Datasets:

semeru

/

code-text-galeras-code-summarization-3k-deduped

like 1

makeDllEntryPoint

def makeDllEntryPoint(cls, source_path, dest_path, package_name): return makeDllEntryPoint( source_path=source_path, dest_path=dest_path, package_name=package_name )

56eb59d93f13815e66d0dea07e7669dfe275fa10

PluginBase.py

Plugins: Massive cleanup and API improvements and Kivy support * Added method to locate a DLL and to create a DLL entry point as expected, removing need for imports and making it more clear as an API. * The location of modules had already an API, but it wasn' used where it could be. * Moved implicit imports and DLL usage for Gi to its plugin, solving a TODO for it. * Make sure sure to only yield, and not return, that is just more error prone. * Also allow generators for implicit dependencies, such that generators work in a yield from fashion. * With this, Kivy apps work on at least Linux.

Nuitka

nuitka/plugins/PluginBase.py

Python

https://github.com/Nuitka/Nuitka.git

contains_point

def contains_point(self, point): return self.patch.contains_point(point, radius=1.0)

f156db08eee54d285ab0fb4e031e48d078ba6aa3

_base.py

DOC: More cleanup axes -> Axes

matplotlib

lib/matplotlib/axes/_base.py

Python

https://github.com/matplotlib/matplotlib.git

to_dict

def to_dict(self) -> dict: if self._data_dict: # If the checkpoint data is already a dict, return checkpoint_data = self._data_dict elif self._obj_ref: # If the checkpoint data is an object reference, resolve checkpoint_data = ray.get(self._obj_ref) elif self._local_path or self._uri: # Else, checkpoint is either on FS or external storage with self.as_directory() as local_path: checkpoint_data_path = os.path.join( local_path, _DICT_CHECKPOINT_FILE_NAME ) if os.path.exists(checkpoint_data_path): # If we are restoring a dict checkpoint, load the dict # from the checkpoint file. with open(checkpoint_data_path, "rb") as f: checkpoint_data = pickle.load(f) # If there are additional files in the directory, add them as # _DICT_CHECKPOINT_ADDITIONAL_FILE_KEY additional_files = {} for file_or_dir in os.listdir(local_path): if file_or_dir in [ ".", "..", _DICT_CHECKPOINT_FILE_NAME, _CHECKPOINT_METADATA_FILE_NAME, ]: continue additional_files[file_or_dir] = _pack( os.path.join(local_path, file_or_dir) ) if additional_files: checkpoint_data[ _DICT_CHECKPOINT_ADDITIONAL_FILE_KEY ] = additional_files else: files = [ f for f in os.listdir(local_path) if os.path.isfile(os.path.join(local_path, f)) and f.endswith(_METADATA_CHECKPOINT_SUFFIX) ] metadata = {} for file in files: with open(os.path.join(local_path, file), "rb") as f: key = file[: -len(_METADATA_CHECKPOINT_SUFFIX)] value = pickle.load(f) metadata[key] = value data = _pack(local_path) checkpoint_data = { _FS_CHECKPOINT_KEY: data, } checkpoint_data.update(metadata) else: raise RuntimeError(f"Empty data for checkpoint {self}") return _CheckpointDict(checkpoint_data, metadata=self._metadata)

5034544d5df5d7d9596b261d7bdffdd28e76fe2b

checkpoint.py

[AIR] Maintain checkpoint type information during serialization (#28387) These changes are needed to fix the errors described in #28134. Signed-off-by: Balaji Veeramani <[email protected]> Co-authored-by: Amog Kamsetty <[email protected]>

ray

python/ray/air/checkpoint.py

Python

https://github.com/ray-project/ray.git

fill_properties

def fill_properties(self, address, props_dict): device = self._devices[Address(address)] operating_flags = props_dict.get("operating_flags", {}) properties = props_dict.get("properties", {}) with patch("pyinsteon.subscriber_base.publish_topic", MagicMock()): for flag in operating_flags: value = operating_flags[flag] if device.operating_flags.get(flag): device.operating_flags[flag].load(value) for flag in properties: value = properties[flag] if device.properties.get(flag): device.properties[flag].load(value)

781ec87dff674b5f47f4138552d818cc490b5201

mock_devices.py

Fix Insteon tests (#71092)

core

tests/components/insteon/mock_devices.py

Python

https://github.com/home-assistant/core.git

set_freqai_targets

def set_freqai_targets(self, dataframe, **kwargs): return dataframe ### # END - Intended to be overridden by strategy ###

c2936d551b8ad6ccf7b57e2ac6cb55d8550622cf

interface.py

improve doc, update test strats, change function names

freqtrade

freqtrade/strategy/interface.py

Python

https://github.com/freqtrade/freqtrade.git

__exit__

def __exit__(self, type, value, traceback): if self.is_locked: self.release()

c541f4ba1fcab8304c7ac4efdce3d63a2e478176

file_lock.py

Add model parallel for FasterGPT. (#1755) * Add model parallel for FasterGPT. * Make GPT model parallel runable * Make FT model parallel optional. * Fix _write_setup_file when kwargs is not empty. * Fix ext_utils.load * Add file lock for model parallel. * Fix model_parallel.flag in CMakeLists.txt. * Use a separated lib for model parallel. * Make from_pretrained get partial model. * Make model parallel support layer group in python. * Fix fit_partial_model when model having keys state not including. Add api docs for model parallel. * Fix the default world_size when mpi is not available. * Add demo for GPT model parallel. * Fix default global ft_para_conf. * Fix GPTModel state_dict wrapper for layer parallel. * Set seed for tensor parallel. * Fix location of gpt.h in cmake. * Fix seed in gpt.h * Fix NV FT GPT embedding. * Add more cases in gpt_mp_sample.py * Fix seed in ker_curand_setupLauncher. Put build dir of FG in PPNLP_HOME with digest of current path. * Refine gpt_mp_sample.py

PaddleNLP

paddlenlp/utils/file_lock.py

Python

https://github.com/PaddlePaddle/PaddleNLP.git

pip_imported_during_build

def pip_imported_during_build(): import traceback return any( frame.f_globals['__file__'].endswith('setup.py') for frame, line in traceback.walk_stack(None) ) DISTUTILS_FINDER = DistutilsMetaFinder()

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

__init__.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/_distutils_hack/__init__.py

Python

https://github.com/jindongwang/transferlearning.git

compute_loss

def compute_loss(self, batch, return_output=False): if batch.label_vec is None: raise ValueError('Cannot compute loss without a label.') model_output = self.model(*self._model_input(batch), ys=batch.label_vec) scores, preds, *_ = model_output score_view = scores.reshape(-1, scores.size(-1)) loss_flattened = self.criterion(score_view, batch.label_vec.view(-1)) loss_per_token = loss_flattened.view(scores.shape[:-1]) notnull = batch.label_vec.ne(self.NULL_IDX) # save loss to metrics # cross entropy loss self.record_local_metric( 'loss', AverageMetric.from_mask(loss_per_token, notnull) ) # perplexity self.record_local_metric('ppl', PPLMetric.from_mask(loss_per_token, notnull)) # token-wise accuracy self.record_local_metric( 'token_acc', AverageMetric.from_mask(batch.label_vec == preds, notnull) ) # utterance-wise exact match num_target_tokens = notnull.long().sum(dim=-1) num_tokens_correct = ((batch.label_vec == preds) * notnull).sum(dim=-1) self.record_local_metric( 'token_em', AverageMetric.many(num_tokens_correct == num_target_tokens) ) # actually do backwards loss loss = loss_per_token.sum(dim=1) loss = loss.sum() loss /= num_target_tokens.sum() # average loss per token if return_output: return (loss, model_output) else: return loss

05ff60935043cf39192535eac38e2730212057c7

torch_generator_agent.py

Add Metric.from_mask helper method (#3411) (#4894) * Add Metric.from_mask helper method (#3411) * Use cls directly instead of passing in MyMetric

ParlAI

parlai/core/torch_generator_agent.py

Python

https://github.com/facebookresearch/ParlAI.git

_relative_position_bucket

def _relative_position_bucket(relative_position, bidirectional=True, num_buckets=32, max_distance=128): relative_buckets = 0 if bidirectional: num_buckets //= 2 relative_buckets += (relative_position > 0).to(torch.long) * num_buckets relative_position = torch.abs(relative_position) else: relative_position = -torch.min(relative_position, torch.zeros_like(relative_position)) # now relative_position is in the range [0, inf) # half of the buckets are for exact increments in positions max_exact = num_buckets // 2 is_small = relative_position < max_exact # The other half of the buckets are for logarithmically bigger bins in positions up to max_distance relative_position_if_large = max_exact + ( torch.log(relative_position.float() / max_exact) / math.log(max_distance / max_exact) * (num_buckets - max_exact) ).to(torch.long) relative_position_if_large = torch.min( relative_position_if_large, torch.full_like(relative_position_if_large, num_buckets - 1) ) relative_buckets += torch.where(is_small, relative_position, relative_position_if_large) return relative_buckets

a72f1c9f5b907f96cbb7de3bbb02a1d431d34071

modeling_longt5.py

Add `LongT5` model (#16792) * Initial commit * Make some fixes * Make PT model full forward pass * Drop TF & Flax implementation, fix copies etc * Add Flax model and update some corresponding stuff * Drop some TF things * Update config and flax local attn * Add encoder_attention_type to config * . * Update docs * Do some cleansing * Fix some issues -> make style; add some docs * Fix position_bias + mask addition + Update tests * Fix repo consistency * Fix model consistency by removing flax operation over attn_mask * [WIP] Add PT TGlobal LongT5 * . * [WIP] Add flax tglobal model * [WIP] Update flax model to use the right attention type in the encoder * Fix flax tglobal model forward pass * Make the use of global_relative_attention_bias * Add test suites for TGlobal model * Fix minor bugs, clean code * Fix pt-flax equivalence though not convinced with correctness * Fix LocalAttn implementation to match the original impl. + update READMEs * Few updates * Update: [Flax] improve large model init and loading #16148 * Add ckpt conversion script accoring to #16853 + handle torch device placement * Minor updates to conversion script. * Typo: AutoModelForSeq2SeqLM -> FlaxAutoModelForSeq2SeqLM * gpu support + dtype fix * Apply some suggestions from code review Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Patrick von Platen <[email protected]> * * Remove (de)parallelize stuff * Edit shape comments * Update README.md * make fix-copies * Remove caching logic for local & tglobal attention * Apply another batch of suggestions from code review * Add missing checkpoints * Format converting scripts * Drop (de)parallelize links from longT5 mdx * Fix converting script + revert config file change * Revert "Remove caching logic for local & tglobal attention" This reverts commit 2a619828f6ddc3e65bd9bb1725a12b77fa883a46. * Stash caching logic in Flax model * Make side relative bias used always * Drop caching logic in PT model * Return side bias as it was * Drop all remaining model parallel logic * Remove clamp statements * Move test files to the proper place * Update docs with new version of hf-doc-builder * Fix test imports * Make some minor improvements * Add missing checkpoints to docs * Make TGlobal model compatible with torch.onnx.export * Replace some np.ndarray with jnp.ndarray * Fix TGlobal for ONNX conversion + update docs * fix _make_global_fixed_block_ids and masked neg value * update flax model * style and quality * fix imports * remove load_tf_weights_in_longt5 from init and fix copies * add slow test for TGlobal model * typo fix * Drop obsolete is_parallelizable and one warning * Update __init__ files to fix repo-consistency * fix pipeline test * Fix some device placements * [wip]: Update tests -- need to generate summaries to update expected_summary * Fix quality * Update LongT5 model card * Update (slow) summarization tests * make style * rename checkpoitns * finish * fix flax tests Co-authored-by: phungvanduy <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Patrick von Platen <[email protected]> Co-authored-by: patil-suraj <[email protected]>

transformers

src/transformers/models/longt5/modeling_longt5.py

Python

https://github.com/huggingface/transformers.git

_file_lists

def _file_lists(load, form): if "env" in load: # "env" is not supported; Use "saltenv". load.pop("env") saltenv = load["saltenv"] actual_saltenv = saltenv if saltenv not in __opts__["file_roots"]: if "__env__" in __opts__["file_roots"]: log.debug( "salt environment '%s' maps to __env__ file_roots directory", saltenv ) saltenv = "__env__" else: return [] list_cachedir = os.path.join(__opts__["cachedir"], "file_lists", "roots") if not os.path.isdir(list_cachedir): try: os.makedirs(list_cachedir) except OSError: log.critical("Unable to make cachedir %s", list_cachedir) return [] list_cache = os.path.join( list_cachedir, "{}.p".format(salt.utils.files.safe_filename_leaf(saltenv)) ) w_lock = os.path.join( list_cachedir, ".{}.w".format(salt.utils.files.safe_filename_leaf(saltenv)) ) cache_match, refresh_cache, save_cache = salt.fileserver.check_file_list_cache( __opts__, form, list_cache, w_lock ) if cache_match is not None: return cache_match if refresh_cache: ret = {"files": set(), "dirs": set(), "empty_dirs": set(), "links": {}}

52e1d0b8116c86777c85cb6c3d940e2c04a518c4

roots.py

add __env__ substitution inside file and pillar root paths

salt

salt/fileserver/roots.py

Python

https://github.com/saltstack/salt.git

_preprocess_conv2d_input

def _preprocess_conv2d_input(x, data_format, force_transpose=False): tf_data_format = "NHWC" if data_format == "channels_first": if not _has_nchw_support() or force_transpose: x = tf.compat.v1.transpose(x, (0, 2, 3, 1)) # NCHW -> NHWC else: tf_data_format = "NCHW" return x, tf_data_format

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/backend.py

Python

https://github.com/keras-team/keras.git

test_changelist_field_classes

def test_changelist_field_classes(self): Podcast.objects.create(name="Django Dose", release_date=datetime.date.today()) response = self.client.get(reverse("admin:admin_views_podcast_changelist")) self.assertContains(response, '<th class="field-name">') self.assertContains(response, '<td class="field-release_date nowrap">') self.assertContains(response, '<td class="action-checkbox">') try: import docutils except ImportError: docutils = None @unittest.skipUnless(docutils, "no docutils installed.") @override_settings(ROOT_URLCONF="admin_views.urls") @modify_settings( INSTALLED_APPS={"append": ["django.contrib.admindocs", "django.contrib.flatpages"]} )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

@unittest.skipUnless(docutils, "no docutils installed.") @override_settings(ROOT_URLCONF="admin_views.urls") @modify_settings( INSTALLED_APPS={"append": ["django.contrib.admindocs", "django.contrib.flatpages"]} )

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

https://github.com/django/django.git

time

def time(self) -> npt.NDArray[np.object_]: # If the Timestamps have a timezone that is not UTC, # convert them into their i8 representation while # keeping their timezone and not using UTC timestamps = self._local_timestamps() return ints_to_pydatetime(timestamps, box="time")

521259299f7829da667ba39302ec77acedde9e5e

datetimes.py

DOC: Improve doc summaries in series.rst (#45237)

pandas

pandas/core/arrays/datetimes.py

Python

https://github.com/pandas-dev/pandas.git

putalpha

def putalpha(self, alpha): self._ensure_mutable() if self.mode not in ("LA", "PA", "RGBA"): # attempt to promote self to a matching alpha mode try: mode = getmodebase(self.mode) + "A" try: self.im.setmode(mode) except (AttributeError, ValueError) as e: # do things the hard way im = self.im.convert(mode) if im.mode not in ("LA", "PA", "RGBA"): raise ValueError from e # sanity check self.im = im self.pyaccess = None self.mode = self.im.mode except KeyError as e: msg = "illegal image mode" raise ValueError(msg) from e if self.mode in ("LA", "PA"): band = 1 else: band = 3 if isImageType(alpha): # alpha layer if alpha.mode not in ("1", "L"): msg = "illegal image mode" raise ValueError(msg) alpha.load() if alpha.mode == "1": alpha = alpha.convert("L") else: # constant alpha try: self.im.fillband(band, alpha) except (AttributeError, ValueError): # do things the hard way alpha = new("L", self.size, alpha) else: return self.im.putband(alpha.im, band)

2ae55ccbdad9c842929fb238ea1eb81d1f999024

Image.py

Improve exception traceback readability

Pillow

src/PIL/Image.py

Python

https://github.com/python-pillow/Pillow.git

run_query

def run_query(filters, extra_fields, extra_joins, extra_filters, as_dict=1): query = .format( extra_fields=extra_fields, extra_joins=extra_joins, extra_filters=extra_filters ) gl_entries = frappe.db.sql(query, filters, as_dict=as_dict) return gl_entries

363ed9ccba3f848908113e6d728735a1c894aec8

datev.py

revert: BU Schlüssel (a21f76f)

erpnext

erpnext/regional/report/datev/datev.py

Python

https://github.com/frappe/erpnext.git

get_preset_choices

def get_preset_choices() -> Dict: PRESETS_PATH = PRESETS_DIRECTORY / "etf" / "screener" PRESETS_PATH_DEFAULT = Path(__file__).parent / "presets" preset_choices = { filepath.name: filepath for filepath in PRESETS_PATH.iterdir() if filepath.suffix == ".ini" } preset_choices.update( { filepath.name: filepath for filepath in PRESETS_PATH_DEFAULT.iterdir() if filepath.suffix == ".ini" } ) return preset_choices @log_start_end(log=logger)

3780cffeced904d41e04e2adfe8c1f2a34337099

@log_start_end(log=logger)

screener_model.py

New path for presets (#2634) * modify path for etf, options, insider * fix small * change path for stocks screener * fix flake 8 * remove preset_path * black * fix * fix tests * fix tests * fix flake8 * change paths_helper load * put ns parser back Co-authored-by: minhhoang1023 <[email protected]>

OpenBBTerminal

openbb_terminal/etf/screener/screener_model.py

Python

https://github.com/OpenBB-finance/OpenBBTerminal.git

tokenize

def tokenize(doc): return (tok.lower() for tok in re.findall(r"\w+", doc)) list(tokenize("This is a simple example, isn't it?")) # %% # We define an additional function that counts the (frequency of) occurrence of # each token in a given document. It returns a frequency dictionary to be used # by the vectorizers. from collections import defaultdict

6ff214c46bacaf0385125bb47b4d8cb4a305fa3a

plot_hashing_vs_dict_vectorizer.py

DOC Rework plot_hashing_vs_dict_vectorizer.py example (#23266) Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]>

scikit-learn

examples/text/plot_hashing_vs_dict_vectorizer.py

Python

https://github.com/scikit-learn/scikit-learn.git

get_first_menu_and_fail

def get_first_menu_and_fail() -> click.testing.Result: command = ["storage", "create"] runner = CliRunner() result = runner.invoke(app, command, input=INVALID_OPTION, catch_exceptions=False) return result

11638691240b7595c0d02542af506a96d344ae8b

test_storage_cli.py

Update tests

prefect

tests/cli/test_storage_cli.py

Python

https://github.com/PrefectHQ/prefect.git

get_cat2imgs

def get_cat2imgs(self) -> Dict[int, list]: classes = self.dataset.metainfo.get('CLASSES', None) if classes is None: raise ValueError('dataset metainfo must contain CLASSES') # sort the label index cat2imgs = {i: [] for i in range(len(classes))} for i in range(len(self.dataset)): cat_ids = set(self.dataset.get_cat_ids(i)) for cat in cat_ids: cat2imgs[cat].append(i) return cat2imgs

36c1f477b273cb2fb0dea3c921ec267db877c039

class_aware_sampler.py

Refactor OpenImages.

mmdetection

mmdet/datasets/samplers/class_aware_sampler.py

Python

https://github.com/open-mmlab/mmdetection.git

print_telemetry_report

def print_telemetry_report(): if is_telemetry_enabled(): user_id = _get_or_create_user_id() meta_data = _get_or_create_telemetry_meta_data() print({**{"user_id": user_id}, **meta_data}) else: print("Telemetry is disabled.")

ac5617e757e9ace6f30b7291686d9dbbc339f433

telemetry.py

Add basic telemetry features (#2314) * add basic telemetry features * change pipeline_config to _component_config * Update Documentation & Code Style * add super().__init__() calls to error classes * make posthog mock work with python 3.7 * Update Documentation & Code Style * update link to docs web page * log exceptions, send event for raised HaystackErrors, refactor Path(CONFIG_PATH) * add comment on send_event in BaseComponent.init() and fix mypy * mock NonPrivateParameters and fix pylint undefined-variable * Update Documentation & Code Style * check model path contains multiple / * add test for writing to file * add test for en-/disable telemetry * Update Documentation & Code Style * merge file deletion methods and ignore pylint global statement * Update Documentation & Code Style * set env variable in demo to activate telemetry * fix mock of HAYSTACK_TELEMETRY_ENABLED * fix mypy and linter * add CI as env variable to execution contexts * remove threading, add test for custom error event * Update Documentation & Code Style * simplify config/log file deletion * add test for final event being sent * force writing config file in test * make test compatible with python 3.7 * switch to posthog production server * Update Documentation & Code Style Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

haystack

haystack/telemetry.py

Python

https://github.com/deepset-ai/haystack.git

test_edgeql_for_in_computable_05

async def test_edgeql_for_in_computable_05(self): await self.assert_query_result( r, [{"select_deck": tb.bag(["Bog monster", "Dragon", "Giant turtle", "Imp"])}], ) # This one caused a totally nonsense type error. await self.assert_query_result( r, [{"select_deck": tb.bag(["Bog monster", "Dragon", "Giant turtle", "Imp"])}], )

26be7d28bdb4eb96c888e373e08f46e6b85711e3

test_edgeql_for.py

Add a `bag` type that tells assert_query_result to ignore order (#3314) assert_query_result currently supports using sets to ignore order, but that doesn't work for objects, which can't be hashed or sorted. There is a system for specifying a sort key for internal data, but it is way clunkier than just saying we don't care about the order. I converted some places that were using sort= to use this.

edgedb

tests/test_edgeql_for.py

Python

https://github.com/edgedb/edgedb.git

stop

async def stop(self, block=False) -> None: self._stop() if block: while self._is_running: await asyncio.sleep(0.1)

b7d5fc52e4235370e368e96da218ca49bd32edcc

loop_service.py

Change default behavior to block=false

prefect

src/prefect/orion/services/loop_service.py

Python

https://github.com/PrefectHQ/prefect.git

run

def run(self): display.debug("in run() - task %s" % self._task._uuid) try: try: items = self._get_loop_items() except AnsibleUndefinedVariable as e: # save the error raised here for use later items = None self._loop_eval_error = e if items is not None: if len(items) > 0: item_results = self._run_loop(items) # create the overall result item res = dict(results=item_results) # loop through the item results and set the global changed/failed/skipped result flags based on any item. res['skipped'] = True for item in item_results: if 'changed' in item and item['changed'] and not res.get('changed'): res['changed'] = True if res['skipped'] and ('skipped' not in item or ('skipped' in item and not item['skipped'])): res['skipped'] = False if 'failed' in item and item['failed']: item_ignore = item.pop('_ansible_ignore_errors') if not res.get('failed'): res['failed'] = True res['msg'] = 'One or more items failed' self._task.ignore_errors = item_ignore elif self._task.ignore_errors and not item_ignore: self._task.ignore_errors = item_ignore # ensure to accumulate these for array in ['warnings', 'deprecations']: if array in item and item[array]: if array not in res: res[array] = [] if not isinstance(item[array], list): item[array] = [item[array]] res[array] = res[array] + item[array] del item[array] if not res.get('failed', False): res['msg'] = 'All items completed' if res['skipped']: res['msg'] = 'All items skipped' else: res = dict(changed=False, skipped=True, skipped_reason='No items in the list', results=[]) else: display.debug("calling self._execute()") res = self._execute() display.debug("_execute() done") # make sure changed is set in the result, if it's not present if 'changed' not in res: res['changed'] = False

a0dede545864b9835f84315b4b3ea17dd1eafe04

def run(self): ''' The main executor entrypoint, where we determine if the specified task requires looping and either runs the task with self._run_loop() or self._execute(). After that, the returned results are parsed and returned as a dict. ''' display.debug("in run() - task %s" % self._task._uuid) try: try: items = self._get_loop_items() except AnsibleUndefinedVariable as e: # save the error raised here for use later items = None self._loop_eval_error = e if items is not None: if len(items) > 0: item_results = self._run_loop(items) # create the overall result item res = dict(results=item_results) # loop through the item results and set the global changed/failed/skipped result flags based on any item. res['skipped'] = True for item in item_results: if 'changed' in item and item['changed'] and not res.get('changed'): res['changed'] = True if res['skipped'] and ('skipped' not in item or ('skipped' in item and not item['skipped'])): res['skipped'] = False if 'failed' in item and item['failed']: item_ignore = item.pop('_ansible_ignore_errors') if not res.get('failed'): res['failed'] = True res['msg'] = 'One or more items failed' self._task.ignore_errors = item_ignore elif self._task.ignore_errors and not item_ignore: self._task.ignore_errors = item_ignore # ensure to accumulate these for array in ['warnings', 'deprecations']: if array in item and item[array]: if array not in res: res[array] = [] if not isinstance(item[array], list): item[array] = [item[array]] res[array] = res[array] + item[array] del item[array] if not res.get('failed', False): res['msg'] = 'All items completed' if res['skipped']: res['msg'] = 'All items skipped' else: res = dict(changed=False, skipped=True, skipped_reason='No items in the list', results=[]) else: display.debug("calling self._execute()") res = self._execute() display.debug("_execute() done") # make sure changed is set in the result, if it's not present if 'changed' not in res: res['changed'] = False

task_executor.py

ansible-connection verboistery (#77509) * ansible-connection verboistery for cli, just use normal parser creation this also adds --help, but that seems fine also some error cleanup Co-authored-by: Nathaniel Case <[email protected]>

ansible

lib/ansible/executor/task_executor.py

Python

https://github.com/ansible/ansible.git

test_orion_full_migration_works_with_data_in_db

async def test_orion_full_migration_works_with_data_in_db(sample_db_data): try: await run_sync_in_worker_thread(alembic_downgrade) finally: await run_sync_in_worker_thread(alembic_upgrade)

36e7e0838aeaffc9492b330297e4905f3ab4b11f

test_migrations.py

code review revisions pt3

prefect

tests/orion/database/test_migrations.py

Python

https://github.com/PrefectHQ/prefect.git

test_execute_in_batch_with_few_requests

def test_execute_in_batch_with_few_requests(self, api, batch, mock_batch_responses): mock_batch_responses( [ { "json": [{"body": json.dumps({"name": "creative 1"}), "code": 200, "headers": {}}] * 3, } ] ) stream = SomeTestStream(api=api) requests = [FacebookRequest("node", "GET", "endpoint") for _ in range(5)] result = list(stream.execute_in_batch(requests)) assert batch.add_request.call_count == len(requests) batch.execute.assert_called_once() assert len(result) == 3

6cd20e6879a42053692c18a16906eb410aad85db

test_base_streams.py

🐛 Source FB Marketing: fix `execute_in_batch` when batch is bigger than 50 (#10588) * fix execute_in_batch * add tests * fix pre-commit config Co-authored-by: Sherif A. Nada <[email protected]> Co-authored-by: Eugene Kulak <[email protected]> Co-authored-by: Sherif A. Nada <[email protected]>

airbyte

airbyte-integrations/connectors/source-facebook-marketing/unit_tests/test_base_streams.py

Python

https://github.com/airbytehq/airbyte.git

get_multi_io_subclass_model

def get_multi_io_subclass_model(use_bn=False, use_dp=False, num_classes=(2, 3)): shared_layer = keras.layers.Dense(32, activation='relu') branch_a = [shared_layer] if use_dp: branch_a.append(keras.layers.Dropout(0.5)) branch_a.append(keras.layers.Dense(num_classes[0], activation='softmax')) branch_b = [shared_layer] if use_bn: branch_b.append(keras.layers.BatchNormalization()) branch_b.append(keras.layers.Dense(num_classes[1], activation='softmax')) model = ( test_utils._MultiIOSubclassModel( # pylint: disable=protected-access branch_a, branch_b, name='test_model')) return model

b96518a22bfd92a29811e507dec0b34248a8a3f5

model_subclassing_test_util.py

- Consolidate disparate test-related files into a single testing_infra folder. - Cleanup TODO related to removing testing infra as a dependency of the Keras target. - Standardize import naming: there is now only "test_combinations" for test combinations, and "test_utils" for utilities. The TF utilities module "test_util" is now always imported as "tf_test_utils" to avoid confusion. PiperOrigin-RevId: 426773173

keras

keras/tests/model_subclassing_test_util.py

Python

https://github.com/keras-team/keras.git

inertia

def inertia(frame, ixx, iyy, izz, ixy=0, iyz=0, izx=0): if not isinstance(frame, ReferenceFrame): raise TypeError('Need to define the inertia in a frame') ol = sympify(ixx) * (frame.x | frame.x) ol += sympify(ixy) * (frame.x | frame.y) ol += sympify(izx) * (frame.x | frame.z) ol += sympify(ixy) * (frame.y | frame.x) ol += sympify(iyy) * (frame.y | frame.y) ol += sympify(iyz) * (frame.y | frame.z) ol += sympify(izx) * (frame.z | frame.x) ol += sympify(iyz) * (frame.z | frame.y) ol += sympify(izz) * (frame.z | frame.z) return ol

65be461082dda54c8748922f9c29a19af1279fe1

functions.py

Remove abbreviations in documentation

sympy

sympy/physics/mechanics/functions.py

Python

https://github.com/sympy/sympy.git

hashes_to_frame

def hashes_to_frame(self) -> Dict[str, Dict[str, int]]: return self._legacy.hashes_to_frame

e5356a417e7c2124e75c4a2994ed604fc0a3cc74

alignments.py

Alignments update: - Store face embeddings in PNG header when sorting - typing + refactor - Update alignments keys for 'identity' and 'video_meta' + bump to v2.3 - General typing fixes

faceswap

lib/align/alignments.py

Python

https://github.com/deepfakes/faceswap.git

start

async def start(self): with ImportExtensions(required=True): import aiohttp self.session = aiohttp.ClientSession(**self._session_kwargs) await self.session.__aenter__() return self

65d6873500f008dafba193340f8731bca39bc7dc

helper.py

feat: expose kwargs to Clients (#4947)

jina

jina/clients/base/helper.py

Python

https://github.com/jina-ai/jina.git

evaluate_accuracy_gpu

def evaluate_accuracy_gpu(net, data_iter, device=None): if isinstance(net, nn.Module): net.eval() # Set the model to evaluation mode if not device: device = next(iter(net.parameters())).device # No. of correct predictions, no. of predictions metric = d2l.Accumulator(2) with torch.no_grad(): for X, y in data_iter: if isinstance(X, list): # Required for BERT Fine-tuning (to be covered later) X = [x.to(device) for x in X] else: X = X.to(device) y = y.to(device) metric.add(d2l.accuracy(net(X), y), d2l.size(y)) return metric[0] / metric[1]

2b1acfbfe84b6c9c4756a615620f9b376d48085a

torch.py

JAX: Fix CI bug; enable build all sections

d2l-en

d2l/torch.py

Python

https://github.com/d2l-ai/d2l-en.git

get_classes_from_csv

def get_classes_from_csv(self, label_file): index_list = [] classes_names = [] with open(label_file, 'r') as f: reader = csv.reader(f) for line in reader: self.cat2label[line[0]] = line[1] classes_names.append(line[1]) index_list.append(line[0]) self.index_dict = {index: i for i, index in enumerate(index_list)} return classes_names

1516986a616fee8bb741d0ab2be40683045efccd

openimages.py

[Feature] Support OpenImages Dataset (#6331) * [Feature] support openimage group of eval * [Feature] support openimage group of eval * support openimage dataset * support openimage challenge dataset * fully support OpenImages-V6 and OpenImages Challenge 2019 * Fix some logic error * update config file * fix get data_infos error * fully support OpenImages evaluation * update OpenImages config files * [Feature] support OpenImages datasets * fix bug * support load image metas from pipeline * fix bug * fix get classes logic error * update code * support get image metas * support openimags * support collect image metas * support Open Images * fix openimages logic * minor fix * add a new function to compute openimages tpfp * minor fix * fix ci error * minor fix * fix indication * minor fix * fix returns * fix returns * fix returns * fix returns * fix returns * minor fix * update readme * support loading image level labels and fix some logic * minor fix * minor fix * add class names * minor fix * minor fix * minor fix * add openimages test unit * minor fix * minor fix * fix test unit * minor fix * fix logic error * minor fix * fully support openimages * minor fix * fix docstring * fix docstrings in readthedocs * update get image metas script * label_description_file -> label_file * update openimages readme * fix test unit * fix test unit * minor fix * update readme file * Update get_image_metas.py

mmdetection

mmdet/datasets/openimages.py

Python

https://github.com/open-mmlab/mmdetection.git

_get_dated_items

def _get_dated_items(self, date): lookup_kwargs = self._make_single_date_lookup(date) qs = self.get_dated_queryset(**lookup_kwargs) return ( None, qs, { "day": date, "previous_day": self.get_previous_day(date), "next_day": self.get_next_day(date), "previous_month": self.get_previous_month(date), "next_month": self.get_next_month(date), }, )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

dates.py

Refs #33476 -- Reformatted code with Black.

django

django/views/generic/dates.py

Python

https://github.com/django/django.git

perform_action

def perform_action(action_id, project, queryset, user, **kwargs): if action_id not in settings.DATA_MANAGER_ACTIONS: raise DataManagerException("Can't find '" + action_id + "' in registered actions") action = settings.DATA_MANAGER_ACTIONS[action_id] # check user permissions for this action if not check_permissions(user, action): raise DRFPermissionDenied(f'Action is not allowed for the current user: {action["id"]}') try: result = action['entry_point'](project, queryset, **kwargs) except Exception as e: text = 'Error while perform action: ' + action_id + '\n' + tb.format_exc() logger.error(text, extra={'sentry_skip': True}) raise e return result register_actions_from_dir('data_manager.actions', os.path.dirname(__file__))

1c4328c5a8b10ee20ac4328ce30612d106350699

__init__.py

feat: DEV-1205: Add task.updated_at column (#1784) * Update task.updated_at on annotation update (DEV-1205) * Fix set updated_at on annotation delete (DEV-1205) * Set update_at for every dm action (DEV-1205) * Stop changing updated_at on actions (DEV-1205) * Update experimental.py Co-authored-by: Max Tkachenko <[email protected]> Co-authored-by: niklub <[email protected]>

label-studio

label_studio/data_manager/actions/__init__.py

Python

https://github.com/heartexlabs/label-studio.git

fit

def fit(self) -> ResultGrid: if not self._is_ray_client: try: return self._local_tuner.fit() except Exception as e: raise TuneError( f"Tune run failed. " f'Please use tuner = Tuner.restore("' f'{self._local_tuner.get_experiment_checkpoint_dir()}") to resume.' ) from e else: experiment_checkpoint_dir = ray.get( self._remote_tuner.get_experiment_checkpoint_dir.remote() ) try: return ray.get(self._remote_tuner.fit.remote()) except Exception as e: raise TuneError( f"Tune run failed. " f'Please use tuner = Tuner.restore("' f'{experiment_checkpoint_dir}") to resume.' ) from e

5c500f6308dce526c50a5230029fb4909b492a35

tuner.py

[docs/air] Fix up some minor docstrings (#28361)

ray

python/ray/tune/tuner.py

Python

https://github.com/ray-project/ray.git

test_task_states_for_dag_run_when_dag_run_not_exists

def test_task_states_for_dag_run_when_dag_run_not_exists(self): with pytest.raises(DagRunNotFound): default_date2 = timezone.datetime(2016, 1, 9) task_command.task_states_for_dag_run( self.parser.parse_args( [ 'tasks', 'states-for-dag-run', 'not_exists_dag', default_date2.isoformat(), '--output', "json", ] ) )

f352ee63a5d09546a7997ba8f2f8702a1ddb4af7

test_task_command.py

Replaced all days_ago functions with datetime functions (#23237) Co-authored-by: Dev232001 <[email protected]>

airflow

tests/cli/commands/test_task_command.py

Python

https://github.com/apache/airflow.git

yeardatescalendar

def yeardatescalendar(self, year, width=3): months = [ self.monthdatescalendar(year, i) for i in range(January, January+12) ] return [months[i:i+width] for i in range(0, len(months), width) ]

8198943edd73a363c266633e1aa5b2a9e9c9f526

calendar.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/calendar.py

Python

https://github.com/XX-net/XX-Net.git

process_downloaded_dataset

def process_downloaded_dataset(self): df = pd.read_csv(os.path.join(self.raw_dataset_path, self.csv_filename)) df[SPLIT] = np.random.choice(3, len(df), p=(0.7, 0.1, 0.2)).astype(np.int8) makedirs(self.processed_temp_path, exist_ok=True) df.to_csv(os.path.join(self.processed_temp_path, self.csv_filename), index=False) rename(self.processed_temp_path, self.processed_dataset_path)

c13bc2cf1443ce9339cde0eb5e0d2b568af341f7

__init__.py

Add medical no-show appointments dataset (#2387) Co-authored-by: Daniel Treiman <[email protected]>

ludwig

ludwig/datasets/noshow_appointments/__init__.py

Python

https://github.com/ludwig-ai/ludwig.git

template

def template(self) -> str | None: if self.value_template is not None: return self.value_template.template return None

dd1463da287f591652e47b00eee0c5b77f5f5b7c

helpers.py

Refactor bayesian observations using dataclass (#79590) * refactor * remove some changes * remove typehint * improve codestyle * move docstring to comment * < 88 chars * avoid short var names * more readable * fix rename * Update homeassistant/components/bayesian/helpers.py Co-authored-by: epenet <[email protected]> * Update homeassistant/components/bayesian/binary_sensor.py Co-authored-by: epenet <[email protected]> * Update homeassistant/components/bayesian/binary_sensor.py Co-authored-by: epenet <[email protected]> * no intermediate * comment why set before list Co-authored-by: epenet <[email protected]>

core

homeassistant/components/bayesian/helpers.py

Python

https://github.com/home-assistant/core.git

get_capacity

def get_capacity(self): if self.is_container_group: return self.max_forks return self.get_instance_capacity()

e403c603d68def3b4cc6e4b253092343d646da1a

task_manager_models.py

use task manager models more consistently in serializer

awx

awx/main/scheduler/task_manager_models.py

Python

https://github.com/ansible/awx.git

create_trial_from_spec

def create_trial_from_spec(spec, output_path, parser, **trial_kwargs): global _cached_pgf spec = spec.copy() resources = spec.pop("resources_per_trial", None) try: args, _ = parser.parse_known_args(to_argv(spec)) except SystemExit: raise TuneError("Error parsing args, see above message", spec) if resources: if isinstance(resources, PlacementGroupFactory): trial_kwargs["placement_group_factory"] = resources else: # This will be converted to a placement group factory in the # Trial object constructor try: trial_kwargs["resources"] = json_to_resources(resources) except (TuneError, ValueError) as exc: raise TuneError("Error parsing resources_per_trial", resources) from exc remote_checkpoint_dir = spec.get("remote_checkpoint_dir") sync_config = spec.get("sync_config", SyncConfig()) if sync_config.syncer is None or isinstance(sync_config.syncer, str): sync_function_tpl = sync_config.syncer elif not isinstance(sync_config.syncer, str): # If a syncer was specified, but not a template, it is a function. # Functions cannot be used for trial checkpointing on remote nodes, # so we set the remote checkpoint dir to None to disable this. sync_function_tpl = None remote_checkpoint_dir = None else: sync_function_tpl = None # Auto-detect return Trial( # Submitting trial via server in py2.7 creates Unicode, which does not # convert to string in a straightforward manner. trainable_name=spec["run"], # json.load leads to str -> unicode in py2.7 config=spec.get("config", {}), local_dir=os.path.join(spec["local_dir"], output_path), # json.load leads to str -> unicode in py2.7 stopping_criterion=spec.get("stop", {}), remote_checkpoint_dir=remote_checkpoint_dir, sync_function_tpl=sync_function_tpl, checkpoint_freq=args.checkpoint_freq, checkpoint_at_end=args.checkpoint_at_end, sync_on_checkpoint=sync_config.sync_on_checkpoint, keep_checkpoints_num=args.keep_checkpoints_num, checkpoint_score_attr=args.checkpoint_score_attr, export_formats=spec.get("export_formats", []), # str(None) doesn't create None restore_path=spec.get("restore"), trial_name_creator=spec.get("trial_name_creator"), trial_dirname_creator=spec.get("trial_dirname_creator"), log_to_file=spec.get("log_to_file"), # str(None) doesn't create None max_failures=args.max_failures, **trial_kwargs )

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

config_parser.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

python/ray/tune/config_parser.py

Python

https://github.com/ray-project/ray.git

test_spectralbiclustering_parameter_validation

def test_spectralbiclustering_parameter_validation(params, type_err, err_msg): data = np.arange(25).reshape((5, 5)) model = SpectralBiclustering(**params) with pytest.raises(type_err, match=err_msg): model.fit(data) @pytest.mark.parametrize("est", (SpectralBiclustering(), SpectralCoclustering()))

604bc5c605b9587526794de2653624b19c6a8031

@pytest.mark.parametrize("est", (SpectralBiclustering(), SpectralCoclustering()))

test_bicluster.py

MNT use check_scalar in SpectralBiClustering and SpectralCoClustering (#20817) Co-authored-by: Thomas J. Fan <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]>

scikit-learn

sklearn/cluster/tests/test_bicluster.py

Python

https://github.com/scikit-learn/scikit-learn.git

categorical_mapping

def categorical_mapping(self, data, palette, order): # -- Identify the order and name of the levels levels = categorical_order(data, order) n_colors = len(levels) # -- Identify the set of colors to use if isinstance(palette, dict): missing = set(levels) - set(palette) if any(missing): err = "The palette dictionary is missing keys: {}" raise ValueError(err.format(missing)) lookup_table = palette else: if palette is None: if n_colors <= len(get_color_cycle()): colors = color_palette(None, n_colors) else: colors = color_palette("husl", n_colors) elif isinstance(palette, list): colors = self._check_list_length(levels, palette, "palette") else: colors = color_palette(palette, n_colors) lookup_table = dict(zip(levels, colors)) return levels, lookup_table

563e96d3be1eaee8db8dfbccf7eed1f1c66dfd31

_oldcore.py

Downgrade exception on mapping list length mismatch to warning (#2856) * Downgrade exception on mapping list length mismatch to warning * Lint * Fix pairplot test * Set stacklevel to report warning in user code

seaborn

seaborn/_oldcore.py

Python

https://github.com/mwaskom/seaborn.git

has_all_dags_access

def has_all_dags_access(self, user): if not user: user = g.user return ( self._has_role(['Admin', 'Viewer', 'Op', 'User'], user) or self.has_access(permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG, user) or self.has_access(permissions.ACTION_CAN_EDIT, permissions.RESOURCE_DAG, user) )

3e9828022b03b60d9e112f1f64340a528c8407e3

security.py

Simplify fab has access lookup (#19294) * Use FAB models. * Remove incorrect conversions to new permission naming scheme. * Fix missing FAB renames. * Remove unused FAB compatibility fixes in models.py. * Set perms directly on user objects. * Set perms properties on User model. * Rename missed old naming scheme conversion. * Remove unused imports. * Remove unused imports. * Remeve get_user_roles() method. * Make permissions eagerload. * Remove unused imports. * Clarify query params. * Modify sort logic so MSSQL passes. * Add text modifier to order_by values. * Remove calls to get_*_dags. * Add back execution_date * Add back comma to match rest of file. * Remove unused permission functions. * Fix failing tests. * Pass user object to current_app.appbuilder.sm.has_all_dags_access. * Remove attempts to fix query. * Update the api_connexion query builders. * Add typing. * Apply sorts directly to model objects. * Apply sorts directly to model objects. * Standardize custom sort code. * Code review * Augment xcom docs (#20755) * Fix relationship join bug in FAB/SecurityManager with SQLA 1.4 (#21296) This is fixed in SQLA 1.4.19, but the fix makes the intent clearer here anyway. * Docs: Fix task order in overview example (#21282) * Update stat_name_handler documentation (#21298) Previously stat_name_handler was under the scheduler section of the configuration but it was moved to the metrics section since 2.0.0. * Update recipe for Google Cloud SDK (#21268) * Use FAB models. * Remove incorrect conversions to new permission naming scheme. * Fix missing FAB renames. * Remove unused FAB compatibility fixes in models.py. * Set perms directly on user objects. * Set perms properties on User model. * Rename missed old naming scheme conversion. * Remove unused imports. * Remove unused imports. * Remeve get_user_roles() method. * Make permissions eagerload. * Remove unused imports. * Clarify query params. * Modify sort logic so MSSQL passes. * Add text modifier to order_by values. * Remove calls to get_*_dags. * Add back execution_date * Add back comma to match rest of file. * Remove unused permission functions. * Fix failing tests. * Pass user object to current_app.appbuilder.sm.has_all_dags_access. * Remove attempts to fix query. * Update the api_connexion query builders. * Add typing. * Apply sorts directly to model objects. * Apply sorts directly to model objects. * Standardize custom sort code. * Make sure joined fields prefetch. * Dont use cached_property, since its only on > 3.8. Co-authored-by: Ash Berlin-Taylor <[email protected]> Co-authored-by: Lewis John McGibbney <[email protected]> Co-authored-by: Ash Berlin-Taylor <[email protected]> Co-authored-by: Lucia Kasman <[email protected]> Co-authored-by: Fran Sánchez <[email protected]> Co-authored-by: Kamil Breguła <[email protected]>

airflow

airflow/www/security.py

Python

https://github.com/apache/airflow.git

bootstrap

def bootstrap(pip, options): # type: (str, t.Dict[str, t.Any]) -> None pip_version = options['pip_version'] packages = options['packages'] url = 'https://ci-files.testing.ansible.com/ansible-test/get-pip-%s.py' % pip_version cache_path = os.path.expanduser('~/.ansible/test/cache/get_pip_%s.py' % pip_version.replace(".", "_")) temp_path = cache_path + '.download' if os.path.exists(cache_path): log('Using cached pip %s bootstrap script: %s' % (pip_version, cache_path)) else: log('Downloading pip %s bootstrap script: %s' % (pip_version, url)) make_dirs(os.path.dirname(cache_path)) download_file(url, temp_path) shutil.move(temp_path, cache_path) log('Cached pip %s bootstrap script: %s' % (pip_version, cache_path)) env = common_pip_environment() env.update(GET_PIP=cache_path) options = common_pip_options() options.extend(packages) command = [sys.executable, pip] + options execute_command(command, env=env)

68fb3bf90efa3a722ba5ab7d66b1b22adc73198c

requirements.py

ansible-test - Fix consistency of managed venvs. (#77028)

ansible

test/lib/ansible_test/_util/target/setup/requirements.py

Python

https://github.com/ansible/ansible.git

_create_sql_query

def _create_sql_query(self) -> str: escaper = ParamEscaper() location = escaper.escape_item(self._file_location) if self._expression_list is not None: location = f"(SELECT {self._expression_list} FROM {location})" files_or_pattern = "" if self._pattern is not None: files_or_pattern = f"PATTERN = {escaper.escape_item(self._pattern)}\n" elif self._files is not None: files_or_pattern = f"FILES = {escaper.escape_item(self._files)}\n" format_options = self._generate_options("FORMAT_OPTIONS", escaper, self._format_options) copy_options = self._generate_options("COPY_OPTIONS", escaper, self._copy_options) # TODO: think on how to make sure that table_name and expression_list aren't used for SQL injection sql = f return sql.strip()

27d19e7626ef80687997a6799762fa00162c1328

databricks_sql.py

Databricks SQL operators (#21363)

airflow

airflow/providers/databricks/operators/databricks_sql.py

Python

https://github.com/apache/airflow.git

map

def map(self, mapper, na_action=None): from pandas.core.indexes.multi import MultiIndex new_values = self._map_values(mapper, na_action=na_action) # we can return a MultiIndex if new_values.size and isinstance(new_values[0], tuple): if isinstance(self, MultiIndex): names = self.names elif self.name: names = [self.name] * len(new_values[0]) else: names = None return MultiIndex.from_tuples(new_values, names=names) dtype = None if not new_values.size: # empty dtype = self.dtype # e.g. if we are floating and new_values is all ints, then we # don't want to cast back to floating. But if we are UInt64 # and new_values is all ints, we want to try. same_dtype = lib.infer_dtype(new_values, skipna=False) == self.inferred_type if same_dtype: new_values = maybe_cast_pointwise_result( new_values, self.dtype, same_dtype=same_dtype ) if self._is_backward_compat_public_numeric_index and is_numeric_dtype( new_values.dtype ): return self._constructor( new_values, dtype=dtype, copy=False, name=self.name ) return Index._with_infer(new_values, dtype=dtype, copy=False, name=self.name) # TODO: De-duplicate with map, xref GH#32349

521259299f7829da667ba39302ec77acedde9e5e

base.py

DOC: Improve doc summaries in series.rst (#45237)

pandas

pandas/core/indexes/base.py

Python

https://github.com/pandas-dev/pandas.git

_handle_deprecations

def _handle_deprecations(self) -> None: if self._args.distributed: deprecation_warning("`-d`, `--distributed`", "Please use `-D`, `--distribution-strategy`") logger.warning("Setting 'distribution-strategy' to 'mirrored'") setattr(self._args, "distribution_strategy", "mirrored") del self._args.distributed

2ea05623bd684b2d1dd75679ad00441a5c751e7e

train.py

Update Distibution Strategies: - Add Central Storage Stategy - Deprecate 'distributed' cli argument

faceswap

scripts/train.py

Python

https://github.com/deepfakes/faceswap.git

multi_input_functional

def multi_input_functional(): input_1 = keras.Input(shape=(1,)) input_2 = keras.Input(shape=(1,)) input_3 = keras.Input(shape=(1,)) added = keras.layers.Add()([input_1, input_2, input_3]) output = test_utils.Bias()(added) return keras.Model([input_1, input_2, input_3], output) @test_combinations.run_with_all_model_types @test_combinations.run_all_keras_modes

b96518a22bfd92a29811e507dec0b34248a8a3f5

@test_combinations.run_with_all_model_types @test_combinations.run_all_keras_modes

correctness_test.py

- Consolidate disparate test-related files into a single testing_infra folder. - Cleanup TODO related to removing testing infra as a dependency of the Keras target. - Standardize import naming: there is now only "test_combinations" for test combinations, and "test_utils" for utilities. The TF utilities module "test_util" is now always imported as "tf_test_utils" to avoid confusion. PiperOrigin-RevId: 426773173

keras

keras/engine/correctness_test.py

Python

https://github.com/keras-team/keras.git

nullify_connected_endpoints

def nullify_connected_endpoints(instance, **kwargs): logger = logging.getLogger('netbox.dcim.cable') # Disassociate the Cable from its termination points if instance.termination_a: logger.debug(f"Nullifying termination A for cable {instance}") model = instance.termination_a_type.model_class() model.objects.filter(pk__in=instance.termination_a_ids).update(_link_peer_type=None, _link_peer_id=None) if instance.termination_b: logger.debug(f"Nullifying termination B for cable {instance}") model = instance.termination_b_type.model_class() model.objects.filter(pk__in=instance.termination_b_ids).update(_link_peer_type=None, _link_peer_id=None) # Delete and retrace any dependent cable paths for cablepath in CablePath.objects.filter(path__contains=instance): cp = CablePath.from_origin(cablepath.origin) if cp: CablePath.objects.filter(pk=cablepath.pk).update( path=cp.path, destination_type=ContentType.objects.get_for_model(cp.destination) if cp.destination else None, destination_id=cp.destination.pk if cp.destination else None, is_active=cp.is_active, is_split=cp.is_split ) else: cablepath.delete()

4bb9b6ee2639db683b70d6ddbee055497e0a3647

signals.py

Extend Cable model to support multiple A/B terminations

netbox

netbox/dcim/signals.py

Python

https://github.com/netbox-community/netbox.git

_async_update

def _async_update(self) -> None: super()._async_update() node = self.gateway.sensors[self.node_id] child = node.children[self.child_id] position: str = child.values[self.value_type] latitude, longitude, _ = position.split(",") self._latitude = float(latitude) self._longitude = float(longitude)

df2d0cd3e3ade2339a18415f92c85810308a9926

device_tracker.py

Refactor mysensors device tracker (#84747)

core

homeassistant/components/mysensors/device_tracker.py

Python

https://github.com/home-assistant/core.git

preprocess_input

def preprocess_input(x, data_format=None): # pylint: disable=unused-argument return x @keras_export("keras.applications.convnext.decode_predictions")

2d1086447a25d281f9428832d046c473d80ad761

@keras_export("keras.applications.convnext.decode_predictions")

convnext.py

Corrected preprocess_input docstring in regnet.py and convnext.py

keras

keras/applications/convnext.py

Python

https://github.com/keras-team/keras.git

get_delivery_notes_to_be_billed

def get_delivery_notes_to_be_billed(doctype, txt, searchfield, start, page_len, filters, as_dict): doctype = "Delivery Note" fields = get_fields(doctype, ["name", "customer", "posting_date"]) return frappe.db.sql( % { "fields": ", ".join(["`tabDelivery Note`.{0}".format(f) for f in fields]), "key": searchfield, "fcond": get_filters_cond(doctype, filters, []), "mcond": get_match_cond(doctype), "start": start, "page_len": page_len, "txt": "%(txt)s", }, {"txt": ("%%%s%%" % txt)}, as_dict=as_dict, ) @frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

9baa2229761c5415f29646a1a5bed4a3f4981e05

@frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

queries.py

fix: specify allowed doctype in queries (#31761)

erpnext

erpnext/controllers/queries.py

Python

https://github.com/frappe/erpnext.git

_build_attention_equation

def _build_attention_equation(rank, attn_axes): target_notation = _CHR_IDX[:rank] # `batch_dims` includes the head dim. batch_dims = tuple(np.delete(range(rank), attn_axes + (rank - 1,))) letter_offset = rank source_notation = "" for i in range(rank): if i in batch_dims or i == rank - 1: source_notation += target_notation[i] else: source_notation += _CHR_IDX[letter_offset] letter_offset += 1 product_notation = "".join( [target_notation[i] for i in batch_dims] + [target_notation[i] for i in attn_axes] + [source_notation[i] for i in attn_axes] ) dot_product_equation = "%s,%s->%s" % ( source_notation, target_notation, product_notation, ) attn_scores_rank = len(product_notation) combine_equation = "%s,%s->%s" % ( product_notation, source_notation, target_notation, ) return dot_product_equation, combine_equation, attn_scores_rank

84afc5193d38057e2e2badf9c889ea87d80d8fbf

multi_head_attention.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/layers/attention/multi_head_attention.py

Python

https://github.com/keras-team/keras.git

nms

def nms(dets, match_threshold=0.6, match_metric='iou'): if dets.shape[0] == 0: return dets[[], :] scores = dets[:, 0] x1 = dets[:, 1] y1 = dets[:, 2] x2 = dets[:, 3] y2 = dets[:, 4] areas = (x2 - x1 + 1) * (y2 - y1 + 1) order = scores.argsort()[::-1] ndets = dets.shape[0] suppressed = np.zeros((ndets), dtype=np.int) for _i in range(ndets): i = order[_i] if suppressed[i] == 1: continue ix1 = x1[i] iy1 = y1[i] ix2 = x2[i] iy2 = y2[i] iarea = areas[i] for _j in range(_i + 1, ndets): j = order[_j] if suppressed[j] == 1: continue xx1 = max(ix1, x1[j]) yy1 = max(iy1, y1[j]) xx2 = min(ix2, x2[j]) yy2 = min(iy2, y2[j]) w = max(0.0, xx2 - xx1 + 1) h = max(0.0, yy2 - yy1 + 1) inter = w * h if match_metric == 'iou': union = iarea + areas[j] - inter match_value = inter / union elif match_metric == 'ios': smaller = min(iarea, areas[j]) match_value = inter / smaller else: raise ValueError() if match_value >= match_threshold: suppressed[j] = 1 keep = np.where(suppressed == 0)[0] dets = dets[keep, :] return dets

0f75cb6c640203bc5c2670f6cbd9ac89ad53ecf4

utils.py

[smalldet] add SAHI slice train eval infer deploy (#6465) * add slice infer for smalldet * add slice infer for smalldet * fix slice infer * fix doc, test=document_fix * fix eval and configs * add slice dataset loader * fix deploy * fix docs, test=document_fix * update docs, test=document_fix

PaddleDetection

deploy/python/utils.py

Python

https://github.com/PaddlePaddle/PaddleDetection.git

test_fetch_period_api_with_minimal_response

async def test_fetch_period_api_with_minimal_response(recorder_mock, hass, hass_client): now = dt_util.utcnow() await async_setup_component(hass, "history", {}) hass.states.async_set("sensor.power", 0, {"attr": "any"}) await async_wait_recording_done(hass) hass.states.async_set("sensor.power", 50, {"attr": "any"}) await async_wait_recording_done(hass) hass.states.async_set("sensor.power", 23, {"attr": "any"}) last_changed = hass.states.get("sensor.power").last_changed await async_wait_recording_done(hass) hass.states.async_set("sensor.power", 23, {"attr": "any"}) await async_wait_recording_done(hass) client = await hass_client() response = await client.get( f"/api/history/period/{now.isoformat()}?filter_entity_id=sensor.power&minimal_response&no_attributes" ) assert response.status == HTTPStatus.OK response_json = await response.json() assert len(response_json[0]) == 3 state_list = response_json[0] assert state_list[0]["entity_id"] == "sensor.power" assert state_list[0]["attributes"] == {} assert state_list[0]["state"] == "0" assert "attributes" not in state_list[1] assert "entity_id" not in state_list[1] assert state_list[1]["state"] == "50" assert "attributes" not in state_list[2] assert "entity_id" not in state_list[2] assert state_list[2]["state"] == "23" assert state_list[2]["last_changed"] == json.dumps( process_timestamp(last_changed), cls=JSONEncoder, ).replace('"', "")

31a787558fd312331b55e5c2c4b33341fc3601fc

test_init.py

Ensure recorder test fixture is setup before hass fixture (#80528) * Ensure recorder test fixture is setup before hass fixture * Adjust more tests

core

tests/components/history/test_init.py

Python

https://github.com/home-assistant/core.git

describe_operation

def describe_operation(operation, backwards): prefix = "" is_error = False if hasattr(operation, "code"): code = operation.reverse_code if backwards else operation.code action = (code.__doc__ or "") if code else None elif hasattr(operation, "sql"): action = operation.reverse_sql if backwards else operation.sql else: action = "" if backwards: prefix = "Undo " if action is not None: action = str(action).replace("\n", "") elif backwards: action = "IRREVERSIBLE" is_error = True if action: action = " -> " + action truncated = Truncator(action) return prefix + operation.describe() + truncated.chars(40), is_error

9c19aff7c7561e3a82978a272ecdaad40dda5c00

migrate.py

Refs #33476 -- Reformatted code with Black.

django

django/core/management/commands/migrate.py

Python

https://github.com/django/django.git

get_binance_available_quotes_for_each_coin

def get_binance_available_quotes_for_each_coin() -> dict: trading_pairs = _get_trading_pairs() results = defaultdict(list) for pair in trading_pairs: results[pair["baseAsset"]].append(pair["quoteAsset"]) return results @log_start_end(log=logger)

e1b6022b9cf156ffc0697d0d25a5ed2772ea8d68

@log_start_end(log=logger)

binance_model.py

Global plot styles (#1228) * Add default stylesheets * Add terminal style helper class and global style initialization in cfg * Style comments and docstrings * Load rich terminal theme from config file * Add application chart styles to candle charts * Add todos * Remove explicit color setting for some ta charts * Add user styles folder to gitignore * Update default stylesheets * Add matplotlib font manager support * Add matplotlib font manager support * Update docstrings and default style * Update stocks candle chart formatting (return fig to style title) * Style common ta overlap view * Make up and down market colors a part of the style helper * Update stylesheets * Style common ta volume view * Style common ta momentum view * Style common ta trend indicators view * Style common ta volatility view * Style common ta volume view * Style common ta custom indicators view * Fix styling bugs and remove the obvious time x lablel * Style charts in the covid menu * Set legend position to upper left in the mpl stylesheet * Add mpl_rcparams configs for parameters not covered by stylesheets * Remove font configuration files * Update style class utility functions * Implement passing external axes and style utility usage in ema & stoch * Add theme watermark and output helpers * Rename style to theme * Update helper usage in ta/ma and ta/stoch * Update style to theme in sample menus * Style forex (#1305) * Make tight layout optional 'cause mplfinance doesn't support it * Apply global style to the forex menu * Update code layout in oanda view and black * Style common TA (#1315) * Make tight layout optional 'cause mplfinance doesn't support it * Apply global style to the forex menu * Add linewidth to theme for use in mpf's addplots * Add vwap to the stocks notebook api * Update common/ta overlap to follow charting style * Apply style on TerminalStyle init * Enable infrastructure for excluding non-trading days from plots * Update notebook api to include there and resolve bandit warning * Update ta/common/overlap to exclude non-trading days * Enable external ax, style and non-trading days in common/ta/momentum * Enable external ax, style and non-trading days in common/ta/trend * Update vwap to the argument naming convention * Enable external ax, style and non-trading days in common/ta/volatility * Enable external ax, style and non-trading days in common/ta/volume * Enable external ax, style and non-trading days in common/ta/custom * Fix controller tests * Forgot to disable rewriting of the cassettes ... * Fix controller errors that came up because a merge conflict * Fix price label position on fib * Fix line having wrong x values in fib Co-authored-by: Colin Delahunty <[email protected]> * Style economy (#1308) * Began converting * Added alphavan_view * Added CNN View * Updated nasdaq view, fixed glitch * Added fred * Refactored URL * Theo's requested changes * Updated docstrings * Updated tests * Fixed pylint * Fixed tests * Theo changes * Econ Fix * Refactor chart style for Crypto context (#1306) * Remove mock for gff * Mock visualize_output helper function * Refactor * Fix plot helper * Update legend loc * Refactor mplfinance candle plot * Fix errors in the helper function * Fix binbook having the wrong call_ function name * Remove hardcoded style params * Resolve kwargs future warning from pandas * Remove warnings import Co-authored-by: Theodore Aptekarev <[email protected]> * funds + custom (#1311) * funds + custom * cleanup cleanup everybody everywhere * Fix external axes conditional and a typo Co-authored-by: Theodore Aptekarev <[email protected]> * Add external axes mode to covid charts (#1328) * Add portfolio menu plots (#1318) * Portfolio view plots (commenting out report stuff) * PA Menu broken. Commenting out and fix tests * portfolio optimization * comment out commented api line * Add notes on disabling the pa submenu Co-authored-by: Theodore Aptekarev <[email protected]> * Plot updates in common BA (#1335) * Add external axes support to common/ba/finbrain * Add external axes support to common/ba/twitter * Add external axes support to common/ba/google * Add external axes support to common/ba/sentimentinvestor * Add sentimentinvestor to the notebooks API * Fix tests * Etf refactor (#1323) * Refactored no ETF * Fixed gtff import * Fixed tests * Fix pie chart style * Refactored etf/candle * Added pylint fix * Fixed tests * Update candle chart layout * Update etf controller test * Remove strange binary file Co-authored-by: Theodore Aptekarev <[email protected]> * Expose ETF candle function in the notebooks API * Common BA and Common QA charts update (#1342) * Add external axes support to common/ba/finbrain * Add external axes support to common/ba/twitter * Add external axes support to common/ba/google * Add external axes support to common/ba/sentimentinvestor * Add sentimentinvestor to the notebooks API * Fix tests * Update stylesheet files * Refactor charts for common/qa * Update the forgotten line plot * Update tests * Add missing arg to a docstring * Remove scientific notation * Black imports Co-authored-by: Minh Hoang <[email protected]> * Options refactor (#1324) * Fixed alphaquery_view * finished options * Fixed pylint * Fixed tests * Fixed tests * Fixed tests * update yfinance * Tradier + Chartexchange * change mocks from gtff to theme.visualize output * tests Co-authored-by: Theodore Aptekarev <[email protected]> Co-authored-by: james <[email protected]> * Refactor Stocks menu (#1325) * Fix backtesting menu * Refactor comparison analysis * Refactor Dark pool shorts * Refactor rest of menu * Fix test * Fix tests failing * Fix tests fail * Fix test failing * Remove record mode=none to record new output * Rewrite test output * Rewrite test outputs * Adding more rewritten test output * Mock plt.show * Mock missing plt.show * Missing @pytest.mark.vcr * Updating tests : common/behavioural_analysis/finbrain * Improve notebooks API coverage for CA and DPS * Silence annoying flake8 warning Co-authored-by: Chavithra PARANA <[email protected]> Co-authored-by: Theodore Aptekarev <[email protected]> * Charts update for common/pred (#1344) * Add external axes support to common/ba/finbrain * Add external axes support to common/ba/twitter * Add external axes support to common/ba/google * Add external axes support to common/ba/sentimentinvestor * Add sentimentinvestor to the notebooks API * Fix tests * Update stylesheet files * Refactor charts for common/qa * Update the forgotten line plot * Update tests * Add missing arg to a docstring * Style pred helper and controllers * Update ETS plot * Update plots in KNN and pred helper * Update plot and pretty table for arima * Update plot for common/pred/regression * Refactor mc_view * Fix linting * Fix mypy * Move plot title to the axis level to make more vertical space Co-authored-by: Minh Hoang <[email protected]> Co-authored-by: jmaslek <[email protected]> * linter * Update common/ba test data * Change etf candle to match stock candle * try updating sia test Co-authored-by: Colin Delahunty <[email protected]> Co-authored-by: jmaslek <[email protected]> Co-authored-by: minhhoang1023 <[email protected]> Co-authored-by: Minh Hoang <[email protected]> Co-authored-by: Chavithra PARANA <[email protected]>

OpenBBTerminal

gamestonk_terminal/cryptocurrency/due_diligence/binance_model.py

Python

https://github.com/OpenBB-finance/OpenBBTerminal.git

test_search_tsquery_chars

def test_search_tsquery_chars(self): # Simple quote should be escaped inside each tsquery term. results = self.backend.search("L'amour piqué par une abeille", models.Book) self.assertUnsortedListEqual([r.title for r in results], []) results = self.backend.search("'starting quote", models.Book) self.assertUnsortedListEqual([r.title for r in results], []) results = self.backend.search("ending quote'", models.Book) self.assertUnsortedListEqual([r.title for r in results], []) results = self.backend.search("double quo''te", models.Book) self.assertUnsortedListEqual([r.title for r in results], []) results = self.backend.search("triple quo

d10f15e55806c6944827d801cd9c2d53f5da4186

test_postgres_backend.py

Reformat with black

wagtail

wagtail/search/tests/test_postgres_backend.py

Python

https://github.com/wagtail/wagtail.git

sample_weights_mismatch

def sample_weights_mismatch(self): # If there is a mismatch between sample weight mode and the placeholders # created, then recompile the sub-graphs that depend on sample weights. return ( self.sample_weight_mode is not None and self.sample_weight is None ) or ( self.sample_weight_mode is None and self.sample_weight is not None )

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training_v1.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/engine/training_v1.py

Python

https://github.com/keras-team/keras.git

set_undefined_options

def set_undefined_options(self, src_cmd, *option_pairs): # Option_pairs: list of (src_option, dst_option) tuples src_cmd_obj = self.distribution.get_command_obj(src_cmd) src_cmd_obj.ensure_finalized() for (src_option, dst_option) in option_pairs: if getattr(self, dst_option) is None: setattr(self, dst_option, getattr(src_cmd_obj, src_option))

8198943edd73a363c266633e1aa5b2a9e9c9f526

cmd.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/distutils/cmd.py

Python

https://github.com/XX-net/XX-Net.git

get_token

def get_token(request): if "CSRF_COOKIE" in request.META: csrf_secret = request.META["CSRF_COOKIE"] # Since the cookie is being used, flag to send the cookie in # process_response() (even if the client already has it) in order to # renew the expiry timer. request.META["CSRF_COOKIE_NEEDS_UPDATE"] = True else: csrf_secret = _add_new_csrf_cookie(request) return _mask_cipher_secret(csrf_secret)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

csrf.py

Refs #33476 -- Reformatted code with Black.

django

django/middleware/csrf.py

Python

https://github.com/django/django.git

as_sql

def as_sql(self, compiler, connection): result = [] result_params = [] if self.connector == AND: full_needed, empty_needed = len(self.children), 1 else: full_needed, empty_needed = 1, len(self.children) for child in self.children: try: sql, params = compiler.compile(child) except EmptyResultSet: empty_needed -= 1 else: if sql: result.append(sql) result_params.extend(params) else: full_needed -= 1 # Check if this node matches nothing or everything. # First check the amount of full nodes and empty nodes # to make this node empty/full. # Now, check if this node is full/empty using the # counts. if empty_needed == 0: if self.negated: return "", [] else: raise EmptyResultSet if full_needed == 0: if self.negated: raise EmptyResultSet else: return "", [] conn = " %s " % self.connector sql_string = conn.join(result) if sql_string: if self.negated: # Some backends (Oracle at least) need parentheses # around the inner SQL in the negated case, even if the # inner SQL contains just a single expression. sql_string = "NOT (%s)" % sql_string elif len(result) > 1 or self.resolved: sql_string = "(%s)" % sql_string return sql_string, result_params

9c19aff7c7561e3a82978a272ecdaad40dda5c00

where.py

Refs #33476 -- Reformatted code with Black.

django

django/db/models/sql/where.py

Python

https://github.com/django/django.git

test_pageurl_with_unknown_site

def test_pageurl_with_unknown_site(self): page = Page.objects.get(url_path="/home/events/") tpl = template.Template( ) # 'request' object in context, but site is None request = HttpRequest() request.META["HTTP_HOST"] = "unknown.example.com" request.META["SERVER_PORT"] = 80 result = tpl.render(template.Context({"page": page, "request": request})) self.assertIn('<a href="/events/">Events</a>', result)

d10f15e55806c6944827d801cd9c2d53f5da4186

tests.py

Reformat with black

wagtail

wagtail/core/tests/tests.py

Python

https://github.com/wagtail/wagtail.git

get_labels

def get_labels(self): return ["O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-MISC", "I-MISC"], \ self.BUILDER_CONFIGS[self.name]['pos_tags']

7b455cce47204d4d664deea9661670a838ec8d35

conll2002.py

feat: add conll2002 dataset (#1561) Co-authored-by: Zeyu Chen <[email protected]>

PaddleNLP

paddlenlp/datasets/conll2002.py

Python

https://github.com/PaddlePaddle/PaddleNLP.git

format_value

def format_value(self, value): if value == "" or value is None: return None if self.is_localized: return formats.localize_input(value) return str(value)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

widgets.py

Refs #33476 -- Reformatted code with Black.

django

django/forms/widgets.py

Python

https://github.com/django/django.git

__iter__

def __iter__(self) -> Iterator[tuple[Widget, Region, Region, Size, Size]]: layers = sorted(self.map.items(), key=lambda item: item[1].order, reverse=True) intersection = Region.intersection for widget, (region, _order, clip, virtual_size, container_size) in layers: yield ( widget, intersection(region, clip), region, virtual_size, container_size, )

1a20b9de7d4cef7f93e4500757d3fb42e680f40c

_compositor.py

docstring

textual

src/textual/_compositor.py

Python

https://github.com/Textualize/textual.git

_express_axis

def _express_axis(self, axis, frame): try: ax_mat = axis.to_matrix(self.parent_interframe) except ValueError: ax_mat = axis.to_matrix(self.child_interframe) try: self.parent_interframe.dcm(frame) # Check if connected int_frame = self.parent_interframe except ValueError: int_frame = self.child_interframe return self._to_vector(ax_mat, int_frame).express(frame)

7c199e306648513c13c9b5c5b5fad06e5f1c3020

joint.py

Fix failing test and simplify joint orient methods

sympy

sympy/physics/mechanics/joint.py

Python

https://github.com/sympy/sympy.git

run_api_experiment

def run_api_experiment(input_features, output_features): config = { "input_features": input_features, "output_features": output_features, "combiner": {"type": "concat", "output_size": 14}, "training": {"epochs": 2}, } model = LudwigModel(config) return model @pytest.fixture(scope="module")

69604268c2ddc06a4ee0b3dce0e05a8fb73b5d16

@pytest.fixture(scope="module")

test_visualization_api.py

Rename fc_size to output_size (#1641) * Rename fc_size to output_size * Responding to comments

ludwig

tests/integration_tests/test_visualization_api.py

Python

https://github.com/ludwig-ai/ludwig.git

label_axes

def label_axes(ax, text): ax.text(.5, .5, text, transform=ax.transAxes, horizontalalignment="center", verticalalignment="center") ax.tick_params(bottom=False, labelbottom=False, left=False, labelleft=False) ############################################################################## # Fixed axes sizes; fixed paddings. fig = plt.figure(figsize=(6, 6)) fig.suptitle("Fixed axes sizes, fixed paddings") # Sizes are in inches. horiz = [Size.Fixed(1.), Size.Fixed(.5), Size.Fixed(1.5), Size.Fixed(.5)] vert = [Size.Fixed(1.5), Size.Fixed(.5), Size.Fixed(1.)] rect = (0.1, 0.1, 0.8, 0.8) # Divide the axes rectangle into a grid with sizes specified by horiz * vert. div = Divider(fig, rect, horiz, vert, aspect=False) # The rect parameter will actually be ignored and overridden by axes_locator. ax1 = fig.add_axes(rect, axes_locator=div.new_locator(nx=0, ny=0)) label_axes(ax1, "nx=0, ny=0") ax2 = fig.add_axes(rect, axes_locator=div.new_locator(nx=0, ny=2)) label_axes(ax2, "nx=0, ny=2") ax3 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, ny=2)) label_axes(ax3, "nx=2, ny=2") ax4 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, nx1=4, ny=0)) label_axes(ax4, "nx=2, nx1=4, ny=0") ############################################################################## # Axes sizes that scale with the figure size; fixed paddings. fig = plt.figure(figsize=(6, 6)) fig.suptitle("Scalable axes sizes, fixed paddings") horiz = [Size.Scaled(1.5), Size.Fixed(.5), Size.Scaled(1.), Size.Scaled(.5)] vert = [Size.Scaled(1.), Size.Fixed(.5), Size.Scaled(1.5)] rect = (0.1, 0.1, 0.8, 0.8) # Divide the axes rectangle into a grid with sizes specified by horiz * vert. div = Divider(fig, rect, horiz, vert, aspect=False) # The rect parameter will actually be ignored and overridden by axes_locator. ax1 = fig.add_axes(rect, axes_locator=div.new_locator(nx=0, ny=0)) label_axes(ax1, "nx=0, ny=0") ax2 = fig.add_axes(rect, axes_locator=div.new_locator(nx=0, ny=2)) label_axes(ax2, "nx=0, ny=2") ax3 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, ny=2)) label_axes(ax3, "nx=2, ny=2") ax4 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, nx1=4, ny=0)) label_axes(ax4, "nx=2, nx1=4, ny=0") plt.show()

162bd59f50a9c59a51574aee5dc9e932133bb971

simple_axes_divider1.py

DOC: More capitalization of Axes In line with #18726. Triggered by #22242.

matplotlib

examples/axes_grid1/simple_axes_divider1.py

Python

https://github.com/matplotlib/matplotlib.git

max_mireds

def max_mireds(self) -> int: max_mireds = self.cluster.get("color_temp_physical_max", self.MAX_MIREDS) if max_mireds == 0: self.warning( "[Max mireds is 0, setting to %s] Please open an issue on the quirks repo to have this device corrected", self.MAX_MIREDS, ) max_mireds = self.MAX_MIREDS return max_mireds

83c6a7e18b1b0e4d5a302e304f117dee11d3aa51

lighting.py

Fix invalid min and max color temp in bad ZHA light devices (#81604) * Fix ZHA default color temps * update test

core

homeassistant/components/zha/core/channels/lighting.py

Python

https://github.com/home-assistant/core.git

get_names

def get_names(adtype): listnames = [] names = adtype.names for name in names: current = adtype[name] if current.names is not None: listnames.append((name, tuple(get_names(current)))) else: listnames.append(name) return tuple(listnames)

569fc6a40ea53054409e00c7d1c0e7f5f53cb0ce

recfunctions.py

Fix docstring and examples for rfn.get_names*

numpy

numpy/lib/recfunctions.py

Python

https://github.com/numpy/numpy.git

pipe

def pipe(*, duplex=False, overlapped=(True, True), bufsize=BUFSIZE): address = tempfile.mktemp( prefix=r'\\.\pipe\python-pipe-{:d}-{:d}-'.format( os.getpid(), next(_mmap_counter))) if duplex: openmode = _winapi.PIPE_ACCESS_DUPLEX access = _winapi.GENERIC_READ | _winapi.GENERIC_WRITE obsize, ibsize = bufsize, bufsize else: openmode = _winapi.PIPE_ACCESS_INBOUND access = _winapi.GENERIC_WRITE obsize, ibsize = 0, bufsize openmode |= _winapi.FILE_FLAG_FIRST_PIPE_INSTANCE if overlapped[0]: openmode |= _winapi.FILE_FLAG_OVERLAPPED if overlapped[1]: flags_and_attribs = _winapi.FILE_FLAG_OVERLAPPED else: flags_and_attribs = 0 h1 = h2 = None try: h1 = _winapi.CreateNamedPipe( address, openmode, _winapi.PIPE_WAIT, 1, obsize, ibsize, _winapi.NMPWAIT_WAIT_FOREVER, _winapi.NULL) h2 = _winapi.CreateFile( address, access, 0, _winapi.NULL, _winapi.OPEN_EXISTING, flags_and_attribs, _winapi.NULL) ov = _winapi.ConnectNamedPipe(h1, overlapped=True) ov.GetOverlappedResult(True) return h1, h2 except: if h1 is not None: _winapi.CloseHandle(h1) if h2 is not None: _winapi.CloseHandle(h2) raise # Wrapper for a pipe handle

8198943edd73a363c266633e1aa5b2a9e9c9f526

windows_utils.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/asyncio/windows_utils.py

Python

https://github.com/XX-net/XX-Net.git

test_unload_config_entry

async def test_unload_config_entry(hass, entry, lcn_connection): await hass.config_entries.async_unload(entry.entry_id) assert hass.states.get("light.light_output1").state == STATE_UNAVAILABLE

d5ec2fe842411aea086333889c4357d8cd6cc394

test_light.py

Add tests for LCN light platform (#64741)

core

tests/components/lcn/test_light.py

Python

https://github.com/home-assistant/core.git

real_get_relative_path

def real_get_relative_path(config, path): requests_pathname = config.requests_pathname_prefix if requests_pathname == "/" and path == "": return "/" if requests_pathname != "/" and path == "": return requests_pathname if not path.startswith("/"): raise exceptions.UnsupportedRelativePath( .format( path ) ) return "/".join([requests_pathname.rstrip("/"), path.lstrip("/")])

cd13276a2df1c33b5daabdd3a07f57e3128e471c

_get_paths.py

Added dash.get_relative_path, dash.strip_relative_path, dash.get_asset_url

dash

dash/_get_paths.py

Python

https://github.com/plotly/dash.git

load_model

def load_model(filepath, custom_objects=None, compile=True, **kwargs): if str(filepath).endswith(".keras") and zipfile.is_zipfile(filepath): if kwargs: raise ValueError( "The following argument(s) are not supported " f"with the native Keras format: {list(kwargs.keys())}" ) return saving_lib.load_model( filepath, custom_objects=custom_objects, compile=compile ) # Legacy case. return legacy_sm_saving_lib.load_model( filepath, custom_objects=custom_objects, compile=compile, **kwargs )

c9068087d9142bab573e0c300bf9874a957accff

saving_api.py

Prepare public API surface for v3 saving. PiperOrigin-RevId: 484397600

keras

keras/saving/saving_api.py

Python

https://github.com/keras-team/keras.git

test_cache_invalidation

def test_cache_invalidation() -> None: ledger_store = DictLedgerStore() user_key = b"1483" ledger = DataSubjectLedger.get_or_create(store=ledger_store, user_key=user_key) assert ledger.delta == 1e-6, "The cache has been changed or is invalid." assert ( ledger._cache_constant2epsilon.all() ), "There is a zero epsilon value in the cache- major security flaw." assert ( ledger._cache_constant2epsilon > 0 ).all(), "Negative epsilon value in the cache- major security flaw."

61f4138eeb028287425f6007d692bf7faa808e75

data_subject_ledger_test.py

Add tests for ledger and cache

PySyft

packages/syft/tests/syft/core/adp/data_subject_ledger_test.py

Python

https://github.com/OpenMined/PySyft.git

test_cancellation

def test_cancellation(self): deferred: "Deferred[str]" = Deferred() wrapper_deferred = stop_cancellation(deferred) # Cancel the new `Deferred`. wrapper_deferred.cancel() self.assertTrue(wrapper_deferred.called) self.failureResultOf(wrapper_deferred, CancelledError) self.assertFalse( deferred.called, "Original `Deferred` was unexpectedly cancelled." ) # Now make the inner `Deferred` fail. # The `Failure` must be consumed, otherwise unwanted tracebacks will be printed # in logs. deferred.errback(ValueError("abc")) self.assertIsNone(deferred.result, "`Failure` was not consumed")

91bc15c772d22fbe814170ab2e0fdbfa50f9c372

test_async_helpers.py

Add `stop_cancellation` utility function (#12106)

synapse

tests/util/test_async_helpers.py

Python

https://github.com/matrix-org/synapse.git

test_from

def test_from(self) -> None: self._create_users_with_media(20, 2) channel = self.make_request( "GET", self.url + "?from=5", access_token=self.admin_user_tok, ) self.assertEqual(200, channel.code, msg=channel.json_body) self.assertEqual(channel.json_body["total"], 20) self.assertEqual(len(channel.json_body["users"]), 15) self.assertNotIn("next_token", channel.json_body) self._check_fields(channel.json_body["users"])

c97042f7eef3748e17c90e48a4122389a89c4735

test_statistics.py

Use literals in place of `HTTPStatus` constants in tests (#13469)

synapse

tests/rest/admin/test_statistics.py

Python

https://github.com/matrix-org/synapse.git

get_internal_block_refs

def get_internal_block_refs(self) -> List[ObjectRef[Block]]: return self._plan.execute().get_blocks()

35a157948efa7ba1adf1d1507c2af1d6d84a7db7

dataset.py

Lay the groundwork for lazy dataset optimization (no behavior changes) (#22233) This PR refactors Dataset execution to enable lazy mode in the future, which can reduce memory usage in large-scale ingest pipelines. There should be no behavior changes in this PR. Many of the optimizations are also punted for future work.

ray

python/ray/data/dataset.py

Python

https://github.com/ray-project/ray.git

get_group_tag_value_count

def get_group_tag_value_count(self, group, environment_id, key): raise NotImplementedError

72e351082168f68cbaa5700a51e8ed577222e887

base.py

feat(perf_issues): Fix `GroupTagKeyDetailsEndpoint` to work for performance issues (#38860) This allows this endpoint to return results for performance issues.

sentry

src/sentry/tagstore/base.py

Python

https://github.com/getsentry/sentry.git

_create_local_rank_map

def _create_local_rank_map(self) -> Dict: rank_mapping = {} ip_dict = defaultdict(int) for world_rank in range(len(self.worker_group)): worker = self.worker_group.workers[world_rank] node_ip = worker.metadata.node_ip rank_mapping[world_rank] = ip_dict[node_ip] ip_dict[node_ip] += 1 return rank_mapping

80ae651f259e1ea13c21b285d6bfcc7fd834ef9c

backend_executor.py

[Train] Clean up `ray.train` package (#25566)

ray

python/ray/train/_internal/backend_executor.py

Python

https://github.com/ray-project/ray.git

iloc

def iloc(self): from dask.dataframe.indexing import _iLocIndexer # For dataframes with unique column names, this will be transformed into a __getitem__ call return _iLocIndexer(self)

cccb9d8d8e33a891396b1275c2448c352ef40c27

core.py

absolufy-imports - No relative - PEP8 (#8796) Conversation in https://github.com/dask/distributed/issues/5889

dask

dask/dataframe/core.py

Python

https://github.com/dask/dask.git

check_for_non_existent_openapi_endpoints

def check_for_non_existent_openapi_endpoints(self) -> None: openapi_paths = set(get_openapi_paths()) undocumented_paths = openapi_paths - self.checked_endpoints undocumented_paths -= self.buggy_documentation_endpoints undocumented_paths -= self.pending_endpoints try: self.assert_length(undocumented_paths, 0) except AssertionError: # nocoverage msg = "The following endpoints have been documented but can't be found in urls.py:" for undocumented_path in undocumented_paths: msg += f"\n + {undocumented_path}" raise AssertionError(msg)

b0ce4f1bce8031881addecb1e86073483517f392

test_openapi.py

docs: Fix many spelling mistakes. Signed-off-by: Anders Kaseorg <[email protected]>

zulip

zerver/tests/test_openapi.py

Python

https://github.com/zulip/zulip.git

_send_connect

def _send_connect(self, identifier): # type: (int) -> List[XCPScannerResult] all_slaves = [] body = Connect(connection_mode=0x00) xcp_req_and_res_list = self._scan(identifier, body, 0xFF, ConnectPositiveResponse) for req_and_res in xcp_req_and_res_list: result = XCPScannerResult(response_id=req_and_res[1].identifier, request_id=identifier) all_slaves.append(result) log_automotive.info( "Detected XCP slave for broadcast identifier: " + str( identifier) + "\nResponse: " + str(result)) if len(all_slaves) == 0: log_automotive.info( "No XCP slave detected for identifier: " + str(identifier)) return all_slaves

495b21f2867e48286767085c8cf2918e4092e9dc

scanner.py

Add Automotive Logger for all debug outputs of the automotive layer

scapy

scapy/contrib/automotive/xcp/scanner.py

Python

https://github.com/secdev/scapy.git

_calc_mode

def _calc_mode(path): try: mode = _path_stat(path).st_mode except OSError: mode = 0o666 # We always ensure write access so we can update cached files # later even when the source files are read-only on Windows (#6074) mode |= 0o200 return mode

8198943edd73a363c266633e1aa5b2a9e9c9f526

_bootstrap_external.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/importlib/_bootstrap_external.py

Python

https://github.com/XX-net/XX-Net.git

download

def download(self, url_or_urls): download_config = self.download_config.copy() download_config.extract_compressed_file = False # Default to using 16 parallel thread for downloading # Note that if we have less than or equal to 16 files, multi-processing is not activated if download_config.num_proc is None: download_config.num_proc = 16 if download_config.download_desc is None: download_config.download_desc = "Downloading data" download_func = partial(self._download, download_config=download_config) start_time = datetime.now() downloaded_path_or_paths = map_nested( download_func, url_or_urls, map_tuple=True, num_proc=download_config.num_proc, parallel_min_length=16, disable_tqdm=not is_progress_bar_enabled(), desc="Downloading data files", ) duration = datetime.now() - start_time logger.info(f"Downloading took {duration.total_seconds() // 60} min") url_or_urls = NestedDataStructure(url_or_urls) downloaded_path_or_paths = NestedDataStructure(downloaded_path_or_paths) self.downloaded_paths.update(dict(zip(url_or_urls.flatten(), downloaded_path_or_paths.flatten()))) start_time = datetime.now() self._record_sizes_checksums(url_or_urls, downloaded_path_or_paths) duration = datetime.now() - start_time logger.info(f"Checksum Computation took {duration.total_seconds() // 60} min") return downloaded_path_or_paths.data

a5e05ccffa49051cbad84c007f31725ad4b2e7f7

download_manager.py

Fix multiprocessing in map_nested (#4740) * Do multiprocessing in map_nested when num_proc >= len(iterable) * Add missing type hint * Update docstring * Fix tests * Document download default and fix docstring * Fix docstring syntax * Add tests * Fix test for Python<3.8 * Download with multiprocessing only if at least 16 files * Revert test fix * Rename multiprocessing_min_length to parallel_min_length

datasets

src/datasets/download/download_manager.py

Python

https://github.com/huggingface/datasets.git

execute_test_case

def execute_test_case(self, test_case): # type: (AutomotiveTestCaseABC) -> None test_case.pre_execute( self.socket, self.target_state, self.configuration) try: test_case_kwargs = self.configuration[test_case.__class__.__name__] except KeyError: test_case_kwargs = dict() log_interactive.debug("[i] Execute test_case %s with args %s", test_case.__class__.__name__, test_case_kwargs) test_case.execute(self.socket, self.target_state, **test_case_kwargs) test_case.post_execute( self.socket, self.target_state, self.configuration) self.check_new_states(test_case) self.check_new_testcases(test_case)

f549b66f3f523c1c1a4a21aadc40c6153c5ad77e

executor.py

Stabilize UDS_Scanner unit tests for appveyor (#3615) * Different approach * add event * fix test * cleanup * cleanup * lower timeout of GMLAN Scanner * apply feedback

scapy

scapy/contrib/automotive/scanner/executor.py

Python

https://github.com/secdev/scapy.git

backfill

def backfill(self, limit=None): warnings.warn( "backfill is deprecated and will be removed in a future version. " "Use bfill instead.", FutureWarning, stacklevel=find_stack_level(inspect.currentframe()), ) return self.bfill(limit=limit)

709f274245dc2f3fe2d91ad53a4cfa57f9d41d59

groupby.py

DOC: Add deprecation infos to deprecated functions (#48599) * DOC: Add deprecation infos to deprecated functions * Add sections * Fix

pandas

pandas/core/groupby/groupby.py

Python

https://github.com/pandas-dev/pandas.git

disable_tf_random_generator

def disable_tf_random_generator(): global _USE_GENERATOR_FOR_RNG _USE_GENERATOR_FOR_RNG = False

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/backend.py

Python

https://github.com/keras-team/keras.git

test_exception_handling

def test_exception_handling(): # Raising an error in a subprocess should propagate to a runtime error in the master process. with pytest.raises(RuntimeError) as ex_info: isolated.call(fail) # The exception should include the offending function's name and the child's traceback which itself includes the # breaking line of code and the exception type and message (in that order). Unfortunately, there seems to be a bug # in pytest's exception rewriting which makes the exception type and message unverifiable when ran under pytest. assert ex_info.match(r) # It should have removed the following line. assert "Traceback (most recent call last)" not in str(ex_info.value)

f4a8368fb0d1f4e0a902cccfabccde3c8c0d93d1

test_isolation.py

Allow sources to be formatted using yapf 0.32.0 Allow sources to be formatted using yapf 0.32.0 in addition to currently pinned 0.31.0. Version 0.32.0 enables `blank_line_before_nested_class_or_def` by default. As this was disabled by default in earlier versions, we now need to explicitly turn it off in configuration. The two versions also seem to disagree about alignment of split string fragments (same line in 0.31, vertically aligned in 0.32). In our code, some cases look better vertically aligned (disable yapf on those via comment to prevent changes on older version), while the remaining cases should have been merged into a single string in the first place; so do that now.

pyinstaller

tests/unit/test_isolation.py

Python

https://github.com/pyinstaller/pyinstaller.git

_set_gradient_checkpointing

def _set_gradient_checkpointing(self, module, value=False): if isinstance(module, (Wav2Vec2ConformerEncoder, Wav2Vec2ConformerFeatureEncoder)): module.gradient_checkpointing = value WAV2VEC2_CONFORMER_START_DOCSTRING = r WAV2VEC2_CONFORMER_INPUTS_DOCSTRING = r @add_start_docstrings( "The bare Wav2Vec2Conformer Model transformer outputting raw hidden-states without any specific head on top.", WAV2VEC2_CONFORMER_START_DOCSTRING, )

5a9957358cebd616e58b2d1ab3b887c2f2793b45

@add_start_docstrings( "The bare Wav2Vec2Conformer Model transformer outputting raw hidden-states without any specific head on top.", WAV2VEC2_CONFORMER_START_DOCSTRING, )

modeling_wav2vec2_conformer.py

Add Wav2Vec2Conformer (#16812) * save intermediate * add wav2vec2 conformer * add more code * more * first test passes * make all checkpoints work * update * up * more clean ups * save clean-up * save clean-up * save more * remove bogus * finalize design conformer * remove vision * finish all tests * more changes * finish code * add doc tests * add slow tests * fix autoconfig test * up * correct docstring * up * update * fix * Apply suggestions from code review Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Anton Lozhkov <[email protected]> * Update docs/source/en/model_doc/wav2vec2-conformer.mdx * upload * save copied from * correct configs * fix model outputs * add to docs * fix imports * finish * finish code * correct copied from * correct again * correct make fix * improve make fix copies * save * correct fix copy from * correct init structure * correct * fix import * apply suggestions Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Anton Lozhkov <[email protected]>

transformers

src/transformers/models/wav2vec2_conformer/modeling_wav2vec2_conformer.py

Python

https://github.com/huggingface/transformers.git

__call__

def __call__(self, results): img = results['img'] if self.to_float32: img = img.astype(np.float32) results['img_path'] = None results['img'] = img height, width = img.shape[:2] results['height'] = height results['width'] = width results['ori_height'] = height results['ori_width'] = width return results @TRANSFORMS.register_module()

c71a160c5193b92f6a4f56c113e96b63decf8354

@TRANSFORMS.register_module()

loading.py

Refacter Visualization

mmdetection

mmdet/datasets/pipelines/loading.py

Python

https://github.com/open-mmlab/mmdetection.git

set_linestyle

def set_linestyle(self, ls): try: dashes = [mlines._get_dash_pattern(ls)] except ValueError: try: dashes = [mlines._get_dash_pattern(x) for x in ls] except ValueError as err: raise ValueError('Do not know how to convert {!r} to ' 'dashes'.format(ls)) from err # get the list of raw 'unscaled' dash patterns self._us_linestyles = dashes # broadcast and scale the lw and dash patterns self._linewidths, self._linestyles = self._bcast_lwls( self._us_lw, self._us_linestyles)

511232b14b6fca586ac92bc5f8e0b0924f23172f

collections.py

remove redundant string handling

matplotlib

lib/matplotlib/collections.py

Python

https://github.com/matplotlib/matplotlib.git

test_valid_incremental_read_with_slices

def test_valid_incremental_read_with_slices(mocker): slices = [{"1": "1"}, {"2": "2"}] stream_output = [{"k1": "v1"}, {"k2": "v2"}, {"k3": "v3"}] s1 = MockStream( [({"sync_mode": SyncMode.incremental, "stream_slice": s, "stream_state": mocker.ANY}, stream_output) for s in slices], name="s1" ) s2 = MockStream( [({"sync_mode": SyncMode.incremental, "stream_slice": s, "stream_state": mocker.ANY}, stream_output) for s in slices], name="s2" ) state = {"cursor": "value"} mocker.patch.object(MockStream, "get_updated_state", return_value=state) mocker.patch.object(MockStream, "supports_incremental", return_value=True) mocker.patch.object(MockStream, "get_json_schema", return_value={}) mocker.patch.object(MockStream, "stream_slices", return_value=slices) src = MockSource(streams=[s1, s2]) catalog = ConfiguredAirbyteCatalog(streams=[_configured_stream(s1, SyncMode.incremental), _configured_stream(s2, SyncMode.incremental)]) expected = [ # stream 1 slice 1 *_as_records("s1", stream_output), _state({"s1": state}), # stream 1 slice 2 *_as_records("s1", stream_output), _state({"s1": state}), # stream 2 slice 1 *_as_records("s2", stream_output), _state({"s1": state, "s2": state}), # stream 2 slice 2 *_as_records("s2", stream_output), _state({"s1": state, "s2": state}), ] messages = _fix_emitted_at(list(src.read(logger, {}, catalog, state=defaultdict(dict)))) assert expected == messages

f83eca58eaf2129d21b5796a301732ab22675130

test_abstract_source.py

CDK: Fix typing errors (#9037) * fix typing, drop AirbyteLogger * format * bump the version * use logger instead of fixture logger Co-authored-by: Eugene Kulak <[email protected]> Co-authored-by: auganbay <[email protected]>

airbyte

airbyte-cdk/python/unit_tests/sources/test_abstract_source.py

Python

https://github.com/airbytehq/airbyte.git

setup_server

async def setup_server(self): from jina.helper import extend_rest_interface self.app = extend_rest_interface( get_fastapi_app( streamer=self.streamer, title=self.title, description=self.description, no_debug_endpoints=self.no_debug_endpoints, no_crud_endpoints=self.no_crud_endpoints, expose_endpoints=self.expose_endpoints, expose_graphql_endpoint=self.expose_graphql_endpoint, cors=self.cors, logger=self.logger, ) ) with ImportExtensions(required=True): from uvicorn import Config, Server

243639dd2b953fab8654747cbfdf6a0953b95578

gateway.py

refactor: extract gateway app logic into custom gateway class (#5153)

jina

jina/serve/runtimes/gateway/http/gateway.py

Python

https://github.com/jina-ai/jina.git

get_sortable_by

def get_sortable_by(self, request): return ( self.sortable_by if self.sortable_by is not None else self.get_list_display(request) )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

options.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/options.py

Python

https://github.com/django/django.git

test_class_weight_does_not_contains_more_classses

def test_class_weight_does_not_contains_more_classses(): tree = DecisionTreeClassifier(class_weight={0: 1, 1: 10, 2: 20}) # Does not raise tree.fit([[0, 0, 1], [1, 0, 1], [1, 2, 0]], [0, 0, 1])

3605c140af992b6ac52f04f1689c58509cc0b5b2

test_class_weight.py

FIX Support extra class_weights in compute_class_weight (#22595)

scikit-learn

sklearn/utils/tests/test_class_weight.py

Python

https://github.com/scikit-learn/scikit-learn.git

_make_replica_execution_function

def _make_replica_execution_function(model, mode): if mode == ModeKeys.TRAIN: func = model.train_on_batch elif mode == ModeKeys.TEST: func = model.test_on_batch else:

84afc5193d38057e2e2badf9c889ea87d80d8fbf

distributed_training_utils_v1.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/distribute/distributed_training_utils_v1.py

Python

https://github.com/keras-team/keras.git

perform_long_operation

def perform_long_operation(self, func, end_key): thread = threading.Thread(target=_long_func_thread, args=(self, end_key, func), daemon=True) thread.start() return thread

992c5db3bcde5d735b0d00af66d9accfa25a1da7

PySimpleGUI.py

Updated Window.perform_long_operation docstring to warn that Threads are used