Datasets:

semeru

/

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

like 0

Follow

Semeru Lab 7

def collect(self): if self.symlink and not self.local: raise CommandError("Can't symlink to a remote destination.") if self.clear: self.clear_dir("") if self.symlink: handler = self.link_file else: handler = self.copy_file found_files = {} for finder in get_finders(): for path, storage in finder.list(self.ignore_patterns): # Prefix the relative path if the source storage contains it if getattr(storage, "prefix", None): prefixed_path = os.path.join(storage.prefix, path) else: prefixed_path = path if prefixed_path not in found_files: found_files[prefixed_path] = (storage, path) handler(path, prefixed_path, storage) else: self.log( "Found another file with the destination path '%s'. It " "will be ignored since only the first encountered file " "is collected. If this is not what you want, make sure " "every static file has a unique path." % prefixed_path, level=1, ) # Storage backends may define a post_process() method. if self.post_process and hasattr(self.storage, "post_process"): processor = self.storage.post_process(found_files, dry_run=self.dry_run) for original_path, processed_path, processed in processor: if isinstance(processed, Exception): self.stderr.write("Post-processing '%s' failed!" % original_path) # Add a blank line before the traceback, otherwise it's # too easy to miss the relevant part of the error message. self.stderr.write() raise processed if processed: self.log( "Post-processed '%s' as '%s'" % (original_path, processed_path), level=2, ) self.post_processed_files.append(original_path) else: self.log("Skipped post-processing '%s'" % original_path) return { "modified": self.copied_files + self.symlinked_files, "unmodified": self.unmodified_files, "post_processed": self.post_processed_files, }

django/contrib/staticfiles/management/commands/collectstatic.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

collectstatic.py

collect

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

Refs #33476 -- Reformatted code with Black.

def test_torch_auto_gpu_to_cpu(ray_start_4_cpus_2_gpus): num_workers = 2 assert os.environ["CUDA_VISIBLE_DEVICES"] == ""

python/ray/train/tests/test_gpu.py

ray

Python

d99eff919bf785f911e4eebc87ddc4960344a139

test_gpu.py

test_torch_auto_gpu_to_cpu

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

[AIR] Hard deprecate old Trainer, old callbacks (#29015) Hard deprecations for ray.train.Trainer, ray.train.callbacks and ray.train.checkpoint.CheckpointStrategy. Restart-on-failure logic from BackendExecutor has also been removed as it is superseded by Tune. Some tests have been refactored to use the new API. Tests that are no longer applicable have been removed. Signed-off-by: Antoni Baum <[email protected]> Signed-off-by: Amog Kamsetty <[email protected]> Co-authored-by: Amog Kamsetty <[email protected]>

def verification_url(self) -> str: return self._device_flow_info.verification_url

homeassistant/components/google/api.py

core

Python

7876ffe9e392b20da16f0d0c44c723f526f807e6

api.py

verification_url

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

Update google calendar integration with a config flow (#68010) * Convert google calendar to config flow and async * Call correct exchange method * Fix async method and reduce unnecessary diffs * Wording improvements * Reduce unnecessary diffs * Run load/update config from executor * Update homeassistant/components/google/calendar.py Co-authored-by: Martin Hjelmare <[email protected]> * Remove unnecessary updating of unexpected multiple config entries. * Remove unnecessary unique_id checks * Improve readability with comments about device code expiration * Update homeassistant/components/google/calendar.py Co-authored-by: Martin Hjelmare <[email protected]> * Update homeassistant/components/google/calendar.py Co-authored-by: Martin Hjelmare <[email protected]> * Update homeassistant/components/google/api.py Co-authored-by: Martin Hjelmare <[email protected]> * Add comment for when code is none on timeout Co-authored-by: Martin Hjelmare <[email protected]>

def step_attempt(self) -> ResultDict:

rllib/agents/trainer.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

trainer.py

step_attempt

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 zauto(self): return self["zauto"]

packages/python/plotly/plotly/graph_objs/_choropleth.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_choropleth.py

zauto

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

switch to black .22

def ravel_multi_index(multi_index, dims, mode='raise', order='C'): assert len(multi_index) == len(dims), f"len(multi_index)={len(multi_index)} != len(dims)={len(dims)}" dims = tuple(core.concrete_or_error(operator.index, d, "in `dims` argument of ravel_multi_index().") for d in dims) _check_arraylike("ravel_multi_index", *multi_index) for index in multi_index: if mode == 'raise': core.concrete_or_error(array, index, "The error occurred because ravel_multi_index was jit-compiled" " with mode='raise'. Use mode='wrap' or mode='clip' instead.") if not issubdtype(_dtype(index), integer): raise TypeError("only int indices permitted") if mode == "raise": if _any(any((i < 0) | (i >= d)) for i, d in zip(multi_index, dims)): raise ValueError("invalid entry in coordinates array") elif mode == "clip": multi_index = [clip(i, 0, d - 1) for i, d in zip(multi_index, dims)] elif mode == "wrap": multi_index = [i % d for i, d in zip(multi_index, dims)] else: raise ValueError(f"invalid mode={mode!r}. Expected 'raise', 'wrap', or 'clip'") if order == "F": strides = np.cumprod((1,) + dims[:-1]) elif order == "C": strides = np.cumprod((1,) + dims[1:][::-1])[::-1] else: raise ValueError(f"invalid order={order!r}. Expected 'C' or 'F'") result = array(0, dtype=dtypes.canonicalize_dtype(int_)) for i, s in zip(multi_index, strides): result = result + i * s return result _UNRAVEL_INDEX_DOC = @_wraps(np.unravel_index, lax_description=_UNRAVEL_INDEX_DOC)

jax/_src/numpy/lax_numpy.py

@_wraps(np.unravel_index, lax_description=_UNRAVEL_INDEX_DOC)

jax

Python

667d63aa2d4fbf7c9da73aab0e24c5c4c33cb5ba

lax_numpy.py

ravel_multi_index

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

replace int with operator.index part2 This change align the behavior of `ravel_multi_index`, `split` and `indices` to their `numpy` counterparts. Also ensure size argument of `nonzero` should be integer. The changes with `*space` are only simplification

def ismethod(object): return isinstance(object, types.MethodType)

python3.10.4/Lib/inspect.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

inspect.py

ismethod

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

add python 3.10.4 for windows

async def test_logbook_invalid_entity(recorder_mock, hass, hass_client): await async_setup_component(hass, "logbook", {}) await hass.async_block_till_done() client = await hass_client() # Today time 00:00:00 start = dt_util.utcnow().date() start_date = datetime(start.year, start.month, start.day) # Test today entries with filter by end_time end_time = start + timedelta(hours=24) response = await client.get( f"/api/logbook/{start_date.isoformat()}?end_time={end_time}&entity=invalid" ) assert response.status == HTTPStatus.INTERNAL_SERVER_ERROR

tests/components/logbook/test_init.py

core

Python

31a787558fd312331b55e5c2c4b33341fc3601fc

test_init.py

test_logbook_invalid_entity

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

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

def recorder_or_dbworker(self) -> bool: thread_name = threading.current_thread().name return bool( thread_name == "Recorder" or thread_name.startswith(DB_WORKER_PREFIX) )

homeassistant/components/recorder/pool.py

core

Python

bc862e97ed68cce8c437327651f85892787e755e

pool.py

recorder_or_dbworker

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

Use a dedicated executor pool for database operations (#68105) Co-authored-by: Erik Montnemery <[email protected]> Co-authored-by: Franck Nijhof <[email protected]>

def get_network_names(self) -> t.Optional[t.List[str]]: if self.networks is None: return None return sorted(self.networks)

test/lib/ansible_test/_internal/docker_util.py

ansible

Python

3eb0485dd92c88cc92152d3656d94492db44b183

docker_util.py

get_network_names

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

ansible-test - Use more native type hints. (#78435) * ansible-test - Use more native type hints. Simple search and replace to switch from comments to native type hints for return types of functions with no arguments. * ansible-test - Use more native type hints. Conversion of simple single-line function annotation type comments to native type hints. * ansible-test - Use more native type hints. Conversion of single-line function annotation type comments with default values to native type hints. * ansible-test - Use more native type hints. Manual conversion of type annotation comments for functions which have pylint directives.

def test_page_number_extraction_on_empty_pages(): preprocessor = PreProcessor(add_page_number=True, split_by="word", split_length=7, split_overlap=0) text_page_one = "This is a text on page one." text_page_three = "This is a text on page three." # this is what we get from PDFToTextConverter in case of an "empty" page document_with_empty_pages = f"{text_page_one}\f\f{text_page_three}" document = Document(content=document_with_empty_pages) documents = preprocessor.process(document) assert documents[0].meta["page"] == 1 assert documents[1].meta["page"] == 3 # verify the placeholder for the empty page has been removed assert documents[0].content.strip() == text_page_one assert documents[1].content.strip() == text_page_three

test/nodes/test_preprocessor.py

haystack

Python

5fedfb03b03496d7ca25f55788e1fa576ff1b2a4

test_preprocessor.py

test_page_number_extraction_on_empty_pages

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

fix: Fix the error of wrong page numbers when documents contain empty pages. (#3330) * Fix the error of wrong page numbers when documents contain empty pages. * Reformat using git hooks. * Use a more descriptive placeholder

def forward(self, pixel_values, output_attentions=None, output_hidden_states=None, return_dict=None): r output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions output_hidden_states = ( output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states ) return_dict = return_dict if return_dict is not None else self.config.use_return_dict encoder_outputs = self.encoder( pixel_values, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, ) sequence_output = encoder_outputs[0] if not return_dict: return (sequence_output,) + encoder_outputs[1:] return BaseModelOutput( last_hidden_state=sequence_output, hidden_states=encoder_outputs.hidden_states, attentions=encoder_outputs.attentions, ) @add_start_docstrings( , SEGFORMER_START_DOCSTRING, )

src/transformers/models/segformer/modeling_segformer.py

@add_start_docstrings( """ SegFormer Model transformer with an image classification head on top (a linear layer on top of the final hidden states) e.g. for ImageNet. """, SEGFORMER_START_DOCSTRING, )

transformers

Python

ac224bb0797c1ee6522d814139f3eb0a8947267b

modeling_segformer.py

forward

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

[Fix doc examples] Add missing from_pretrained (#15044) * fix doc example - ValueError: Parameter config should be an instance of class `PretrainedConfig` * Update src/transformers/models/segformer/modeling_segformer.py Co-authored-by: NielsRogge <[email protected]> * update Co-authored-by: ydshieh <[email protected]> Co-authored-by: NielsRogge <[email protected]>

def logout(self): from django.contrib.auth import get_user, logout request = HttpRequest() if self.session: request.session = self.session request.user = get_user(request) else: engine = import_module(settings.SESSION_ENGINE) request.session = engine.SessionStore() logout(request) self.cookies = SimpleCookie()

django/test/client.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

client.py

logout

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

Refs #33476 -- Reformatted code with Black.

def test_add_prefix_outputs(self) -> None: self._test_add_prefix(rename_outputs=True)

onnx/test/compose_test.py

onnx

Python

83fa57c74edfd13ddac9548b8a12f9e3e2ed05bd

compose_test.py

test_add_prefix_outputs

https://github.com/onnx/onnx.git

Use Python type annotations rather than comments (#3962) * These have been supported since Python 3.5. ONNX doesn't support Python < 3.6, so we can use the annotations. Diffs generated by https://pypi.org/project/com2ann/. Signed-off-by: Gary Miguel <[email protected]> * Remove MYPY conditional logic in gen_proto.py It breaks the type annotations and shouldn't be needed. Signed-off-by: Gary Miguel <[email protected]> * Get rid of MYPY bool from more scripts Signed-off-by: Gary Miguel <[email protected]> * move Descriptors class above where its referenced in type annotation Signed-off-by: Gary Miguel <[email protected]> * fixes Signed-off-by: Gary Miguel <[email protected]> * remove extra blank line Signed-off-by: Gary Miguel <[email protected]> * fix type annotations Signed-off-by: Gary Miguel <[email protected]> * fix type annotation in gen_docs Signed-off-by: Gary Miguel <[email protected]> * fix Operators.md Signed-off-by: Gary Miguel <[email protected]> * fix TestCoverage.md Signed-off-by: Gary Miguel <[email protected]> * fix protoc-gen-mypy.py Signed-off-by: Gary Miguel <[email protected]>

def coroutine(func): warnings.warn('"@coroutine" decorator is deprecated since Python 3.8, use "async def" instead', DeprecationWarning, stacklevel=2) if inspect.iscoroutinefunction(func): # In Python 3.5 that's all we need to do for coroutines # defined with "async def". return func if inspect.isgeneratorfunction(func): coro = func else:

python3.10.4/Lib/asyncio/coroutines.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

coroutines.py

coroutine

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

add python 3.10.4 for windows

def update_styles(self) -> None: self.post_message_no_wait(messages.RefreshStyles(self))

src/textual/app.py

textual

Python

c611fd84ff3a4f67a1f2a5a38d42fad37215cb9a

app.py

update_styles

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

docstrings

def pinv(a, rcond=1e-15, hermitian=False): a, wrap = _makearray(a) rcond = asarray(rcond) if _is_empty_2d(a): m, n = a.shape[-2:] res = empty(a.shape[:-2] + (n, m), dtype=a.dtype) return wrap(res) a = a.conjugate() u, s, vt = svd(a, full_matrices=False, hermitian=hermitian) # discard small singular values cutoff = rcond[..., newaxis] * amax(s, axis=-1, keepdims=True) large = s > cutoff s = divide(1, s, where=large, out=s) s[~large] = 0 res = matmul(transpose(vt), multiply(s[..., newaxis], transpose(u))) return wrap(res) # Determinant @array_function_dispatch(_unary_dispatcher)

numpy/linalg/linalg.py

@array_function_dispatch(_unary_dispatcher)

numpy

Python

3ba8be6f748edc3afedc49a320423093acfb43d4

linalg.py

pinv

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

DOC:linalg: Remove ref to scipy.linalg.pinv2

def test_save_as_continue_false(self): post_data = {"_saveasnew": "", "name": "John M", "gender": 1, "age": 42} url = reverse( "admin:admin_views_person_change", args=(self.per1.pk,), current_app=site2.name, ) response = self.client.post(url, post_data) self.assertEqual(len(Person.objects.filter(name="John M")), 1) self.assertEqual(len(Person.objects.filter(id=self.per1.pk)), 1) self.assertRedirects( response, reverse("admin:admin_views_person_changelist", current_app=site2.name), )

tests/admin_views/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_save_as_continue_false

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

Refs #33476 -- Reformatted code with Black.

def get_forward_related_filter(self, obj): return { "%s__%s" % (self.name, rh_field.name): getattr(obj, rh_field.attname) for _, rh_field in self.related_fields }

django/db/models/fields/related.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

related.py

get_forward_related_filter

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

Refs #33476 -- Reformatted code with Black.

def test_operator_extra_link_override_plugin(dag_run, task_2, viewer_client): response = viewer_client.get( f"{ENDPOINT}?dag_id={task_2.dag_id}&task_id={task_2.task_id}" f"&execution_date={DEFAULT_DATE}&link_name=airflow", follow_redirects=True, ) assert response.status_code == 200 response_str = response.data if isinstance(response.data, bytes): response_str = response_str.decode() assert json.loads(response_str) == {'url': 'https://airflow.apache.org/1.10.5/', 'error': None}

tests/www/views/test_views_extra_links.py

airflow

Python

08575ddd8a72f96a3439f73e973ee9958188eb83

test_views_extra_links.py

test_operator_extra_link_override_plugin

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

Change BaseOperatorLink interface to take a ti_key, not a datetime (#21798)

def histogram(self, mask=None, extrema=None): self.load() if mask: mask.load() return self.im.histogram((0, 0), mask.im) if self.mode in ("I", "F"): if extrema is None: extrema = self.getextrema() return self.im.histogram(extrema) return self.im.histogram()

src/PIL/Image.py

Pillow

Python

de968dd920eaa3d1a27877059c6bbb9043a9d26b

Image.py

histogram

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

Document that histogram() uses 256 bins per channel

def _error_page_workaround(self, js_enabled, html): match = re.search(r'"errorCode":"([^"]*)"', html) if match is None: return error = match.group(1) log.webview.error("Load error: {}".format(error)) if js_enabled: return self._show_error_page(self.url(), error=error)

qutebrowser/browser/webengine/webenginetab.py

qutebrowser

Python

86b5bed388544d2d445a3dba151e3c3a4c8814b7

webenginetab.py

_error_page_workaround

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

Partially re-revert _error_page_workaround changes The logging part removed in 438b8b46094890a28db6bac07ff1ae67bbc5ee78 is still needed for some tests, and debugging too.

def _get_validity_buffer(self) -> Tuple[PandasBuffer, Any]: null, invalid = self.describe_null if self.dtype[0] == DtypeKind.STRING: # For now, use byte array as the mask. # TODO: maybe store as bit array to save space?.. buf = self._col.to_numpy() # Determine the encoding for valid values valid = invalid == 0 invalid = not valid mask = np.zeros(shape=(len(buf),), dtype=np.bool8) for i, obj in enumerate(buf): mask[i] = valid if isinstance(obj, str) else invalid # Convert the mask array to a Pandas "buffer" using # a NumPy array as the backing store buffer = PandasBuffer(mask) # Define the dtype of the returned buffer dtype = (DtypeKind.BOOL, 8, ArrowCTypes.BOOL, Endianness.NATIVE) return buffer, dtype try: msg = _NO_VALIDITY_BUFFER[null] + " so does not have a separate mask" except KeyError: # TODO: implement for other bit/byte masks? raise NotImplementedError("See self.describe_null") raise NoBufferPresent(msg)

pandas/core/exchange/column.py

pandas

Python

90140f055892a46f473bd26affab88a7f171e394

column.py

_get_validity_buffer

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

ENH: Implement DataFrame interchange protocol (#46141)

def is_installable_dir(path): # type: (str) -> bool if not os.path.isdir(path): return False setup_py = os.path.join(path, "setup.py") if os.path.isfile(setup_py): return True pyproject_toml = os.path.join(path, "pyproject.toml") if os.path.isfile(pyproject_toml): return True return False

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

misc.py

is_installable_dir

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

upd; format

def put_cluster_metadata(gcs_client, num_retries) -> None: metadata = _generate_cluster_metadata() ray._private.utils.internal_kv_put_with_retry( gcs_client, usage_constant.CLUSTER_METADATA_KEY, json.dumps(metadata).encode(), namespace=ray_constants.KV_NAMESPACE_CLUSTER, num_retries=num_retries, ) return metadata

python/ray/_private/usage/usage_lib.py

ray

Python

20ab9188c61d91ef0c79cc5d527f17db7c43b604

usage_lib.py

put_cluster_metadata

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

[Ray Usage Stats] Record cluster metadata + Refactoring. (#22170) This is the first PR to implement usage stats on Ray. Please refer to the file `usage_lib.py` for more details. The full specification is here https://docs.google.com/document/d/1ZT-l9YbGHh-iWRUC91jS-ssQ5Qe2UQ43Lsoc1edCalc/edit#heading=h.17dss3b9evbj. You can see the full PR for phase 1 from here; https://github.com/rkooo567/ray/pull/108/files. The PR is doing some basic refactoring + adding cluster metadata to GCS instead of the version numbers. After this PR, we will add code to enable usage report "off by default".

def extra_action_out(self, input_dict, state_batches, model, action_dist): # Return value function outputs. VF estimates will hence be added to # the SampleBatches produced by the sampler(s) to generate the train # batches going into the loss function. return { SampleBatch.VF_PREDS: model.value_function(), }

rllib/policy/torch_mixins.py

ray

Python

dea134a4726c46d57567e724bcc7a2de43f5200e

torch_mixins.py

extra_action_out

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

[RLlib] Clean up Policy mixins. (#24746)

async def test_kill_job_actor_in_before_driver_finish(self, job_manager): with tempfile.TemporaryDirectory() as tmp_dir: pid_file, _, job_id = await _run_hanging_command(job_manager, tmp_dir) with open(pid_file, "r") as file: pid = int(file.read()) assert psutil.pid_exists(pid), "driver subprocess should be running" actor = job_manager._get_actor_for_job(job_id) ray.kill(actor, no_restart=True) await async_wait_for_condition_async_predicate( check_job_failed, job_manager=job_manager, job_id=job_id ) # Ensure driver subprocess gets cleaned up after job reached # termination state await async_wait_for_condition(check_subprocess_cleaned, pid=pid)

dashboard/modules/job/tests/test_job_manager.py

ray

Python

326b5bd1acc6d3d00ab0546e4ae45da6bed501f7

test_job_manager.py

test_kill_job_actor_in_before_driver_finish

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

Convert job_manager to be async (#27123) Updates jobs api Updates snapshot api Updates state api Increases jobs api version to 2 Signed-off-by: Alan Guo [email protected] Why are these changes needed? follow-up for #25902 (comment)

def mint_data_fixture(): return json.loads(load_fixture("awair/mint.json")) @pytest.fixture(name="no_devices", scope="session")

tests/components/awair/conftest.py

@pytest.fixture(name="no_devices", scope="session")

core

Python

ebbff7b60e43f17d65ead811d314602b9daddfc4

conftest.py

mint_data_fixture

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

Add Awair Local API support (#75535)

async def _async_wait_for_pairing_mode(self) -> None: assert self._discovery device = self._discovery.device

homeassistant/components/snooz/config_flow.py

core

Python

7d097d18b0c6041475080b3c400e37b25185faba

config_flow.py

_async_wait_for_pairing_mode

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

Add support for Snooz BLE devices (#78790) Co-authored-by: J. Nick Koston <[email protected]>

def on_chord_header_end(self, chord, **header) -> None: self.on_group_end(chord.tasks, **header)

celery/canvas.py

celery

Python

1c4ff33bd22cf94e297bd6449a06b5a30c2c1fbc

canvas.py

on_chord_header_end

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

Canvas Header Stamping (#7384) * Strip down the header-stamping PR to the basics. * Serialize groups. * Add groups to result backend meta data. * Fix spelling mistake. * Revert changes to canvas.py * Revert changes to app/base.py * Add stamping implementation to canvas.py * Send task to AMQP with groups. * Successfully pass single group to result. * _freeze_gid dict merge fixed * First draft of the visitor API. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * OptionsVisitor created * Fixed canvas.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Added test for simple test for chord and fixed chord implementation * Changed _IMMUTABLE_OPTIONS * Fixed chord interface * Fixed chord interface * Fixed chord interface * Fixed chord interface * Fixed list order * Fixed tests (stamp test and chord test), fixed order in groups * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fixed lint and elements * Changed implementation of stamp API and fix lint * Added documentation to Stamping API. Added chord with groups test * Implemented stamping inside replace and added test for an implementation * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Added test additonal tests for chord, improved coverage * Added test additonal tests for chord, improved coverage * Added test additonal tests for chord, improved coverage * Splitted into subtests * Group stamping rollback * group.id is None fixed * Added integration test * Added integration test * apply_async fixed * Integration test and test_chord fixed * Lint fixed * chord freeze fixed * Minor fixes. * Chain apply_async fixed and tests fixed * lint fixed * Added integration test for chord * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * type -> isinstance * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Redo header stamping (#7341) * _freeze_gid dict merge fixed * OptionsVisitor created * Fixed canvas.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Added test for simple test for chord and fixed chord implementation * Changed _IMMUTABLE_OPTIONS * Fixed chord interface * Fixed chord interface * Fixed chord interface * Fixed chord interface * Fixed list order * Fixed tests (stamp test and chord test), fixed order in groups * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fixed lint and elements * Changed implementation of stamp API and fix lint * Added documentation to Stamping API. Added chord with groups test * Implemented stamping inside replace and added test for an implementation * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Added test additonal tests for chord, improved coverage * Added test additonal tests for chord, improved coverage * Added test additonal tests for chord, improved coverage * Splitted into subtests * Group stamping rollback * group.id is None fixed * Added integration test * Added integration test * apply_async fixed * Integration test and test_chord fixed * Lint fixed * chord freeze fixed * Minor fixes. * Chain apply_async fixed and tests fixed * lint fixed * Added integration test for chord * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * type -> isinstance * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Omer Katz <[email protected]> * Added stamping mechanism * Manual stamping improved * flake8 fixed * Added subtests * Add comma. * Moved groups to stamps * Fixed chord and added test for that * Strip down the header-stamping PR to the basics. * Serialize groups. * Add groups to result backend meta data. * Fix spelling mistake. * Revert changes to canvas.py * Revert changes to app/base.py * Add stamping implementation to canvas.py * Send task to AMQP with groups. * Successfully pass single group to result. * _freeze_gid dict merge fixed * First draft of the visitor API. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * OptionsVisitor created * Fixed canvas.py * Added test for simple test for chord and fixed chord implementation * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Changed _IMMUTABLE_OPTIONS * Fixed chord interface * Fixed chord interface * Fixed chord interface * Fixed chord interface * Fixed list order * Fixed tests (stamp test and chord test), fixed order in groups * Fixed lint and elements * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Changed implementation of stamp API and fix lint * Added documentation to Stamping API. Added chord with groups test * Implemented stamping inside replace and added test for an implementation * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Added test additonal tests for chord, improved coverage * Added test additonal tests for chord, improved coverage * Added test additonal tests for chord, improved coverage * Splitted into subtests * Group stamping rollback * group.id is None fixed * Added integration test * Added integration test * apply_async fixed * Integration test and test_chord fixed * Lint fixed * chord freeze fixed * Minor fixes. * Chain apply_async fixed and tests fixed * lint fixed * Added integration test for chord * type -> isinstance * Added stamping mechanism * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Manual stamping improved * fail_ci_if_error uncommented * flake8 fixed * Added subtests * Changes * Add comma. * Fixed chord and added test for that * canvas.py fixed * Test chord.py fixed * Fixed stamped_headers * collections import fixed * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * collections import fixed * Update celery/backends/base.py Co-authored-by: Omer Katz <[email protected]> * ampq.py fixed * Refrain from using deprecated import path. * Fix test_complex_chain regression. Whenever we stamp a group we need to freeze it first if it wasn't already frozen. Somewhere along the line, the group id changed because we were freezing twice. This commit places the stamping operation after preparing the chain's steps which fixes the problem somehow. We don't know why yet. * Fixed integration tests * Fixed integration tests * Fixed integration tests * Fixed integration tests * Fixed issues with maybe_list. Add documentation * Fixed potential issue with integration tests * Fixed issues with _regen * Fixed issues with _regen * Fixed test_generator issues * Fixed _regen stamping * Fixed _regen stamping * Fixed TimeOut issue * Fixed TimeOut issue * Fixed TimeOut issue * Update docs/userguide/canvas.rst Co-authored-by: Omer Katz <[email protected]> * Fixed Couchbase * Better stamping intro * New GroupVisitor example * Adjust documentation. Co-authored-by: Naomi Elstein <[email protected]> Co-authored-by: Omer Katz <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Asif Saif Uddin <[email protected]> Co-authored-by: Omer Katz <[email protected]>

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

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

airbyte

Python

f83eca58eaf2129d21b5796a301732ab22675130

test_abstract_source.py

test_valid_incremental_read_with_slices

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

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

def require_docker() -> DockerCommand: if command := get_docker_command(): return command raise ApplicationError(f'No container runtime detected. Supported commands: {", ".join(DOCKER_COMMANDS)}') @cache

test/lib/ansible_test/_internal/docker_util.py

@cache

ansible

Python

3eb0485dd92c88cc92152d3656d94492db44b183

docker_util.py

require_docker

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

ansible-test - Use more native type hints. (#78435) * ansible-test - Use more native type hints. Simple search and replace to switch from comments to native type hints for return types of functions with no arguments. * ansible-test - Use more native type hints. Conversion of simple single-line function annotation type comments to native type hints. * ansible-test - Use more native type hints. Conversion of single-line function annotation type comments with default values to native type hints. * ansible-test - Use more native type hints. Manual conversion of type annotation comments for functions which have pylint directives.

def skip(self): self._skip = True

sympy/combinatorics/graycode.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

graycode.py

skip

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

Updated import locations

def test_dynamic_sampling_rules_should_contain_single_uniform_rule(self): with Feature({self.universal_ds_flag: True, self.old_ds_flag: True}): response = self.get_response( self.org_slug, self.proj_slug, dynamicSampling=_dyn_sampling_data(multiple_uniform_rules=True), ) assert response.status_code == 400 assert ( response.json()["dynamicSampling"]["non_field_errors"][0] == "Uniform rule " "must be in the last position only" )

tests/sentry/api/endpoints/test_project_details.py

sentry

Python

5462ee11ad11ebb9a50323befcd286816d7898c8

test_project_details.py

test_dynamic_sampling_rules_should_contain_single_uniform_rule

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

feat(ds): Support new DS behaviour in project_details endpoint (#40387) Supports new adaptive dynamic sampling behaviour alongside the deprecated dynamic sampling behaviour and achieves that through feature flag differentiation This PR achieve that through the following: - Introducing a new `DynamicSamplingBiasSerializer` which is composed of id representing the bias name and a boolean flag indicating whether that particular flag is active or not - Modifies current existing behavior for both old sampling flag and new sampling flag. Essentially the new setup entails that to be on the old dynamic sampling, the following flags need to be enabled "organizations:server-side-sampling" and "organizations:server-side-sampling-ui", and to be on the new dynamic sampling configurations, you need the following flags to be enabled "organizations:dynamic-sampling-basic" and "organizations:server-side-sampling" P.S. 1: These flags will be replaced "organizations:server-side-sampling-ui" -> "organizations:dynamic-sampling-deprecated" "organizations:server-side-sampling-basic" -> "organizations:dynamic-sampling" Hence, these feature flags need to be updated once this PR lands https://github.com/getsentry/sentry/pull/40388 P.S. 2: If a project is on the new plan and the old plan, the new plan takes precedence - Introduces default biases that are enabled by default and can be overwritten. The motivation to do this is to be able to add new biases that are enabled by default, and both the GET and PUT request honor this list - `GET` and `POST` endpoint does a dictionary update of user's stored biases on the default biases that are hardcoded, and returns them to the UI/ relay. This means that the introduced project option "sentry:dynamic_sampling_biases" might not have all the toggles enabled/disabled through the UI but only the ones that a customer chose to modify Followup: - This new feature flag behaviour needs to be reflected in ProjectConfig computations

def test_submessage_event_sent_after_transaction_commits(self) -> None: hamlet = self.example_user("hamlet") message_id = self.send_stream_message(hamlet, "Denmark") with self.tornado_redirected_to_list([], expected_num_events=1): with mock.patch("zerver.actions.submessage.send_event") as m: m.side_effect = AssertionError( "Events should be sent only after the transaction commits." ) do_add_submessage(hamlet.realm, hamlet.id, message_id, "whatever", "whatever")

zerver/tests/test_submessage.py

zulip

Python

3a135b04d9e9f84aa2a31d6fc0b1b08e9cf9aeac

test_submessage.py

test_submessage_event_sent_after_transaction_commits

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

actions: Split out zerver.actions.submessage. Signed-off-by: Anders Kaseorg <[email protected]>

def _reverse_pointer(self): reverse_octets = str(self).split('.')[::-1] return '.'.join(reverse_octets) + '.in-addr.arpa'

python3.10.4/Lib/ipaddress.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

ipaddress.py

_reverse_pointer

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

add python 3.10.4 for windows

def configure_architecture_optimizers(self): return None

nni/retiarii/oneshot/pytorch/base_lightning.py

nni

Python

8b2eb425274cdb4537fbce4a315aec12a378d6db

base_lightning.py

configure_architecture_optimizers

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

Lightning implementation for retiarii oneshot nas (#4479)

def _get_simple_image_viewer(self): # Try to render the env, if required. if not self._render: return None try: from gym.envs.classic_control.rendering import SimpleImageViewer return SimpleImageViewer() except (ImportError, ModuleNotFoundError): self._render = False # disable rendering logger.warning( "Could not import gym.envs.classic_control." "rendering! Try `pip install gym[all]`." ) return None

rllib/evaluation/env_runner_v2.py

ray

Python

52bb8e47d483082e528fc8595005e0813a46efb8

env_runner_v2.py

_get_simple_image_viewer

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

[RLlib] EnvRunnerV2 and EpisodeV2 that support Connectors. (#25922)

def _update_api_throttle_limit(self): self._api.account.get_insights()

airbyte-integrations/connectors/source-facebook-marketing/source_facebook_marketing/streams/async_job_manager.py

airbyte

Python

a3aae8017a0a40ff2006e2567f71dccb04c997a5

async_job_manager.py

_update_api_throttle_limit

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

🎉 🎉 Source FB Marketing: performance and reliability fixes (#9805) * Facebook Marketing performance improvement * add comments and little refactoring * fix integration tests with the new config * improve job status handling, limit concurrency to 10 * fix campaign jobs, refactor manager * big refactoring of async jobs, support random order of slices * update source _read_incremental to hook new state logic * fix issues with timeout * remove debugging and clean up, improve retry logic * merge changes from #8234 * fix call super _read_increment * generalize batch execution, add use_batch flag * improve coverage, do some refactoring of spec * update test, remove overrides of source * add split by AdSet * add smaller insights * fix end_date < start_date case * add account_id to PK * add notes * fix new streams * fix reversed incremental stream * update spec.json for SAT * upgrade CDK and bump version Co-authored-by: Dmytro Rezchykov <[email protected]> Co-authored-by: Eugene Kulak <[email protected]>

def test_two_configs_one_default_app(self): with self.settings(INSTALLED_APPS=["apps.two_configs_one_default_app"]): config = apps.get_app_config("two_configs_one_default_app") self.assertIsInstance(config, TwoConfig)

tests/apps/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_two_configs_one_default_app

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

Refs #33476 -- Reformatted code with Black.

def variables(self): if isinstance(self.model, tf.keras.Model): return self.model.variables else: return self.model.variables()

rllib/policy/eager_tf_policy_v2.py

ray

Python

bc3a1d35cf6e9a5fd7eef908a8e76aefb80ce6a9

eager_tf_policy_v2.py

variables

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

[RLlib] Introduce new policy base classes. (#24742)

async def _send_renewal_emails(self) -> None: expiring_users = await self.store.get_users_expiring_soon() if expiring_users: for user_id, expiration_ts_ms in expiring_users: await self._send_renewal_email( user_id=user_id, expiration_ts=expiration_ts_ms )

synapse/handlers/account_validity.py

synapse

Python

1783156dbcf4164692e66275d1c29857c434995b

account_validity.py

_send_renewal_emails

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

Add some type hints to datastore (#12423) * Add some type hints to datastore * newsfile * change `Collection` to `List` * refactor return type of `select_users_txn` * correct type hint in `stream.py` * Remove `Optional` in `select_users_txn` * remove not needed return type in `__init__` * Revert change in `get_stream_id_for_event_txn` * Remove import from `Literal`

def ones(shape, *, dtype=None, meta=None, **kwargs): raise NotImplementedError

dask/array/backends.py

dask

Python

c4d35f5515191409913827fd4faa3b69a3d7399a

backends.py

ones

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

Backend library dispatching for IO in Dask-Array and Dask-DataFrame (#9475)

def selective_find(str, char, index, pos): l = len(str) while 1: pos += 1 if pos == l: return (-1, -1) c = str[pos] if c == char: return index+1, pos elif c < char: index += 1

python3.10.4/Lib/encodings/punycode.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

punycode.py

selective_find

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

add python 3.10.4 for windows

def forward(self, input, mask, kv=None, cache=None, head_mask=None, output_attentions=False): # Input is (bs, qlen, dim) # Mask is (bs, klen) (non-causal) or (bs, klen, klen) bs, qlen, dim = input.size() if kv is None: klen = qlen if cache is None else cache["slen"] + qlen else: klen = kv.size(1) # assert dim == self.dim, f'Dimensions do not match: {dim} input vs {self.dim} configured' n_heads = self.n_heads dim_per_head = self.dim // n_heads mask_reshape = (bs, 1, qlen, klen) if mask.dim() == 3 else (bs, 1, 1, klen)

src/transformers/models/xlm/modeling_xlm.py

transformers

Python

d3cb28886ac68beba9a6646b422a4d727b056c0c

modeling_xlm.py

forward

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

Not use -1e4 as attn mask (#17306) * Use torch.finfo(self.dtype).min * for GPTNeoX * for Albert * For Splinter * Update src/transformers/models/data2vec/modeling_data2vec_audio.py Co-authored-by: Patrick von Platen <[email protected]> * fix -inf used in Bart-like models * Fix a few remaining -inf * more fix * clean up * For CLIP * For FSMT * clean up * fix test * Add dtype argument and use it for LayoutLMv3 * update FlaxLongT5Attention Co-authored-by: ydshieh <[email protected]> Co-authored-by: Patrick von Platen <[email protected]>

def test_userreport(django_cache, default_project, monkeypatch): event_id = uuid.uuid4().hex start_time = time.time() - 3600 mgr = EventManager(data={"event_id": event_id, "user": {"email": "[email protected]"}}) mgr.normalize() mgr.save(default_project.id) (evtuser,) = EventUser.objects.all() assert not evtuser.name assert not UserReport.objects.all() assert process_userreport( { "type": "user_report", "start_time": start_time, "payload": json.dumps( { "name": "Hans Gans", "event_id": event_id, "comments": "hello world", "email": "[email protected]", } ), "project_id": default_project.id, }, projects={default_project.id: default_project}, ) (report,) = UserReport.objects.all() assert report.comments == "hello world" (evtuser,) = EventUser.objects.all() assert evtuser.name == "Hans Gans" @pytest.mark.django_db

tests/sentry/ingest/ingest_consumer/test_ingest_consumer_processing.py

@pytest.mark.django_db

sentry

Python

8384b745769e08ffa2b10e9a546fce5d9d435da9

test_ingest_consumer_processing.py

test_userreport

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

fix(tests): More django cache clears in ingest consumer tests (#39481)

def readinto(self, b): self._unsupported("readinto")

python3.10.4/Lib/_pyio.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pyio.py

readinto

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

add python 3.10.4 for windows

def test_recovery_cluster_failure_resume_all(tmp_path, shutdown_only): ray.shutdown() tmp_path = tmp_path subprocess.check_call(["ray", "start", "--head"]) time.sleep(1) workflow_dir = tmp_path / "workflow" lock_file = tmp_path / "lock_file" lock = FileLock(lock_file) lock.acquire() proc = run_string_as_driver_nonblocking( f

python/ray/workflow/tests/test_recovery.py

proc = run_string_as_driver_nonblocking( f"""@ray.remote

ray

Python

ddd63aba77b0e4da699e358beba37cd907f7cb37

test_recovery.py

test_recovery_cluster_failure_resume_all

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

[workflow] Major refactoring - new async workflow executor (#25618) * major workflow refactoring

def calc(term): # This part is for reading and converting arithmetic terms. term = term.replace(" ", "") term = term.replace("^", "**") term = term.replace("=", "") term = term.replace("?", "") term = term.replace("%", "/100.00") term = term.replace("rad", "radians") term = term.replace("mod", "%") term = term.replace("aval", "abs") functions = [ "sin", "cos", "tan", "pow", "cosh", "sinh", "tanh", "sqrt", "pi", "radians", "e", ] # This part is for reading and converting function expressions. term = term.lower() for func in functions: if func in term: withmath = "math." + func term = term.replace(func, withmath) try: # here goes the actual evaluating. term = eval(term) # here goes to the error cases. except ZeroDivisionError: print("Can't divide by 0. Please try again.") except NameError: print("Invalid input. Please try again") except AttributeError: print("Please check usage method and try again.") except TypeError: print("please enter inputs of correct datatype ") return term

calculator.py

Python

Python

f0af0c43340763724f139fa68aa1e5a9ffe458b4

calculator.py

calc

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

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

def csc_median_axis_0(X): if not isinstance(X, sp.csc_matrix): raise TypeError("Expected matrix of CSC format, got %s" % X.format) indptr = X.indptr n_samples, n_features = X.shape median = np.zeros(n_features) for f_ind, (start, end) in enumerate(zip(indptr[:-1], indptr[1:])): # Prevent modifying X in place data = np.copy(X.data[start:end]) nz = n_samples - data.size median[f_ind] = _get_median(data, nz) return median

sklearn/utils/sparsefuncs.py

scikit-learn

Python

15599753b63f10748ffb374aacd37dbb37806a37

sparsefuncs.py

csc_median_axis_0

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

DOC ensures sklearn.utils.sparsefuncs.csc_median_axis_0 passes numpydoc validation (#24461)

def get_block_class(self, name=None, module_path=None): meta = type( "Meta", (self.base_block_class._meta_class,), { "icon": self.icon, }, ) cls = type( name or "%sChooserBlock" % self.model_name, (self.base_block_class,), { "target_model": self.model, "widget": self.widget_class(), "Meta": meta, }, ) if module_path: cls.__module__ = module_path return cls

wagtail/admin/viewsets/chooser.py

wagtail

Python

b4bc6818659ae785af39965569ed4bca51f0bf0d

chooser.py

get_block_class

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

Fix DocumentChooserBlock deconstruction for custom document models Fixes #8989. The previous fix #9004 failed for custom document models because ChooserViewset assigns an internal name for the ChooserBlock class based on the model name, and if this is anything other than Document it won't match the name DocumentChooserBlock that it's exposed under in wagtail.documents.blocks. Fix this by replacing the `block_class` property with a `get_block_class` method that lets us specify the class name. As a bonus, user code that defines chooser blocks no longer has to directly hack the `__module__` attribute.

def unapply(self, project_state, schema_editor, collect_sql=False): # Construct all the intermediate states we need for a reverse migration to_run = [] new_state = project_state # Phase 1 for operation in self.operations: # If it's irreversible, error out if not operation.reversible: raise IrreversibleError( "Operation %s in %s is not reversible" % (operation, self) ) # Preserve new state from previous run to not tamper the same state # over all operations new_state = new_state.clone() old_state = new_state.clone() operation.state_forwards(self.app_label, new_state) to_run.insert(0, (operation, old_state, new_state)) # Phase 2 for operation, to_state, from_state in to_run: if collect_sql: schema_editor.collected_sql.append("--") if not operation.reduces_to_sql: schema_editor.collected_sql.append( "-- MIGRATION NOW PERFORMS OPERATION THAT CANNOT BE WRITTEN AS SQL:" ) schema_editor.collected_sql.append("-- %s" % operation.describe()) schema_editor.collected_sql.append("--") if not operation.reduces_to_sql: continue atomic_operation = operation.atomic or ( self.atomic and operation.atomic is not False ) if not schema_editor.atomic_migration and atomic_operation: # Force a transaction on a non-transactional-DDL backend or an # atomic operation inside a non-atomic migration. with atomic(schema_editor.connection.alias): operation.database_backwards( self.app_label, schema_editor, from_state, to_state ) else: # Normal behaviour operation.database_backwards( self.app_label, schema_editor, from_state, to_state ) return project_state

django/db/migrations/migration.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

migration.py

unapply

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

Refs #33476 -- Reformatted code with Black.

def do_filter(self) -> bool: return self._active and self._do_filter

plugins/extract/align/_base/processing.py

faceswap

Python

9e2026f6feba4fc1d60e0d985cbc1ba9c44a4848

processing.py

do_filter

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

Extract: Implement re-align/2nd pass - implement configurable re-align function in extract - update locales + documentation - re-factor align._base and split to separate modules - move normalization method to plugin parent - bugfix: FAN use zeros for pre-processing crop - lint AlignedFilter

def vector_part(self): return Quaternion(0, self.b, self.c, self.d)

sympy/algebras/quaternion.py

sympy

Python

72b9b01d0ede4543c1d3f10e08a79345c550254a

quaternion.py

vector_part

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

minor changes

def get_results_limit(request): config = get_config() try: limit = int(request.query_params.get('limit', config.PAGINATE_COUNT)) or config.MAX_PAGE_SIZE except ValueError: limit = config.PAGINATE_COUNT if config.MAX_PAGE_SIZE: limit = min(limit, config.MAX_PAGE_SIZE) return limit

netbox/ipam/api/views.py

netbox

Python

de17a651e6f976e8b7c16b49d4e78f6a6988b870

views.py

get_results_limit

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

Closes #10043: Add support for 'limit' query parameter to available VLANs API endpoint

def parse_with_tabs(self) -> "ParserElement": self.keepTabs = True return self

pipenv/patched/notpip/_vendor/pyparsing/core.py

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

core.py

parse_with_tabs

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

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

def sql_flush(style, connection, reset_sequences=True, allow_cascade=False): tables = connection.introspection.django_table_names( only_existing=True, include_views=False ) return connection.ops.sql_flush( style, tables, reset_sequences=reset_sequences, allow_cascade=allow_cascade, )

django/core/management/sql.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

sql.py

sql_flush

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

Refs #33476 -- Reformatted code with Black.

def set_saved_weights_in_checkpoint_flag(config): for input_feature in config.get("input_features", []): input_feature["saved_weights_in_checkpoint"] = True

ludwig/utils/misc_utils.py

ludwig

Python

7a2bfd65e97e81f02e4c8821e2a82a78d5f6ab00

misc_utils.py

set_saved_weights_in_checkpoint_flag

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

Set saved_weights_in_checkpoint immediately after creating model. Also adds test. (#2131) * Set saved_weights_in_checkpoint immediately after creating model. Also adds integration test. * Set saved_weights_in_checkpoint config key on load. Co-authored-by: Daniel Treiman <[email protected]>

def test_condinst_maskhead_loss(self): s = 256 img_metas = [{ 'img_shape': (s, s, 3), 'pad_shape': (s, s, 3), 'scale_factor': 1, }] condinst_bboxhead = CondInstBboxHead( num_classes=4, in_channels=1, feat_channels=1, stacked_convs=1, norm_cfg=None) mask_feature_head = _fake_mask_feature_head() condinst_maskhead = CondInstMaskHead( mask_feature_head=mask_feature_head, loss_mask=dict( type='DiceLoss', use_sigmoid=True, activate=True, eps=5e-6, loss_weight=1.0)) # Fcos head expects a multiple levels of features per image feats = [] for i in range(len(condinst_bboxhead.strides)): feats.append( torch.rand(1, 1, s // (2**(i + 3)), s // (2**(i + 3)))) feats = tuple(feats) cls_scores, bbox_preds, centernesses, param_preds =\ condinst_bboxhead.forward(feats) # Test that empty ground truth encourages the network to # predict background gt_instances = InstanceData() gt_instances.bboxes = torch.empty((0, 4)) gt_instances.labels = torch.LongTensor([]) gt_instances.masks = _rand_masks(0, gt_instances.bboxes.numpy(), s, s) _ = condinst_bboxhead.loss_by_feat(cls_scores, bbox_preds, centernesses, param_preds, [gt_instances], img_metas) # When truth is empty then all mask loss # should be zero for random inputs positive_infos = condinst_bboxhead.get_positive_infos() mask_outs = condinst_maskhead.forward(feats, positive_infos) empty_gt_mask_losses = condinst_maskhead.loss_by_feat( *mask_outs, [gt_instances], img_metas, positive_infos) loss_mask = empty_gt_mask_losses['loss_mask'] self.assertEqual(loss_mask, 0, 'mask loss should be zero') # When truth is non-empty then all cls, box loss and centerness loss # should be nonzero for random inputs gt_instances = InstanceData() gt_instances.bboxes = torch.Tensor( [[23.6667, 23.8757, 238.6326, 151.8874]]) gt_instances.labels = torch.LongTensor([2]) gt_instances.masks = _rand_masks(1, gt_instances.bboxes.numpy(), s, s) _ = condinst_bboxhead.loss_by_feat(cls_scores, bbox_preds, centernesses, param_preds, [gt_instances], img_metas) positive_infos = condinst_bboxhead.get_positive_infos() mask_outs = condinst_maskhead.forward(feats, positive_infos) one_gt_mask_losses = condinst_maskhead.loss_by_feat( *mask_outs, [gt_instances], img_metas, positive_infos) loss_mask = one_gt_mask_losses['loss_mask'] self.assertGreater(loss_mask, 0, 'mask loss should be nonzero')

tests/test_models/test_dense_heads/test_condinst_head.py

mmdetection

Python

79c8295801acedee0cbdbf128a01b9fe162646b0

test_condinst_head.py

test_condinst_maskhead_loss

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

[Feature]: Support Condinst (#9223) * [Feature]: support condinst for instance segmentation * update * update * update * fix config name and add test unit * fix squeeze error * add README and chang mask to poly

def get_updates_for(self, inputs): if inputs is None: # Requesting unconditional updates. return [u for u in self.updates if u._unconditional_update] # Requesting input-conditional updates. updates = [u for u in self.updates if not u._unconditional_update] inputs = tf.nest.flatten(inputs) reachable = tf_utils.get_reachable_from_inputs(inputs, updates) return [u for u in updates if u in reachable]

keras/engine/base_layer_v1.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

base_layer_v1.py

get_updates_for

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def _get_free_vram(self) -> List[float]: vram = [] self._log("debug", f"GPU VRAM free: {vram}") return vram

lib/gpu_stats/cpu.py

faceswap

Python

bdbbad4d310fb606b6f412aa81e9f57ccd994e97

cpu.py

_get_free_vram

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

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

def _ensure_html_response(url, session): # type: (str, PipSession) -> None scheme, netloc, path, query, fragment = urllib.parse.urlsplit(url) if scheme not in {'http', 'https'}: raise _NotHTTP() resp = session.head(url, allow_redirects=True) raise_for_status(resp) _ensure_html_header(resp)

.venv/lib/python3.8/site-packages/pip/_internal/index/collector.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

collector.py

_ensure_html_response

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

upd; format

def __new__(cls, name, patch, symbols=None, relations={}, **kwargs): if not isinstance(name, Str): name = Str(name) # canonicallize the symbols if symbols is None: names = kwargs.get('names', None) if names is None: symbols = Tuple( *[Symbol('%s_%s' % (name.name, i), real=True) for i in range(patch.dim)] ) else: sympy_deprecation_warning( f, deprecated_since_version="1.7", active_deprecations_target="deprecated-diffgeom-mutable", ) symbols = Tuple( *[Symbol(n, real=True) for n in names] ) else: syms = [] for s in symbols: if isinstance(s, Symbol): syms.append(Symbol(s.name, **s._assumptions.generator)) elif isinstance(s, str): sympy_deprecation_warning( f, deprecated_since_version="1.7", active_deprecations_target="deprecated-diffgeom-mutable", ) syms.append(Symbol(s, real=True)) symbols = Tuple(*syms) # canonicallize the relations rel_temp = {} for k,v in relations.items(): s1, s2 = k if not isinstance(s1, Str): s1 = Str(s1) if not isinstance(s2, Str): s2 = Str(s2) key = Tuple(s1, s2) # Old version used Lambda as a value. if isinstance(v, Lambda): v = (tuple(v.signature), tuple(v.expr)) else: v = (tuple(v[0]), tuple(v[1])) rel_temp[key] = v relations = Dict(rel_temp) # construct the object obj = super().__new__(cls, name, patch, symbols, relations) # Add deprecated attributes obj.transforms = _deprecated_dict( , {}) obj._names = [str(n) for n in symbols] obj.patch.coord_systems.append(obj) # deprecated obj._dummies = [Dummy(str(n)) for n in symbols] # deprecated obj._dummy = Dummy() return obj

sympy/diffgeom/diffgeom.py

sympy

Python

f8674bfe4988332e7ce60ceb36b365ce9aff662a

diffgeom.py

__new__

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

Update the sympy.diffgeom mutability deprecations

def GetHeaderGuardCPPVariable(filename): # Restores original filename in case that cpplint is invoked from Emacs's # flymake. filename = re.sub(r'_flymake\.h$', '.h', filename) filename = re.sub(r'/\.flymake/([^/]*)$', r'/\1', filename) fileinfo = FileInfo(filename) file_path_from_root = fileinfo.RepositoryName() if _root: file_path_from_root = re.sub('^' + _root + os.sep, '', file_path_from_root) return re.sub(r'[-./\s]', '_', file_path_from_root).upper() + '_'

code/deep/BJMMD/caffe/scripts/cpp_lint.py

transferlearning

Python

cc4d0564756ca067516f71718a3d135996525909

cpp_lint.py

GetHeaderGuardCPPVariable

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

Balanced joint maximum mean discrepancy for deep transfer learning

def husl_palette(n_colors=6, h=.01, s=.9, l=.65, as_cmap=False): # noqa if as_cmap: n_colors = 256 hues = np.linspace(0, 1, int(n_colors) + 1)[:-1] hues += h hues %= 1 hues *= 359 s *= 99 l *= 99 # noqa palette = [_color_to_rgb((h_i, s, l), input="husl") for h_i in hues] if as_cmap: return mpl.colors.ListedColormap(palette, "hsl") else: return _ColorPalette(palette)

seaborn/palettes.py

seaborn

Python

e644793f0ac2b1be178425f20f529121f37f29de

palettes.py

husl_palette

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

Convert color palette docstrings to notebooks (#3034) * Convert color palette docstrings to notebooks and rerun all with py310 kernel * Add v0.12.1 release notes to index * Improve failure mode when ipywidgets is not involved * Update palettes docstrings * Remove all other doctest-style examples * Remove doctest-oriented testing infrastructure * Mention in release notes * Skip colormap patch test on matplotlib's where it's not relevant * Use more robust approach to mpl backcompat

def aix_platform(): # type: () -> str vrmf, bd = _aix_bosmp64() return _aix_tag(_aix_vrtl(vrmf), bd) # extract vrtl from the BUILD_GNU_TYPE as an int

python3.10.4/Lib/_aix_support.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_aix_support.py

aix_platform

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

add python 3.10.4 for windows

def __call__(self, *fields): orders = (covariant_order(e) + contravariant_order(e) for e in self.args) mul = 1/Mul(*(factorial(o) for o in orders)) perms = permutations(fields) perms_par = (Permutation( p).signature() for p in permutations(range(len(fields)))) tensor_prod = TensorProduct(*self.args) return mul*Add(*[tensor_prod(*p[0])*p[1] for p in zip(perms, perms_par)])

sympy/diffgeom/diffgeom.py

sympy

Python

8fc835bcd86ea080644783a363e47adca6dff3a7

diffgeom.py

__call__

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

Remove redundant list calls

def _check_ordering(cls): if cls._meta._ordering_clash: return [ checks.Error( "'ordering' and 'order_with_respect_to' cannot be used together.", obj=cls, id="models.E021", ), ] if cls._meta.order_with_respect_to or not cls._meta.ordering: return [] if not isinstance(cls._meta.ordering, (list, tuple)): return [ checks.Error( "'ordering' must be a tuple or list (even if you want to order by only one field).", obj=cls, id="models.E014", ) ] errors = [] fields = cls._meta.ordering # Skip expressions and '?' fields. fields = (f for f in fields if isinstance(f, str) and f != "?") # Convert "-field" to "field". fields = ((f[1:] if f.startswith("-") else f) for f in fields) # Separate related fields and non-related fields. _fields = [] related_fields = [] for f in fields: if LOOKUP_SEP in f: related_fields.append(f) else: _fields.append(f) fields = _fields # Check related fields. for field in related_fields: _cls = cls fld = None for part in field.split(LOOKUP_SEP): try: # pk is an alias that won't be found by opts.get_field. if part == "pk": fld = _cls._meta.pk else: fld = _cls._meta.get_field(part) if fld.is_relation: _cls = fld.path_infos[-1].to_opts.model else: _cls = None except (FieldDoesNotExist, AttributeError): if fld is None or ( fld.get_transform(part) is None and fld.get_lookup(part) is None ): errors.append( checks.Error( "'ordering' refers to the nonexistent field, " "related field, or lookup '%s'." % field, obj=cls, id="models.E015", ) ) # Skip ordering on pk. This is always a valid order_by field # but is an alias and therefore won't be found by opts.get_field. fields = {f for f in fields if f != "pk"} # Check for invalid or nonexistent fields in ordering. invalid_fields = [] # Any field name that is not present in field_names does not exist. # Also, ordering by m2m fields is not allowed. opts = cls._meta valid_fields = set( chain.from_iterable( (f.name, f.attname) if not (f.auto_created and not f.concrete) else (f.field.related_query_name(),) for f in chain(opts.fields, opts.related_objects) ) ) invalid_fields.extend(fields - valid_fields) for invalid_field in invalid_fields: errors.append( checks.Error( "'ordering' refers to the nonexistent field, related " "field, or lookup '%s'." % invalid_field, obj=cls, id="models.E015", ) ) return errors

django/db/models/base.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

base.py

_check_ordering

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

Refs #33476 -- Reformatted code with Black.

def cyclic_reduction(self, removed=False): word = self.copy() g = self.group.identity while not word.is_cyclically_reduced(): exp1 = abs(word.exponent_syllable(0)) exp2 = abs(word.exponent_syllable(-1)) exp = min(exp1, exp2) start = word[0]**abs(exp) end = word[-1]**abs(exp) word = start**-1*word*end**-1 g = g*start if removed: return word, g return word

sympy/combinatorics/free_groups.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

free_groups.py

cyclic_reduction

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

Updated import locations

def execute(): frappe.reload_doc("manufacturing", "doctype", "bom") frappe.reload_doc("manufacturing", "doctype", "bom_operation") frappe.db.sql( )

erpnext/patches/v13_0/set_operation_time_based_on_operating_cost.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

set_operation_time_based_on_operating_cost.py

execute

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

style: format code with black

def predict(self, X): # Note: since `predict` does not accept semi-supervised labels as input, # `fit(X, y).predict(X) != fit(X, y).transduction_`. # Hence, `fit_predict` is not implemented. # See https://github.com/scikit-learn/scikit-learn/pull/24898 probas = self.predict_proba(X) return self.classes_[np.argmax(probas, axis=1)].ravel()

sklearn/semi_supervised/_label_propagation.py

scikit-learn

Python

2b34dfde2453743fa046312a49cc312a5586ea04

_label_propagation.py

predict

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

DOC Improve docs of BaseLabelPropagation.transduction_ (#24985)

def _array_perimeter(arr): # note we use Python's half-open ranges to avoid repeating # the corners forward = np.s_[0:-1] # [0 ... -1) backward = np.s_[-1:0:-1] # [-1 ... 0) return np.concatenate(( arr[0, forward], arr[forward, -1], arr[-1, backward], arr[backward, 0], ))

lib/matplotlib/cbook/__init__.py

matplotlib

Python

13438f842729df1b04445d44ea83f616d1b85567

__init__.py

_array_perimeter

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

Fix some minor docstring typos

def _hits_numpy(G, normalized=True): import numpy as np if len(G) == 0: return {}, {} adj_ary = nx.to_numpy_array(G) # Hub matrix H = adj_ary @ adj_ary.T e, ev = np.linalg.eig(H) h = ev[:, np.argmax(e)] # eigenvector corresponding to the maximum eigenvalue # Authority matrix A = adj_ary.T @ adj_ary e, ev = np.linalg.eig(A) a = ev[:, np.argmax(e)] # eigenvector corresponding to the maximum eigenvalue if normalized: h /= h.sum() a /= a.sum() else: h /= h.max() a /= a.max() hubs = dict(zip(G, map(float, h))) authorities = dict(zip(G, map(float, a))) return hubs, authorities

networkx/algorithms/link_analysis/hits_alg.py

networkx

Python

e5f1edb82a379ceb6afcf421fa5f6b4cb43cfbaf

hits_alg.py

_hits_numpy

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

Make HITS numpy and scipy private functions (#5771) * Make HITS numpy and scipy private functions * fix examples with correct imports * remove functions from TOC

def _get_dependency_info() -> dict[str, JSONSerializable]: deps = [ "pandas", # required "numpy", "pytz", "dateutil", # install / build, "setuptools", "pip", "Cython", # test "pytest", "hypothesis", # docs "sphinx", # Other, need a min version "blosc", "feather", "xlsxwriter", "lxml.etree", "html5lib", "pymysql", "psycopg2", "jinja2", # Other, not imported. "IPython", "pandas_datareader", ] deps.extend(list(VERSIONS)) result: dict[str, JSONSerializable] = {} for modname in deps: mod = import_optional_dependency(modname, errors="ignore") result[modname] = get_version(mod) if mod else None return result

pandas/util/_print_versions.py

pandas

Python

44b660dc4a07f4fb507c31795ae63dca2e6e9440

_print_versions.py

_get_dependency_info

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

fix pandas.show_versions() and remove pin for setuptools (#47096)

def push(self, actor): busy_actors = [] if self._future_to_actor.values(): _, busy_actors = zip(*self._future_to_actor.values()) if actor in self._idle_actors or actor in busy_actors: raise ValueError("Actor already belongs to current ActorPool") else: self._return_actor(actor)

python/ray/util/actor_pool.py

ray

Python

21f1e8a5c65241ef618df88885c38222550209dd

actor_pool.py

push

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

[Core] Use newly pushed actor for existing pending tasks (#24980) Newly pushed actors will never be used with existing pending submits, so the worker will not be used to speed up existing tasks. If _return_actor is called at the end of push instead, the actor is pushed to _idle_actors and immediately used if there are pending submits.

def concat(cls, axis, left_parts, right_parts): # TODO: Possible change is `isinstance(right_parts, list)` if type(right_parts) is list: # `np.array` with partitions of empty ModinFrame has a shape (0,) # but `np.concatenate` can concatenate arrays only if its shapes at # specified axis are equals, so filtering empty frames to avoid concat error right_parts = [o for o in right_parts if o.size != 0] to_concat = ( [left_parts] + right_parts if left_parts.size != 0 else right_parts ) result = ( np.concatenate(to_concat, axis=axis) if len(to_concat) else left_parts ) else: result = np.append(left_parts, right_parts, axis=axis) if axis == 0: return cls.rebalance_partitions(result) else: return result, None

modin/core/dataframe/pandas/partitioning/partition_manager.py

modin

Python

eee5f435f68786778184c4886ff25d386fce0c4f

partition_manager.py

concat

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

PERF-#4892: Compute `lengths` in `rebalance_partitions` when possible (#4893) Signed-off-by: Myachev <[email protected]>

def _secs2timedelta(secs): msec = int(abs(secs - int(secs)) * 100) return f"{datetime.timedelta(seconds=int(secs))}.{msec:02d}"

paddlenlp/trainer/trainer_utils.py

PaddleNLP

Python

44a290e94d1becd1f09fddc3d873f9e19c9d6919

trainer_utils.py

_secs2timedelta

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

[Trainer] Add init version of paddlenlp trainer and apply finetune for ernie-1.0 pretraining. (#1761) * add some datasets for finetune. * support fine tune for all tastks. * add trainer prototype. * init verison for paddlenlp trainer. * refine trainer. * update for some details. * support multi-cards training evaluation. * support load from ckpt. * support for export inference model. * first version of trainer. * seq cls support clue. * trainer support for token classification and question answersing tasks. * fix as reviews. Co-authored-by: Zeyu Chen <[email protected]>

def _get_module_collection_mode(mode_dict, name, noarchive=False): # Default mode: collect into PYZ, unless noarchive is enabled. In that case, collect as pyc. mode_flags = _ModuleCollectionMode.PYC if noarchive else _ModuleCollectionMode.PYZ # If we have no collection mode settings, end here and now. if not mode_dict: return mode_flags # Search the parent modules/packages in top-down fashion, and take the last given setting. This ensures that # a setting given for the top-level package is recursively propagated to all its subpackages and submodules, # but also allows individual sub-modules to override the setting again. mode = 'pyz' name_parts = name.split('.') for i in range(len(name_parts)): modlevel = ".".join(name_parts[:i + 1]) modlevel_mode = mode_dict.get(modlevel, None) if modlevel_mode is not None: mode = modlevel_mode # Convert mode string to _ModuleCollectionMode flags try: mode_flags = _MODULE_COLLECTION_MODES[mode] except KeyError: raise ValueError(f"Unknown module collection mode for {name!r}: {mode!r}!") # noarchive flag being set means that we need to change _ModuleCollectionMode.PYZ into _ModuleCollectionMode.PYC if noarchive and _ModuleCollectionMode.PYZ in mode_flags: mode_flags ^= _ModuleCollectionMode.PYZ mode_flags |= _ModuleCollectionMode.PYC return mode_flags

PyInstaller/building/build_main.py

pyinstaller

Python

6e1bfa2de254d8ae302f54dcea0cfefae4dd3585

build_main.py

_get_module_collection_mode

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

building: more module collection modes, consolidate noarchive codepath Map the module collection mode strings into (combinations of) integer flags that control try basic collection modes: - collect a pyc into PYZ archive - collect a pyc as a data file - collect a py as a data file Consolidate the `noarchive=True` codepath into module collection mode, where "collect a pyc into PYZ archive" flag is swapped for a "collect a pyc as a data file". The new collection mode also implicitly fixes couple of minor annoyances of the `noarchive=True` mode: - the user-writable paths containing python source code are not littered with pyc/pyo files anymore; all pycs are now gathered in build directory - the name of pycs in local build directory are not mangled anymore (was previously the case for pycs that could not be written to their original locations due to lack of permissions) - the pycs have code paths stripped from them, same as in noarchive=False mode

def adapt(self, data, batch_size=None, steps=None): super().adapt(data, batch_size=batch_size, steps=steps)

keras/layers/preprocessing/discretization.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

discretization.py

adapt

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def calculate_bounds_for_mechanism(value_array, min_val_array, max_val_array): # TODO: Double check whether the iDPGaussianMechanism class squares its squared_l2_norm values!! worst_case_l2_norm = np.sqrt(np.sum(np.square(max_val_array - min_val_array))) * np.ones_like(value_array) l2_norm = np.sqrt(np.sum(np.square(value_array))) * np.ones_like(value_array) # print(l2_norm.shape, worst_case_l2_norm.shape) # print(l2_norm.shape) return l2_norm, worst_case_l2_norm

packages/syft/src/syft/core/adp/vectorized_publish.py

PySyft

Python

56137bacda6fea5a0053c65eb6fd88688f5298cc

vectorized_publish.py

calculate_bounds_for_mechanism

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

Implemented working vectorized_publish method into codebase Took 26 minutes

def __call__(self, f):

jina/serve/instrumentation/__init__.py

jina

Python

71e422211fe10930d384f2bf679785d3c415f514

__init__.py

__call__

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

feat: record existing Prometheus metrics into OpenTelemetry Histograms (#5275)

def _node_redundancy(G, v): n = len(G[v]) overlap = sum( 1 for (u, w) in combinations(G[v], 2) if (G[u].keys() & G[w].keys()) - {v} ) return (2 * overlap) / (n * (n - 1))

networkx/algorithms/bipartite/redundancy.py

networkx

Python

1f033118f2e0cca12c6e2375708dc92197b62da6

redundancy.py

_node_redundancy

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

Minor Python 2 cleanup (#6219) Python3 cleanup Use dict.keys() for set operations rather than explicitly creating sets.

def add_edges_from(self, ebunch_to_add, **attr): for e in ebunch_to_add: ne = len(e) if ne == 3: u, v, dd = e elif ne == 2: u, v = e dd = {} else: raise NetworkXError(f"Edge tuple {e} must be a 2-tuple or 3-tuple.") if u not in self._succ: if u is None: raise ValueError("None cannot be a node") self._succ[u] = self.adjlist_inner_dict_factory() self._pred[u] = self.adjlist_inner_dict_factory() self._node[u] = self.node_attr_dict_factory() if v not in self._succ: if v is None: raise ValueError("None cannot be a node") self._succ[v] = self.adjlist_inner_dict_factory() self._pred[v] = self.adjlist_inner_dict_factory() self._node[v] = self.node_attr_dict_factory() datadict = self._adj[u].get(v, self.edge_attr_dict_factory()) datadict.update(attr) datadict.update(dd) self._succ[u][v] = datadict self._pred[v][u] = datadict

networkx/classes/digraph.py

networkx

Python

979d54acba7c3d372c93d44c6c149700608ce8b0

digraph.py

add_edges_from

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

doc: update documentation when providing an iterator over current graph to add/remove_edges_from. (#6268) * doc for add_edges_from * doc for digraph * doc for multigraph * multigraph.add_nodes_from returns keylist * update docs for graph - edges * doc update: graph.add_nodes_from * doc update: graph.remove_nodes_from * doc update: graph.add_edges_from * doc update: rewording for graph.add_edges_from * doc update: graph.add_weighted_edges_from rewording * doc update: digraph updated as graph * doc update: digraph minor sync * doc update: multigraph same as graph * Update graph.py * Update digraph.py * Update multigraph.py

def validate_house_rent_dates(doc): if not doc.rented_to_date or not doc.rented_from_date: frappe.throw(_("House rented dates required for exemption calculation")) if date_diff(doc.rented_to_date, doc.rented_from_date) < 14: frappe.throw(_("House rented dates should be atleast 15 days apart")) proofs = frappe.db.sql( , { "employee": doc.employee, "payroll_period": doc.payroll_period, "from_date": doc.rented_from_date, "to_date": doc.rented_to_date, }, ) if proofs: frappe.throw(_("House rent paid days overlapping with {0}").format(proofs[0][0]))

erpnext/regional/india/utils.py

erpnext

Python

12b7e14fded587abc0f7821e3c3dfbea64498a7d

utils.py

validate_house_rent_dates

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

chore: keep back code to be a part of other apps / to be ported later

def customer_query(doctype, txt, searchfield, start, page_len, filters): conditions = [] cust_master_name = frappe.defaults.get_user_default("cust_master_name") if cust_master_name == "Customer Name": fields = ["name", "customer_group", "territory"] else: fields = ["name", "customer_name", "customer_group", "territory"] fields = get_fields("Customer", fields) searchfields = frappe.get_meta("Customer").get_search_fields() searchfields = " or ".join(field + " like %(txt)s" for field in searchfields) return frappe.db.sql( .format( **{ "fields": ", ".join(fields), "scond": searchfields, "mcond": get_match_cond(doctype), "fcond": get_filters_cond(doctype, filters, conditions).replace("%", "%%"), } ), {"txt": "%%%s%%" % txt, "_txt": txt.replace("%", ""), "start": start, "page_len": page_len}, ) # searches for supplier @frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

erpnext/controllers/queries.py

@frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

queries.py

customer_query

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

style: format code with black

def get_default_contact(out, name): contact_persons = frappe.db.sql( , (name), as_dict=1, ) if contact_persons: for out.contact_person in contact_persons: if out.contact_person.is_primary_contact: return out.contact_person out.contact_person = contact_persons[0] return out.contact_person

erpnext/stock/doctype/delivery_trip/delivery_trip.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

delivery_trip.py

get_default_contact

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

style: format code with black

def distance(hass, *args): locations = [] to_process = list(args) while to_process: value = to_process.pop(0) if isinstance(value, str) and not valid_entity_id(value): point_state = None else: point_state = _resolve_state(hass, value) if point_state is None: # We expect this and next value to be lat&lng if not to_process: _LOGGER.warning( "Distance:Expected latitude and longitude, got %s", value ) return None value_2 = to_process.pop(0) latitude = convert(value, float) longitude = convert(value_2, float) if latitude is None or longitude is None: _LOGGER.warning( "Distance:Unable to process latitude and longitude: %s, %s", value, value_2, ) return None else: if not loc_helper.has_location(point_state): _LOGGER.warning( "Distance:State does not contain valid location: %s", point_state ) return None latitude = point_state.attributes.get(ATTR_LATITUDE) longitude = point_state.attributes.get(ATTR_LONGITUDE) locations.append((latitude, longitude)) if len(locations) == 1: return hass.config.distance(*locations[0]) return hass.config.units.length( loc_util.distance(*locations[0] + locations[1]), UnitOfLength.METERS )

homeassistant/helpers/template.py

core

Python

9f7fd8956f22bd873d14ae89460cdffe6ef6f85d

template.py

distance

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

Use new unit enums in helpers (#83387)

def test_filter_with_failing_queryset(self): modeladmin = DecadeFilterBookAdminWithFailingQueryset(Book, site) request = self.request_factory.get("/", {}) request.user = self.alfred with self.assertRaises(ZeroDivisionError): modeladmin.get_changelist_instance(request)

tests/admin_filters/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_filter_with_failing_queryset

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

Refs #33476 -- Reformatted code with Black.

def test_background_populate_rooms_creator_column(self) -> None: # Insert a room without the creator room_id = self._generate_room() self.get_success( self.store.db_pool.simple_update( table="rooms", keyvalues={"room_id": room_id}, updatevalues={"creator": None}, desc="test", ) ) # Make sure the test is starting out with a room without a creator room_creator_before = self.get_success( self.store.db_pool.simple_select_one_onecol( table="rooms", keyvalues={"room_id": room_id}, retcol="creator", allow_none=True, ) ) self.assertEqual(room_creator_before, None) # Insert and run the background update. self.get_success( self.store.db_pool.simple_insert( "background_updates", { "update_name": _BackgroundUpdates.POPULATE_ROOMS_CREATOR_COLUMN, "progress_json": "{}", }, ) ) # ... and tell the DataStore that it hasn't finished all updates yet self.store.db_pool.updates._all_done = False # Now let's actually drive the updates to completion self.wait_for_background_updates() # Make sure the background update filled in the room creator room_creator_after = self.get_success( self.store.db_pool.simple_select_one_onecol( table="rooms", keyvalues={"room_id": room_id}, retcol="creator", allow_none=True, ) ) self.assertEqual(room_creator_after, self.user_id)

tests/storage/databases/main/test_room.py

synapse

Python

3ac412b4e2f8c5ba11dc962b8a9d871c1efdce9b

test_room.py

test_background_populate_rooms_creator_column

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

Require types in tests.storage. (#14646) Adds missing type hints to `tests.storage` package and does not allow untyped definitions.

def with_content_json(self, content): obj = super().with_content_json(content) # Ensure other values that are meaningful for the object as a whole (rather than # to a specific revision) are preserved obj.locked = self.locked obj.locked_at = self.locked_at obj.locked_by = self.locked_by return obj

wagtail/models/__init__.py

wagtail

Python

1cec004d97f0cfa3d4a8a1e99eea42ae7f651993

__init__.py

with_content_json

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

Extract page locking fields into a mixin

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

packages/python/plotly/plotly/graph_objs/_surface.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_surface.py

hidesurface

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

switch to black .22

def _total_vram_required(self) -> float: vrams = self._vram_per_phase vram_required_count = sum(1 for p in vrams.values() if p > 0) logger.debug("VRAM requirements: %s. Plugins requiring VRAM: %s", vrams, vram_required_count) retval = (sum(vrams.values()) * self._parallel_scaling.get(vram_required_count, self._scaling_fallback)) logger.debug("Total VRAM required: %s", retval) return retval

plugins/extract/pipeline.py

faceswap

Python

13cfb3f39e72e9ca181f173b7b3db2a048db0d08

pipeline.py

_total_vram_required

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

extract: Add batch processing mode

def test_check_perms_grant_test_true(test_file): expected = { "comment": "", "changes": {"grant_perms": {"Users": {"permissions": "read_execute"}}}, "name": str(test_file), "result": None, } with patch.dict(win_dacl.__opts__, {"test": True}): result = win_file.check_perms( path=str(test_file), grant_perms={"Users": {"perms": "read_execute"}}, inheritance=None, ) assert result == expected

tests/pytests/functional/modules/win_file/test_check_perms.py

salt

Python

5550d1823e9cb571740ae9e57b25424cfe6a919e

test_check_perms.py

test_check_perms_grant_test_true

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

Add changelong

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

packages/python/plotly/plotly/graph_objs/layout/_annotation.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_annotation.py

ayref

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

switch to black .22

def serialize(learning_rate_schedule): return generic_utils.serialize_keras_object(learning_rate_schedule) @keras_export("keras.optimizers.schedules.deserialize")

keras/optimizers/schedules/learning_rate_schedule.py

@keras_export("keras.optimizers.schedules.deserialize")

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

learning_rate_schedule.py

serialize

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def get_arguments(): parser = argparse.ArgumentParser(description="DML_CSR Network") parser.add_argument("--batch-size", type=int, default=1, help="Number of images sent to the network in one step.") parser.add_argument("--data-dir", type=str, default=DATA_DIRECTORY, help="Path to the directory containing the PASCAL VOC dataset.") parser.add_argument("--out-dir", type=str, default=DATA_DIRECTORY, help="Path to the directory containing the PASCAL VOC dataset.") parser.add_argument("--dataset", type=str, default='val', help="Path to the file listing the images in the dataset.") parser.add_argument("--ignore-label", type=int, default=IGNORE_LABEL, help="The index of the label to ignore during the training.") parser.add_argument("--num-classes", type=int, default=NUM_CLASSES, help="Number of classes to predict (including background).") parser.add_argument("--restore-from", type=str, help="Where restore model parameters from.") parser.add_argument("--gpu", type=str, default='7', help="choose gpu device.") parser.add_argument("--input-size", type=str, default=INPUT_SIZE, help="Comma-separated string with height and width of images.") parser.add_argument("--local_rank", type=int, default=0, help="choose gpu numbers") parser.add_argument('--dist-backend', default='nccl', type=str, help='distributed backend') parser.add_argument("--model_type", type=int, default=0, help="choose model type") return parser.parse_args()

parsing/dml_csr/test.py

insightface

Python

af2d71fab71bfd819daef263f4988f36499c0af2

test.py

get_arguments

https://github.com/deepinsight/insightface.git

Create test.py

def is_link_local(self): return (self.network_address.is_link_local and self.broadcast_address.is_link_local)

python3.10.4/Lib/ipaddress.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

ipaddress.py

is_link_local

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

add python 3.10.4 for windows

def no_style(): return make_style("nocolor")

django/core/management/color.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

color.py

no_style

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

Refs #33476 -- Reformatted code with Black.

def _add_speaker_embedding(x, speaker_embedding): # Save the dimensions as human-readable names batch_size = x.size()[0] text_num_chars = x.size()[1] # Start by making a copy of each speaker embedding to match the input text length # The output of this has size (batch_size, text_num_chars * speaker_embedding_size) speaker_embedding_size = speaker_embedding.size()[1] e = speaker_embedding.repeat_interleave(text_num_chars, dim=1) # Reshape it and transpose e = e.reshape(batch_size, speaker_embedding_size, text_num_chars) e = e.transpose(1, 2) # Concatenate the tiled speaker embedding with the encoder output x = torch.cat((x, e), 2) return x

synthesizer/models/tacotron.py

MockingBird

Python

f17e3b04e1049528e13ae340db3ac8212c56a35d

tacotron.py

_add_speaker_embedding