedding image bytes, so there will be fewer instances where we use the `.filename` attribute." ]

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