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semeru

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text-code-galeras-code-generation-from-docstring-3k-deduped

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Semeru Lab 7

def tutorial_taskflow_api_etl_docker_virtualenv(): # [END instantiate_dag] # [START extract_virtualenv]

airflow/providers/docker/example_dags/tutorial_taskflow_api_etl_docker_virtualenv.py

airflow

Python

5d89dea56843d7b76d5e308e373ba16ecbcffa77

tutorial_taskflow_api_etl_docker_virtualenv.py

tutorial_taskflow_api_etl_docker_virtualenv

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

Switch to Debian 11 (bullseye) as base for our dockerfiles (#21378) Debian 11 Bullseye have been released some time ago as the new LTS Debian release and already all our dependencies (including MySQL and MSSQL ODBC drivers) caught up with it so we can finally migrate to it. This change switches base images to bullsey for our Dockerfiles as well as for Redis image we are using in CI. The relevant packages have been updated to include that and documentation have been updated. Examples of ours also are updated to use "bullseye" rather than buster. Closes: #18190 Closes: #18279

def call_score(self, other_args): parser = argparse.ArgumentParser( add_help=False, formatter_class=argparse.ArgumentDefaultsHelpFormatter, prog="score", description=, ) ns_parser = parse_known_args_and_warn( parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED ) if ns_parser: pycoingecko_view.display_score( self.coin_map_df["CoinGecko"], ns_parser.export )

gamestonk_terminal/cryptocurrency/due_diligence/dd_controller.py

OpenBBTerminal

Python

ea964109d654394cc0a5237e6ec5510ba6404097

dd_controller.py

call_score

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

Crypto menu refactor (#1119) * enabled some crypto commands in dd to be called independent of source loaded * support for coin_map_df in all dd functions + load ta and plot chart refactor * updated tests and removed coingecko scrapping where possible * removed ref of command from hugo * updated pycoingecko version * refactoring load * refactored load to fetch prices; pred can run independent of source now * load by default usd on cp/cg and usdt on cb/bin * updated to rich for formatting and updated dependencies * fixed changes requested * update docs * revert discord requirements * removed absolute from calculate change for price * fixing pr issues * fix loading issue when similar coins exist, move coins to home, fill n/a * update docs for coins * adds load to ta and pred menu

def defragment6(packets): # Remove non fragments lst = [x for x in packets if IPv6ExtHdrFragment in x] if not lst: return [] id = lst[0][IPv6ExtHdrFragment].id llen = len(lst) lst = [x for x in lst if x[IPv6ExtHdrFragment].id == id] if len(lst) != llen: warning("defragment6: some fragmented packets have been removed from list") # noqa: E501 # reorder fragments res = [] while lst: min_pos = 0 min_offset = lst[0][IPv6ExtHdrFragment].offset for p in lst: cur_offset = p[IPv6ExtHdrFragment].offset if cur_offset < min_offset: min_pos = 0 min_offset = cur_offset res.append(lst[min_pos]) del lst[min_pos] # regenerate the fragmentable part fragmentable = b"" for p in res: q = p[IPv6ExtHdrFragment] offset = 8 * q.offset if offset != len(fragmentable): warning("Expected an offset of %d. Found %d. Padding with XXXX" % (len(fragmentable), offset)) # noqa: E501 fragmentable += b"X" * (offset - len(fragmentable)) fragmentable += raw(q.payload) # Regenerate the unfragmentable part. q = res[0].copy() nh = q[IPv6ExtHdrFragment].nh q[IPv6ExtHdrFragment].underlayer.nh = nh q[IPv6ExtHdrFragment].underlayer.plen = len(fragmentable) del q[IPv6ExtHdrFragment].underlayer.payload q /= conf.raw_layer(load=fragmentable) del q.plen if q[IPv6].underlayer: q[IPv6] = IPv6(raw(q[IPv6])) else: q = IPv6(raw(q)) return q

scapy/layers/inet6.py

scapy

Python

08b1f9d67c8e716fd44036a027bdc90dcb9fcfdf

inet6.py

defragment6

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

E275 - Missing whitespace after keyword (#3711) Co-authored-by: Alexander Aring <[email protected]> Co-authored-by: Anmol Sarma <[email protected]> Co-authored-by: antoine.torre <[email protected]> Co-authored-by: Antoine Vacher <[email protected]> Co-authored-by: Arnaud Ebalard <[email protected]> Co-authored-by: atlowl <[email protected]> Co-authored-by: Brian Bienvenu <[email protected]> Co-authored-by: Chris Packham <[email protected]> Co-authored-by: CQ <[email protected]> Co-authored-by: Daniel Collins <[email protected]> Co-authored-by: Federico Maggi <[email protected]> Co-authored-by: Florian Maury <[email protected]> Co-authored-by: _Frky <[email protected]> Co-authored-by: g-mahieux <[email protected]> Co-authored-by: gpotter2 <[email protected]> Co-authored-by: Guillaume Valadon <[email protected]> Co-authored-by: Hao Zheng <[email protected]> Co-authored-by: Haresh Khandelwal <[email protected]> Co-authored-by: Harri Hämäläinen <[email protected]> Co-authored-by: hecke <[email protected]> Co-authored-by: Jan Romann <[email protected]> Co-authored-by: Jan Sebechlebsky <[email protected]> Co-authored-by: jdiog0 <[email protected]> Co-authored-by: jockque <[email protected]> Co-authored-by: Julien Bedel <[email protected]> Co-authored-by: Keith Scott <[email protected]> Co-authored-by: Kfir Gollan <[email protected]> Co-authored-by: Lars Munch <[email protected]> Co-authored-by: ldp77 <[email protected]> Co-authored-by: Leonard Crestez <[email protected]> Co-authored-by: Marcel Patzlaff <[email protected]> Co-authored-by: Martijn Thé <[email protected]> Co-authored-by: Martine Lenders <[email protected]> Co-authored-by: Michael Farrell <[email protected]> Co-authored-by: Michał Mirosław <[email protected]> Co-authored-by: mkaliszan <[email protected]> Co-authored-by: mtury <[email protected]> Co-authored-by: Neale Ranns <[email protected]> Co-authored-by: Octavian Toader <[email protected]> Co-authored-by: Peter Eisenlohr <[email protected]> Co-authored-by: Phil <[email protected]> Co-authored-by: Pierre Lalet <[email protected]> Co-authored-by: Pierre Lorinquer <[email protected]> Co-authored-by: piersoh <[email protected]> Co-authored-by: plorinquer <[email protected]> Co-authored-by: pvinci <[email protected]> Co-authored-by: Rahul Jadhav <[email protected]> Co-authored-by: Robin Jarry <[email protected]> Co-authored-by: romain-perez <[email protected]> Co-authored-by: rperez <rperez@debian> Co-authored-by: Sabrina Dubroca <[email protected]> Co-authored-by: Sebastian Baar <[email protected]> Co-authored-by: sebastien mainand <[email protected]> Co-authored-by: smehner1 <[email protected]> Co-authored-by: speakinghedge <[email protected]> Co-authored-by: Steven Van Acker <[email protected]> Co-authored-by: Thomas Faivre <[email protected]> Co-authored-by: Tran Tien Dat <[email protected]> Co-authored-by: Wael Mahlous <[email protected]> Co-authored-by: waeva <[email protected]> Co-authored-by: Alexander Aring <[email protected]> Co-authored-by: Anmol Sarma <[email protected]> Co-authored-by: antoine.torre <[email protected]> Co-authored-by: Antoine Vacher <[email protected]> Co-authored-by: Arnaud Ebalard <[email protected]> Co-authored-by: atlowl <[email protected]> Co-authored-by: Brian Bienvenu <[email protected]> Co-authored-by: Chris Packham <[email protected]> Co-authored-by: CQ <[email protected]> Co-authored-by: Daniel Collins <[email protected]> Co-authored-by: Federico Maggi <[email protected]> Co-authored-by: Florian Maury <[email protected]> Co-authored-by: _Frky <[email protected]> Co-authored-by: g-mahieux <[email protected]> Co-authored-by: gpotter2 <[email protected]> Co-authored-by: Guillaume Valadon <[email protected]> Co-authored-by: Hao Zheng <[email protected]> Co-authored-by: Haresh Khandelwal <[email protected]> Co-authored-by: Harri Hämäläinen <[email protected]> Co-authored-by: hecke <[email protected]> Co-authored-by: Jan Romann <[email protected]> Co-authored-by: Jan Sebechlebsky <[email protected]> Co-authored-by: jdiog0 <[email protected]> Co-authored-by: jockque <[email protected]> Co-authored-by: Julien Bedel <[email protected]> Co-authored-by: Keith Scott <[email protected]> Co-authored-by: Kfir Gollan <[email protected]> Co-authored-by: Lars Munch <[email protected]> Co-authored-by: ldp77 <[email protected]> Co-authored-by: Leonard Crestez <[email protected]> Co-authored-by: Marcel Patzlaff <[email protected]> Co-authored-by: Martijn Thé <[email protected]> Co-authored-by: Martine Lenders <[email protected]> Co-authored-by: Michael Farrell <[email protected]> Co-authored-by: Michał Mirosław <[email protected]> Co-authored-by: mkaliszan <[email protected]> Co-authored-by: mtury <[email protected]> Co-authored-by: Neale Ranns <[email protected]> Co-authored-by: Octavian Toader <[email protected]> Co-authored-by: Peter Eisenlohr <[email protected]> Co-authored-by: Phil <[email protected]> Co-authored-by: Pierre Lalet <[email protected]> Co-authored-by: Pierre Lorinquer <[email protected]> Co-authored-by: piersoh <[email protected]> Co-authored-by: pvinci <[email protected]> Co-authored-by: Rahul Jadhav <[email protected]> Co-authored-by: Robin Jarry <[email protected]> Co-authored-by: romain-perez <[email protected]> Co-authored-by: rperez <rperez@debian> Co-authored-by: Sabrina Dubroca <[email protected]> Co-authored-by: Sebastian Baar <[email protected]> Co-authored-by: sebastien mainand <[email protected]> Co-authored-by: smehner1 <[email protected]> Co-authored-by: Steven Van Acker <[email protected]> Co-authored-by: Thomas Faivre <[email protected]> Co-authored-by: Tran Tien Dat <[email protected]> Co-authored-by: Wael Mahlous <[email protected]> Co-authored-by: waeva <[email protected]>

def flattened_having(self) -> List[Condition]: flattened: List[Condition] = [] boolean_conditions: List[BooleanCondition] = [] for condition in self.having: if isinstance(condition, Condition): flattened.append(condition) elif isinstance(condition, BooleanCondition): boolean_conditions.append(condition) while len(boolean_conditions) > 0: boolean_condition = boolean_conditions.pop() for condition in boolean_condition.conditions: if isinstance(condition, Condition): flattened.append(condition) elif isinstance(condition, BooleanCondition): boolean_conditions.append(condition) return flattened

src/sentry/search/events/builder.py

sentry

Python

2a4da479b2d4a2faa901701f4c73ff823236e9e8

builder.py

flattened_having

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

fix(snql): Add aggregations to select in auto_aggregation (#31061) - This is to fix an issue for queries that have the uniq aggregation in the HAVING clause, and is not selected. - Previously we would not add the aggregation to the select clause in these cases - Now anything in the having clause will get added to the select clause as well if auto_aggregation is enabled - if its disabled we raise an invalid search query error - This also fixes a bug where this having validation wasn't working correctly for boolean conditions

def scale_var(self) -> tk.StringVar: retval = self._vars["scale"] assert isinstance(retval, tk.StringVar) return retval

lib/training/preview_tk.py

faceswap

Python

7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5

preview_tk.py

scale_var

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

Training - Use custom preview pop-out

def test_second_upgrade_from_different_user(self) -> None: channel = self._upgrade_room() self.assertEqual(200, channel.code, channel.result) channel = self._upgrade_room(self.other_token, expire_cache=False) self.assertEqual(400, channel.code, channel.result)

tests/rest/client/test_upgrade_room.py

synapse

Python

99d3931974e65865d1102ee79d7b7e2b017a3180

test_upgrade_room.py

test_second_upgrade_from_different_user

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

Add more tests for room upgrades (#13074) Signed-off-by: Sean Quah <[email protected]>

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 tex_dir.exists(): tex_dir.mkdir() result = tex_dir / (tex_hash(output) + ".tex") if not result.exists(): logger.info( "Writing %(expression)s to %(path)s", {"expression": expression, "path": f"{result}"}, ) result.write_text(output, encoding="utf-8") return result

manim/utils/tex_file_writing.py

manim

Python

9d1f066d637cb15baea10e6907ab85efff8fb36f

tex_file_writing.py

generate_tex_file

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

Migrate more `os.path` to `pathlib` (#2980) * Migrate more `os.path` to `pathlib` * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix type errors with recent pathlib code * pathlib fixes * more pathlib fixes * remove unused imports introduced by pathlib migration * convert `open()` calls to pathlib * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Migrate tex_file_writing to pathlib * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * converted more old code to pathlib, and fixed a bug in module_ops * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix test failures * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix test failures * Apply suggestions from code review Co-authored-by: Benjamin Hackl <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Benjamin Hackl <[email protected]>

def find_legacy_row() -> StatementLambdaElement: return lambda_stmt(lambda: select(func.max(States.event_id)))

homeassistant/components/recorder/queries.py

core

Python

a70e2a33dcd85608f1145d8fc2e89a87620f4ef3

queries.py

find_legacy_row

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

Fixing purging legacy rows and improve performance (#71916)

def completed_count(self): return sum(int(result.successful()) for result in self.results)

celery/result.py

celery

Python

720d1928c4b583f36ca0cce7607b616466f2ffbb

result.py

completed_count

https://github.com/celery/celery.git

Add clarifying information to completed_count documentation (#7873) * Add clarifying information to completed_count docstring * Update canvas documentation

def _create_mock_app_session(*args, **kwargs): mock_id = mock.PropertyMock( return_value="mock_id:%s" % ServerTestCase._next_session_id ) ServerTestCase._next_session_id += 1 mock_session = mock.MagicMock(AppSession, autospec=True, *args, **kwargs) type(mock_session).id = mock_id return mock_session

lib/tests/server_test_case.py

streamlit

Python

704eab3478cf69847825b23dabf15813a8ac9fa2

server_test_case.py

_create_mock_app_session

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

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".

def upgrade(refresh=True, dist_upgrade=False, **kwargs): cache_valid_time = kwargs.pop("cache_valid_time", 0) if salt.utils.data.is_true(refresh): refresh_db(cache_valid_time) old = list_pkgs() if "force_conf_new" in kwargs and kwargs["force_conf_new"]: dpkg_options = ["--force-confnew"] else: dpkg_options = ["--force-confold", "--force-confdef"] cmd = [ "apt-get", "-q", "-y", ] for option in dpkg_options: cmd.append("-o") cmd.append("DPkg::Options::={}".format(option)) if kwargs.get("force_yes", False): cmd.append("--force-yes") if kwargs.get("skip_verify", False): cmd.append("--allow-unauthenticated") if kwargs.get("download_only", False) or kwargs.get("downloadonly", False): cmd.append("--download-only") if kwargs.get("allow_downgrades", False): cmd.append("--allow-downgrades") cmd.append("dist-upgrade" if dist_upgrade else "upgrade") result = _call_apt(cmd, env=DPKG_ENV_VARS.copy()) __context__.pop("pkg.list_pkgs", None) new = list_pkgs() ret = salt.utils.data.compare_dicts(old, new) if result["retcode"] != 0: raise CommandExecutionError( "Problem encountered upgrading packages", info={"changes": ret, "result": result}, ) return ret

salt/modules/aptpkg.py

salt

Python

9e1ca8b5b9e7006fea28f473711917755cf5a262

aptpkg.py

upgrade

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

Add --allow-downgrades capability for apt upgrade

def elu(x, alpha=1.0): return backend.elu(x, alpha) @keras_export("keras.activations.selu") @tf.__internal__.dispatch.add_dispatch_support

keras/activations.py

@keras_export("keras.activations.selu") @tf.__internal__.dispatch.add_dispatch_support

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

activations.py

elu

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

async def async_update(self) -> None: try: self._weather = await self._weather_api.async_get_weather(self._station) except (asyncio.TimeoutError, aiohttp.ClientError, ValueError) as error: _LOGGER.error("Could not fetch weather data: %s", error) return self._attr_native_value = getattr( self._weather, self.entity_description.api_key ) if ( self._attr_native_value is None and self.entity_description.key in NONE_IS_ZERO_SENSORS ): self._attr_native_value = 0 self._attr_extra_state_attributes = { ATTR_ACTIVE: self._weather.active, ATTR_MEASURE_TIME: self._weather.measure_time, }

homeassistant/components/trafikverket_weatherstation/sensor.py

core

Python

395093351428d349246e4c1de526b159a167f382

sensor.py

async_update

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

Code improvements to trafikverket_weatherstation (#62854) * Code cleanup * Fix extra state attributes * Fix review comments * Fix precipitation_amount if None * Fix sensors returning None * Use const for sensors reporting None

def required_resources(self) -> Dict[str, float]: return _sum_bundles(self._bundles)

python/ray/tune/execution/placement_groups.py

ray

Python

96cceb08e8bf73df990437002e25883c5a72d30c

placement_groups.py

required_resources

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

[tune] Raise error in PGF if head and worker bundles are empty (#28445) Scheduling empty placement groups is not supported by Ray core (see e.g. #28443), so we shouldn't allow them to be created in the first place. If we need fully empty resource requests, we can include this in the upcoming execution/resource refactor. Signed-off-by: Kai Fricke <[email protected]>

def chvatal_graph(create_using=None): description = [ "adjacencylist", "Chvatal Graph", 12, [ [2, 5, 7, 10], [3, 6, 8], [4, 7, 9], [5, 8, 10], [6, 9], [11, 12], [11, 12], [9, 12], [11], [11, 12], [], [], ], ] G = make_small_undirected_graph(description, create_using) return G

networkx/generators/small.py

networkx

Python

dec723f072eb997a497a159dbe8674cd39999ee9

small.py

chvatal_graph

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

Docstrings for the small.py module (#5240) * added description for the first 5 small graphs * modified descriptions based on comment and added description for two more functions * added doctrings to all the functions * Minor touchups. Co-authored-by: Ross Barnowski <[email protected]>

async def test_igration_and_updating_configuration(hass, hass_storage): core_data = { "data": { "elevation": 10, "latitude": 55, "location_name": "Home", "longitude": 13, "time_zone": "Europe/Copenhagen", "unit_system": "imperial", "external_url": "https://www.example.com", "internal_url": "http://example.local", "currency": "BTC", }, "key": "core.config", "version": 1, "minor_version": 1, } hass_storage["core.config"] = dict(core_data) await config_util.async_process_ha_core_config( hass, {"allowlist_external_dirs": "/etc"} ) await hass.config.async_update(latitude=50, currency="USD") expected_new_core_data = copy.deepcopy(core_data) # From async_update above expected_new_core_data["data"]["latitude"] = 50 expected_new_core_data["data"]["currency"] = "USD" # 1.1 -> 1.2 store migration with migrated unit system expected_new_core_data["data"]["unit_system_v2"] = "us_customary" expected_new_core_data["minor_version"] = 2 assert hass_storage["core.config"] == expected_new_core_data assert hass.config.latitude == 50 assert hass.config.currency == "USD"

tests/test_config.py

core

Python

67d1dde69fbacf33f2c39ea14d89f2afa425ed18

test_config.py

test_igration_and_updating_configuration

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

Rename IMPERIAL_SYSTEM to US_CUSTOMARY_SYSTEM (#80253) * Rename IMPERIAL_SYSTEM * Deprecate is_metric property and adjust tests * Adjust unit_system config validation * Add yaml tests * Add tests for private name * Fix incorrect rebase * Adjust docstring * Add store migration * Update unit_system.py * Minimise test tweaks * Fix tests * Add conversion to migration * Rename new key and adjust tests * Adjust websocket_detect_config * Move original_unit_system tracking to subclass

def mock_cpuinfo_config_flow() -> Generator[MagicMock, None, None]: with patch( "homeassistant.components.cpuspeed.config_flow.cpuinfo.get_cpu_info", return_value=True, ) as cpuinfo_mock: yield cpuinfo_mock @pytest.fixture

tests/components/cpuspeed/conftest.py

@pytest.fixture

core

Python

63d519c1a896c6eb20f7ffb032cb7712bbac6b5c

conftest.py

mock_cpuinfo_config_flow

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

Spelling updates (#82867)

def _propagate_index_objs(self, axis=None): self._filter_empties() if axis is None or axis == 0: cum_row_lengths = np.cumsum([0] + self._row_lengths) if axis is None or axis == 1: cum_col_widths = np.cumsum([0] + self._column_widths) if axis is None:

modin/core/dataframe/pandas/dataframe/dataframe.py

modin

Python

3c740dbfcdd69ddc3ab45a42be996e5c61104342

dataframe.py

_propagate_index_objs

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

FEAT-#3111: Ensure relabeling Modin Frame does not lose partition shape (#3662) Co-authored-by: Devin Petersohn <[email protected]> Signed-off-by: Naren Krishna <[email protected]>

def _get_counts(values, uniques): if values.dtype.kind in "OU": counter = _NaNCounter(values) output = np.zeros(len(uniques), dtype=np.int64) for i, item in enumerate(uniques): with suppress(KeyError): output[i] = counter[item] return output unique_values, counts = _unique_np(values, return_counts=True) # Recorder unique_values based on input: `uniques` uniques_in_values = np.isin(uniques, unique_values, assume_unique=True) if np.isnan(unique_values[-1]) and np.isnan(uniques[-1]): uniques_in_values[-1] = True unique_valid_indices = np.searchsorted(unique_values, uniques[uniques_in_values]) output = np.zeros_like(uniques, dtype=np.int64) output[uniques_in_values] = counts[unique_valid_indices] return output

sklearn/utils/_encode.py

scikit-learn

Python

7f0006c8aad1a09621ad19c3db19c3ff0555a183

_encode.py

_get_counts

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

ENH Adds infrequent categories to OneHotEncoder (#16018) * ENH Completely adds infrequent categories * STY Linting * STY Linting * DOC Improves wording * DOC Lint * BUG Fixes * CLN Address comments * CLN Address comments * DOC Uses math to description float min_frequency * DOC Adds comment regarding drop * BUG Fixes method name * DOC Clearer docstring * TST Adds more tests * FIX Fixes mege * CLN More pythonic * CLN Address comments * STY Flake8 * CLN Address comments * DOC Fix * MRG * WIP * ENH Address comments * STY Fix * ENH Use functiion call instead of property * ENH Adds counts feature * CLN Rename variables * DOC More details * CLN Remove unneeded line * CLN Less lines is less complicated * CLN Less diffs * CLN Improves readiabilty * BUG Fix * CLN Address comments * TST Fix * CLN Address comments * CLN Address comments * CLN Move docstring to userguide * DOC Better wrapping * TST Adds test to handle_unknown='error' * ENH Spelling error in docstring * BUG Fixes counter with nan values * BUG Removes unneeded test * BUG Fixes issue * ENH Sync with main * DOC Correct settings * DOC Adds docstring * DOC Immprove user guide * DOC Move to 1.0 * DOC Update docs * TST Remove test * DOC Update docstring * STY Linting * DOC Address comments * ENH Neater code * DOC Update explaination for auto * Update sklearn/preprocessing/_encoders.py Co-authored-by: Roman Yurchak <[email protected]> * TST Uses docstring instead of comments * TST Remove call to fit * TST Spelling error * ENH Adds support for drop + infrequent categories * ENH Adds infrequent_if_exist option * DOC Address comments for user guide * DOC Address comments for whats_new * DOC Update docstring based on comments * CLN Update test with suggestions * ENH Adds computed property infrequent_categories_ * DOC Adds where the infrequent column is located * TST Adds more test for infrequent_categories_ * DOC Adds docstring for _compute_drop_idx * CLN Moves _convert_to_infrequent_idx into its own method * TST Increases test coverage * TST Adds failing test * CLN Careful consideration of dropped and inverse_transform * STY Linting * DOC Adds docstrinb about dropping infrequent * DOC Uses only * DOC Numpydoc * TST Includes test for get_feature_names_out * DOC Move whats new * DOC Address docstring comments * DOC Docstring changes * TST Better comments * TST Adds check for handle_unknown='ignore' for infrequent * CLN Make _infrequent_indices private * CLN Change min_frequency default to None * DOC Adds comments * ENH adds support for max_categories=1 * ENH Describe lexicon ordering for ties * DOC Better docstring * STY Fix * CLN Error when explicity dropping an infrequent category * STY Grammar Co-authored-by: Joel Nothman <[email protected]> Co-authored-by: Roman Yurchak <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]>

def log_error(self, format, *args): self.log_message(format, *args)

python3.10.4/Lib/http/server.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

server.py

log_error

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

add python 3.10.4 for windows

def _video_tmp_file(self) -> str: path, filename = os.path.split(self._output_filename) retval = os.path.join(path, f"__tmp_{filename}") logger.debug(retval) return retval

plugins/convert/writer/ffmpeg.py

faceswap

Python

60291d49c4da1cd260fbc0b04aa6a312eedfefbb

ffmpeg.py

_video_tmp_file

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

ffmpeg writer: Create new filename if output pre-exists

def bar_chart(self, data=None, width=0, height=0, use_container_width=True): if _use_arrow(): return self.dg._arrow_bar_chart(data, width, height, use_container_width) else: return self.dg._legacy_bar_chart(data, width, height, use_container_width)

lib/streamlit/elements/dataframe_selector.py

streamlit

Python

72703b38029f9358a0ec7ca5ed875a6b438ece19

dataframe_selector.py

bar_chart

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

Replace static apps with live Cloud apps (#4317) Co-authored-by: kajarenc <[email protected]>

def write_filepath(filepath, strategy): dirpath = os.path.dirname(filepath) base = os.path.basename(filepath) return os.path.join(write_dirpath(dirpath, strategy), base)

keras/distribute/distributed_file_utils.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

distributed_file_utils.py

write_filepath

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def draw_tex(self, gc, x, y, s, prop, angle, *, mtext=None): self._draw_text_as_path(gc, x, y, s, prop, angle, ismath="TeX")

lib/matplotlib/backend_bases.py

matplotlib

Python

3b52d2b64f58c1eb912bd343e7c197a1ed0b92b5

backend_bases.py

draw_tex

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

Remove redundant method, fix signature and add doc-string to draw_tex

def tax_account_query(doctype, txt, searchfield, start, page_len, filters): company_currency = erpnext.get_company_currency(filters.get("company")) def get_accounts(with_account_type_filter): account_type_condition = "" if with_account_type_filter: account_type_condition = "AND account_type in %(account_types)s" accounts = frappe.db.sql( .format( account_type_condition=account_type_condition, searchfield=searchfield, mcond=get_match_cond(doctype), ), dict( account_types=filters.get("account_type"), company=filters.get("company"), disabled=filters.get("disabled", 0), currency=company_currency, txt="%{}%".format(txt), offset=start, limit=page_len, ), ) return accounts tax_accounts = get_accounts(True) if not tax_accounts: tax_accounts = get_accounts(False) return tax_accounts @frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

erpnext/controllers/queries.py

@frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

erpnext

Python

a1e3ae8869194a487acccc706a381db74c4aa1ff

queries.py

tax_account_query

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

fix: user can select disabled accounts in taxes table

def filter_packages_untagged(self, package_data): matches = {} for package in package_data: if "metadata" in package and "container" in package["metadata"]: container_metadata = package["metadata"]["container"] if "tags" in container_metadata: container_tags = container_metadata["tags"] if not len(container_tags): matches[package["name"]] = package return matches

.github/scripts/cleanup-tags.py

paperless-ngx

Python

0fdd3d56f43c8442a0c9ecd3cad07a88137ff7de

cleanup-tags.py

filter_packages_untagged

https://github.com/paperless-ngx/paperless-ngx.git

Changes the cleanup images workflow so it uses a OAuth token with the correct scope (GITHUB_TOKEN is not enough). Also prevents running if the token is not defined and generally does commenting/cleanups"

def employee_query(doctype, txt, searchfield, start, page_len, filters): filters = frappe._dict(filters) conditions = [] include_employees = [] emp_cond = "" if not filters.payroll_frequency: frappe.throw(_("Select Payroll Frequency.")) if filters.start_date and filters.end_date: employee_list = get_employee_list(filters) emp = filters.get("employees") or [] include_employees = [ employee.employee for employee in employee_list if employee.employee not in emp ] filters.pop("start_date") filters.pop("end_date") filters.pop("salary_slip_based_on_timesheet") filters.pop("payroll_frequency") filters.pop("payroll_payable_account") filters.pop("currency") if filters.employees is not None: filters.pop("employees") if include_employees: emp_cond += "and employee in %(include_employees)s" return frappe.db.sql( .format( **{ "key": searchfield, "fcond": get_filters_cond(doctype, filters, conditions), "mcond": get_match_cond(doctype), "emp_cond": emp_cond, } ), { "txt": "%%%s%%" % txt, "_txt": txt.replace("%", ""), "start": start, "page_len": page_len, "include_employees": include_employees, }, )

erpnext/payroll/doctype/payroll_entry/payroll_entry.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

payroll_entry.py

employee_query

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

style: format code with black

def _process_contour_level_args(self, args): if self.levels is None: if len(args) == 0: levels_arg = 7 # Default, hard-wired. else: levels_arg = args[0] else: levels_arg = self.levels if isinstance(levels_arg, Integral): self.levels = self._autolev(levels_arg) else: self.levels = np.asarray(levels_arg, np.float64) if not self.filled: inside = (self.levels > self.zmin) & (self.levels < self.zmax) levels_in = self.levels[inside] if len(levels_in) == 0: self.levels = [self.zmin] _api.warn_external( "No contour levels were found within the data range.") if self.filled and len(self.levels) < 2: raise ValueError("Filled contours require at least 2 levels.") if len(self.levels) > 1 and np.min(np.diff(self.levels)) <= 0.0: raise ValueError("Contour levels must be increasing")

lib/matplotlib/contour.py

matplotlib

Python

1068a6faa19767724437461bcfb88c6852ec435c

contour.py

_process_contour_level_args

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

Remove unnecessary np.{,as}array / astype calls. Quite often numpy will call asarray for us, saving us the need to call asarray explicitly. When we do call asarray (or array) ourselves, a dtype can directly be passed in, rather than immediately calling astype immediately after. Passing the dtype makes it unnecessary for asarray to infer the dtype of the passed-in container, and can also save an extra array allocation if asarray first has to allocate an array of a type and astype immediately has to allocate an array of another type.

def _get_classifier_global_metrics(is_binomial, y, y_pred, y_probs, labels): metrics = {} metrics["accuracy"] = sk_metrics.accuracy_score(y, y_pred) metrics["example_count"] = len(y) if not is_binomial: metrics["f1_score_micro"] = sk_metrics.f1_score(y, y_pred, average="micro", labels=labels) metrics["f1_score_macro"] = sk_metrics.f1_score(y, y_pred, average="macro", labels=labels) if y_probs is not None: metrics["log_loss"] = sk_metrics.log_loss(y, y_probs, labels=labels) return metrics

mlflow/models/evaluation/default_evaluator.py

mlflow

Python

964f5ab75098c55f028f8acfeeae05df35ea68d5

default_evaluator.py

_get_classifier_global_metrics

https://github.com/mlflow/mlflow.git

Evaluation Default evaluator (#5092) * init Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * rename module Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * revert black change Signed-off-by: Weichen Xu <[email protected]> * change module path Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * fix Signed-off-by: Weichen Xu <[email protected]> * refactor Signed-off-by: Weichen Xu <[email protected]> * lazy load pyspark Signed-off-by: Weichen Xu <[email protected]> * revert export Signed-off-by: Weichen Xu <[email protected]> * fix curcit import Signed-off-by: Weichen Xu <[email protected]> * update tests Signed-off-by: Weichen Xu <[email protected]> * fix conftest.py Signed-off-by: Weichen Xu <[email protected]> * Revert "fix conftest.py" This reverts commit 2ea29c62bfffc5461bf77f3da15b5c00f51de19b. * fix tests Signed-off-by: Weichen Xu <[email protected]> * update doc Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * default evaluator Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * fix Signed-off-by: Weichen Xu <[email protected]> * fix Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * fix doc Signed-off-by: Weichen Xu <[email protected]> * fix doc Signed-off-by: Weichen Xu <[email protected]> * update import Signed-off-by: Weichen Xu <[email protected]> * fix doc Signed-off-by: Weichen Xu <[email protected]> * update hash algo Signed-off-by: Weichen Xu <[email protected]> * update import Signed-off-by: Weichen Xu <[email protected]> * address comment Signed-off-by: Weichen Xu <[email protected]> * add tests Signed-off-by: Weichen Xu <[email protected]> * fix lint Signed-off-by: Weichen Xu <[email protected]> * add tests Signed-off-by: Weichen Xu <[email protected]> * add more tests Signed-off-by: Weichen Xu <[email protected]> * add tests Signed-off-by: Weichen Xu <[email protected]> * fix lint Signed-off-by: Weichen Xu <[email protected]> * update shap explainer Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * remove scikitplot dep Signed-off-by: Weichen Xu <[email protected]> * add pr curve Signed-off-by: Weichen Xu <[email protected]> * add shap.summary_plot Signed-off-by: Weichen Xu <[email protected]> * log explainer Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * improve explainer code Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * update shap init Signed-off-by: Weichen Xu <[email protected]> * update explainer creating Signed-off-by: Weichen Xu <[email protected]> * update predict_proba Signed-off-by: Weichen Xu <[email protected]> * address comments Signed-off-by: Weichen Xu <[email protected]> * refactor Signed-off-by: Weichen Xu <[email protected]> * add multi-class metrics artifacts Signed-off-by: Weichen Xu <[email protected]> * update doc Signed-off-by: Weichen Xu <[email protected]> * add log_loss metric Signed-off-by: Weichen Xu <[email protected]> * lazy load pyspark Signed-off-by: Weichen Xu <[email protected]> * address ben comments Signed-off-by: Weichen Xu <[email protected]> * fix Signed-off-by: Weichen Xu <[email protected]> * prevent show shap logo, add tests Signed-off-by: Weichen Xu <[email protected]> * support spark model Signed-off-by: Weichen Xu <[email protected]> * add tests Signed-off-by: Weichen Xu <[email protected]> * add shap version check Signed-off-by: Weichen Xu <[email protected]> * update docs, loose classifier label limit Signed-off-by: Weichen Xu <[email protected]> * add tests Signed-off-by: Weichen Xu <[email protected]> * multiclass classifier merge metrics/plots Signed-off-by: Weichen Xu <[email protected]> * zfill feature name Signed-off-by: Weichen Xu <[email protected]> * update doc Signed-off-by: Weichen Xu <[email protected]> * add config max_num_classes_threshold_logging_roc_pr_curve_for_multiclass_classifier Signed-off-by: Weichen Xu <[email protected]> * refactor Signed-off-by: Weichen Xu <[email protected]> * update tests Signed-off-by: Weichen Xu <[email protected]> * improve label handling Signed-off-by: Weichen Xu <[email protected]> * refactor Signed-off-by: Weichen Xu <[email protected]> * add tests Signed-off-by: Weichen Xu <[email protected]> * black Signed-off-by: Weichen Xu <[email protected]> * update Signed-off-by: Weichen Xu <[email protected]> * increase plot dpi Signed-off-by: Weichen Xu <[email protected]> * fix test fixture Signed-off-by: Weichen Xu <[email protected]> * fix pylint Signed-off-by: Weichen Xu <[email protected]> * update doc Signed-off-by: Weichen Xu <[email protected]> * use matplot rc_context Signed-off-by: Weichen Xu <[email protected]> * fix shap import Signed-off-by: Weichen Xu <[email protected]> * refactor EvaluationDataset Signed-off-by: Weichen Xu <[email protected]> * limit user specify shap algos Signed-off-by: Weichen Xu <[email protected]> * clean Signed-off-by: Weichen Xu <[email protected]> * update evaluation dataset Signed-off-by: Weichen Xu <[email protected]> * use svg fig Signed-off-by: Weichen Xu <[email protected]> * revert svg Signed-off-by: Weichen Xu <[email protected]> * curve dashline, legend display ap/roc, legend move out Signed-off-by: Weichen Xu <[email protected]> * linewidth 1 Signed-off-by: Weichen Xu <[email protected]> * keyword arguments for evaluate, fix tests Signed-off-by: Weichen Xu <[email protected]> * mark abc.abstractmethod, kw args for ModelEvaluator methods Signed-off-by: Weichen Xu <[email protected]> * fix pylint Signed-off-by: Weichen Xu <[email protected]> * fix pylint Signed-off-by: Weichen Xu <[email protected]>

def test_show_message_twice(view, info1, info2, count): view.show_message(info1) view.show_message(info2) assert len(view._messages) == count

tests/unit/mainwindow/test_messageview.py

qutebrowser

Python

676e01677183825d19107d3b2fbf1bb2c0684ede

test_messageview.py

test_show_message_twice

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

Only replace the exact same message If we have a error message followed by an info message with the same text, they should both be shown, not replaced automatically.

def check_auth(f):

py/visdom/utils/server_utils.py

visdom

Python

60c90e313e106c0af62339d29eeda0e62823c648

server_utils.py

check_auth

https://github.com/fossasia/visdom.git

Refactoring server.py into more intentional files

def start_leader_mode(self): logger.info("Running rpc.replicate in Leader mode") logger.info("-" * 15) logger.info(f"API_KEY: {self.secret_api_key}") logger.info("-" * 15) self.register_leader_endpoint() self.submit_coroutine(self.leader_loop())

freqtrade/rpc/replicate/__init__.py

freqtrade

Python

9f6bba40af1a407f190a89f5c0c8b4e3f528ba46

__init__.py

start_leader_mode

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

initial concept for replicate, basic leader and follower logic

def test_exclude_glob_case5(): incl_dom = {} incl_glob = {} incl_ent = {"binary_sensor.working"} excl_dom = {} excl_glob = {"binary_sensor.*"} excl_ent = {"light.ignoreme", "sensor.notworking"} testfilter = generate_filter( incl_dom, incl_ent, excl_dom, excl_ent, incl_glob, excl_glob ) assert testfilter("sensor.test") assert testfilter("sensor.notworking") is False assert testfilter("light.test") assert testfilter("light.ignoreme") is False assert testfilter("binary_sensor.working") assert testfilter("binary_sensor.another") is False assert testfilter("sun.sun") is True

tests/helpers/test_entityfilter.py

core

Python

a8349a4866d22cddbca9ac9367d4affae39a8325

test_entityfilter.py

test_exclude_glob_case5

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

Adjust entity filters to make includes stronger than excludes (#74080) * Adjust entity filters to make includes stronger than excludes Fixes #59080 * adjust test for stronger entity glob includes * sync with docs

def _generate_client_device_id() -> str: return random_uuid_hex()

homeassistant/components/jellyfin/config_flow.py

core

Python

5b0a37a44752edbbf785d6a200e3b7a3f5fa2047

config_flow.py

_generate_client_device_id

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

Use persistent device id for jellyfin requests (#79840)

def evaluate_loss(net, data_iter, loss): metric = d2l.Accumulator(2) # Sum of losses, no. of examples for X, y in data_iter: l = loss(net(X), y) metric.add(d2l.reduce_sum(l), d2l.size(l)) return metric[0] / metric[1] DATA_HUB = dict() DATA_URL = 'http://d2l-data.s3-accelerate.amazonaws.com/'

d2l/mxnet.py

d2l-zh

Python

b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2

mxnet.py

evaluate_loss

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

[PaddlePaddle] Merge master into Paddle branch (#1186) * change 15.2 title in chinese version (#1109) change title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘ * 修改部分语义表述 (#1105) * Update r0.17.5 (#1120) * Bump versions in installation * 94行typo: （“bert.mall”）->（“bert.small”） (#1129) * line 313: "bert.mall" -> "bert.small" (#1130) * fix: update language as native reader (#1114) * Fix the translation of "stride" (#1115) * Update index.md (#1118) 修改部分语义表述 * Update self-attention-and-positional-encoding.md (#1133) 依照本书的翻译习惯，将pooling翻译成汇聚 * maybe a comment false (#1149) * maybe a little false * maybe a little false * A minor bug in the rcnn section (Chinese edition) (#1148) * Update bert.md (#1137) 一个笔误 # 假设batch_size=2，num_pred_positions=3 # 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1] * Update calculus.md (#1135) * fix typo in git documentation (#1106) * fix: Update the Chinese translation in lr-scheduler.md (#1136) * Update lr-scheduler.md * Update chapter_optimization/lr-scheduler.md Co-authored-by: goldmermaid <[email protected]> Co-authored-by: goldmermaid <[email protected]> * fix translation for kaggle-house-price.md (#1107) * fix translation for kaggle-house-price.md * fix translation for kaggle-house-price.md Signed-off-by: sunhaizhou <[email protected]> * Update weight-decay.md (#1150) * Update weight-decay.md 关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解 关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。 并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释 解释为何会增加复杂性以及为何需要细粒度工具。 * Update chapter_multilayer-perceptrons/weight-decay.md yep Co-authored-by: goldmermaid <[email protected]> * Update chapter_multilayer-perceptrons/weight-decay.md yep Co-authored-by: goldmermaid <[email protected]> Co-authored-by: goldmermaid <[email protected]> * Fix a spelling error (#1161) * Update gru.md (#1152) The key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state. 翻译错误 * Unify the function naming (#1113) Unify naming of the function 'init_xavier()'. * Update mlp-concise.md (#1166) * Update mlp-concise.md 语句不通顺 * Update environment.md 语序异常 * Update config.ini * fix the imprecise description (#1168) Co-authored-by: yuande <yuande> * fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175) * Fix some typos. (#1163) * Update batch-norm.md (#1170) fixing typos u->x in article * Update linear-regression.md (#1090) We invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that 原译文把who也直接翻译出来了。 * Update mlp.md (#1117) * Update mlp.md 修改部分语义表述 * Update chapter_multilayer-perceptrons/mlp.md Co-authored-by: goldmermaid <[email protected]> * Update chapter_multilayer-perceptrons/mlp.md Co-authored-by: Aston Zhang <[email protected]> Co-authored-by: goldmermaid <[email protected]> * Correct a translation error. (#1091) * Correct a translation error. * Update chapter_computer-vision/image-augmentation.md Co-authored-by: Aston Zhang <[email protected]> * Update aws.md (#1121) * Update aws.md * Update chapter_appendix-tools-for-deep-learning/aws.md Co-authored-by: Aston Zhang <[email protected]> * Update image-augmentation.md (#1093) * Update anchor.md (#1088) fix a minor issue in code * Update anchor.md * Update image-augmentation.md * fix typo and improve translation in chapter_linear-networks\softmax-regression.md (#1087) * Avoid `torch.meshgrid` user warning (#1174) Avoids the following user warning: ```python ~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2228.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] ``` * bump to 2.0.0-beta1 * Update sequence.md * bump beta1 on readme * Add latex code block background to config * BLD: Bump python support version 3.9 (#1183) * BLD: Bump python support version 3.9 * Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4 * BLD: Bump torch and tensorflow * Update Jenkinsfile * Update chapter_installation/index.md * Update chapter_installation/index.md Co-authored-by: Aston Zhang <[email protected]> * Update config.ini * Update INFO.md * Update INFO.md * Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187) * resolve the conflicts * revise from publisher (#1089) * revise from publisher * d2l api * post_latex * revise from publisher * revise ch11 * Delete d2l-Copy1.bib * clear cache * rm d2lbook clear * debug anchor * keep original d2l doc Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Aston Zhang <[email protected]> Co-authored-by: Aston Zhang <[email protected]> * 重复语句 (#1188) Co-authored-by: Aston Zhang <[email protected]> * Improve expression for chapter_preliminaries/pandas.md (#1184) * Update pandas.md * Improve expression * Improve expression * Update chapter_preliminaries/pandas.md Co-authored-by: Aston Zhang <[email protected]> * Improce expression for chapter_preliminaries/linear-algebra.md (#1185) * Improce expression * Improve code comments * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md Co-authored-by: Aston Zhang <[email protected]> * Fix multibox_detection bugs * Update d2l to 0.17.5 version * restore older version * Upgrade pandas * change to python3.8 * Test warning log * relocate warning log * test logs filtering * Update gru.md * Add DeprecationWarning filter * Test warning log * Update attention mechanisms & computational performance * Update multilayer perceptron& linear & convolution networks & computer vision * Update recurrent&optimition&nlp pretraining & nlp applications * ignore warnings * Update index.md * Update linear networks * Update multilayer perceptrons&deep learning computation * Update preliminaries * Check and Add warning filter * Update kaggle-cifar10.md * Update object-detection-dataset.md * Update ssd.md fcn.md * Update hybridize.md * Update hybridize.md Signed-off-by: sunhaizhou <[email protected]> Co-authored-by: zhou201505013 <[email protected]> Co-authored-by: Xinwei Liu <[email protected]> Co-authored-by: Anirudh Dagar <[email protected]> Co-authored-by: Aston Zhang <[email protected]> Co-authored-by: hugo_han <[email protected]> Co-authored-by: gyro永不抽风 <[email protected]> Co-authored-by: CanChengZheng <[email protected]> Co-authored-by: linlin <[email protected]> Co-authored-by: iuk <[email protected]> Co-authored-by: yoos <[email protected]> Co-authored-by: Mr. Justice Lawrence John Wargrave <[email protected]> Co-authored-by: Chiyuan Fu <[email protected]> Co-authored-by: Sunhuashan <[email protected]> Co-authored-by: Haiker Sun <[email protected]> Co-authored-by: Ming Liu <[email protected]> Co-authored-by: goldmermaid <[email protected]> Co-authored-by: silenceZheng66 <[email protected]> Co-authored-by: Wenchao Yan <[email protected]> Co-authored-by: Kiki2049 <[email protected]> Co-authored-by: Krahets <[email protected]> Co-authored-by: friedmainfunction <[email protected]> Co-authored-by: Jameson <[email protected]> Co-authored-by: P. Yao <[email protected]> Co-authored-by: Yulv-git <[email protected]> Co-authored-by: Liu,Xiao <[email protected]> Co-authored-by: YIN, Gang <[email protected]> Co-authored-by: Joe-HZ <[email protected]> Co-authored-by: lybloveyou <[email protected]> Co-authored-by: VigourJiang <[email protected]> Co-authored-by: zxhd863943427 <[email protected]> Co-authored-by: LYF <[email protected]> Co-authored-by: Aston Zhang <[email protected]> Co-authored-by: xiaotinghe <[email protected]> Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Holly-Max <[email protected]> Co-authored-by: HinGwenWoong <[email protected]> Co-authored-by: Shuai Zhang <[email protected]>

def _copy2_ignoring_special_files(src, dest): # type: (str, str) -> None try: copy2_fixed(src, dest) except shutil.SpecialFileError as e: # SpecialFileError may be raised due to either the source or # destination. If the destination was the cause then we would actually # care, but since the destination directory is deleted prior to # copy we ignore all of them assuming it is caused by the source. logger.warning( "Ignoring special file error '%s' encountered copying %s to %s.", str(e), src, dest, )

.venv/lib/python3.8/site-packages/pip/_internal/operations/prepare.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

prepare.py

_copy2_ignoring_special_files

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

upd; format

def prepare_template(self) -> None:

airflow/models/base.py

airflow

Python

ff3bbc3db24f9f3f4f88033d48859fb08fc3237b

base.py

prepare_template

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

Implement enough interface for MappedOperator to be baggable (#20945)

def hiddenlabels(self): return self["hiddenlabels"]

packages/python/plotly/plotly/graph_objs/_layout.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_layout.py

hiddenlabels

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

switch to black .22

def test_dataset_shard_error_with_both_format_and_loader_fn(self): dset = ray.data.range(100) config = { "input": "dataset", "input_config": { "format": "json", "paths": self.dset_path, "loader_fn": lambda: dset, }, } with self.assertRaises(ValueError): get_dataset_and_shards(config)

rllib/offline/tests/test_dataset_reader.py

ray

Python

569fe0109629048d08e1d9e023f7769f10bd2244

test_dataset_reader.py

test_dataset_shard_error_with_both_format_and_loader_fn

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

[RLlib] improved unittests for dataset_reader and fixed bugs (#26458)

async def async_refresh_sensor(self) -> None: _LOGGER.debug("Refreshing library sensor for '%s'", self.name) try: await self.hass.async_add_executor_job(self._update_state_and_attrs) self._attr_available = True except NotFound: self._attr_available = False except requests.exceptions.RequestException as err: _LOGGER.error( "Could not update library sensor for '%s': %s", self.library_section.title, err, ) self._attr_available = False self.async_write_ha_state()

homeassistant/components/plex/sensor.py

core

Python

474844744bdd2b0dcba46b82d9d3fcd8e3dbad24

sensor.py

async_refresh_sensor

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

Improve entity type hints [p] (#77871)

def test_joindocuments_score_none(join_mode, sort_by_score): inputs = [ {"documents": [Document(content="text document 1", content_type="text", score=0.2)]}, {"documents": [Document(content="text document 2", content_type="text", score=None)]}, ] join_docs = JoinDocuments(join_mode=join_mode, sort_by_score=sort_by_score) result, _ = join_docs.run(inputs) assert len(result["documents"]) == 2 result, _ = join_docs.run(inputs, top_k_join=1) assert len(result["documents"]) == 1

test/nodes/test_other.py

haystack

Python

408d8e6ff559ed0a195b68284baf3ab23707ffd7

test_other.py

test_joindocuments_score_none

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

Enable the `JoinDocuments` node to work with documents with `score=None` (#2984) * Enable the `JoinDocuments` node to work with documents with `score=None` This fixes #2983 As of now, the `JoinDocuments` node will error out if any of the documents has `score=None` - which is possible, as some retriever are not able to provide a score, like the `TfidfRetriever` on Elasticsearch or the `BM25Retriever` on Weaviate. THe reason for the error is that the `JoinDocuments` always sorts the documents by score and cannot sort when `score=None`. There was a very similar issue for `JoinAnswers` too, which was addressed by this PR: https://github.com/deepset-ai/haystack/pull/2436 This solution applies the same solution to `JoinDocuments` - so both the `JoinAnswers` and `JoinDocuments` now will have the same additional argument to disable sorting when that is requried. The solution is to add an argument to `JoinDocuments` called `sort_by_score: bool`, which allows the user to turn off the sorting of documents by score, but keeps the current functionality of sorting being performed as the default. * Fixing test bug * Addressing PR review comments - Extending unit tests - Simplifying logic * Making the sorting work even with no scores By making the no score being sorted as -Inf * Forgot to commit the change in `join_docs.py` * [EMPTY] Re-trigger CI * Added am INFO log if the `JoinDocuments` is sorting while some of the docs have `score=None` * Adjusting the arguments of `any()` * [EMPTY] Re-trigger CI

def test_parent_skip_branch(session, dag_maker): start_date = pendulum.datetime(2020, 1, 1) with dag_maker( "test_parent_skip_branch_dag", schedule_interval=None, start_date=start_date, session=session, ): op1 = BranchPythonOperator(task_id="op1", python_callable=lambda: "op3") op2 = EmptyOperator(task_id="op2") op3 = EmptyOperator(task_id="op3") op1 >> [op2, op3] tis = { ti.task_id: ti for ti in dag_maker.create_dagrun(run_type=DagRunType.MANUAL, state=State.RUNNING).task_instances } tis["op1"].run() dep = NotPreviouslySkippedDep() assert len(list(dep.get_dep_statuses(tis["op2"], session, DepContext()))) == 1 assert not dep.is_met(tis["op2"], session) assert tis["op2"].state == State.SKIPPED

tests/ti_deps/deps/test_not_previously_skipped_dep.py

airflow

Python

49e336ae0302b386a2f47269a6d13988382d975f

test_not_previously_skipped_dep.py

test_parent_skip_branch

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

Replace usage of `DummyOperator` with `EmptyOperator` (#22974) * Replace usage of `DummyOperator` with `EmptyOperator`

def _check_precomputed(X): if not issparse(X): X = check_array(X) check_non_negative(X, whom="precomputed distance matrix.") return X else: graph = X if graph.format not in ("csr", "csc", "coo", "lil"): raise TypeError( "Sparse matrix in {!r} format is not supported due to " "its handling of explicit zeros".format(graph.format) ) copied = graph.format != "csr" graph = check_array(graph, accept_sparse="csr") check_non_negative(graph, whom="precomputed distance matrix.") graph = sort_graph_by_row_values(graph, copy=not copied, warn_when_not_sorted=True) return graph

sklearn/neighbors/_base.py

scikit-learn

Python

b94bc5ea6821607d1e9826ce2d084c76379820ba

_base.py

_check_precomputed

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

ENH add new function sort_graph_by_row_values (#23139) Co-authored-by: Thomas J. Fan <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]>

def _set_per_output_metric_attributes(self, metrics_dict, output_index): updated_metrics_dict = collections.OrderedDict() for metric_name, metric_fn in metrics_dict.items(): metric_name = self._add_unique_metric_name( metric_name, metric_fn, output_index ) # Update the name on the metric class to be the unique generated name. metric_fn._name = metric_name # pylint: disable=protected-access updated_metrics_dict[metric_name] = metric_fn # Keep track of metric name and function. self._compile_metric_functions.append(metric_fn) return updated_metrics_dict

keras/engine/training_v1.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training_v1.py

_set_per_output_metric_attributes

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

async def test_peer_cert_ignored_with_supervisor(hass, tmpdir): cert_path, key_path, peer_cert_path = await hass.async_add_executor_job( _setup_empty_ssl_pem_files, tmpdir ) with patch("ssl.SSLContext.load_cert_chain"), patch( "homeassistant.components.http.supervisor.has_supervisor", return_value=True ), patch( "ssl.SSLContext.load_verify_locations" ) as mock_load_verify_locations, patch( "homeassistant.util.ssl.server_context_modern", side_effect=server_context_modern, ) as mock_context: assert ( await async_setup_component( hass, "http", { "http": { "ssl_peer_certificate": peer_cert_path, "ssl_profile": "modern", "ssl_certificate": cert_path, "ssl_key": key_path, } }, ) is True ) await hass.async_start() await hass.async_block_till_done() assert len(mock_context.mock_calls) == 1 mock_load_verify_locations.assert_not_called()

tests/components/http/test_init.py

core

Python

938b64081b0cbc21d1a9c1141c1e575824ce31ae

test_init.py

test_peer_cert_ignored_with_supervisor

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

Block peer certs on supervisor (#66837) Co-authored-by: Pascal Vizeli <[email protected]> Co-authored-by: Mike Degatano <[email protected]>

def get_default_locale(self): # Check if the object has any parental keys to another translatable model # If so, take the locale from the object referenced in that parental key parental_keys = [ field for field in self._meta.get_fields() if isinstance(field, ParentalKey) and issubclass(field.related_model, TranslatableMixin) ] if parental_keys: parent_id = parental_keys[0].value_from_object(self) return ( parental_keys[0] .related_model.objects.defer() .select_related("locale") .get(id=parent_id) .locale ) return Locale.get_default()

wagtail/core/models/i18n.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

i18n.py

get_default_locale

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

Reformat with black

def test_copy_with_encryption(self): op = DatabricksCopyIntoOperator( file_location=COPY_FILE_LOCATION, file_format='CSV', table_name='test', task_id=TASK_ID, encryption={'TYPE': 'AWS_SSE_C', 'MASTER_KEY': 'abc'}, ) assert ( op._create_sql_query() == f.strip() )

tests/providers/databricks/operators/test_databricks_sql.py

airflow

Python

401419432082d222b823e4f2a66f21e5cc3ab28d

test_databricks_sql.py

test_copy_with_encryption

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

Add new options to DatabricksCopyIntoOperator (#22076) This includes: * `encryption` - to specify encryption options for a given location * `credential` - to specify authentication options for a given location * `validate` - to control validation of schema & data

def tokenize(lines, token='word'): if token == 'word': return [line.split() for line in lines] elif token == 'char': return [list(line) for line in lines] else: print('ERROR: unknown token type: ' + token)

d2l/mxnet.py

d2l-zh

Python

b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2

mxnet.py

tokenize

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

[PaddlePaddle] Merge master into Paddle branch (#1186) * change 15.2 title in chinese version (#1109) change title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘ * 修改部分语义表述 (#1105) * Update r0.17.5 (#1120) * Bump versions in installation * 94行typo: （“bert.mall”）->（“bert.small”） (#1129) * line 313: "bert.mall" -> "bert.small" (#1130) * fix: update language as native reader (#1114) * Fix the translation of "stride" (#1115) * Update index.md (#1118) 修改部分语义表述 * Update self-attention-and-positional-encoding.md (#1133) 依照本书的翻译习惯，将pooling翻译成汇聚 * maybe a comment false (#1149) * maybe a little false * maybe a little false * A minor bug in the rcnn section (Chinese edition) (#1148) * Update bert.md (#1137) 一个笔误 # 假设batch_size=2，num_pred_positions=3 # 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1] * Update calculus.md (#1135) * fix typo in git documentation (#1106) * fix: Update the Chinese translation in lr-scheduler.md (#1136) * Update lr-scheduler.md * Update chapter_optimization/lr-scheduler.md Co-authored-by: goldmermaid <[email protected]> Co-authored-by: goldmermaid <[email protected]> * fix translation for kaggle-house-price.md (#1107) * fix translation for kaggle-house-price.md * fix translation for kaggle-house-price.md Signed-off-by: sunhaizhou <[email protected]> * Update weight-decay.md (#1150) * Update weight-decay.md 关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解 关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。 并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释 解释为何会增加复杂性以及为何需要细粒度工具。 * Update chapter_multilayer-perceptrons/weight-decay.md yep Co-authored-by: goldmermaid <[email protected]> * Update chapter_multilayer-perceptrons/weight-decay.md yep Co-authored-by: goldmermaid <[email protected]> Co-authored-by: goldmermaid <[email protected]> * Fix a spelling error (#1161) * Update gru.md (#1152) The key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state. 翻译错误 * Unify the function naming (#1113) Unify naming of the function 'init_xavier()'. * Update mlp-concise.md (#1166) * Update mlp-concise.md 语句不通顺 * Update environment.md 语序异常 * Update config.ini * fix the imprecise description (#1168) Co-authored-by: yuande <yuande> * fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175) * Fix some typos. (#1163) * Update batch-norm.md (#1170) fixing typos u->x in article * Update linear-regression.md (#1090) We invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that 原译文把who也直接翻译出来了。 * Update mlp.md (#1117) * Update mlp.md 修改部分语义表述 * Update chapter_multilayer-perceptrons/mlp.md Co-authored-by: goldmermaid <[email protected]> * Update chapter_multilayer-perceptrons/mlp.md Co-authored-by: Aston Zhang <[email protected]> Co-authored-by: goldmermaid <[email protected]> * Correct a translation error. (#1091) * Correct a translation error. * Update chapter_computer-vision/image-augmentation.md Co-authored-by: Aston Zhang <[email protected]> * Update aws.md (#1121) * Update aws.md * Update chapter_appendix-tools-for-deep-learning/aws.md Co-authored-by: Aston Zhang <[email protected]> * Update image-augmentation.md (#1093) * Update anchor.md (#1088) fix a minor issue in code * Update anchor.md * Update image-augmentation.md * fix typo and improve translation in chapter_linear-networks\softmax-regression.md (#1087) * Avoid `torch.meshgrid` user warning (#1174) Avoids the following user warning: ```python ~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2228.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] ``` * bump to 2.0.0-beta1 * Update sequence.md * bump beta1 on readme * Add latex code block background to config * BLD: Bump python support version 3.9 (#1183) * BLD: Bump python support version 3.9 * Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4 * BLD: Bump torch and tensorflow * Update Jenkinsfile * Update chapter_installation/index.md * Update chapter_installation/index.md Co-authored-by: Aston Zhang <[email protected]> * Update config.ini * Update INFO.md * Update INFO.md * Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187) * resolve the conflicts * revise from publisher (#1089) * revise from publisher * d2l api * post_latex * revise from publisher * revise ch11 * Delete d2l-Copy1.bib * clear cache * rm d2lbook clear * debug anchor * keep original d2l doc Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Aston Zhang <[email protected]> Co-authored-by: Aston Zhang <[email protected]> * 重复语句 (#1188) Co-authored-by: Aston Zhang <[email protected]> * Improve expression for chapter_preliminaries/pandas.md (#1184) * Update pandas.md * Improve expression * Improve expression * Update chapter_preliminaries/pandas.md Co-authored-by: Aston Zhang <[email protected]> * Improce expression for chapter_preliminaries/linear-algebra.md (#1185) * Improce expression * Improve code comments * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md Co-authored-by: Aston Zhang <[email protected]> * Fix multibox_detection bugs * Update d2l to 0.17.5 version * restore older version * Upgrade pandas * change to python3.8 * Test warning log * relocate warning log * test logs filtering * Update gru.md * Add DeprecationWarning filter * Test warning log * Update attention mechanisms & computational performance * Update multilayer perceptron& linear & convolution networks & computer vision * Update recurrent&optimition&nlp pretraining & nlp applications * ignore warnings * Update index.md * Update linear networks * Update multilayer perceptrons&deep learning computation * Update preliminaries * Check and Add warning filter * Update kaggle-cifar10.md * Update object-detection-dataset.md * Update ssd.md fcn.md * Update hybridize.md * Update hybridize.md Signed-off-by: sunhaizhou <[email protected]> Co-authored-by: zhou201505013 <[email protected]> Co-authored-by: Xinwei Liu <[email protected]> Co-authored-by: Anirudh Dagar <[email protected]> Co-authored-by: Aston Zhang <[email protected]> Co-authored-by: hugo_han <[email protected]> Co-authored-by: gyro永不抽风 <[email protected]> Co-authored-by: CanChengZheng <[email protected]> Co-authored-by: linlin <[email protected]> Co-authored-by: iuk <[email protected]> Co-authored-by: yoos <[email protected]> Co-authored-by: Mr. Justice Lawrence John Wargrave <[email protected]> Co-authored-by: Chiyuan Fu <[email protected]> Co-authored-by: Sunhuashan <[email protected]> Co-authored-by: Haiker Sun <[email protected]> Co-authored-by: Ming Liu <[email protected]> Co-authored-by: goldmermaid <[email protected]> Co-authored-by: silenceZheng66 <[email protected]> Co-authored-by: Wenchao Yan <[email protected]> Co-authored-by: Kiki2049 <[email protected]> Co-authored-by: Krahets <[email protected]> Co-authored-by: friedmainfunction <[email protected]> Co-authored-by: Jameson <[email protected]> Co-authored-by: P. Yao <[email protected]> Co-authored-by: Yulv-git <[email protected]> Co-authored-by: Liu,Xiao <[email protected]> Co-authored-by: YIN, Gang <[email protected]> Co-authored-by: Joe-HZ <[email protected]> Co-authored-by: lybloveyou <[email protected]> Co-authored-by: VigourJiang <[email protected]> Co-authored-by: zxhd863943427 <[email protected]> Co-authored-by: LYF <[email protected]> Co-authored-by: Aston Zhang <[email protected]> Co-authored-by: xiaotinghe <[email protected]> Co-authored-by: Ubuntu <[email protected]> Co-authored-by: Holly-Max <[email protected]> Co-authored-by: HinGwenWoong <[email protected]> Co-authored-by: Shuai Zhang <[email protected]>

def export_model(self, model_path, calibration_path=None, onnx_path=None, input_shape=None, device=None): assert model_path is not None, 'model_path must be specified' self._unwrap_model() calibration_config = {} for name, module in self.bound_model.named_modules(): if hasattr(module, 'weight_bits'): calibration_config[name] = {} calibration_config[name]['weight_bits'] = int(module.weight_bits) self._del_simulated_attr(module) self.export_model_save(self.bound_model, model_path, calibration_config, calibration_path, onnx_path, input_shape, device) return calibration_config

nni/compression/pytorch/quantization/bnn_quantizer.py

nni

Python

d68c786ff81bad19c04619d6a999ff34aaa724e7

bnn_quantizer.py

export_model

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

[Compression] remove pruning v1 & refactor directory (#5228)

def test_new_room_user_is_not_local(self) -> None: channel = self.make_request( "DELETE", self.url, content={"new_room_user_id": "@not:exist.bla"}, access_token=self.admin_user_tok, ) self.assertEqual(400, channel.code, msg=channel.json_body) self.assertEqual( "User must be our own: @not:exist.bla", channel.json_body["error"], )

tests/rest/admin/test_room.py

synapse

Python

2281427175e4c93a30c39607fb4ac23c2a1f399f

test_room.py

test_new_room_user_is_not_local

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

Use literals in place of `HTTPStatus` constants in tests (#13488) * Use literals in place of `HTTPStatus` constants in tests * newsfile * code style * code style

def _make_zipfile(base_name, base_dir, verbose=0, dry_run=0, logger=None): zip_filename = base_name + ".zip" archive_dir = os.path.dirname(base_name) if not os.path.exists(archive_dir): if logger is not None: logger.info("creating %s", archive_dir) if not dry_run: os.makedirs(archive_dir) # If zipfile module is not available, try spawning an external 'zip' # command. try: import zipfile except ImportError: zipfile = None if zipfile is None: _call_external_zip(base_dir, zip_filename, verbose, dry_run) else: if logger is not None: logger.info("creating '%s' and adding '%s' to it", zip_filename, base_dir) if not dry_run: zip = zipfile.ZipFile(zip_filename, "w", compression=zipfile.ZIP_DEFLATED) for dirpath, dirnames, filenames in os.walk(base_dir): for name in filenames: path = os.path.normpath(os.path.join(dirpath, name)) if os.path.isfile(path): zip.write(path, path) if logger is not None: logger.info("adding '%s'", path) zip.close() return zip_filename _ARCHIVE_FORMATS = { 'gztar': (_make_tarball, [('compress', 'gzip')], "gzip'ed tar-file"), 'bztar': (_make_tarball, [('compress', 'bzip2')], "bzip2'ed tar-file"), 'tar': (_make_tarball, [('compress', None)], "uncompressed tar file"), 'zip': (_make_zipfile, [], "ZIP file"), } if _BZ2_SUPPORTED: _ARCHIVE_FORMATS['bztar'] = (_make_tarball, [('compress', 'bzip2')], "bzip2'ed tar-file")

pipenv/patched/notpip/_vendor/distlib/_backport/shutil.py

pipenv

Python

c69d55f7c82d5ae2cce542bcfb98d043ca4836a0

shutil.py

_make_zipfile

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

Vendor in pip 22.1.2

def test_get_instance_view_filters_out_name_with_filter_backend(self): instance_view = InstanceView.as_view(filter_backends=(ExclusiveFilterBackend,)) request = factory.get('/1') response = instance_view(request, pk=1).render() assert response.status_code == status.HTTP_404_NOT_FOUND assert response.data == { 'detail': ErrorDetail( string='No BasicModel matches the given query.', code='not_found' ) }

tests/test_generics.py

django-rest-framework

Python

56946fac8f29aa44ce84391f138d63c4c8a2a285

test_generics.py

test_get_instance_view_filters_out_name_with_filter_backend

https://github.com/encode/django-rest-framework.git

Preserve exception messages for wrapped Django exceptions (#8051) * Preserve messages for wrapped Django exceptions * Fix the test * Update test_generics.py * Update test_generics.py Co-authored-by: Tom Christie <[email protected]>

def onCopiedDLL(self, dll_filename): # Virtual method, pylint: disable=no-self-use,unused-argument return None

nuitka/plugins/PluginBase.py

Nuitka

Python

87c7dd5551f276dc0b68168d952c55aa3e4d07f8

PluginBase.py

onCopiedDLL

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

Plugins: Add support for modifying DLLs after standalone copy

def set_video_backend(backend): global _video_backend if backend not in ["pyav", "video_reader", "cuda"]: raise ValueError("Invalid video backend '%s'. Options are 'pyav', 'video_reader' and 'cuda'" % backend) if backend == "video_reader" and not io._HAS_VIDEO_OPT: # TODO: better messages message = "video_reader video backend is not available. Please compile torchvision from source and try again" raise RuntimeError(message) elif backend == "cuda" and not _HAS_GPU_VIDEO_DECODER: # TODO: better messages message = "cuda video backend is not available." raise RuntimeError(message) else: _video_backend = backend

torchvision/__init__.py

vision

Python

2e833520618dc460cbeb693e29e40b65a02ccafb

__init__.py

set_video_backend

https://github.com/pytorch/vision.git

Pyav backend for VideoReader API (#6598) * Test: add backend parameter * VideoReader object now works on backend * Frame reading now passes * Keyframe seek now passes * Pyav backend now supports metadata * changes in test to reflect GPU decoder change * Linter? * Test GPU output * Addressing Joao's comments * lint * lint * Revert "Test GPU output" This reverts commit f62e955d7dc81bcb23b40d58ea75413b9b62e76d. * lint? * lint * lint * Address issues in build? * hopefully doc fix * Arrgh * arrgh * fix typos * fix input options * remove read from memory option in pyav * skip read from mem test for gpu and pyab be * fix test * remove unused import * Hack to get reading from memory work with pyav * patch audio test Co-authored-by: Bruno Korbar <[email protected]> Co-authored-by: Joao Gomes <[email protected]>

def step(self, action, sumo_handler): logger.debug("Agent %s: action %d", self.agent_id, action) # Subscriptions EXAMPLE: # {"agent_0": {64: 14.603468282230542, 104: None}, # "agent_1": {64: 12.922797055918513, # 104: ("veh.19", 27.239870121802596)}} logger.debug( "Subscriptions: %s", pformat(sumo_handler.veh_subscriptions[self.agent_id]) ) previous_speed = sumo_handler.veh_subscriptions[self.agent_id][tc.VAR_SPEED] new_speed = previous_speed + self.action_to_meaning[action] logger.debug("Before %.2f", previous_speed) sumo_handler.traci_handler.vehicle.setSpeed(self.agent_id, new_speed) logger.debug("After %.2f", new_speed) return

rllib/examples/simulators/sumo/marlenvironment.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

marlenvironment.py

step

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

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

def test_kbinsdiscrtizer_get_feature_names_out(encode, expected_names): X = [[-2, 1, -4], [-1, 2, -3], [0, 3, -2], [1, 4, -1]] kbd = KBinsDiscretizer(n_bins=4, encode=encode).fit(X) Xt = kbd.transform(X) input_features = [f"feat{i}" for i in range(3)] output_names = kbd.get_feature_names_out(input_features) assert Xt.shape[1] == output_names.shape[0] assert_array_equal(output_names, expected_names)

sklearn/preprocessing/tests/test_discretization.py

scikit-learn

Python

36c6c74e5fd9033e9b89a1348de2466e7ac48a8c

test_discretization.py

test_kbinsdiscrtizer_get_feature_names_out

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

FIX Fixes KBinsDiscretizer for encode=ordinal (#22735) Co-authored-by: Guillaume Lemaitre <[email protected]>

def _has_arrow_table(self): if not isinstance(self._op, FrameNode): return False return all(p.arrow_table is not None for p in self._partitions.flatten())

modin/experimental/core/execution/native/implementations/hdk_on_native/dataframe/dataframe.py

modin

Python

027f92a7655ae5b473839b7956ff52bf7879f3cc

dataframe.py

_has_arrow_table

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

FIX-#4022: Fixed empty data frame with index (#4910) Signed-off-by: Andrey Pavlenko <[email protected]>

def get_experiment_checkpoint_dir(cls, run_obj, local_dir=None, name=None): assert run_obj local_dir = _get_local_dir_with_expand_user(local_dir) run_identifier = cls.get_trainable_name(run_obj) combined_name = name or run_identifier dir_name = _get_dir_name(run_obj, name, combined_name) return os.path.join(local_dir, dir_name)

python/ray/tune/experiment.py

ray

Python

814b49356c1e773f2ec8d7c643acef48b6db08cf

experiment.py

get_experiment_checkpoint_dir

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

[tuner] Tuner impl. (#22848)

def dag_id(self) -> str: if self.dag: return self.dag.dag_id return "_in_memory_dag_"

airflow/models/taskmixin.py

airflow

Python

34154803ac73d62d3e969e480405df3073032622

taskmixin.py

dag_id

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

Show tasks in grid view based on topological sort. (#22741) This takes the existing topological sort that existed on a DAG and moves it down to TaskGroup. In order to do this (and not have duplicated sort) the existing sort on DAG is re-implemented on top of the new method. This also surfaced a tiny bug in deserialize_task_group where the SerializedTaskGroup did not have `dag` set -- it didn't cause any problems until now but was needed to call `upstream_list` on a SerializedTaskGroup object.

def _check_pkg(target): log.debug(f"_check_pkg target '{target}'") ret = {} cmd = ["/usr/bin/lslpp", "-Lc", target] lines = __salt__["cmd.run_all"](cmd, python_shell=False).splitlines() name = "" version_num = "" rpmpkg = False for line in lines: if line.startswith("#"): continue comps = line.split(":") if len(comps) < 7: raise CommandExecutionError( "Error occurred finding fileset/package", info={"errors": comps[1].strip()}, ) # handle first matching line if "R" in comps[6]: name = comps[0] rpmpkg = True else: name = comps[1] # use fileset rather than rpm package version_num = comps[2] break log.debug( f"_check_pkg returning name '{name}', version number '{version_num}', rpmpkg '{rpmpkg}'" ) return name, version_num, rpmpkg

salt/modules/aixpkg.py

salt

Python

b2f8271fed3f05160431c55ad7c4e8f3e3e95c3e

aixpkg.py

_check_pkg

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

Complete intial tests for AIX yum and dnf support

def polyfit(x, y, deg, rcond=None, full=False, w=None): return pu._fit(polyvander, x, y, deg, rcond, full, w)

numpy/polynomial/polynomial.py

numpy

Python

4f479744bb9f5150d1406fdb0203c5d8714e7283

polynomial.py

polyfit

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

DOC: Replace the mathematical notation N(...) with text. The meaning of the second argument in the mathematical notation N(mu, b) for the normal distribution is not consistent. In some references it is the variance while in others it is the standard deviation. Let's avoid the ambiguity by not using the notation. Fixes #21296

def get_metrics(self, font, font_class, sym, fontsize, dpi): r info = self._get_info(font, font_class, sym, fontsize, dpi) return info.metrics

lib/matplotlib/_mathtext.py

matplotlib

Python

85f30cbd485eddc93e3c9ff115ac21c0886909d5

_mathtext.py

get_metrics

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

Remove *math* parameter of various mathtext internal APIs. The *math* parameter is passed through many layers of the call stack but is ultimately only used for a single purpose: deciding whether to replace the ASCII hyphen by a (longer) unicode minus. Instead of doing that, just do the substitution at the parsing stage. In particular, this fixes problematic unicode minus support with the "cm" fontset. This patch also reverts a significant part of 52003e4, as LogFormatters no longer need to pass unicode minuses in mathtext -- everything gets converted by mathtext. Likewise, this change also invalidates the test_log_scales baseline image (old, buggy wrt. unicode minus); replace it by a test that the drawn ticks are as expected (which was the intent in 90c1aa3).

def to_objectchange(self, action): from extras.models import ObjectChange objectchange = ObjectChange( changed_object=self, object_repr=str(self)[:200], action=action ) if hasattr(self, '_prechange_snapshot'): objectchange.prechange_data = self._prechange_snapshot if action in (ObjectChangeActionChoices.ACTION_CREATE, ObjectChangeActionChoices.ACTION_UPDATE): objectchange.postchange_data = serialize_object(self) return objectchange

netbox/netbox/models/features.py

netbox

Python

b67859832afa52742defa0a5bd60f9be1ddbe8e4

features.py

to_objectchange

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

Refactor to_objectchange()

def custom_lemmas(self, tab_file, lang): lg = lang.split("_")[0] if len(lg) != 3: raise ValueError("lang should be a (3 character) ISO 639-3 code") self._lang_data[lang] = [ defaultdict(list), defaultdict(list), defaultdict(list), defaultdict(list), ] for line in tab_file.readlines(): if isinstance(line, bytes): # Support byte-stream files (e.g. as returned by Python 2's # open() function) as well as text-stream ones line = line.decode("utf-8") if not line.startswith("#"): triple = line.strip().split("\t") if len(triple) < 3: continue offset_pos, label = triple[:2] val = triple[-1] if self.map30: if offset_pos in self.map30: # Map offset_pos to current Wordnet version: offset_pos = self.map30[offset_pos] else: # Some OMW offsets were never in Wordnet: if ( offset_pos not in self.nomap and offset_pos.replace("a", "s") not in self.nomap ): warnings.warn( f"{lang}: invalid offset {offset_pos} in '{line}'" ) continue elif offset_pos[-1] == "a": wnss = self.of2ss(offset_pos) if wnss and wnss.pos() == "s": # Wordnet pos is "s" # Label OMW adjective satellites back to their Wordnet pos ("s") offset_pos = self.ss2of(wnss) pair = label.split(":") attr = pair[-1] if len(pair) == 1 or pair[0] == lg: if attr == "lemma": val = val.strip().replace(" ", "_") self._lang_data[lang][1][val.lower()].append(offset_pos) if attr in self.lg_attrs: self._lang_data[lang][self.lg_attrs.index(attr)][ offset_pos ].append(val)

nltk/corpus/reader/wordnet.py

nltk

Python

3ca43e26efd7d5aa37b3cd79446258d8bfa79561

wordnet.py

custom_lemmas

https://github.com/nltk/nltk.git

Fix wordnet's all_synsets() function (#3078) * Fix all_synsets() function * Add simple regression tests for #3077 * Add suggestions by @tomaarsen Co-authored-by: Tom Aarsen <[email protected]>

def connect(self, **kwargs) -> Dict[str, int]: raise NotImplementedError()

mindsdb/integrations/libs/base_handler.py

mindsdb

Python

c40c732253043ea111fbf197248a1bff4b7a524e

base_handler.py

connect

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

handlers

def get_function_for_token(frame, token, previous_frame=None): frame_function_name = frame.get("function") token_function_name = token.function_name # Try to use the function name we got from sourcemap-cache, filtering useless names. if token_function_name not in USELESS_FN_NAMES: return token_function_name # If not found, ask the callsite (previous token) for function name if possible. if previous_frame is not None: # `preprocess_frame` is supposed to make sure that `data` is present, # but better safe than sorry. last_token = (previous_frame.get("data") or {}).get("token") if last_token: return last_token.name # If there was no minified name at all, return even useless, filtered one from the original token. if not frame_function_name: return token_function_name # Otherwise fallback to the old, minified name. return frame_function_name

src/sentry/lang/javascript/processor.py

sentry

Python

a00ada51c238564b48412cd59f261b84492b96a5

processor.py

get_function_for_token

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

ref(processor): Try to fallback to previous frames token function name (#40602) This change applies the same heuristic that we previously used in the original `JavaScriptStacktraceProcessor`. The rest is described in `get_function_for_token` function comment.

def _expand_to_beam_size(self, x): r check_type(x, 'x', (Variable), 'BeamSearchDecoder._expand_to_beam_size') x = nn.unsqueeze(x, [1]) expand_times = [1] * len(x.shape) expand_times[1] = self.beam_size x = paddle.tile(x, expand_times) return x

modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/beam.py

PaddleHub

Python

ffcde21305c61d950a9f93e57e6180c9a9665b87

beam.py

_expand_to_beam_size

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

add disco_diffusion_ernievil_base

def get_object_id(cls, **data): object_id, ext_ref = data.get("id"), data.get("external_reference") validate_one_of_args_is_in_mutation( CoreErrorCode, "id", object_id, "external_reference", ext_ref ) if ext_ref and not object_id: object_id = ext_ref_to_global_id_or_error(cls._meta.model, ext_ref) return object_id

saleor/graphql/core/mutations.py

saleor

Python

db7e91a3e124b0df2c08d373a541d9a225ebcb05

mutations.py

get_object_id

https://github.com/saleor/saleor.git

Allow external references to be used instead of Saleor-assigned IDs (#11410) * Add external_reference to Product model; handle product query, update and delete by external_reference; cover changes with tests Handle ProductVariant Handle Order Handle Attribute Handle Warehouse query only Refactor resolvers Handle Account Code rafctor, fix tests Allow updating external_reference field; rename ext_ref in resolvers; * update changelog * Add tests to check externalReference uniqueness

def test_mod_gen_f77(capfd, hello_world_f90, monkeypatch): MNAME = "hi" foutl = get_io_paths(hello_world_f90, mname=MNAME) ipath = foutl.f90inp monkeypatch.setattr(sys, "argv", f'f2py {ipath} -m {MNAME}'.split()) with util.switchdir(ipath.parent): f2pycli() # Always generate C module assert Path.exists(foutl.cmodf) # File contains a function, check for F77 wrappers assert Path.exists(foutl.wrap77)

numpy/f2py/tests/test_f2py2e.py

numpy

Python

729ad4f92420231e2a7009b3223c6c7620b8b808

test_f2py2e.py

test_mod_gen_f77

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

TST: Initialize f2py2e tests of the F2PY CLI (#20668) Increases F2PY coverage by around 15 percent. For the CLI itself it covers the major features (around 70 percent), with the exception of mostly numpy.distutils stuff. More importantly, sets the groundwork for #20056, in that passing the same testsuite should indicate feature parity.

def average(inputs, **kwargs): return Average(**kwargs)(inputs)

keras/layers/merging/average.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

average.py

average

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def get_data(filters): conditions = get_conditions(filters) data = frappe.db.sql( % conditions, as_dict=1, ) unit = { "Bag": "BAGS", "Bottle": "BOTTLES", "Kg": "KILOGRAMS", "Liter": "LITERS", "Meter": "METERS", "Nos": "NUMBERS", "PKT": "PACKS", "Roll": "ROLLS", "Set": "SETS", } # Regular expression set to remove all the special characters special_characters = r"[$%^*()+\\[\]{};':\"\\|<>.?]" for row in data: set_defaults(row) set_taxes(row, filters) set_address_details(row, special_characters) # Eway Bill accepts date as dd/mm/yyyy and not dd-mm-yyyy row.posting_date = "/".join(str(row.posting_date).replace("-", "/").split("/")[::-1]) row.lr_date = "/".join(str(row.lr_date).replace("-", "/").split("/")[::-1]) if row.gst_vehicle_type == "Over Dimensional Cargo (ODC)": row.gst_vehicle_type = "ODC" row.item_name = re.sub(special_characters, " ", row.item_name) row.description = row.item_name row.uom = unit.get(row.uom, row.uom) # For removing special charactes and numbers from customer. row.customer = re.sub(special_characters[:-1] + "&0-9" + "]", "", row.customer) return data

erpnext/regional/report/eway_bill/eway_bill.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

eway_bill.py

get_data

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

style: format code with black

def _get_credentials_and_project_id(self) -> Tuple[google.auth.credentials.Credentials, Optional[str]]: if self._cached_credentials is not None: return self._cached_credentials, self._cached_project_id key_path: Optional[str] = self._get_field('key_path', None) try: keyfile_dict: Optional[str] = self._get_field('keyfile_dict', None) keyfile_dict_json: Optional[Dict[str, str]] = None if keyfile_dict: keyfile_dict_json = json.loads(keyfile_dict) except json.decoder.JSONDecodeError: raise AirflowException('Invalid key JSON.') key_secret_name: Optional[str] = self._get_field('key_secret_name', None) key_secret_project_id: Optional[str] = self._get_field('key_secret_project_id', None) target_principal, delegates = _get_target_principal_and_delegates(self.impersonation_chain) credentials, project_id = get_credentials_and_project_id( key_path=key_path, keyfile_dict=keyfile_dict_json, key_secret_name=key_secret_name, key_secret_project_id=key_secret_project_id, scopes=self.scopes, delegate_to=self.delegate_to, target_principal=target_principal, delegates=delegates, ) overridden_project_id = self._get_field('project') if overridden_project_id: project_id = overridden_project_id self._cached_credentials = credentials self._cached_project_id = project_id return credentials, project_id

airflow/providers/google/common/hooks/base_google.py

airflow

Python

55fd02a38919526776cfe69d715873da75d6f26f

base_google.py

_get_credentials_and_project_id

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

Add key_secret_project_id parameter which specifies a project with KeyFile (#23930)

def connect(self): if hasattr(self, "_connecting_future") and not self._connecting_future.done(): future = self._connecting_future else: future = salt.ext.tornado.concurrent.Future() self._connecting_future = future self.io_loop.add_callback(self._connect) # Add the callback only when a new future is created if self.connect_callback is not None:

salt/transport/tcp.py

salt

Python

43277294a3454e5dcd9079e005f747bf880801f6

tcp.py

connect

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

Test fix

def test_state_changes_on_tab_change(backforward_widget, tabs, fake_web_tab): tab_with_history = fake_web_tab(can_go_back=True, can_go_forward=True) tab_without_history = fake_web_tab(can_go_back=False, can_go_forward=False) tabs.widget.tabs = [tab_with_history] backforward_widget.enabled = True backforward_widget.on_tab_cur_url_changed(tabs) assert backforward_widget.isVisible() tabs.widget.tabs = [tab_without_history] backforward_widget.on_tab_cur_url_changed(tabs) assert backforward_widget.text() == '' assert not backforward_widget.isVisible()

tests/unit/mainwindow/statusbar/test_backforward.py

qutebrowser

Python

79bb6670d8969b850965cd5d895bcd8f09d59311

test_backforward.py

test_state_changes_on_tab_change

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

bar: Test enabled attribute on progress and backforward There is now some code in statusbar relying on the enabled attribute stopping events from being processed (or at least stopping them from showing the widget again). So add tests to make sure that behaviour keeps working. Also split the big test in test_backforward into a couple of smaller ones and pull some common lines out to a (still clunky) fixture.

def execute(): if frappe.db.exists("DocType", "Lost Reason Detail"): frappe.reload_doc("crm", "doctype", "opportunity_lost_reason") frappe.reload_doc("crm", "doctype", "opportunity_lost_reason_detail") frappe.reload_doc("setup", "doctype", "quotation_lost_reason_detail") frappe.db.sql( ) frappe.db.sql( ) frappe.db.sql( ) frappe.delete_doc("DocType", "Lost Reason Detail")

erpnext/patches/v12_0/rename_lost_reason_detail.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

rename_lost_reason_detail.py

execute

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

style: format code with black

async def _async_run_connected_events(self) -> None: await self._async_connect_ble_scanner()

homeassistant/components/shelly/coordinator.py

core

Python

435fc237375b86a5d6d8498ba5216c208b665ecc

coordinator.py

_async_run_connected_events

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

Add shelly ble scanner support (#82007)

def _tf_tensor_numpy_output(self, string): modified_string = self._NUMPY_OUTPUT_RE.sub(r"\1", string) return modified_string, modified_string != string MESSAGE = textwrap.dedent( )

keras/testing_infra/keras_doctest_lib.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras_doctest_lib.py

_tf_tensor_numpy_output

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def cli(): @cli.command()

scripts-dev/release.py

@cli.command()

synapse

Python

12d1f82db213603972d60be3f46f6a36c3c2330f

release.py

cli

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

Generate announcement links in release script (#12242)

def check_for_new_doc_with_same_name_as_deleted_parent(doc): parent_creation_time = frappe.db.get_value(doc["parenttype"], doc["parent"], "creation") child_creation_time = doc["creation"] return getdate(parent_creation_time) > getdate(child_creation_time)

erpnext/patches/v13_0/delete_orphaned_tables.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

delete_orphaned_tables.py

check_for_new_doc_with_same_name_as_deleted_parent

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

style: format code with black

def set_capstyle(self, s): cs = CapStyle(s) self._capstyle = cs self.stale = True

lib/matplotlib/patches.py

matplotlib

Python

b24acb7772e0534f4bcdb0b5b492d9d94954dd91

patches.py

set_capstyle

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

DOC: Document default cap styles - remove '(default)' from cap style demo as this is only true for Line2D and the default rcParameters - document default cap styles for Line2D and Patch in their cap style setters - document default cap style for GraphicsContextBase in the same way as it's already done for joinstyle

def mode(self, axis=0, numeric_only=False, dropna=True): # noqa: PR01, RT01, D200 axis = self._get_axis_number(axis) return self.__constructor__( query_compiler=self._query_compiler.mode( axis=axis, numeric_only=numeric_only, dropna=dropna ) )

modin/pandas/base.py

modin

Python

605efa618e7994681f57b11d04d417f353ef8d50

base.py

mode

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

DOCS-#3099: Fix `BasePandasDataSet` docstrings warnings (#4333) Co-authored-by: Yaroslav Igoshev <[email protected]> Signed-off-by: Alexander Myskov <[email protected]>

def read_text(self, filename):

python3.10.4/Lib/importlib/metadata/__init__.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

__init__.py

read_text

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

add python 3.10.4 for windows

async def test_load_types(hass, create_hdmi_network, create_cec_entity): config = {"platform": "media_player", "types": {"hdmi_cec.hdmi_3": "switch"}} hdmi_network = await create_hdmi_network(config=config) mock_hdmi_device = MockHDMIDevice(logical_address=3) await create_cec_entity(hdmi_network, mock_hdmi_device) mock_hdmi_device.set_update_callback.assert_called_once() state = hass.states.get("media_player.hdmi_3") assert state is None state = hass.states.get("switch.hdmi_3") assert state is not None mock_hdmi_device = MockHDMIDevice(logical_address=4) await create_cec_entity(hdmi_network, mock_hdmi_device) mock_hdmi_device.set_update_callback.assert_called_once() state = hass.states.get("media_player.hdmi_4") assert state is not None state = hass.states.get("switch.hdmi_4") assert state is None

tests/components/hdmi_cec/test_switch.py

core

Python

7cd4be1310b3f76398b4404d3f4ecb26b9533cee

test_switch.py

test_load_types

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

Add tests for the HDMI-CEC integration (#75094) * Add basic tests to the HDMI-CEC component * Add tests for the HDMI-CEC switch component * Add test for watchdog code * Start adding tests for the HDMI-CEC media player platform Also some cleanup and code move. * Add more tests for media_player And cleanup some switch tests. * Improve xfail message for features * Align test pyCEC dependency with main dependency * Make fixtures snake_case * Cleanup call asserts * Cleanup service tests * fix issues with media player tests * Cleanup MockHDMIDevice class * Cleanup watchdog tests * Add myself as code owner for the HDMI-CEC integration * Fix async fire time changed time jump * Fix event api sync context * Delint tests * Parametrize watchdog test Co-authored-by: Martin Hjelmare <[email protected]>

def track_tf1_style_variables(method):

keras/legacy_tf_layers/variable_scope_shim.py

"""Wrapmodulethis decorator to capturestyle weights. Decorating a `tf.keras.Layer`'s or `tf.Module`'s methods withwill cause the layermodule to track weightsviaand by extensioninside the decorated method. In addition to tracking the weights themselves under theif the methodto a `tf.keras.Layer` then any regularization losses specified via`tf.compat.v1.layers` regularizer arguments willtracked by the layer under the standard `layer.losses` property. This tracking enables using large classes ofpropertymodelcode inside of KerasTF2 behaviors enabled. Example of capturingmodeling codea Keras```

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

variable_scope_shim.py

track_tf1_style_variables

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def warning(self, response): return '110 - "Response is Stale"'

.venv/lib/python3.8/site-packages/pip/_vendor/cachecontrol/heuristics.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

heuristics.py

warning

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

upd; format

def debug_launcher(function, args=(), num_processes=2): if is_torch_version("<", "1.5.0"): raise ImportError( "Using `debug_launcher` for distributed training on GPUs require torch >= 1.5.0, got " f"{torch.__version__}." ) from torch.multiprocessing import start_processes with tempfile.NamedTemporaryFile() as tmp_file: # torch.distributed will expect a few environment variable to be here. We set the ones common to each # process here (the other ones will be set be the launcher). with patch_environment( world_size=num_processes, master_addr="127.0.01", master_port="29500", mixed_precision="no", accelerate_debug_rdv_file=tmp_file.name, use_cpu="yes", ): launcher = PrepareForLaunch(function, debug=True) start_processes(launcher, args=args, nprocs=num_processes, start_method="fork")

src/accelerate/launchers.py

accelerate

Python

f6ec2660f01e5bb37399407b3a01b72a43ceb328

launchers.py

debug_launcher

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

Refactor version checking into a utility (#395) Co-authored-by: Sylvain Gugger <[email protected]>

def _autodetect_num_gpus(): result = 0 if importlib.util.find_spec("GPUtil"): gpu_list = GPUtil.getGPUs() result = len(gpu_list) elif sys.platform.startswith("linux"): proc_gpus_path = "/proc/driver/nvidia/gpus" if os.path.isdir(proc_gpus_path): result = len(os.listdir(proc_gpus_path)) elif sys.platform == "win32": props = "AdapterCompatibility" cmdargs = ["WMIC", "PATH", "Win32_VideoController", "GET", props] lines = subprocess.check_output(cmdargs).splitlines()[1:] result = len([x.rstrip() for x in lines if x.startswith(b"NVIDIA")]) return result

python/ray/_private/resource_spec.py

ray

Python

b87731c1b64988cea5ce80a6aec55207ef7efd6f

resource_spec.py

_autodetect_num_gpus

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

Windows gpu detection workaround with GPUtil (#25701) Because [WMIC is now deprecated](https://docs.microsoft.com/en-us/windows/deployment/planning/windows-10-deprecated-features), #9300 may stop working on recent Windows systems. As a workaround this PR extends GPUtil to do GPU detection when installed on Windows systems. Co-authored-by: Matti Picus <[email protected]>

def apply_valid_mask(losses, sw, mask, reduction): if mask is not None: mask = tf.cast(mask, losses.dtype) if reduction in (ReductionV2.AUTO, ReductionV2.SUM_OVER_BATCH_SIZE): # Valid entries have weight `total/valid`, while invalid ones # have 0. When summed over batch, they will be reduced to: # # mean(loss * sample_weight * total / valid) # = sum(loss * sample_weight * total / valid) / total # = sum(loss * sample_weight) / total * total / valid # = sum(loss * sample_weight) / valid total = tf.cast(tf.size(mask), losses.dtype) valid = tf.reduce_sum(mask) mask *= total / valid return apply_mask(losses, sw, mask)

keras/utils/losses_utils.py

keras

Python

4f1308112f4188c4e14fdf3a59af8fe5f30db61f

losses_utils.py

apply_valid_mask

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

Update docs

def modified_vars(self) -> Dict[str, "tk.BooleanVar"]: assert self.command_notebook is not None return self.command_notebook.modified_vars

lib/gui/utils.py

faceswap

Python

dc18c74eea0c7837a820d27628cb12b0824fa30e

utils.py

modified_vars

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

Bugfix: Preview for extract in batch mode

def _is_zero_copy_possible(self) -> bool: if self.__is_zero_copy_possible is None: if self._df._has_arrow_table(): # If PyArrow table is already materialized then we can # retrieve data zero-copy self.__is_zero_copy_possible = True elif not self._df._can_execute_arrow(): # When not able to execute the plan via PyArrow means # that we have to involve OmniSci, so no zero-copy. self.__is_zero_copy_possible = False else: # Check whether the plan for PyArrow can be executed zero-copy self.__is_zero_copy_possible = self._is_zero_copy_arrow_op(self._df._op) return self.__is_zero_copy_possible

modin/experimental/core/execution/native/implementations/omnisci_on_native/exchange/dataframe_protocol/dataframe.py

modin

Python

0c1a2129df64cf45bf1ff49c8ed92c510fdb1c82

dataframe.py

_is_zero_copy_possible

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

FEAT-#4244: Implement dataframe exchange protocol for OmniSci (#4269) Co-authored-by: Yaroslav Igoshev <[email protected]> Co-authored-by: Vasily Litvinov <[email protected]> Signed-off-by: Dmitry Chigarev <[email protected]>

def test_loss_of_perfect_prediction(loss, sample_weight): if not loss.is_multiclass: # Use small values such that exp(value) is not nan. raw_prediction = np.array([-10, -0.1, 0, 0.1, 3, 10]) # If link is identity, we must respect the interval of y_pred: if isinstance(loss.link, IdentityLink): eps = 1e-10 low = loss.interval_y_pred.low if not loss.interval_y_pred.low_inclusive: low = low + eps high = loss.interval_y_pred.high if not loss.interval_y_pred.high_inclusive: high = high - eps raw_prediction = np.clip(raw_prediction, low, high) y_true = loss.link.inverse(raw_prediction) else: # HalfMultinomialLoss y_true = np.arange(loss.n_classes).astype(float) # raw_prediction with entries -exp(10), but +exp(10) on the diagonal # this is close enough to np.inf which would produce nan raw_prediction = np.full( shape=(loss.n_classes, loss.n_classes), fill_value=-np.exp(10), dtype=float, ) raw_prediction.flat[:: loss.n_classes + 1] = np.exp(10) if sample_weight == "range": sample_weight = np.linspace(1, y_true.shape[0], num=y_true.shape[0]) loss_value = loss.loss( y_true=y_true, raw_prediction=raw_prediction, sample_weight=sample_weight, ) constant_term = loss.constant_to_optimal_zero( y_true=y_true, sample_weight=sample_weight ) # Comparing loss_value + constant_term to zero would result in large # round-off errors. assert_allclose(loss_value, -constant_term, atol=1e-14, rtol=1e-15) @pytest.mark.parametrize("loss", LOSS_INSTANCES, ids=loss_instance_name) @pytest.mark.parametrize("sample_weight", [None, "range"])

sklearn/_loss/tests/test_loss.py

@pytest.mark.parametrize("loss", LOSS_INSTANCES, ids=loss_instance_name) @pytest.mark.parametrize("sample_weight", [None, "range"])

scikit-learn

Python

75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc

test_loss.py

test_loss_of_perfect_prediction

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

ENH migrate GLMs / TweedieRegressor to linear loss (#22548) Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]>

def head_bundle_is_empty(self): return self._head_bundle_is_empty

python/ray/air/execution/resources/request.py

ray

Python

edb17fd2069844f12237c85ba6607afae536401d

request.py

head_bundle_is_empty

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

[air/tune] Internal resource management 1 - Ray AIR resource manager implementation (#30777) Prerequisite to #30016 This PR adds a new Ray AIR resource manager to replace the PlacementGroupManager of Ray Tune. Details can be found in #30016. Specifically, this PR - Adds the main resource manager abstractions - Renames (and moves) PlacementGroupFactory to ResourceRequest - Adds implementations and tests for a placement group based manager and a budget based manager Signed-off-by: Kai Fricke <[email protected]> Signed-off-by: Kai Fricke <[email protected]> Co-authored-by: matthewdeng <[email protected]>

def _transform_unaggregated_gradients(self, grads_and_vars): return grads_and_vars

keras/optimizers/optimizer_v2/optimizer_v2.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

optimizer_v2.py

_transform_unaggregated_gradients

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def execute(): frappe.db.sql( )

erpnext/patches/v12_0/set_quotation_status.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

set_quotation_status.py

execute

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

style: format code with black