Datasets:

semeru

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

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Semeru Lab 7

_expire_url_cache_data

async def _expire_url_cache_data(self) -> None: assert self._worker_run_media_background_jobs now = self.clock.time_msec() logger.debug("Running url preview cache expiry") if not (await self.store.db_pool.updates.has_completed_background_updates()): logger.debug("Still running DB updates; skipping url preview cache expiry") return

57f6c496d0e26b1b455de936bd950e1899a5ae25

preview_url_resource.py

URL preview cache expiry logs: INFO -> DEBUG, text clarifications (#12720)

synapse

synapse/rest/media/v1/preview_url_resource.py

Python

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

reset_format

def reset_format(self): self._check_values_type() for dataset in self.values(): dataset.set_format()

e35be138148333078284b942ccc9ed7b1d826f97

dataset_dict.py

Update docs to new frontend/UI (#3690) * WIP: update docs to new UI * make style * Rm unused * inject_arrow_table_documentation __annotations__ * hasattr(arrow_table_method, "__annotations__") * Update task_template.rst * Codeblock PT-TF-SPLIT * Convert loading scripts * Convert docs to mdx * Fix mdx * Add <Tip> * Convert mdx tables * Fix codeblock * Rm unneded hashlinks * Update index.mdx * Redo dev change * Rm circle ci `build_doc` & `deploy_doc` * Rm unneeded files * Update docs reamde * Standardize to `Example::` * mdx logging levels doc * Table properties inject_arrow_table_documentation * ``` to ```py mdx * Add Tips mdx * important,None -> <Tip warning={true}> * More misc * Center imgs * Update instllation page * `setup.py` docs section * Rm imgs since they are in hf.co * Update docs/source/access.mdx Co-authored-by: Steven Liu <[email protected]> * Update index mdx * Update docs/source/access.mdx Co-authored-by: Steven Liu <[email protected]> * just `Dataset` obj * Addedversion just italics * Update ReadInstruction doc example syntax * Change docstring for `prepare_for_task` * Chore * Remove `code` syntax from headings * Rm `code` syntax from headings * Hashlink backward compatability * S3FileSystem doc * S3FileSystem doc updates * index.mdx updates * Add darkmode gifs * Index logo img css classes * Index mdx dataset logo img size * Docs for DownloadMode class * Doc DownloadMode table * format docstrings * style * Add doc builder scripts (#3790) * add doc builder scripts * fix docker image * Docs new UI actions no self hosted (#3793) * No self hosted * replace doc injection by actual docstrings * Docstring formatted Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Mishig Davaadorj <[email protected]> Co-authored-by: Lysandre Debut <[email protected]> Co-authored-by: Mishig Davaadorj <[email protected]> * Rm notebooks from docs actions since they dont exi * Update tsting branch * More docstring * Chore * bump up node version * bump up node * ``` -> ```py for audio_process.mdx * Update .github/workflows/build_documentation.yml Co-authored-by: Quentin Lhoest <[email protected]> * Uodate dev doc build * remove run on PR * fix action * Fix gh doc workflow * forgot this change when merging master * Update build doc Co-authored-by: Steven Liu <[email protected]> Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Lysandre Debut <[email protected]>

datasets

src/datasets/dataset_dict.py

Python

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

_assert_text_deltas

def _assert_text_deltas(self, scriptrunner, text_deltas): self.assertEqual(text_deltas, scriptrunner.text_deltas())

704eab3478cf69847825b23dabf15813a8ac9fa2

script_runner_test.py

Rename and refactor `Report` machinery (#4141) This refactor renames (almost) everything related to the outdated "report" concept with more precise concepts that we use throughout our code, primarily "script run", "session", and "app".

streamlit

lib/tests/streamlit/scriptrunner/script_runner_test.py

Python

https://github.com/streamlit/streamlit.git

typename

def typename(typ, short=False) -> str: if not isinstance(typ, type): return typename(type(typ)) try: if not typ.__module__ or typ.__module__ == "builtins": return typ.__name__ else: if short: module, *_ = typ.__module__.split(".") else: module = typ.__module__ return module + "." + typ.__name__ except AttributeError: return str(typ)

261bf174931580230717abca93fe172e166cc1e8

utils.py

Add mild typing to common utils functions (#8848)

dask

dask/utils.py

Python

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

test_batch_mapper_pandas_data_format

def test_batch_mapper_pandas_data_format(ds_with_expected_pandas_numpy_df): ds, expected_df, expected_numpy_df = ds_with_expected_pandas_numpy_df

9c39a28ba2f6221ffd8327fa21cb8294f0390fee

test_batch_mapper.py

[AIR][Numpy] Add numpy narrow waist to `Preprocessor` and `BatchMapper` (#28418) Co-authored-by: Eric Liang <[email protected]> Co-authored-by: Clark Zinzow <[email protected]> Co-authored-by: Amog Kamsetty <[email protected]>

ray

python/ray/data/tests/test_batch_mapper.py

Python

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

lexer

def lexer(self) -> Optional[Lexer]: if isinstance(self._lexer, Lexer): return self._lexer try: return get_lexer_by_name( self._lexer, stripnl=False, ensurenl=True, tabsize=self.tab_size, ) except ClassNotFound: return None

f3166e673fe8d40277b804d35d77dcdb760fc3b3

syntax.py

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4

pipenv

pipenv/patched/notpip/_vendor/rich/syntax.py

Python

https://github.com/pypa/pipenv.git

get_placement_group_id

def get_placement_group_id(self) -> Optional[str]: pg_id = self.worker.placement_group_id return pg_id.hex() if not pg_id.is_nil() else None

90cea203befa8f2e86e9c1c18bb3972296358e7b

runtime_context.py

Ray 2.0 API deprecation (#26116) Ray 2.0 API deprecation for: ray.remote(): placement_group ray.remote(): placement_group_bundle_index ray.remote(): placement_group_capture_child_tasks ray.get_dashboard_url() ray.get_resource_ids() ray.disconnect() ray.connect() ray.util.ActorGroup ray.util.ActorPool Add get_xx_id() to return hex (rather than object), and then deprecate the xx_id() (which returns Cython object): the xx here can be node, task etc. ray start: --plasma-store-socket-name ray start: --raylet-socket-name

ray

python/ray/runtime_context.py

Python

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

test_array_vs_scalar_is_equal

def test_array_vs_scalar_is_equal(self): a = np.array([1., 1., 1.]) b = 1. self._test_equal(a, b)

cafec60a5e28af98fb8798049edd7942720d2d74

test_utils.py

ENH: Add strict parameter to assert_array_equal. (#21595) Fixes #9542 Co-authored-by: Bas van Beek <[email protected]>

numpy

numpy/testing/tests/test_utils.py

Python

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

generate_tex_file

def generate_tex_file(expression, environment=None, tex_template=None): if tex_template is None: tex_template = config["tex_template"] if environment is not None: output = tex_template.get_texcode_for_expression_in_env(expression, environment) else: output = tex_template.get_texcode_for_expression(expression) tex_dir = config.get_dir("tex_dir") if not os.path.exists(tex_dir): os.makedirs(tex_dir) result = os.path.join(tex_dir, tex_hash(output)) + ".tex" if not os.path.exists(result): logger.info(f"Writing {expression} to %(path)s", {"path": f"{result}"}) with open(result, "w", encoding="utf-8") as outfile: outfile.write(output) return result

5b11a0e48b5564cdf02c11dd177f7f5c9f0b9f7a

tex_file_writing.py

Improved Error in :mod:`.utils.tex_file_writing` (#2574) * Better Error and insight * Do not use keywords as identifiers * add_tests * Nasty comma * Windows does its own thing * Use os.path.join for windows * Do not log path * Include Insights * Full stop. Co-authored-by: Darylgolden <[email protected]> * Full stop to test data. Co-authored-by: Darylgolden <[email protected]>

manim

manim/utils/tex_file_writing.py

Python

https://github.com/ManimCommunity/manim.git

has_leading_dir

def has_leading_dir(paths): # type: (Iterable[str]) -> bool common_prefix = None for path in paths: prefix, rest = split_leading_dir(path) if not prefix: return False elif common_prefix is None: common_prefix = prefix elif prefix != common_prefix: return False return True

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

unpacking.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/utils/unpacking.py

Python

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

test_stream_with_splitting_properties_with_new_record

def test_stream_with_splitting_properties_with_new_record(self, requests_mock, common_params, api, fake_properties_list): parsed_properties = list(split_properties(fake_properties_list)) self.set_mock_properties(requests_mock, "/properties/v2/deal/properties", fake_properties_list) test_stream = Deals(**common_params) deal_stage_history_response = { "deals": [ { "portalId": 123, "dealId": 111, "isDeleted": False, "associations": None, "properties": { "dealstage": { "value": "appointmentscheduled", "timestamp": 1610533842221, "source": "API", "sourceId": None, "updatedByUserId": None, "versions": [ { "name": "dealstage", "value": "appointmentscheduled", "timestamp": 1610533842221, "source": "API", "sourceVid": [], "requestId": "19f07c43-b187-4ab6-9fab-4a0f261f0a8c", } ], } }, "stateChanges": [], }, { "portalId": 123, "dealId": 112, "isDeleted": False, "associations": None, "properties": { "dealstage": { "value": "appointmentscheduled", "timestamp": 1610533911154, "source": "API", "sourceId": None, "updatedByUserId": None, "versions": [ { "name": "dealstage", "value": "appointmentscheduled", "timestamp": 1610533911154, "source": "API", "sourceVid": [], "requestId": "41a1eeff-569b-4193-ba80-238d3bd13f56", } ], } }, "stateChanges": [], }, ] } requests_mock.register_uri( "GET", test_stream._stage_history.path(), [ { "json": deal_stage_history_response, "status_code": 200, } ], ) ids_list = ["6043593519", "1092593519", "1092593518", "1092593517", "1092593516"] for property_slice in parsed_properties: record_responses = [ { "json": { "results": [ {**self.BASE_OBJECT_BODY, **{"id": id, "properties": {p: "fake_data" for p in property_slice}}} for id in ids_list ], "paging": {}, }, "status_code": 200, } ] requests_mock.register_uri("GET", f"{test_stream.url}?properties={','.join(property_slice)}", record_responses) ids_list.append("1092593513") stream_records = list(test_stream.read_records(sync_mode=SyncMode.incremental)) assert len(stream_records) == 6 @pytest.fixture(name="configured_catalog")

2282a4ae0221b1fb88e16eca8bc14a166998d2d2

@pytest.fixture(name="configured_catalog")

test_source.py

🎉 Source Hubspot: Migrate to CDK (#10177) * migrate SourceHubspot to cdk * refactor discover method * change method name * deleted Client class * remove comment * added get_updated_state * fix setting initial state * fix stream_state dict key * fix cursor_field * change check test case status * refactor streams method * remove comment * remove TODOs * remove comments * fix get_updated_state * refactor chunk_read * override _read_incremental * fix unit tests * remove comments * fix test_check_connection_backoff_on_server_error * fix test_check_connection_backoff_on_server_error 2 * fix test_check_connection_backoff_on_limit_reached * fix unit tests * clear comments * override read method on Source * added comments to overriding methods * some improvements * reafactor overridden _read_incremental * format code * refactor discovery * remove discover * format code 2 * added return types * refactor template stream classes * remove comments * remove _name field * rename api.py to streams.py * move to HttpStream * refactor FormSubmissions * refactor Campaings * refactor ContactsListMemberships * CRMSearchStream refactor * CRMSearchStream refactor 2 * CRMObjectStream refactor * DealStageHistoryStream refactor * Deals refactor * Engagements refactor * path method refactor * refactor authentication * fix check_connection * fix call parse_response * fix Engagements stream * fix CRMSearchStream * fix CRMObjectIncremental stream * override _read_incremental * remove commented codes * format code * update cdk version * fix cursor field * fix unit tests * removed client * clear comments * clear comments 2 * clear comments 3 * clear comments 4 * override backoff_time * remove comment * format code * backoff_time modified * refactor backoff_time * format code * added return typing * format code * removed cursor_paths * bump version * updated spec and def yaml Co-authored-by: auganbay <[email protected]>

airbyte

airbyte-integrations/connectors/source-hubspot/unit_tests/test_source.py

Python

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

test_cartesian_mix_types

def test_cartesian_mix_types(arrays, output_dtype): output = cartesian(arrays) assert output.dtype == output_dtype

86080bbd5fe9513cd42cf34148ea5907a1a9fc6c

test_extmath.py

ENH cartesian accepts mixed dtypes arrays (#25067) Co-authored-by: Christian Lorentzen <[email protected]>

scikit-learn

sklearn/utils/tests/test_extmath.py

Python

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

get_optimizer

def get_optimizer(self) -> List: optimizer1 = get_optimizer( self.config.optimizer, self.config.optimizer_params, self.config.lr_gen, self.model_g ) optimizer2 = get_optimizer( self.config.optimizer, self.config.optimizer_params, self.config.lr_disc, self.model_d ) return [optimizer2, optimizer1]

a0a9279e4b8c306875b6437f853bdcc31ee5f1cf

gan.py

Fix GAN optimizer order commit 212d330929c22d0cd970be2023770dc1e39449ab Author: Edresson Casanova <[email protected]> Date: Fri Apr 29 16:29:44 2022 -0300 Fix unit test commit 44456b0483bf42b1337a8e408ac17af38b26b1fa Author: Edresson Casanova <[email protected]> Date: Fri Apr 29 07:28:39 2022 -0300 Fix style commit d545beadb932758eb7d1c632778fe317d467a6a4 Author: Edresson Casanova <[email protected]> Date: Thu Apr 28 17:08:04 2022 -0300 Change order of HIFI-GAN optimizers to be equal than the original repository commit 657c5442e5339581e5c09168f5212112a342d97a Author: Edresson Casanova <[email protected]> Date: Thu Apr 28 15:40:16 2022 -0300 Remove audio padding before mel spec extraction commit 76b274e6901495ffe62ec745fd8ca9fd010f4857 Merge: 379ccd7b 6233f4fc Author: Edresson Casanova <[email protected]> Date: Wed Apr 27 07:28:48 2022 -0300 Merge pull request #1541 from coqui-ai/comp_emb_fix Bug fix in compute embedding without eval partition commit 379ccd7ba6b7e7b550e7d6acf55760c6d0623ba8 Author: WeberJulian <[email protected]> Date: Wed Apr 27 10:42:26 2022 +0200 returns y_mask in VITS inference (#1540) * returns y_mask * make style

TTS

TTS/vocoder/models/gan.py

Python

https://github.com/coqui-ai/TTS.git

_update_slice

def _update_slice(operand, update, start_indices, update_dims): operand_shape = operand.shape operand = lax.pad(operand, jnp.array(0, operand.dtype), [(0, d, 0) for d in update.shape]) start_indices = tuple(jnp.int32(i) for i in start_indices) t = lax.dynamic_slice(operand, start_indices, update.shape) t = _mask(update, update_dims, t) operand = lax.dynamic_update_slice(operand, t, start_indices) return lax.slice(operand, [0] * operand.ndim, operand_shape)

b64e36b60fca9661ca2c8ae51a56fae07bf5efe6

eigh.py

Make QDWH-eig implementation jit-table. Move QDWH-eig from jax._src.scipy.eigh to jax._src.lax.eigh, in preparation for using it to back `lax.eigh` in a future change. PiperOrigin-RevId: 449362382

jax

jax/_src/lax/eigh.py

Python

https://github.com/google/jax.git

async_step_link

async def async_step_link(self, user_input=None): errors = {} if user_input is not None: # Do not authenticate if the host is already configured self._async_abort_entries_match({CONF_HOST: self._host}) try: info = await authenticate( self.hass, self._host, self._port, self._servers ) except InvalidAuth: errors["base"] = "invalid_auth" except Exception: # pylint: disable=broad-except _LOGGER.exception("Unexpected exception") errors["base"] = "unknown" else: return self.async_create_entry(title=DEFAULT_NAME, data=info) return self.async_show_form(step_id="link", errors=errors)

23264c8fd4a3f8bcff5961ed11cab6388d3c67a4

config_flow.py

Improve roon integraton (#66000) * Update to new library, revise discovery to work with new library, specify port to work with new library. * Move user gui to fallback. * Revise tests. * Handle old config. * Improve debugging, refresh faster on load. * Remove duplicate. * Bump library version. * Fix docstring per review. * Review suggestion Co-authored-by: Martin Hjelmare <[email protected]> * Review suggestion Co-authored-by: Martin Hjelmare <[email protected]> * Add check for duplicate host. * Add error message to strings. * Tidy. * Review changes. * Remove default. Co-authored-by: Martin Hjelmare <[email protected]>

core

homeassistant/components/roon/config_flow.py

Python

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

_test_migrate_stream_data

def _test_migrate_stream_data(self): self.apply_migration() instances = self.model.objects.all().annotate( raw_content=Cast(F("content"), JSONField()) ) for instance in instances: prev_content = self.original_raw_data[instance.id] self.assertBlocksRenamed( old_content=prev_content, new_content=instance.raw_content ) # TODO test multiple operations applied in one migration

ad65741b94f36fbe793cf15f0ab002482070cdb6

test_migrations.py

Add tests for streamfield migration helpers Currently failing due to wagtail-factories being broken on Wagtail 4.1: https://github.com/wagtail/wagtail-factories/issues/65

wagtail

wagtail/tests/streamfield_migrations/test_migrations.py

Python

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

synchronized_output_end_sequence

def synchronized_output_end_sequence(self) -> str: if self.synchronised_output: return TERMINAL_MODES_ANSI_SEQUENCES[Mode.SynchronizedOutput]["end_sync"] return ""

7f27e70440c177b2a047b7f74a78ed5cd5b4b596

_terminal_features.py

[terminal buffering] Address PR feedback

textual

src/textual/_terminal_features.py

Python

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

num_rows

def num_rows(self) -> int: if self._indices is not None: return self._indices.num_rows return self._data.num_rows

445107bae3fcd6ac9eeae503232960fa4ba8ccfd

arrow_dataset.py

Add code examples to API docs (#4168) * add code examples for functions related to the base dataset class * ✨ make style * 🖍 make each code example fully reproducible where applicable * 🖍 show parameter usage for some functions * 🖍 add examples for DatasetInfo functions

datasets

src/datasets/arrow_dataset.py

Python

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

current_cover_position

def current_cover_position(self) -> int | None: position = None if self.roller.type != 7: position = 100 - self.roller.closed_percent return position

10dc38e0ec27f7bef990ee431459342f9c3c52b4

cover.py

Adjust CoverEntity property type hints in components (#73943) * Adjust CoverEntity property type hints in components * Revert changes to rflink * Revert changes to wilight

core

homeassistant/components/acmeda/cover.py

Python

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

TextParser

def TextParser(*args, **kwds) -> TextFileReader: kwds["engine"] = "python" return TextFileReader(*args, **kwds)

e48c9c3973286e257f6da1966c91806d86b917e0

readers.py

TYP: more return annotations for io/* (#47524) * TYP: more return annotations for io/* * import future

pandas

pandas/io/parsers/readers.py

Python

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

_nodb_cursor

def _nodb_cursor(self): conn = self.__class__({**self.settings_dict, "NAME": None}, alias=NO_DB_ALIAS) try: with conn.cursor() as cursor: yield cursor finally: conn.close()

9c19aff7c7561e3a82978a272ecdaad40dda5c00

base.py

Refs #33476 -- Reformatted code with Black.

django

django/db/backends/base/base.py

Python

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

test_command_runner_interface_abstraction_violation

def test_command_runner_interface_abstraction_violation(): cmd_runner_interface_public_functions = dir(CommandRunnerInterface) allowed_public_interface_functions = { func for func in cmd_runner_interface_public_functions if not func.startswith("_") } for subcls in [SSHCommandRunner, DockerCommandRunner, KubernetesCommandRunner]: subclass_available_functions = dir(subcls) subclass_public_functions = { func for func in subclass_available_functions if not func.startswith("_") } assert allowed_public_interface_functions == subclass_public_functions

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

test_command_runner.py

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

ray

python/ray/tests/test_command_runner.py

Python

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

resolve_granularity

def resolve_granularity(self) -> Granularity: start = cast(datetime, self.params["start"]) end = cast(datetime, self.params["end"]) duration = (end - start).seconds # TODO: could probably allow some leeway on the start & end (a few minutes) and use a bigger granularity # eg. yesterday at 11:59pm to tomorrow at 12:01am could still use the day bucket # Query is at least an hour if start.minute == end.minute == 0 and duration % 3600 == 0: # we're going from midnight -> midnight which aligns with our daily buckets if start.hour == end.hour == 0 and duration % 86400 == 0: granularity = 86400 # we're roughly going from start of hour -> next which aligns with our hourly buckets else: granularity = 3600 # We're going from one random minute to another, we could use the 10s bucket, but no reason for that precision # here else: granularity = 60 return Granularity(granularity)

cf30c11a194aa5e61d8d7c7fc506764f846fcf82

builder.py

feat(MEP): Add initial framework for metric queries (#31649) - This adds a MetricsQueryBuilder, which works very similarily to our QueryBuilder, but with specific handlers for how metrics construct queries - This MetricsQueryBuilder does not yet construct snql queries, and will not because table queries will require multiple queries to construct similar table data - that is, if we want [transaction, p95, count_unique(user)], we need a query against distributions with [transaction, p95] followed by a second query for [transaction, count_unique(user)] against the sets table - This is so we can maintain a sortby

sentry

src/sentry/search/events/builder.py

Python

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

test_vr_connector_respects_training_or_inference_vr_flags

def test_vr_connector_respects_training_or_inference_vr_flags(self): view_rq_dict = { "both": ViewRequirement( "obs", used_for_training=True, used_for_compute_actions=True ), "only_inference": ViewRequirement( "obs", used_for_training=False, used_for_compute_actions=True ), "none": ViewRequirement( "obs", used_for_training=False, used_for_compute_actions=False ), "only_training": ViewRequirement( "obs", used_for_training=True, used_for_compute_actions=False ), } obs_arr = np.array([0, 1, 2, 3]) agent_data = dict(obs=obs_arr) data = AgentConnectorDataType(0, 1, agent_data) ctx = ConnectorContext(view_requirements=view_rq_dict) # TODO @jun What is the expected behavior of this test? for_action_expected_list = [ # is_training = False SampleBatch({"both": obs_arr, "only_inference": obs_arr}), # is_training = True SampleBatch({"both": obs_arr, "only_inference": obs_arr}), ] for_training_expected_list = [ # is_training = False None, # is_training = True agent_data, ] for is_training in [True, False]: c = ViewRequirementAgentConnector(ctx) c.is_training(is_training) processed = c([data]) for_training = processed[0].data.for_training for_training_expected = for_training_expected_list[is_training] for_action = processed[0].data.for_action for_action_expected = for_action_expected_list[is_training] print("-" * 30) print(f"is_training = {is_training}") print("for action:") print(for_action) print("for training:") print(for_training) # TODO @jun is for_training expected to always be equal to data? check(for_training, for_training_expected) check(for_action, for_action_expected)

5030a4c1d384e4bb1a25169384d7465e718e99a5

test_agent.py

[RLlib] Simplify agent collector (#26803)

ray

rllib/connectors/tests/test_agent.py

Python

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

fixture_dirs

def fixture_dirs(self): dirs = [] fixture_dirs = settings.FIXTURE_DIRS if len(fixture_dirs) != len(set(fixture_dirs)): raise ImproperlyConfigured("settings.FIXTURE_DIRS contains duplicates.") for app_config in apps.get_app_configs(): app_label = app_config.label app_dir = os.path.join(app_config.path, "fixtures") if app_dir in fixture_dirs: raise ImproperlyConfigured( "'%s' is a default fixture directory for the '%s' app " "and cannot be listed in settings.FIXTURE_DIRS." % (app_dir, app_label) ) if self.app_label and app_label != self.app_label: continue if os.path.isdir(app_dir): dirs.append(app_dir) dirs.extend(fixture_dirs) dirs.append("") return [os.path.realpath(d) for d in dirs]

9c19aff7c7561e3a82978a272ecdaad40dda5c00

loaddata.py

Refs #33476 -- Reformatted code with Black.

django

django/core/management/commands/loaddata.py

Python

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

get_config_file_for_auto_config

def get_config_file_for_auto_config(self) -> Optional[Text]: return self.config_file

6339856514897056716bb531acb8489c9cf05d26

importer.py

Add support for different recipes (#10641) * Add support for different recipes Fixes https://github.com/RasaHQ/rasa/issues/10473 * Update docs/docs/graph-recipe.mdx Co-authored-by: Joe Juzl <[email protected]>

rasa

rasa/shared/importers/importer.py

Python

https://github.com/RasaHQ/rasa.git

receive_file

def receive_file(filename="example.txt"): with open(filename, "wb") as out_file: ftp.retrbinary("RETR " + filename, out_file.write, 1024) ftp.quit()

f0af0c43340763724f139fa68aa1e5a9ffe458b4

ftp_send_receive.py

refactor: clean code Signed-off-by: slowy07 <[email protected]>

Python

ftp_send_receive.py

Python

https://github.com/geekcomputers/Python.git

get_queryset

def get_queryset(self): qs = self.model_admin.get_queryset(self.request) qs = qs.complex_filter(self.source_field.get_limit_choices_to()) qs, search_use_distinct = self.model_admin.get_search_results( self.request, qs, self.term ) if search_use_distinct: qs = qs.distinct() return qs

9c19aff7c7561e3a82978a272ecdaad40dda5c00

autocomplete.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/views/autocomplete.py

Python

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

test_hub_not_support_wireless

async def test_hub_not_support_wireless(hass, mock_device_registry_devices): await setup_mikrotik_entry(hass, support_wireless=False) device_1 = hass.states.get("device_tracker.device_1") assert device_1 assert device_1.state == "home" # device_2 is added from DHCP device_2 = hass.states.get("device_tracker.device_2") assert device_2 assert device_2.state == "home"

b09aaba421d6d6178d582bef9ea363017e55639d

test_device_tracker.py

Add type hints and code cleanup for mikrotik (#74296) * Add type hints and code cleanup for mikrotik * update test and increase coverage * move setup_mikrotik_entry to __init__.py

core

tests/components/mikrotik/test_device_tracker.py

Python

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

__dask_postcompute__

def __dask_postcompute__(self) -> tuple[PostComputeCallable, tuple]: raise NotImplementedError("Inheriting class must implement this method.")

1e783d9a714160e968936cb22d54d085959ab09e

typing.py

Collection Protocol (#8674) [PEP 544](https://www.python.org/dev/peps/pep-0544/) introduces the `Protocol` class to the `typing` module in Python 3.8 (the soon be the minimum supported version, https://github.com/dask/community/issues/213). Writing new Dask collections for [dask-awkward](https://github.com/ContinuumIO/dask-awkward/) has had me thinking about working on a `DaskCollection` protocol. I imagine the benefits to be: - usage with static type checkers - other activity in this area at - #8295 - #8706 - #8854 - Python supporting IDEs take advantage of typing - self-documenting; some improvements to [the custom collections page](https://docs.dask.org/en/latest/custom-collections.html) of the docs. The protocol docs can be autogenerated and added to that page. - purely opt-in feature The `typing.runtime_checkable` decorator allows use of `isinstance(x, DaskCollection)` in any code base that uses Dask collections; for example: ```python >>> from dask.typing import DaskCollection >>> import dask.array as da >>> x = da.zeros((10, 3)) >>> isinstance(x, DaskCollection) True ``` (though this is an order of magnitude slower than `dask.base.is_dask_collection` which only checks for `x.__dask_graph__() is not None`; static typing checking & built-in interface documentation are the core benefits IMO) Something else that came up in the brief discussion on a call last week was having `{Scheduler,Worker,Nanny}Plugin` protocols in `distributed`; and perhaps those are better places to start introducing protocols to Dask since on the user side typically more folks would write plugins than new collections.

dask

dask/typing.py

Python

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

require_intel_extension_for_pytorch

def require_intel_extension_for_pytorch(test_case): return unittest.skipUnless(is_ipex_available(), "test requires Intel Extension for PyTorch")(test_case)

34097b3304d79ace845316d4929220623279c8bc

testing_utils.py

Extend Transformers Trainer Class to Enable CPU AMP and Integrate Intel Extension for PyTorch (#17138) * init PR * fix import ipex * minor fix on bf16 * refine optimizer * refine args notes * refine code * refine ipex optimize args * refine half_precision_backend * black format * isort format * isort format files * flake8 format * doc builder format * refine codes * remove jit and optim bits * black preview format * Update src/transformers/trainer.py Co-authored-by: Sylvain Gugger <[email protected]> * refine code * refine notes * Update src/transformers/trainer.py Co-authored-by: Sylvain Gugger <[email protected]> * Update src/transformers/trainer.py Co-authored-by: Sylvain Gugger <[email protected]> * code refine * add ipex ut * add performance cpu doc * link to the cpu doc from main perf doc * install ipex into CI's docker * Update perf_train_cpu.mdx * Update docs/source/en/perf_train_cpu.mdx Co-authored-by: Stas Bekman <[email protected]> * Update perf_train_cpu.mdx * Update perf_train_cpu.mdx Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Stas Bekman <[email protected]> Co-authored-by: Stas Bekman <[email protected]>

transformers

src/transformers/testing_utils.py

Python

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

options_spec

def options_spec() -> str: if not hasattr(options_spec, 'ans'): OPTIONS = setattr(options_spec, 'ans', OPTIONS.format( appname=appname, conf_name=appname, config_help=CONFIG_HELP.format(appname=appname, conf_name=appname), )) ans: str = getattr(options_spec, 'ans') return ans

45bbe17559a541289699643ef0b541a2138a09d6

cli.py

Docs: Minor improvements to the kitty cli help documentation Add some text roles. Use `kitty --hold`. Use `appname` and `conf_name`. `appname` is also applied to the system-wide configuration path.

kitty

kitty/cli.py

Python

https://github.com/kovidgoyal/kitty.git

execute

def execute(): warehouse_perm = frappe.get_all( "User Permission", fields=["count(*) as p_count", "is_default", "user"], filters={"allow": "Warehouse"}, group_by="user", ) if not warehouse_perm: return execute_patch = False for perm_data in warehouse_perm: if perm_data.p_count == 1 or ( perm_data.p_count > 1 and frappe.get_all( "User Permission", filters={"user": perm_data.user, "allow": "warehouse", "is_default": 1}, limit=1, ) ): execute_patch = True break if not execute_patch: return for doctype in ["Sales Invoice", "Delivery Note"]: if not frappe.get_meta(doctype + " Item").get_field("target_warehouse").hidden: continue cond = "" if doctype == "Sales Invoice": cond = " AND parent_doc.update_stock = 1" data = frappe.db.sql( .format( doctype=doctype, cond=cond ), as_dict=1, ) if data: names = [d.child_name for d in data] frappe.db.sql( .format( doctype, ",".join(["%s"] * len(names)) ), tuple(names), ) frappe.db.sql( .format( doctype, ",".join(["%s"] * len(names)) ), tuple(names), ) parent_names = list(set([d.name for d in data])) for d in parent_names: doc = frappe.get_doc(doctype, d) if doc.docstatus != 1: continue doc.docstatus = 2 doc.update_stock_ledger() doc.make_gl_entries_on_cancel(repost_future_gle=False) # update stock & gl entries for submit state of PR doc.docstatus = 1 doc.update_stock_ledger() doc.make_gl_entries() if frappe.get_meta("Sales Order Item").get_field("target_warehouse").hidden: frappe.db.sql( ) frappe.db.sql( )

494bd9ef78313436f0424b918f200dab8fc7c20b

repost_stock_ledger_entries_for_target_warehouse.py

style: format code with black

erpnext

erpnext/patches/v12_0/repost_stock_ledger_entries_for_target_warehouse.py

Python

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

build_wheel

def build_wheel(self): # type: () -> S need_delete = False if not self.pyproject.exists(): if not self.build_requires: build_requires = '"setuptools", "wheel"' else: build_requires = ", ".join( ['"{0}"'.format(r) for r in self.build_requires] ) self.pyproject.write_text( str( .format( build_requires, self.build_backend ).strip() ) ) need_delete = True parsed = urlparse(str(self.ireq.link)) subdir = parse_qs(parsed.fragment).get('subdirectory', []) if subdir: directory = f"{self.base_dir}/{subdir[0]}" else: directory = self.base_dir result = build_pep517( directory, self.extra_kwargs["build_dir"], config_settings=self.pep517_config, dist_type="wheel", ) if need_delete: self.pyproject.unlink() return result # noinspection PyPackageRequirements

2669b4ce0696de02610cbea1b7547d53cead85bb

setup_info.py

patch newly occuring test failure where the base_dir does not contain the subdirectory.

pipenv

pipenv/vendor/requirementslib/models/setup_info.py

Python

https://github.com/pypa/pipenv.git

make_rev_options

def make_rev_options(cls, rev=None, extra_args=None): # type: (Optional[str], Optional[CommandArgs]) -> RevOptions return RevOptions(cls, rev, extra_args=extra_args)

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

versioncontrol.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py

Python

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

generate_module_groups

def generate_module_groups(self) -> Dict[int, List[str]]: assert self.bound_model is not None, 'No model bounded in this compressor, please use Compressor.reset(model, config_list) to set it.' assert self.config_list is not None, 'No config_list set in this compressor, please use Compressor.reset(model, config_list) to set it.' self._unwrap_model() module_groups = {} for name, module in self.bound_model.named_modules(): if module == self.bound_model: continue layer = LayerInfo(name, module) ret = None for idx, config in enumerate(self.config_list): config = config.copy() # expand config if key `default` is in config['op_types'] if 'op_types' in config and 'default' in config['op_types']: expanded_op_types = [] for op_type in config['op_types']: if op_type == 'default': expanded_op_types.extend(weighted_modules) else: expanded_op_types.append(op_type) config['op_types'] = expanded_op_types # check if condition is satisified if 'op_types' in config and layer.type not in config['op_types']: continue if 'op_names' in config and layer.name not in config['op_names']: continue ret = (idx, config) if ret is not None and 'exclude' not in ret[1]: module_groups.setdefault(ret[0], []) module_groups[ret[0]].append(name) self._wrap_model() return module_groups

cbac2c5c0f7606aca8ccf08fbd418ffe3adfe427

compressor.py

[Compression] fix typehints (#4800)

nni

nni/algorithms/compression/v2/pytorch/base/compressor.py

Python

https://github.com/microsoft/nni.git

send_welcome

def send_welcome(message): text = markdown = telebot.types.InlineKeyboardMarkup() markdown.add( telebot.types.InlineKeyboardButton( "Star us on GitHub", url="https://github.com/GamestonkTerminal/GamestonkTerminal", ) ) markdown.add( telebot.types.InlineKeyboardButton( "Join us on Discord", url="https://discord.gg/XHsYvvjjWg" ) ) bot.send_message( chat_id=message.chat.id, text=text, reply_markup=markdown, parse_mode="MARKDOWN" ) # bot.reply_to(markdown, text, parse_mode="MARKDOWN") # bot.reply_to(message, text, parse_mode="MARKDOWN") @bot.message_handler(commands=["cmds", "commands"])

635851cbf633a6ea9423ba31fe8f68ab34423a8c

@bot.message_handler(commands=["cmds", "commands"])

run_telegram.py

Telegram Bot (#1458) * added initial code for telegram * improving suggestions and messages * improving messages * typo Co-authored-by: teh_coderer <[email protected]>

OpenBBTerminal

bots/telegram/run_telegram.py

Python

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

filter

def filter(names, pat): result = [] pat = os.path.normcase(pat) match = _compile_pattern(pat) if os.path is posixpath: # normcase on posix is NOP. Optimize it away from the loop. for name in names: if match(name): result.append(name) else: for name in names: if match(os.path.normcase(name)): result.append(name) return result

8198943edd73a363c266633e1aa5b2a9e9c9f526

fnmatch.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/fnmatch.py

Python

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

test_stream_unsupported_by_bulk

def test_stream_unsupported_by_bulk(stream_config, stream_api, caplog): stream_name = "AcceptedEventRelation" stream = _generate_stream(stream_name, stream_config, stream_api) assert not isinstance(stream, BulkSalesforceStream)

0a3713a5a52995dc0dc205d8edfd097bf625899f

unit_test.py

Source Salesforce: Deprecate API Type parameter (#9302) * use BULK for the first sync, REST for incremental sync * if stream contains compound data or/and base64 use always REST * fix get stream state from connector state * fix integration test * refactor catalog name * format code * refactor unit tests * refactor unit tests 2 * format code 2 * Set additionalProperties to true not to break test temporarily * fix unit test and remove unnecessary filtering fields * bump version * updated spec and def yaml Co-authored-by: auganbay <[email protected]>

airbyte

airbyte-integrations/connectors/source-salesforce/unit_tests/unit_test.py

Python

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

call_exception_handler

def call_exception_handler(self, context): if self._exception_handler is None: try: self.default_exception_handler(context) except (SystemExit, KeyboardInterrupt): raise except BaseException: # Second protection layer for unexpected errors # in the default implementation, as well as for subclassed # event loops with overloaded "default_exception_handler". logger.error('Exception in default exception handler', exc_info=True) else: try: self._exception_handler(self, context) except (SystemExit, KeyboardInterrupt): raise except BaseException as exc: # Exception in the user set custom exception handler. try: # Let's try default handler. self.default_exception_handler({ 'message': 'Unhandled error in exception handler', 'exception': exc, 'context': context, }) except (SystemExit, KeyboardInterrupt): raise except BaseException: # Guard 'default_exception_handler' in case it is # overloaded. logger.error('Exception in default exception handler ' 'while handling an unexpected error ' 'in custom exception handler', exc_info=True)

8198943edd73a363c266633e1aa5b2a9e9c9f526

base_events.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/asyncio/base_events.py

Python

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

test_sept_child

def test_sept_child() -> None: rows = 10_000 cols = 7 # these times and sizes are based on the above constants and Madhavas MacBook Pro 2019 expected_sept_mem_size = 0.8035125732421875 expected_sept_ser_size = 1.4993972778320312 macbook_pro_2019_ser_time = 0.03371272199999975 macbook_pro_2019_de_time = 0.02922678500000009 sept = make_sept(rows=rows, cols=cols) start = timeit.default_timer() ser = sy.serialize(sept, to_bytes=True) end = timeit.default_timer() time_ser = end - start start = timeit.default_timer() de = sy.deserialize(ser, from_bytes=True) end = timeit.default_timer() time_de = end - start assert sept == de current_sept_mem_size = size(sept) mem_diff = (current_sept_mem_size / expected_sept_mem_size * 100) - 100 current_sept_bytes_size = size(ser) bytes_diff = (current_sept_bytes_size / expected_sept_ser_size * 100) - 100 ser_time_diff = (time_ser / macbook_pro_2019_ser_time * 100) - 100 de_time_diff = (time_de / macbook_pro_2019_de_time * 100) - 100 print("SEPT Stats") print("==========") print("In-memory size of SEPT", size(sept)) print("Serialized size of SEPT", size(ser)) print(f"Serializing {rows}x{cols} took {time_ser} secs") print(f"Deserializing {rows}x{cols} took {time_de} secs") print("Current Results") print("===============") print(f"In-memory size delta: {mem_diff}%") print(f"Serialized size delta: {bytes_diff}%") print(f"Serializing time delta: {ser_time_diff}%") print(f"Deserializing time delta: {de_time_diff}%") # we want to assert that our calculated values are smaller than the old values with # some tolerance assert (current_sept_mem_size - expected_sept_mem_size) < 1e-3 assert (current_sept_bytes_size - expected_sept_ser_size) < 2e-3 # TODO: make time benchmarks stable (probably can't run in parallel) # assert (time_ser - macbook_pro_2019_ser_time) < 2e-1 # assert (time_de - macbook_pro_2019_de_time) < 2e-1

10ae1d589044a6ae4722ead7aedc63fcdc4923b5

tensor_serde_test.py

Started DPTensor resource optimization - Added initial REPT and SEPT benchmarking tests - Deleted unused old Tensor classes - Added pympler for memory size tests Co-authored-by: @IshanMi Co-authored-by: @rasswanth-s

PySyft

packages/syft/tests/syft/core/tensor/tensor_serde_test.py

Python

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

test_xcom_pull_after_deferral

def test_xcom_pull_after_deferral(self, create_task_instance, session): key = 'xcom_key' value = 'xcom_value' ti = create_task_instance( dag_id='test_xcom', schedule_interval='@monthly', task_id='test_xcom', pool='test_xcom', ) ti.run(mark_success=True) ti.xcom_push(key=key, value=value) ti.next_method = "execute" session.merge(ti) session.commit() ti.run(ignore_all_deps=True) assert ti.xcom_pull(task_ids='test_xcom', key=key) == value

8b687ec82a7047fc35410f5c5bb0726de434e749

test_taskinstance.py

Do not clear XCom when resuming from deferral (#22932)

airflow

tests/models/test_taskinstance.py

Python

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

test_pisa_ssd_head_loss

def test_pisa_ssd_head_loss(self): s = 300 img_metas = [{ 'img_shape': (s, s, 3), 'scale_factor': 1, }] cfg = Config( dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.5, neg_iou_thr=0.5, min_pos_iou=0., ignore_iof_thr=-1, gt_max_assign_all=False), sampler=dict(type='PseudoSampler'), smoothl1_beta=1., allowed_border=-1, pos_weight=-1, neg_pos_ratio=3, debug=False)) pisa_ssd_head = PISASSDHead( num_classes=4, in_channels=(1, 1, 1, 1, 1, 1), anchor_generator=dict( type='SSDAnchorGenerator', scale_major=False, input_size=s, basesize_ratio_range=(0.15, 0.9), strides=[8, 16, 32, 64, 100, 300], ratios=[[2], [2, 3], [2, 3], [2, 3], [2], [2]]), train_cfg=cfg) # PISA SSD head expects a multiple levels of features per image feats = ( torch.rand(1, 1, ceil(s / stride[0]), ceil(s / stride[0])) for stride in pisa_ssd_head.prior_generator.strides) cls_scores, bbox_preds = pisa_ssd_head.forward(feats) # test without isr and carl # Test that empty ground truth encourages the network to # predict background gt_instances = InstanceData() gt_instances.bboxes = torch.empty((0, 4)) gt_instances.labels = torch.LongTensor([]) empty_gt_losses = pisa_ssd_head.loss(cls_scores, bbox_preds, [gt_instances], img_metas) # When there is no truth, cls_loss and box_loss should all be zero. empty_cls_loss = sum(empty_gt_losses['loss_cls']) empty_box_loss = sum(empty_gt_losses['loss_bbox']) self.assertEqual( empty_cls_loss.item(), 0, 'there should be no cls loss when there are no true boxes') self.assertEqual( empty_box_loss.item(), 0, 'there should be no box loss when there are no true boxes') # When truth is non-empty then both cls and box loss # should be nonzero for random inputs gt_instances = InstanceData() gt_instances.bboxes = torch.Tensor( [[23.6667, 23.8757, 238.6326, 151.8874]]) gt_instances.labels = torch.LongTensor([2]) one_gt_losses = pisa_ssd_head.loss(cls_scores, bbox_preds, [gt_instances], img_metas) onegt_cls_loss = sum(one_gt_losses['loss_cls']) onegt_box_loss = sum(one_gt_losses['loss_bbox']) self.assertGreater(onegt_cls_loss.item(), 0, 'cls loss should be non-zero') self.assertGreater(onegt_box_loss.item(), 0, 'box loss should be non-zero') pisa_ssd_head.train_cfg.update( dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2))) # test with isr and carl # Test that empty ground truth encourages the network to # predict background gt_instances = InstanceData() gt_instances.bboxes = torch.empty((0, 4)) gt_instances.labels = torch.LongTensor([]) empty_gt_losses = pisa_ssd_head.loss(cls_scores, bbox_preds, [gt_instances], img_metas) # When there is no truth, cls_loss and box_loss should all be zero. empty_cls_loss = sum(empty_gt_losses['loss_cls']) empty_box_loss = sum(empty_gt_losses['loss_bbox']) self.assertEqual( empty_cls_loss.item(), 0, 'there should be no cls loss when there are no true boxes') self.assertEqual( empty_box_loss.item(), 0, 'there should be no box loss when there are no true boxes') # When truth is non-empty then both cls and box loss # should be nonzero for random inputs gt_instances = InstanceData() gt_instances.bboxes = torch.Tensor( [[23.6667, 23.8757, 238.6326, 151.8874]]) gt_instances.labels = torch.LongTensor([2]) one_gt_losses = pisa_ssd_head.loss(cls_scores, bbox_preds, [gt_instances], img_metas) onegt_cls_loss = sum(one_gt_losses['loss_cls']) onegt_box_loss = sum(one_gt_losses['loss_bbox']) self.assertGreater(onegt_cls_loss.item(), 0, 'cls loss should be non-zero') self.assertGreater(onegt_box_loss.item(), 0, 'box loss should be non-zero')

9d7511d8c35df1f9c13b17eb770136859bf370be

test_pisa_ssd_head.py

Update SSD and PISA-SSD model config

mmdetection

tests/test_models/test_dense_heads/test_pisa_ssd_head.py

Python

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

get_installation_order

def get_installation_order(self, req_set): # type: (RequirementSet) -> List[InstallRequirement] # The current implementation, which we may change at any point # installs the user specified things in the order given, except when # dependencies must come earlier to achieve topological order. order = [] ordered_reqs = set() # type: Set[InstallRequirement]

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

resolver.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/resolution/legacy/resolver.py

Python

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

bump_client_version

def bump_client_version(self): path = os.path.join(".", "client", "package.json") input_file = io.open(path, "r") try: package = json.loads(input_file.read().decode("utf-8")) except (ValueError) as e: print("Unable to read " + path + " " + e) # noqa raise SystemExit(1) package["version"] = __semver__ try: with io.open(path, "w", encoding="utf-8") as f: f.write(str(json.dumps(package, indent=2, ensure_ascii=False))) except (IOError) as e: print("Error setting the version for front-end assets: " + str(e)) # noqa raise SystemExit(1)

d10f15e55806c6944827d801cd9c2d53f5da4186

setup.py

Reformat with black

wagtail

wagtail/utils/setup.py

Python

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

native_min_value

def native_min_value(self) -> float: return (self.max_value * -1) if self._is_bidirectional else 6

5b32eea3d04d223b01efddb5c13a88e540df8741

number.py

Add support for bidirectional chargers to Wallbox integration (#74313) * Add support for the Quasar bidirectional charger to the Wallbox integration, including ability to control charger while discharging, set a negative charge rate and monitor discharged amount * Make code more generic in order to support other bidirectional models in the future * Updates to files to comply with HA formatting rules * Change const file to fix black check failure * Remove unnecessay loop in number entity

core

homeassistant/components/wallbox/number.py

Python

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

test_cache_limit_ttl_greater_than_default_cache_ttl

def test_cache_limit_ttl_greater_than_default_cache_ttl(self): page1 = create_page('test page 1', 'nav_playground.html', 'en', published=True) page1_url = page1.get_absolute_url() limit_page_cache_ttl_function = ".".join([PlaceholderCacheTestCase.__module__, limit_page_cache_ttl_test_500.__name__]) with self.settings(CMS_LIMIT_TTL_CACHE_FUNCTION=limit_page_cache_ttl_function): page1.publish('en') request = self.get_request(page1_url) request.current_page = Page.objects.get(pk=page1.pk) response = self.client.get(page1_url) self.assertTrue('max-age=40' in response['Cache-Control'], response['Cache-Control']) # noqa

c412e97acba65a2a68e70ca15ea950bd31f90d3e

test_cache.py

feat: add cache ttl extension point (#7299) Adds the setting `CMS_CACHE_LIMIT_TTL_CLASS` that should have a `limit_page_cache_ttl` method that would be called to limit the cache ttl of a page using business logic. Closes #7296

django-cms

cms/tests/test_cache.py

Python

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

subordinate_to_user

def subordinate_to_user(self, user, site): # get user level from cms.utils.page_permissions import get_change_permissions_id_list from cms.utils.permissions import get_user_permission_level try: user_level = get_user_permission_level(user, site) except NoPermissionsException: return self.none() if user_level == ROOT_USER_LEVEL: return self.all() # get all permissions page_id_allow_list = get_change_permissions_id_list(user, site, check_global=False) # get permission set, but without objects targeting user, or any group # in which he can be qs = self.filter( page__id__in=page_id_allow_list, page__node__depth__gte=user_level, ) qs = qs.exclude(user=user).exclude(group__user=user) return qs

a3110e1ff24085373898c7d2a85f628abeb8518d

managers.py

Enabled isort workflow (#7200) * Ran isort * Enabled isort workflow Co-authored-by: Vinit Kumar <[email protected]>

django-cms

cms/models/managers.py

Python

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

test_finditer

def test_finditer(): matches = list(finditer(re.compile(rb"\d+"), b"0123 4567 890 12 3 4")) aligned = [i.group() for i in matches] assert aligned == [b"0123", b"567", b"890", b"12"]

dc12cb59559f99110917bcbd21c9960ab57d994f

test_bytecode.py

tests: fix test_finditer Have the test use bytestrings instead of strings. Also assert that the bytecode string passed to bytecode.finditer() is in fact a bytestring.

pyinstaller

tests/unit/test_bytecode.py

Python

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

cartesian_product

def cartesian_product(X) -> list[np.ndarray]: msg = "Input must be a list-like of list-likes" if not is_list_like(X): raise TypeError(msg) for x in X: if not is_list_like(x): raise TypeError(msg) if len(X) == 0: return [] lenX = np.fromiter((len(x) for x in X), dtype=np.intp) cumprodX = np.cumproduct(lenX) if np.any(cumprodX < 0): raise ValueError("Product space too large to allocate arrays!") a = np.roll(cumprodX, 1) a[0] = 1 if cumprodX[-1] != 0: b = cumprodX[-1] / cumprodX else: # if any factor is empty, the cartesian product is empty b = np.zeros_like(cumprodX) return [tile_compat(np.repeat(x, b[i]), np.product(a[i])) for i, x in enumerate(X)]

f65417656ba8c59438d832b6e2a431f78d40c21c

util.py

TYP: more return annotations in core/ (#47618) * TYP: more return annotations in core/ * from __future__ import annotations * more __future__

pandas

pandas/core/reshape/util.py

Python

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

is_monotonic_decreasing

def is_monotonic_decreasing(self) -> bool: return self._engine.is_monotonic_decreasing

62a69beddbedde349891378992c902c0b9341a9f

base.py

DOC: Add numpydoc SS06 validation (#47885)

pandas

pandas/core/indexes/base.py

Python

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

get_traceback_frame_variables

def get_traceback_frame_variables(self, request, tb_frame): # Loop through the frame's callers to see if the sensitive_variables # decorator was used. current_frame = tb_frame.f_back sensitive_variables = None while current_frame is not None: if ( current_frame.f_code.co_name == "sensitive_variables_wrapper" and "sensitive_variables_wrapper" in current_frame.f_locals ): # The sensitive_variables decorator was used, so we take note # of the sensitive variables' names. wrapper = current_frame.f_locals["sensitive_variables_wrapper"] sensitive_variables = getattr(wrapper, "sensitive_variables", None) break current_frame = current_frame.f_back cleansed = {} if self.is_active(request) and sensitive_variables: if sensitive_variables == "__ALL__": # Cleanse all variables for name in tb_frame.f_locals: cleansed[name] = self.cleansed_substitute else: # Cleanse specified variables for name, value in tb_frame.f_locals.items(): if name in sensitive_variables: value = self.cleansed_substitute else: value = self.cleanse_special_types(request, value) cleansed[name] = value else: # Potentially cleanse the request and any MultiValueDicts if they # are one of the frame variables. for name, value in tb_frame.f_locals.items(): cleansed[name] = self.cleanse_special_types(request, value) if ( tb_frame.f_code.co_name == "sensitive_variables_wrapper" and "sensitive_variables_wrapper" in tb_frame.f_locals ): # For good measure, obfuscate the decorated function's arguments in # the sensitive_variables decorator's frame, in case the variables # associated with those arguments were meant to be obfuscated from # the decorated function's frame. cleansed["func_args"] = self.cleansed_substitute cleansed["func_kwargs"] = self.cleansed_substitute return cleansed.items()

9c19aff7c7561e3a82978a272ecdaad40dda5c00

debug.py

Refs #33476 -- Reformatted code with Black.

django

django/views/debug.py

Python

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

image2hmap

def image2hmap(self, image_tensor): return self.model.forward(image_tensor, training=False)

803b90729d25fda253011c505d0189e8e63cc039

DBNet.py

add dbnet

EasyOCR

easyocr/DBNet/DBNet.py

Python

https://github.com/JaidedAI/EasyOCR.git

get_extended_attribute

def get_extended_attribute(value): # XXX: should we have an ExtendedAttribute TokenList? attribute = Attribute() if value and value[0] in CFWS_LEADER: token, value = get_cfws(value) attribute.append(token) if value and value[0] in EXTENDED_ATTRIBUTE_ENDS: raise errors.HeaderParseError( "expected token but found '{}'".format(value)) token, value = get_extended_attrtext(value) attribute.append(token) if value and value[0] in CFWS_LEADER: token, value = get_cfws(value) attribute.append(token) return attribute, value

8198943edd73a363c266633e1aa5b2a9e9c9f526

_header_value_parser.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/email/_header_value_parser.py

Python

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

test_table_options_language

def test_table_options_language(self): # default must always contain a language value block = TableBlock() self.assertIn("language", block.table_options) # French translation.activate("fr-fr") block_fr = TableBlock() self.assertEqual("fr-fr", block_fr.table_options["language"]) translation.activate("it") # Italian block_it = TableBlock() self.assertEqual("it", block_it.table_options["language"]) # table_options with language provided, different to environment block_with_lang = TableBlock(table_options={"language": "ja"}) self.assertNotEqual("it", block_with_lang.table_options["language"]) self.assertEqual("ja", block_with_lang.table_options["language"]) translation.activate("en")

d10f15e55806c6944827d801cd9c2d53f5da4186

tests.py

Reformat with black

wagtail

wagtail/contrib/table_block/tests.py

Python

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

get_static_batch_size

def get_static_batch_size(layer): batch_input_shape, _ = get_input_shape_and_dtype(layer) if batch_input_shape is not None: return tf.compat.v1.Dimension(batch_input_shape[0]).value return None

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training_utils.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/engine/training_utils.py

Python

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

modularity

def modularity(G, communities, weight="weight", resolution=1): r if not isinstance(communities, list): communities = list(communities) if not is_partition(G, communities): raise NotAPartition(G, communities) directed = G.is_directed() if directed: out_degree = dict(G.out_degree(weight=weight)) in_degree = dict(G.in_degree(weight=weight)) m = sum(out_degree.values()) norm = 1 / m**2 else: out_degree = in_degree = dict(G.degree(weight=weight)) deg_sum = sum(out_degree.values()) m = deg_sum / 2 norm = 1 / deg_sum**2

f6755ffa00211b523c6c0bec5398bc6c3c43c8b1

quality.py

Update black (#5438) * CI: sync up black dev requirements version with precommit * Run black Co-authored-by: Jarrod Millman <[email protected]>

networkx

networkx/algorithms/community/quality.py

Python

https://github.com/networkx/networkx.git

handle

def handle(self, query, args, env, session): if isinstance(self.result, dict): return self.result else: return self.result(query, args, env, session)

3023d6e0223e50c2d7cbe850f1c5355e5d505ceb

responder.py

renaming

mindsdb

mindsdb/api/mongo/classes/responder.py

Python

https://github.com/mindsdb/mindsdb.git

GetContainingXLAContext

def GetContainingXLAContext(ctxt): while ctxt: if ctxt.IsXLAContext(): return ctxt ctxt = ctxt.outer_context return None

84afc5193d38057e2e2badf9c889ea87d80d8fbf

control_flow_util.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/utils/control_flow_util.py

Python

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

get_model

def get_model(self, git_model_id, model_filename, backend): model = GetModel(model_filename, git_model_id).model_path model = cv2.dnn.readNetFromCaffe(model[1], model[0]) model.setPreferableTarget(self.get_backend(backend)) return model

f2e6f24651f62b28ccfb412180baca0aa7baf96a

vgg_face.py

Centralize model storage

faceswap

lib/vgg_face.py

Python

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

copy_sign

def copy_sign(self, a, b): a = _convert_other(a, raiseit=True) return a.copy_sign(b)

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pydecimal.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/_pydecimal.py

Python

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

forward

def forward(self, feats, img_metas): batch_size = len(img_metas) input_img_h, input_img_w = img_metas[0]['batch_input_shape'] padding_mask = feats[-1].new_ones( (batch_size, input_img_h, input_img_w), dtype=torch.float32) for i in range(batch_size): img_h, img_w, _ = img_metas[i]['img_shape'] padding_mask[i, :img_h, :img_w] = 0 padding_mask = F.interpolate( padding_mask.unsqueeze(1), size=feats[-1].shape[-2:], mode='nearest').to(torch.bool).squeeze(1) # when backbone is swin, memory is output of last stage of swin. # when backbone is r50, memory is output of tranformer encoder. mask_features, memory = self.pixel_decoder(feats, img_metas) pos_embed = self.decoder_pe(padding_mask) memory = self.decoder_input_proj(memory) # shape (batch_size, c, h, w) -> (h*w, batch_size, c) memory = memory.flatten(2).permute(2, 0, 1) pos_embed = pos_embed.flatten(2).permute(2, 0, 1) # shape (batch_size, h * w) padding_mask = padding_mask.flatten(1) # shape = (num_queries, embed_dims) query_embed = self.query_embed.weight # shape = (num_queries, batch_size, embed_dims) query_embed = query_embed.unsqueeze(1).repeat(1, batch_size, 1) target = torch.zeros_like(query_embed) # shape (num_decoder, num_queries, batch_size, embed_dims) out_dec = self.transformer_decoder( query=target, key=memory, value=memory, key_pos=pos_embed, query_pos=query_embed, key_padding_mask=padding_mask) # shape (num_decoder, batch_size, num_queries, embed_dims) out_dec = out_dec.transpose(1, 2) # cls_scores all_cls_scores = self.cls_embed(out_dec) # mask_preds mask_embed = self.mask_embed(out_dec) all_mask_preds = torch.einsum('lbqc,bchw->lbqhw', mask_embed, mask_features) return all_cls_scores, all_mask_preds

cac356380d505bf15587f07c0529218cc36b9652

maskformer_head.py

[Feature] Add Maskformer to mmdet (#7212) * first commit * add README * move model description from config to readme add description for binary_input add description for dice loss add a independent panoptic gt processing function add a independent panoptic gt processing function remove compatibility of pretrain in maskformer * update comments in maskformer_head * update docs format

mmdetection

mmdet/models/dense_heads/maskformer_head.py

Python

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

test_text

def test_text(self, qt_key, upper): modifiers = Qt.KeyboardModifier.ShiftModifier if upper else Qt.KeyboardModifiers() info = keyutils.KeyInfo(qt_key.member, modifiers=modifiers) expected = qt_key.uppertext if upper else qt_key.text assert info.text() == expected

0877fb0d78635692e481c8bde224fac5ad0dd430

test_keyutils.py

Run scripts/dev/rewrite_enums.py

qutebrowser

tests/unit/keyinput/test_keyutils.py

Python

https://github.com/qutebrowser/qutebrowser.git

present

def present(name, acl_type, acl_name="", perms="", recurse=False, force=False): ret = {"name": name, "result": True, "changes": {}, "comment": ""} _octal = {"r": 4, "w": 2, "x": 1, "-": 0} _octal_lookup = {0: "-", 1: "r", 2: "w", 4: "x"} if not os.path.exists(name): ret["comment"] = "{} does not exist".format(name) ret["result"] = False return ret __current_perms = __salt__["acl.getfacl"](name, recursive=recurse) if acl_type.startswith(("d:", "default:")): _acl_type = ":".join(acl_type.split(":")[1:]) _current_perms = __current_perms[name].get("defaults", {}) _default = True else: _acl_type = acl_type _current_perms = __current_perms[name] _default = False # The getfacl execution module lists default with empty names as being # applied to the user/group that owns the file, e.g., # default:group::rwx would be listed as default:group:root:rwx # In this case, if acl_name is empty, we really want to search for root # but still uses '' for other # We search through the dictionary getfacl returns for the owner of the # file if acl_name is empty. if acl_name == "": _search_name = __current_perms[name].get("comment").get(_acl_type, "") else: _search_name = acl_name if _current_perms.get(_acl_type, None) or _default: try: user = [ i for i in _current_perms[_acl_type] if next(iter(i.keys())) == _search_name ].pop() except (AttributeError, IndexError, StopIteration, KeyError): user = None if user: octal_sum = sum(_octal.get(i, i) for i in perms) need_refresh = False # If recursive check all paths retrieved via acl.getfacl if recurse: for path in __current_perms: acl_found = False if _default: # Recusive default acls only apply to directories if not os.path.isdir(path): continue _current_perms_path = __current_perms[path].get("defaults", {}) else: _current_perms_path = __current_perms[path] for user_acl in _current_perms_path.get(_acl_type, []): if ( _search_name in user_acl and user_acl[_search_name]["octal"] == octal_sum ): acl_found = True if not acl_found: need_refresh = True break # Check the permissions from the already located file elif user[_search_name]["octal"] == sum(_octal.get(i, i) for i in perms): need_refresh = False # If they don't match then refresh else: need_refresh = True if not need_refresh: ret["comment"] = "Permissions are in the desired state" else: _num = user[_search_name]["octal"] new_perms = "{}{}{}".format( _octal_lookup[_num & 1], _octal_lookup[_num & 2], _octal_lookup[_num & 4], ) changes = { "new": {"acl_name": acl_name, "acl_type": acl_type, "perms": perms}, "old": { "acl_name": acl_name, "acl_type": acl_type, "perms": new_perms, }, } if __opts__["test"]: ret.update( { "comment": ( "Updated permissions will be applied for " "{}: {} -> {}".format(acl_name, new_perms, perms) ), "result": None, "changes": changes, } ) return ret try: if force: __salt__["acl.wipefacls"]( name, recursive=recurse, raise_err=True ) __salt__["acl.modfacl"]( acl_type, acl_name, perms, name, recursive=recurse, raise_err=True, ) ret.update( { "comment": "Updated permissions for {}".format(acl_name), "result": True, "changes": changes, } ) except CommandExecutionError as exc: ret.update( { "comment": "Error updating permissions for {}: {}".format( acl_name, exc.strerror ), "result": False, } ) else: changes = { "new": {"acl_name": acl_name, "acl_type": acl_type, "perms": perms} } if __opts__["test"]: ret.update( { "comment": "New permissions will be applied for {}: {}".format( acl_name, perms ), "result": None, "changes": changes, } ) ret["result"] = None return ret try: if force: __salt__["acl.wipefacls"](name, recursive=recurse, raise_err=True) __salt__["acl.modfacl"]( acl_type, acl_name, perms, name, recursive=recurse, raise_err=True ) ret.update( { "comment": "Applied new permissions for {}".format(acl_name), "result": True, "changes": changes, } ) except CommandExecutionError as exc: ret.update( { "comment": "Error updating permissions for {}: {}".format( acl_name, exc.strerror ), "result": False, } ) else: ret["comment"] = "ACL Type does not exist" ret["result"] = False return ret

f2a783643de61cac1ff3288b40241e5ce6e1ddc8

linux_acl.py

Update to latest ``pyupgrade`` hook. Stop skipping it on CI. Signed-off-by: Pedro Algarvio <[email protected]>

salt

salt/states/linux_acl.py

Python

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

test_rate_limited

def test_rate_limited(self): org_strings = {1: {"a", "b", "c"}, 2: {"e", "f"}, 3: {"g"}} with override_options( { "sentry-metrics.writes-limiter.limits.releasehealth.per-org": [ {"window_seconds": 10, "granularity_seconds": 10, "limit": 1} ], } ): results = self.indexer.bulk_record( use_case_id=self.use_case_id, org_strings=org_strings ) assert len(results[1]) == 3 assert len(results[2]) == 2 assert len(results[3]) == 1 assert results[3]["g"] is not None rate_limited_strings = set() for org_id in 1, 2, 3: for k, v in results[org_id].items(): if v is None: rate_limited_strings.add(k) assert len(rate_limited_strings) == 3 assert "g" not in rate_limited_strings for string in rate_limited_strings: assert results.get_fetch_metadata()[string] == ( None, FetchType.RATE_LIMITED, FetchTypeExt(is_global=False), ) org_strings = {1: rate_limited_strings} with override_options( { "sentry-metrics.writes-limiter.limits.releasehealth.global": [ {"window_seconds": 10, "granularity_seconds": 10, "limit": 2} ], } ): results = self.indexer.bulk_record( use_case_id=self.use_case_id, org_strings=org_strings ) rate_limited_strings2 = set() for k, v in results[1].items(): if v is None: rate_limited_strings2.add(k) assert len(rate_limited_strings2) == 1 assert len(rate_limited_strings - rate_limited_strings2) == 2

c4cc0467974bcfb2b3c95120bd19c337aa977183

test_postgres_indexer.py

feat(metrics_indexer): Add rate limits functionality to indexer [INGEST-1380] (#36263) * feat(metrics_indexer): Add rate limits functionality to indexer [INGEST-1380] The postgres string indexer now is able to rate limit writes using four sentry options. If that happens, `None` is returned in place of an integer, and the FetchType is RATE_LIMITED. The kafka consumer/message processor explicitly checks for those `None` values and throws away every message that references a rate-limited string. It logs a Sentry error for every dropped message just because that's already what we do for other kinds of dropped messages. Rate limiting and quota management currently creates a ton of dataclasses and that probably wastes time. There are a ton of low-hanging fruits: * the return value of _construct_quotas could be globally cached, as long as the cache is wiped when the sentry options change. * the same Quota object (for global limits) is referenced from multiple RequestedQuota instances (one for each org). `sentry.ratelimits.sliding_windows` could check the `id()` of the quota (if there is no prefix override) to avoid computing and checking the same quota multiple times. An even lower hanging fruit is that we're fetching the same keys from Redis multiple times, because multiple organizations (and therefore multiple RequestedQuota instances) adhere to the global quota. So that's been fixed, but as for the rest let's wait for timings from prod. * fix typo * fix typing * apply review feedback * fix typing, add test * fix tests * apply review feedback about logging too many msgs * fix leaking option in test * sike, more test failures

sentry

tests/sentry/sentry_metrics/test_postgres_indexer.py

Python

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

register_for_auto_class

def register_for_auto_class(cls, auto_class="FlaxAutoModel"): if not isinstance(auto_class, str): auto_class = auto_class.__name__ import transformers.models.auto as auto_module if not hasattr(auto_module, auto_class): raise ValueError(f"{auto_class} is not a valid auto class.") cls._auto_class = auto_class # To update the docstring, we need to copy the method, otherwise we change the original docstring. FlaxPreTrainedModel.push_to_hub = copy_func(FlaxPreTrainedModel.push_to_hub) FlaxPreTrainedModel.push_to_hub.__doc__ = FlaxPreTrainedModel.push_to_hub.__doc__.format( object="model", object_class="FlaxAutoModel", object_files="model checkpoint" )

44b21f117bcf71e3d88a11c3523c94b27949fdbf

modeling_flax_utils.py

Save code of registered custom models (#15379) * Allow dynamic modules to use relative imports * Work for configs * Fix last merge conflict * Save code of registered custom objects * Map strings to strings * Fix test * Add tokenizer * Rework tests * Tests * Ignore fixtures py files for tests * Tokenizer test + fix collection * With full path * Rework integration * Fix typo * Remove changes in conftest * Test for tokenizers * Add documentation * Update docs/source/custom_models.mdx Co-authored-by: Lysandre Debut <[email protected]> * Add file structure and file content * Add more doc * Style * Update docs/source/custom_models.mdx Co-authored-by: Suraj Patil <[email protected]> * Address review comments Co-authored-by: Lysandre Debut <[email protected]> Co-authored-by: Suraj Patil <[email protected]>

transformers

src/transformers/modeling_flax_utils.py

Python

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

SearchBackend

def SearchBackend(params): if connection.vendor == 'postgresql': from .postgres.postgres import PostgresSearchBackend return PostgresSearchBackend(params) elif connection.vendor == 'mysql': from .mysql.mysql import MySQLSearchBackend return MySQLSearchBackend(params) elif connection.vendor == 'sqlite': from .sqlite.utils import fts5_available if fts5_available(): from .sqlite.sqlite import SQLiteSearchBackend return SQLiteSearchBackend(params) else: from .fallback import DatabaseSearchBackend return DatabaseSearchBackend(params) else: from .fallback import DatabaseSearchBackend return DatabaseSearchBackend(params)

4248d406c011d6ba6207bb0e0e9b885813d961be

__init__.py

Test for presence of fts5 extension in sqlite backend initialisation and migration

wagtail

wagtail/search/backends/database/__init__.py

Python

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

test_nca_feature_names_out

def test_nca_feature_names_out(): X = iris_data y = iris_target est = NeighborhoodComponentsAnalysis().fit(X, y) names_out = est.get_feature_names_out() class_name_lower = est.__class__.__name__.lower() expected_names_out = np.array( [f"{class_name_lower}{i}" for i in range(est.components_.shape[1])], dtype=object, ) assert_array_equal(names_out, expected_names_out)

330881a21ca48c543cc8a67aa0d4e4c1dc1001ab

test_nca.py

ENH Adds get_feature_names_out to neighbors module (#22212) Co-authored-by: Olivier Grisel <[email protected]>

scikit-learn

sklearn/neighbors/tests/test_nca.py

Python

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

test_query_with_bool_in_params

def test_query_with_bool_in_params(client): with mock.patch("rest_api.controller.search.query_pipeline") as mocked_pipeline: # `run` must return a dictionary containing a `query` key mocked_pipeline.run.return_value = {"query": TEST_QUERY} request_body = { "query": TEST_QUERY, "params": {"debug": True, "Retriever": {"top_k": 5}, "Reader": {"top_k": 3}}, } response = client.post(url="/query", json=request_body) assert 200 == response.status_code response_json = response.json() assert response_json["documents"] == [] assert response_json["answers"] == []

632cd1c141a8b485c6ef8695685d2d8eef3ca50f

test_rest_api.py

Allow values that are not dictionaries in the request params in the `/search` endpoint (#2720) * let params contain something else than dictionaries * rewrite the test same style as the main branch

haystack

rest_api/test/test_rest_api.py

Python

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

_setup_amd

def _setup_amd(cls, arguments): logger.debug("Setting up for AMD") try: import plaidml # noqa pylint:disable=unused-import,import-outside-toplevel except ImportError: logger.error("PlaidML not found. Run `pip install plaidml-keras` for AMD support") return False from lib.gpu_stats import setup_plaidml # pylint:disable=import-outside-toplevel setup_plaidml(arguments.loglevel, arguments.exclude_gpus) logger.debug("setup up for PlaidML") return True

bdbbad4d310fb606b6f412aa81e9f57ccd994e97

launcher.py

Refactor lib.gpu_stats (#1218) * inital gpu_stats refactor * Add dummy CPU Backend * Update Sphinx documentation

faceswap

lib/cli/launcher.py

Python

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

is_arborescence

def is_arborescence(G): return is_tree(G) and max(d for n, d in G.in_degree()) <= 1 @nx.utils.not_implemented_for("undirected")

5a7985fc41bc0c686c035de43c66cf4fb5fcc94f

@nx.utils.not_implemented_for("undirected")

recognition.py

Added examples in tournament and tree functions (#5536) * examples * examples * examples * Example changed * improved styling * revised * edge labels * improved styling * spacing * error testing * examples * styling * add_nodes removed * spaceing * spacing * spacing * added examples * removed random_tournament example * added examples in branching and aborescence * error removed

networkx

networkx/algorithms/tree/recognition.py

Python

https://github.com/networkx/networkx.git

test_public_receipt_can_override_private

def test_public_receipt_can_override_private(self) -> None: # Send a message as the first user res = self.helper.send(self.room_id, body="hello", tok=self.tok) # Send a private read receipt channel = self.make_request( "POST", f"/rooms/{self.room_id}/receipt/{ReceiptTypes.READ_PRIVATE}/{res['event_id']}", {}, access_token=self.tok2, ) self.assertEqual(channel.code, 200) self.assertIsNone(self._get_read_receipt()) # Send a public read receipt channel = self.make_request( "POST", f"/rooms/{self.room_id}/receipt/{ReceiptTypes.READ}/{res['event_id']}", {}, access_token=self.tok2, ) self.assertEqual(channel.code, 200) # Test that we did override the private read receipt self.assertNotEqual(self._get_read_receipt(), None)

116a4c8340b729ffde43be33df24d417384cb28b

test_sync.py

Implement changes to MSC2285 (hidden read receipts) (#12168) * Changes hidden read receipts to be a separate receipt type (instead of a field on `m.read`). * Updates the `/receipts` endpoint to accept `m.fully_read`.

synapse

tests/rest/client/test_sync.py

Python

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

_print_pgf_to_fh

def _print_pgf_to_fh(self, fh, *, bbox_inches_restore=None): header_text = # append the preamble used by the backend as a comment for debugging header_info_preamble = ["%% Matplotlib used the following preamble"] for line in _get_preamble().splitlines(): header_info_preamble.append("%% " + line) header_info_preamble.append("%%") header_info_preamble = "\n".join(header_info_preamble) # get figure size in inch w, h = self.figure.get_figwidth(), self.figure.get_figheight() dpi = self.figure.dpi # create pgfpicture environment and write the pgf code fh.write(header_text) fh.write(header_info_preamble) fh.write("\n") _writeln(fh, r"\begingroup") _writeln(fh, r"\makeatletter") _writeln(fh, r"\begin{pgfpicture}") _writeln(fh, r"\pgfpathrectangle{\pgfpointorigin}{\pgfqpoint{%fin}{%fin}}" % (w, h)) _writeln(fh, r"\pgfusepath{use as bounding box, clip}") renderer = MixedModeRenderer(self.figure, w, h, dpi, RendererPgf(self.figure, fh), bbox_inches_restore=bbox_inches_restore) self.figure.draw(renderer) # end the pgfpicture environment _writeln(fh, r"\end{pgfpicture}") _writeln(fh, r"\makeatother") _writeln(fh, r"\endgroup")

7bafb8be7c6e81180e9518a91d10da9422321a0c

backend_pgf.py

Deprecate internal use of get/set dpi

matplotlib

lib/matplotlib/backends/backend_pgf.py

Python

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

to_pandas_refs

def to_pandas_refs(self) -> List[ObjectRef["pandas.DataFrame"]]: block_to_df = cached_remote_fn(_block_to_df) return [block_to_df.remote(block) for block in self._blocks.get_blocks()]

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

dataset.py

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

ray

python/ray/data/dataset.py

Python

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

build

def build(self, var_list, exclude_from_weight_decay=None): super().build(var_list) if hasattr(self, "_built") and self._built: return self._built = True if not hasattr(self, "_exclude_from_weight_decay"): self._exclude_from_weight_decay = exclude_from_weight_decay or [] self._momentums = [] self._velocities = [] for var in var_list: self._momentums.append( self.add_variable_from_reference( model_variable=var, variable_name="m" ) ) self._velocities.append( self.add_variable_from_reference( model_variable=var, variable_name="v" ) ) if self.amsgrad: self._velocity_hats = [] for var in var_list: self._velocity_hats.append( self.add_variable_from_reference( model_variable=var, variable_name="vhat" ) )

84afc5193d38057e2e2badf9c889ea87d80d8fbf

adamw.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/optimizers/optimizer_experimental/adamw.py

Python

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

validate_input

async def validate_input(data): base = Alpha2Base(data["host"]) try: await base.update_data() except (aiohttp.client_exceptions.ClientConnectorError, asyncio.TimeoutError): return {"error": "cannot_connect"} except Exception: # pylint: disable=broad-except _LOGGER.exception("Unexpected exception") return {"error": "unknown"} # Return info that you want to store in the config entry. return {"title": base.name}

243d003acc11d638feb3867410c3cbb1987520bc

config_flow.py

Add Moehlenhoff Alpha2 underfloor heating system integration (#42771) * Add Moehlenhoff Alpha2 underfloor heating system integration * isort changes * flake8 changes * Do not exclude config_flow.py * pylint changes * Add config_flow test * correct requirements_test_all.txt * more tests * Update test description * Test connection and catch TimeoutError in async_setup_entry * Add version to manifest file * Remove version from manifest file * Replace tests.async_mock.patch by unittest.mock.patch * Update moehlenhoff-alpha2 to version 1.0.1 * Update requirements for moehlenhoff-alpha2 1.0.1 * Update moehlenhoff-alpha2 to 1.0.2 * Use async_setup_platforms * Use async_unload_platforms * Separate connection and devices for each entry_id * Use async_track_time_interval to schedule updates * Check if input is valid before checking uniqueness * Move Exception handling to validate_input * Catch aiohttp.client_exceptions.ClientConnectorError * Remove translation files * Mock TimeoutError * Fix data update * Replace current callback implementation with ha dispatcher * Return False in should_poll * Remove unused argument * Remove CONNECTION_CLASS * Use _async_current_entries * Call async_schedule_update_ha_state after data update * Remove unneeded async_setup Co-authored-by: Milan Meulemans <[email protected]> * Remove unneeded async_setup_platform Co-authored-by: Milan Meulemans <[email protected]> * Set Schema attribute host required Co-authored-by: Milan Meulemans <[email protected]> * Remove unused Exception class Co-authored-by: Milan Meulemans <[email protected]> * Update manifest.json Co-authored-by: Milan Meulemans <[email protected]> * pylint constructor return type None * Replace properties by class variables * use pass instead of return * Remove unused sync update method * remove property hvac_action * remove pass * rework exception handling * Update homeassistant/components/moehlenhoff_alpha2/config_flow.py Co-authored-by: Milan Meulemans <[email protected]> * Correct indentation * catch Exception in validate_input * Replace HomeAssistantType with HomeAssistant * Update to moehlenhoff-alpha2 1.0.3 * Allow to switch between heating and cooling mode * Update moehlenhoff-alpha2 to version 1.0.4 * Update heatarea data after setting target temperature * Support hvac_action * Fix heatarea update with multiple bases * Update data after setting preset mode * Use custom preset modes like defined by device * Fix config flow test * Fix test_duplicate_error * Rename property to extra_state_attributes Rename property device_state_attributes to extra_state_attributes and return lowercase keys in dict. * Refactor using DataUpdateCoordinator * Remove _attr_should_poll * Raise HomeAssistantError on communication error Catch HTTPError instead of broad except and reraise as HomeAssistantError * Change DataUpdateCoordinator name to alpha2_base * Refresh coordinator before setting data * Raise ValueError on invalid heat area mode * Rename heatarea to heat_area * Set type annotation in class attribute * Move coordinator to top * Move exception handling to the coordinator * Use heat_area_id directly * Sore get_cooling() result into local var * Add explanation of status attributes and remove BLOCK_HC * Fix pylint warnings * from __future__ import annotations * Use Platform Enum * Move data handling to coordinator * Remove property extra_state_attributes * Add missing annotations * Update moehlenhoff-alpha2 to version 1.1.2 * Rework tests based on the scaffold template * Set also heat/cool/day/night temp with target temp * Remove unneeded code from tests Co-authored-by: Milan Meulemans <[email protected]>

core

homeassistant/components/moehlenhoff_alpha2/config_flow.py

Python

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

_update

def _update(self) -> int: retval = self.update() logger.debug("Updated %s: %s", self.__class__.__name__, retval) return retval

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

test_edgeql_scope_for_with_computable_01

async def test_edgeql_scope_for_with_computable_01(self): await self.assert_query_result( r, tb.bag([ {"name": "Alice", "namelen": 5}, {"name": "Bob", "namelen": 3}, {"name": "Carol", "namelen": 5}, {"name": "Dave", "namelen": 4} ]) )

0dada08f4eedb104bfa40932b576e44d82218547

test_edgeql_scope.py

Always include the definition context namespace in computable contexts (#3331) We need to include the *original* source namespace in our ctx namespace when compiling computables. The current mechanism of trying to look up in view_sets or failing that using the source namespace from the computable use, but this was failing to find it in some cases with FOR. Fix this by instead directly pulling in the namespace from qlctx. The inclusion of qlctx's namespace nicely allows us to ditch so later logic as well. Additionally we need to merge the namespace into *both* sides in get_view_map_remapping, to handle cases like referencing a `FOR` variable where the current ns doesn't get merged in. Fixes #3323.

edgedb

tests/test_edgeql_scope.py

Python

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

transform

def transform(self, X): check_is_fitted(self) if self.n_neighbors is not None: distances, indices = self.nbrs_.kneighbors(X, return_distance=True) else: distances, indices = self.nbrs_.radius_neighbors(X, return_distance=True) # Create the graph of shortest distances from X to # training data via the nearest neighbors of X. # This can be done as a single array operation, but it potentially # takes a lot of memory. To avoid that, use a loop: n_samples_fit = self.nbrs_.n_samples_fit_ n_queries = distances.shape[0] if hasattr(X, "dtype") and X.dtype == np.float32: dtype = np.float32 else: dtype = np.float64 G_X = np.zeros((n_queries, n_samples_fit), dtype) for i in range(n_queries): G_X[i] = np.min(self.dist_matrix_[indices[i]] + distances[i][:, None], 0) G_X **= 2 G_X *= -0.5 return self.kernel_pca_.transform(G_X)

e2e7d75d1e81ce3b67257fcc4cce32ab2d2acd2f

_isomap.py

MAINT Extend dtype preserved common test to check transform (#24982)

scikit-learn

sklearn/manifold/_isomap.py

Python

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

check_status

def check_status(self): status = { 'success': False } try: con = self.__connect() with closing(con) as con: status['success'] = con.is_connected() except Exception as e: log.error(f'Error connecting to MySQL {self.database}, {e}!') status['error'] = e return status

ef0262e95a1e1a5403896088ca3938adb895a8d6

mysql_handler.py

Add mysql handler

mindsdb

mindsdb/integrations/mysql_handler/mysql_handler.py

Python

https://github.com/mindsdb/mindsdb.git

execute

def execute(): auto_email_reports = frappe.db.get_values( "Auto Email Report", {"report": "Requested Items to Order"}, ["name"] ) for auto_email_report in auto_email_reports: frappe.delete_doc("Auto Email Report", auto_email_report[0]) frappe.db.sql( )

494bd9ef78313436f0424b918f200dab8fc7c20b

delete_report_requested_items_to_order.py

style: format code with black

erpnext

erpnext/patches/v13_0/delete_report_requested_items_to_order.py

Python

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

check_send_to_ereader

def check_send_to_ereader(entry): formats = list() book_formats = list() if len(entry.data): for ele in iter(entry.data): if ele.uncompressed_size < config.mail_size: formats.append(ele.format) if 'EPUB' in formats: book_formats.append({'format': 'Epub', 'convert': 0, 'text': _('Send %(format)s to E-Reader', format='Epub')}) if 'MOBI' in formats: book_formats.append({'format': 'Mobi', 'convert': 0, 'text': _('Send %(format)s to E-Reader', format='Mobi')}) if 'PDF' in formats: book_formats.append({'format': 'Pdf', 'convert': 0, 'text': _('Send %(format)s to E-Reader', format='Pdf')}) if 'AZW' in formats: book_formats.append({'format': 'Azw', 'convert': 0, 'text': _('Send %(format)s to E-Reader', format='Azw')}) if config.config_converterpath: book_formats.extend(check_send_to_ereader_with_converter(formats)) return book_formats else: log.error(u'Cannot find book entry %d', entry.id) return None # Check if a reader is existing for any of the book formats, if not, return empty list, otherwise return # list with supported formats

fbac3e38ac116855b930ee60fb3c997337ae17b7

helper.py

Eenabled send epubs to E-Reader devices

calibre-web

cps/helper.py

Python

https://github.com/janeczku/calibre-web.git

test_async_on_entire_period

async def test_async_on_entire_period(recorder_mock, hass): start_time = dt_util.utcnow() - timedelta(minutes=60) t0 = start_time + timedelta(minutes=20) t1 = t0 + timedelta(minutes=10) t2 = t1 + timedelta(minutes=10) # Start t0 t1 t2 End # |--20min--|--20min--|--10min--|--10min--| # |---on----|--off----|---on----|--off----|

31a787558fd312331b55e5c2c4b33341fc3601fc

test_sensor.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_stats/test_sensor.py

Python

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

on_post_template

def on_post_template(self, output_content, template_name, config): return output_content # Page events

f79b34d174e41084391868e7b503f5c61b8b1bdf

plugins.py

Move plugin events docs into source code + refactor * Create real (no-op) methods for each event in the base class. * Refactor event dispatcher to not check for methods' existence, instead just call them. * Move documentation from Markdown into docstrings of these methods. * Activate the 'mkdocstrings' plugin. * Use 'mkdocstrings' to insert documentation from those docstrings into the site.

mkdocs

mkdocs/plugins.py

Python

https://github.com/mkdocs/mkdocs.git

frame_has_faces

def frame_has_faces(self, frame_name): retval = bool(self._data.get(frame_name, {}).get("faces", [])) logger.trace("'%s': %s", frame_name, retval) return retval

5e73437be47f2410439a3c6716de96354e6a0c94

alignments.py

lib.align updates: - alignments.py - Add typed dicts for imported alignments - Explicitly check for presence of thumb value in alignments dict - linting - detected_face.py - Typing - Linting - Legacy support for pre-aligned face - Update dependencies to new property names

faceswap

lib/align/alignments.py

Python

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

smart_resize

def smart_resize(x, size, interpolation='bilinear'): if len(size) != 2: raise ValueError('Expected `size` to be a tuple of 2 integers, ' f'but got: {size}.') img = tf.convert_to_tensor(x) if img.shape.rank is not None: if img.shape.rank < 3 or img.shape.rank > 4: raise ValueError( 'Expected an image array with shape `(height, width, channels)`, ' 'or `(batch_size, height, width, channels)`, but ' f'got input with incorrect rank, of shape {img.shape}.') shape = tf.shape(img) height, width = shape[-3], shape[-2] target_height, target_width = size if img.shape.rank is not None: static_num_channels = img.shape[-1] else: static_num_channels = None crop_height = tf.cast( tf.cast(width * target_height, 'float32') / target_width, 'int32') crop_width = tf.cast( tf.cast(height * target_width, 'float32') / target_height, 'int32') # Set back to input height / width if crop_height / crop_width is not smaller. crop_height = tf.minimum(height, crop_height) crop_width = tf.minimum(width, crop_width) crop_box_hstart = tf.cast( tf.cast(height - crop_height, 'float32') / 2, 'int32') crop_box_wstart = tf.cast(tf.cast(width - crop_width, 'float32') / 2, 'int32') if img.shape.rank == 4: crop_box_start = tf.stack([0, crop_box_hstart, crop_box_wstart, 0]) crop_box_size = tf.stack([-1, crop_height, crop_width, -1]) else: crop_box_start = tf.stack([crop_box_hstart, crop_box_wstart, 0]) crop_box_size = tf.stack([crop_height, crop_width, -1]) img = tf.slice(img, crop_box_start, crop_box_size) img = tf.image.resize(images=img, size=size, method=interpolation) # Apparent bug in resize_images_v2 may cause shape to be lost if img.shape.rank is not None: if img.shape.rank == 4: img.set_shape((None, None, None, static_num_channels)) if img.shape.rank == 3: img.set_shape((None, None, static_num_channels)) if isinstance(x, np.ndarray): return img.numpy() return img

9dc9a78cc6502226775a99725c654fab3298aa5f

image_utils.py

Expose all utilities in `keras.utils.__init__.py`, and resolve the hourglass import issues that led to the creation of an extraneous `all_utils.py` file / library. PiperOrigin-RevId: 435725558

keras

keras/utils/image_utils.py

Python

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

_port_scan_icmp

def _port_scan_icmp(self, port): ret = None # Create the ping command # Use the system ping command because it already have the sticky bit set # Python can not create ICMP packet with non root right if WINDOWS: timeout_opt = '-w' count_opt = '-n' elif MACOS or BSD: timeout_opt = '-t' count_opt = '-c' else: # Linux and co... timeout_opt = '-W' count_opt = '-c' # Build the command line # Note: Only string are allowed cmd = [ 'ping', count_opt, '1', timeout_opt, str(self._resolv_name(port['timeout'])), self._resolv_name(port['host']), ] fnull = open(os.devnull, 'w') try: counter = Counter() ret = subprocess.check_call(cmd, stdout=fnull, stderr=fnull, close_fds=True) if ret == 0: port['status'] = counter.get() else: port['status'] = False except subprocess.CalledProcessError: # Correct issue #1084: No Offline status for timed-out ports port['status'] = False except Exception as e: logger.debug("{}: Error while pinging host {} ({})".format(self.plugin_name, port['host'], e)) fnull.close() return ret

be927fda3dc4118b77ad0f88d5e6deb652a5f5b3

glances_ports.py

Prepare memory leak test. Not active for the moment

glances

glances/plugins/glances_ports.py

Python

https://github.com/nicolargo/glances.git

shutdown

async def shutdown(self) -> None: # Stop polling/writing Console dimensions to clients self.shutdown_event.set() await self.size_poll_task # We're shutting down the server, so inform all connected clients for client in self.clients: await client.close() self.clients.clear()

36d7973c7c6792fd1100d5512140a4701b53ba3d

service.py

Code review actions

textual

src/textual/devtools/service.py

Python

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

_intersection

def _intersection(self, other, sort): # For IntervalIndex we also know other.inclusive == self.inclusive if self.left.is_unique and self.right.is_unique: taken = self._intersection_unique(other) elif other.left.is_unique and other.right.is_unique and self.isna().sum() <= 1: # Swap other/self if other is unique and self does not have # multiple NaNs taken = other._intersection_unique(self) else: # duplicates taken = self._intersection_non_unique(other) if sort is None: taken = taken.sort_values() return taken

7e23a37e1c5bda81234801a6584563e2880769eb

interval.py

ENH: consistency of input args for boundaries - Interval (#46522)

pandas

pandas/core/indexes/interval.py

Python

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

load_from_saved_model

def load_from_saved_model(saved_model_path, custom_objects=None): warnings.warn( "`tf.keras.experimental.load_from_saved_model` is deprecated" "and will be removed in a future version. " "Please switch to `tf.keras.models.load_model`.", stacklevel=2, ) # restore model topology from json string model_json_filepath = tf.io.gfile.join( tf.compat.as_bytes(saved_model_path), tf.compat.as_bytes(tf.saved_model.ASSETS_DIRECTORY), tf.compat.as_bytes(SAVED_MODEL_FILENAME_JSON), ) with tf.io.gfile.GFile(model_json_filepath, "r") as f: model_json = f.read() model = model_config.model_from_json( model_json, custom_objects=custom_objects ) # restore model weights checkpoint_prefix = tf.io.gfile.join( tf.compat.as_text(saved_model_path), tf.compat.as_text(tf.saved_model.VARIABLES_DIRECTORY), tf.compat.as_text(tf.saved_model.VARIABLES_FILENAME), ) model.load_weights(checkpoint_prefix) return model #### Directory / path helpers

84afc5193d38057e2e2badf9c889ea87d80d8fbf

saved_model_experimental.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/saving/saved_model_experimental.py

Python

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

add_html_cache_busting

def add_html_cache_busting(app, pagename, templatename, context, doctree): from sphinx.builders.html import Stylesheet, JavaScript css_tag = context['css_tag'] js_tag = context['js_tag']

e87416b33b01f6fc4e3b2290d6e8a60e6ddb6e55

conf.py

DOC: Add cache busting to all static assets We have seen both in `/stable` and `/3.6.0`, some styling is broken because old CSS is cached. CSS might change from updating sphinx-gallery, mpl-sphinx-theme, pydata-sphinx-theme, etc. Adding a versioned query breaks the cache. It's a bit over-eager to base it on Matplotlib version and not the file contents (since those dependencies may not have updated), but this should work well enough.

matplotlib

doc/conf.py

Python

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

target_temperature_high

def target_temperature_high(self): if self.hvac_mode == HVACMode.HEAT_COOL: return self._econet.cool_set_point return None

04b9c9300645fb30541e2bf0881d35cc698a47c5

climate.py

Use climate enums in econet (#70633)

core

homeassistant/components/econet/climate.py

Python

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

_promote_shapes

def _promote_shapes(fun_name, *args): if len(args) < 2: return args else: shapes = [shape(arg) for arg in args] if _all(len(shapes[0]) == len(s) for s in shapes[1:]): return args # no need for rank promotion, so rely on lax promotion nonscalar_ranks = {len(shp) for shp in shapes if shp} if len(nonscalar_ranks) < 2: return args else: if config.jax_numpy_rank_promotion != "allow": _rank_promotion_warning_or_error(fun_name, shapes) result_shape = lax.broadcast_shapes(*shapes) return [broadcast_to(arg, result_shape) for arg, shp in zip(args, shapes)]

d9dcd1394aedf760272f14c3560cd5415495c28a

lax_numpy.py

djax: let make_jaxpr build dyn shape jaxprs

jax

jax/_src/numpy/lax_numpy.py

Python

https://github.com/google/jax.git

_build_attention

def _build_attention(self, qkv_rank): if self._attention_axes is None: self._attention_axes = tuple(range(1, qkv_rank - 2)) else: self._attention_axes = tuple(self._attention_axes) # pragma: no cover ( self._dot_product_equation, self._combine_equation, attn_scores_rank, ) = _build_attention_equation(qkv_rank, attn_axes=self._attention_axes) norm_axes = tuple( range(attn_scores_rank - len(self._attention_axes), attn_scores_rank) ) self._masked_softmax = MaskedSoftmax( mask_expansion_axes=[1], normalization_axes=norm_axes ) self._dropout_layer = layers.Dropout(rate=self._dropout)

b97d27d2e916025f65fed751d54c089d4d4bd022

keras_layers.py

clean up imports

autokeras

autokeras/keras_layers.py

Python

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

test_visibility_when_disabled

def test_visibility_when_disabled(self) -> None: room_id = self.helper.create_room_as(self.user_id, tok=self.token) self.helper.send_state( room_id=room_id, event_type=EventTypes.Retention, body={"max_lifetime": one_day_ms}, tok=self.token, ) resp = self.helper.send(room_id=room_id, body="test", tok=self.token) self.reactor.advance(one_day_ms * 2 / 1000) self.get_event(room_id, resp["event_id"])

4cc4229cd7a55d2556c798fecbb1c9660dc821c8

test_retention.py

Prevent expired events from being filtered out when retention is disabled (#12611) Co-authored-by: Richard van der Hoff <[email protected]> Co-authored-by: Patrick Cloke <[email protected]>

synapse

tests/rest/client/test_retention.py

Python

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

update_status_for_contracts

def update_status_for_contracts(): contracts = frappe.get_all( "Contract", filters={"is_signed": True, "docstatus": 1}, fields=["name", "start_date", "end_date"], ) for contract in contracts: status = get_status(contract.get("start_date"), contract.get("end_date")) frappe.db.set_value("Contract", contract.get("name"), "status", status)

494bd9ef78313436f0424b918f200dab8fc7c20b

contract.py

style: format code with black

erpnext

erpnext/crm/doctype/contract/contract.py

Python

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

test_unique_id

async def test_unique_id(hass): await setup_test_entity( hass, { "unique": { "command_open": "echo open", "command_close": "echo close", "command_stop": "echo stop", "unique_id": "unique", }, "not_unique_1": { "command_open": "echo open", "command_close": "echo close", "command_stop": "echo stop", "unique_id": "not-so-unique-anymore", }, "not_unique_2": { "command_open": "echo open", "command_close": "echo close", "command_stop": "echo stop", "unique_id": "not-so-unique-anymore", }, }, ) assert len(hass.states.async_all()) == 2 ent_reg = entity_registry.async_get(hass) assert len(ent_reg.entities) == 2 assert ent_reg.async_get_entity_id("cover", "command_line", "unique") is not None assert ( ent_reg.async_get_entity_id("cover", "command_line", "not-so-unique-anymore") is not None )

d26275011ae4e8ba0a8dcdc2a7ef81b5911d3900

test_cover.py

Add unique_id configuration variable to command_line integration (#58596)

core

tests/components/command_line/test_cover.py

Python

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

MultivariateT

def MultivariateT(syms, mu, sigma, v): return multivariate_rv(MultivariateTDistribution, syms, mu, sigma, v) #------------------------------------------------------------------------------- # Multivariate Normal Gamma distribution ---------------------------------------

7fe8e027ae1d7f683243c0229b961671a6cbb4c5

joint_rv_types.py

Improved some documentation in the stats module

sympy

sympy/stats/joint_rv_types.py

Python

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

choose_agent

async def choose_agent(self) -> Optional[JobAgentSubmissionClient]: # the number of agents which has an available HTTP port. while True: raw_agent_infos = await DataOrganizer.get_all_agent_infos() agent_infos = { key: value for key, value in raw_agent_infos.items() if value.get("httpPort", -1) > 0 } if len(agent_infos) > 0: break await asyncio.sleep(dashboard_consts.TRY_TO_GET_AGENT_INFO_INTERVAL_SECONDS) # delete dead agents. for dead_node in set(self._agents) - set(agent_infos): client = self._agents.pop(dead_node) await client.close() if len(self._agents) >= dashboard_consts.CANDIDATE_AGENT_NUMBER: node_id = sample(set(self._agents), 1)[0] return self._agents[node_id] else: # Randomly select one from among all agents, it is possible that # the selected one already exists in `self._agents` node_id = sample(set(agent_infos), 1)[0] agent_info = agent_infos[node_id] if node_id not in self._agents: node_ip = agent_info["ipAddress"] http_port = agent_info["httpPort"] agent_http_address = f"http://{node_ip}:{http_port}" self._agents[node_id] = JobAgentSubmissionClient(agent_http_address) return self._agents[node_id]

db2f84bdfa49d218f97bf7f10678232bff8c48d5

job_head.py

[Job Submission][refactor 5/N] Remove the head node dependency on the `Raylet` process (#28599) * introduce stop_job Signed-off-by: Catch-Bull <[email protected]> * save Signed-off-by: Catch-Bull <[email protected]> * save Signed-off-by: Catch-Bull <[email protected]> * save Signed-off-by: Catch-Bull <[email protected]> * head rayletless Signed-off-by: Catch-Bull <[email protected]> * fix UT Signed-off-by: Catch-Bull <[email protected]> * fix UT Signed-off-by: Catch-Bull <[email protected]> * save Signed-off-by: Catch-Bull <[email protected]> * refactor choose_agent Signed-off-by: Catch-Bull <[email protected]> * fix Signed-off-by: Catch-Bull <[email protected]> * save Signed-off-by: Catch-Bull <[email protected]> * save Signed-off-by: Catch-Bull <[email protected]> * fix UT * delete mock Signed-off-by: Catch-Bull <[email protected]> * Use "auto" for entrypoint script Signed-off-by: Archit Kulkarni <[email protected]> Signed-off-by: Catch-Bull <[email protected]> Signed-off-by: Archit Kulkarni <[email protected]> Co-authored-by: Archit Kulkarni <[email protected]>