Datasets:

semeru

/

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

like 1

sorted_items

def sorted_items(self) -> List[Tuple[str, "PNGHeaderDict"]]: items = sorted(self.process_folder(), key=itemgetter(0)) logger.trace(items) # type: ignore return items

c79175cbde5600bebd65785f3821fc74b3a80cbe

media.py

Alignments Tool updates - Copy info back to alignments file from faces

faceswap

tools/alignments/media.py

Python

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

encrypt_file

def encrypt_file(self, file, key=0): # precondition assert isinstance(file, str) and isinstance(key, int) try: with open(file, "r") as fin: with open("encrypt.out", "w+") as fout: # actual encrypt-process for line in fin: fout.write(self.encrypt_string(line, key)) except: return False return True

f0af0c43340763724f139fa68aa1e5a9ffe458b4

XOR_cipher.py

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

Python

XORcipher/XOR_cipher.py

Python

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

_get_next_prev

def _get_next_prev(generic_view, date, is_previous, period): date_field = generic_view.get_date_field() allow_empty = generic_view.get_allow_empty() allow_future = generic_view.get_allow_future() get_current = getattr(generic_view, "_get_current_%s" % period) get_next = getattr(generic_view, "_get_next_%s" % period) # Bounds of the current interval start, end = get_current(date), get_next(date) # If allow_empty is True, the naive result will be valid if allow_empty: if is_previous: result = get_current(start - datetime.timedelta(days=1)) else: result = end if allow_future or result <= timezone_today(): return result else: return None # Otherwise, we'll need to go to the database to look for an object # whose date_field is at least (greater than/less than) the given # naive result else: # Construct a lookup and an ordering depending on whether we're doing # a previous date or a next date lookup. if is_previous: lookup = {"%s__lt" % date_field: generic_view._make_date_lookup_arg(start)} ordering = "-%s" % date_field else: lookup = {"%s__gte" % date_field: generic_view._make_date_lookup_arg(end)} ordering = date_field # Filter out objects in the future if appropriate. if not allow_future: # Fortunately, to match the implementation of allow_future, # we need __lte, which doesn't conflict with __lt above. if generic_view.uses_datetime_field: now = timezone.now() else: now = timezone_today() lookup["%s__lte" % date_field] = now qs = generic_view.get_queryset().filter(**lookup).order_by(ordering) # Snag the first object from the queryset; if it doesn't exist that # means there's no next/previous link available. try: result = getattr(qs[0], date_field) except IndexError: return None # Convert datetimes to dates in the current time zone. if generic_view.uses_datetime_field: if settings.USE_TZ: result = timezone.localtime(result) result = result.date() # Return the first day of the period. return get_current(result)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

dates.py

Refs #33476 -- Reformatted code with Black.

django

django/views/generic/dates.py

Python

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

request_url

def request_url(self, request, proxies): proxy = select_proxy(request.url, proxies) scheme = urlparse(request.url).scheme is_proxied_http_request = proxy and scheme != "https" using_socks_proxy = False if proxy: proxy_scheme = urlparse(proxy).scheme.lower() using_socks_proxy = proxy_scheme.startswith("socks") url = request.path_url if is_proxied_http_request and not using_socks_proxy: url = urldefragauth(request.url) return url

cd5a9683be69c86c8f3adcd13385a9bc5db198ec

adapters.py

Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.

pipenv

pipenv/patched/pip/_vendor/requests/adapters.py

Python

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

cast_to_floatx

def cast_to_floatx(x): if isinstance(x, (tf.Tensor, tf.Variable, tf.SparseTensor)): return tf.cast(x, dtype=floatx()) return np.asarray(x, dtype=floatx()) @keras_export("keras.backend.get_uid")

84afc5193d38057e2e2badf9c889ea87d80d8fbf

@keras_export("keras.backend.get_uid")

backend.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/backend.py

Python

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

query

def query(self, table, columns=None, where=None, where_data=None, order_by=None, group_by=None, integration_name=None, integration_type=None): if table == 'predictors': return self._select_predictors() if table == 'datasources': return self._select_datasources() new_where = {} if where_data is None: for key, value in where_data.items(): if isinstance(value, dict) is False or len(value.keys()) != 1 or list(value.keys())[0] != '$eq': # TODO value should be just string or number raise Exception() new_where[key] = value['$eq'] if len(new_where) == 0: return [] where_data = [new_where] if isinstance(where_data, dict): where_data = [where_data] result = self.handler.predict(table, where_data) return result

b9ee4a5930e20a09350a3e0774283ba658a42da7

mindsdb_datanode.py

del code

mindsdb

mindsdb/api/mysql/mysql_proxy/datahub/datanodes/mindsdb_datanode.py

Python

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

mock_json_schema

def mock_json_schema(request, monkeypatch, tmp_path): # Do not patch integration tests if "integration" in request.keywords: return # Mock the subclasses list to make it very small, containing only mock nodes monkeypatch.setattr( haystack.nodes._json_schema, "find_subclasses_in_modules", lambda *a, **k: [(conftest, MockDocumentStore), (conftest, MockReader), (conftest, MockRetriever)], ) # Point the JSON schema path to tmp_path monkeypatch.setattr(haystack.pipelines.config, "JSON_SCHEMAS_PATH", tmp_path) # Generate mock schema in tmp_path filename = f"haystack-pipeline-unstable.schema.json" test_schema = _json_schema.get_json_schema(filename=filename, compatible_versions=["unstable"]) with open(tmp_path / filename, "w") as schema_file: json.dump(test_schema, schema_file, indent=4) # # Integration # @pytest.mark.integration @pytest.mark.elasticsearch

11cf94a9652a577732941f27ad59eb7c8bc5063e

@pytest.mark.integration @pytest.mark.elasticsearch

test_pipeline_yaml.py

Pipeline's YAML: syntax validation (#2226) * Add BasePipeline.validate_config, BasePipeline.validate_yaml, and some new custom exception classes * Make error composition work properly * Clarify typing * Help mypy a bit more * Update Documentation & Code Style * Enable autogenerated docs for Milvus1 and 2 separately * Revert "Enable autogenerated docs for Milvus1 and 2 separately" This reverts commit 282be4a78a6e95862a9b4c924fc3dea5ca71e28d. * Update Documentation & Code Style * Re-enable 'additionalProperties: False' * Add pipeline.type to JSON Schema, was somehow forgotten * Disable additionalProperties on the pipeline properties too * Fix json-schemas for 1.1.0 and 1.2.0 (should not do it again in the future) * Cal super in PipelineValidationError * Improve _read_pipeline_config_from_yaml's error handling * Fix generate_json_schema.py to include document stores * Fix json schemas (retro-fix 1.1.0 again) * Improve custom errors printing, add link to docs * Add function in BaseComponent to list its subclasses in a module * Make some document stores base classes abstract * Add marker 'integration' in pytest flags * Slighly improve validation of pipelines at load * Adding tests for YAML loading and validation * Make custom_query Optional for validation issues * Fix bug in _read_pipeline_config_from_yaml * Improve error handling in BasePipeline and Pipeline and add DAG check * Move json schema generation into haystack/nodes/_json_schema.py (useful for tests) * Simplify errors slightly * Add some YAML validation tests * Remove load_from_config from BasePipeline, it was never used anyway * Improve tests * Include json-schemas in package * Fix conftest imports * Make BasePipeline abstract * Improve mocking by making the test independent from the YAML version * Add exportable_to_yaml decorator to forget about set_config on mock nodes * Fix mypy errors * Comment out one monkeypatch * Fix typing again * Improve error message for validation * Add required properties to pipelines * Fix YAML version for REST API YAMLs to 1.2.0 * Fix load_from_yaml call in load_from_deepset_cloud * fix HaystackError.__getattr__ * Add super().__init__()in most nodes and docstore, comment set_config * Remove type from REST API pipelines * Remove useless init from doc2answers * Call super in Seq3SeqGenerator * Typo in deepsetcloud.py * Fix rest api indexing error mismatch and mock version of JSON schema in all tests * Working on pipeline tests * Improve errors printing slightly * Add back test_pipeline.yaml * _json_schema.py supports different versions with identical schemas * Add type to 0.7 schema for backwards compatibility * Fix small bug in _json_schema.py * Try alternative to generate json schemas on the CI * Update Documentation & Code Style * Make linux CI match autoformat CI * Fix super-init-not-called * Accidentally committed file * Update Documentation & Code Style * fix test_summarizer_translation.py's import * Mock YAML in a few suites, split and simplify test_pipeline_debug_and_validation.py::test_invalid_run_args * Fix json schema for ray tests too * Update Documentation & Code Style * Reintroduce validation * Usa unstable version in tests and rest api * Make unstable support the latest versions * Update Documentation & Code Style * Remove needless fixture * Make type in pipeline optional in the strings validation * Fix schemas * Fix string validation for pipeline type * Improve validate_config_strings * Remove type from test p[ipelines * Update Documentation & Code Style * Fix test_pipeline * Removing more type from pipelines * Temporary CI patc * Fix issue with exportable_to_yaml never invoking the wrapped init * rm stray file * pipeline tests are green again * Linux CI now needs .[all] to generate the schema * Bugfixes, pipeline tests seems to be green * Typo in version after merge * Implement missing methods in Weaviate * Trying to avoid FAISS tests from running in the Milvus1 test suite * Fix some stray test paths and faiss index dumping * Fix pytest markers list * Temporarily disable cache to be able to see tests failures * Fix pyproject.toml syntax * Use only tmp_path * Fix preprocessor signature after merge * Fix faiss bug * Fix Ray test * Fix documentation issue by removing quotes from faiss type * Update Documentation & Code Style * use document properly in preprocessor tests * Update Documentation & Code Style * make preprocessor capable of handling documents * import document * Revert support for documents in preprocessor, do later * Fix bug in _json_schema.py that was breaking validation * re-enable cache * Update Documentation & Code Style * Simplify calling _json_schema.py from the CI * Remove redundant ABC inheritance * Ensure exportable_to_yaml works only on implementations * Rename subclass to class_ in Meta * Make run() and get_config() abstract in BasePipeline * Revert unintended change in preprocessor * Move outgoing_edges_input_node check inside try block * Rename VALID_CODE_GEN_INPUT_REGEX into VALID_INPUT_REGEX * Add check for a RecursionError on validate_config_strings * Address usages of _pipeline_config in data silo and elasticsearch * Rename _pipeline_config into _init_parameters * Fix pytest marker and remove unused imports * Remove most redundant ABCs * Rename _init_parameters into _component_configuration * Remove set_config and type from _component_configuration's dict * Remove last instances of set_config and replace with super().__init__() * Implement __init_subclass__ approach * Simplify checks on the existence of _component_configuration * Fix faiss issue * Dynamic generation of node schemas & weed out old schemas * Add debatable test * Add docstring to debatable test * Positive diff between schemas implemented * Improve diff printing * Rename REST API YAML files to trigger IDE validation * Fix typing issues * Fix more typing * Typo in YAML filename * Remove needless type:ignore * Add tests * Fix tests & validation feedback for accessory classes in custom nodes * Refactor RAGeneratorType out * Fix broken import in conftest * Improve source error handling * Remove unused import in test_eval.py breaking tests * Fix changed error message in tests matches too * Normalize generate_openapi_specs.py and generate_json_schema.py in the actions * Fix path to generate_openapi_specs.py in autoformat.yml * Update Documentation & Code Style * Add test for FAISSDocumentStore-like situations (superclass with init params) * Update Documentation & Code Style * Fix indentation * Remove commented set_config * Store model_name_or_path in FARMReader to use in DistillationDataSilo * Rename _component_configuration into _component_config * Update Documentation & Code Style Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

haystack

test/test_pipeline_yaml.py

Python

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

_get_object_config

def _get_object_config(obj): if isinstance(obj, str): # Use the content of the string as the config for string. return obj elif isinstance(obj, types.FunctionType): # Keep track of the function's module and name in a dict as the config. return { 'module': obj.__module__, 'function_name': obj.__name__, } if not hasattr(obj, 'get_config'): raise TypeError(f'Unable to recognize the config of {obj}.') return obj.get_config()

e70d21c144503f560d8659fec0e08267e686a431

saving_lib.py

Keras saving: A prototype of config-based (idempotent) saving and loading. This shows an example of custom Model, Layer, Optimizer, and Loss, and adds test to confirm that the basic aforementioned elements work across this new saving and loading scheme. PiperOrigin-RevId: 447193044

keras

keras/saving/experimental/saving_lib.py

Python

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

_get

def _get(self, serialized_key): cur = self.connection.cursor() # should always be a single match, hence the [0] return list(cur.execute(f))[0][0]

0fd3b436c38f38bcae6fed9e14dc4d2a12e90793

storage_handler.py

fix tests and reformat

mindsdb

mindsdb/integrations/libs/storage_handler.py

Python

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

deal_duplicate_bb

def deal_duplicate_bb(thead_part): # 1. find out <td></td> in <thead></thead>. td_pattern = "<td rowspan=\"(\d)+\" colspan=\"(\d)+\">(.+?)</td>|" \ "<td colspan=\"(\d)+\" rowspan=\"(\d)+\">(.+?)</td>|" \ "<td rowspan=\"(\d)+\">(.+?)</td>|" \ "<td colspan=\"(\d)+\">(.+?)</td>|" \ "<td>(.*?)</td>" td_iter = re.finditer(td_pattern, thead_part) td_list = [t.group() for t in td_iter] # 2. is multiply <b></b> in <td></td> or not? new_td_list = [] for td_item in td_list: if td_item.count('<b>') > 1 or td_item.count('</b>') > 1: # multiply <b></b> in <td></td> case. # 1. remove all <b></b> td_item = td_item.replace('<b>', '').replace('</b>', '') # 2. replace <tb> -> <tb><b>, </tb> -> </b></tb>. td_item = td_item.replace('<td>', '<td><b>').replace('</td>', '</b></td>') new_td_list.append(td_item) else: new_td_list.append(td_item) # 3. replace original thead part. for td_item, new_td_item in zip(td_list, new_td_list): thead_part = thead_part.replace(td_item, new_td_item) return thead_part

ddaa2c2552e19635cd6cdf38619f1f176c358f89

table_master_match.py

add SLANet

PaddleOCR

ppstructure/table/table_master_match.py

Python

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

test_readback_tfrecords

def test_readback_tfrecords(ray_start_regular_shared, tmp_path): # The dataset we will write to a .tfrecords file. ds = ray.data.from_items( [ # Row one. { "int_item": 1, "int_list": [2, 2, 3], "float_item": 1.0, "float_list": [2.0, 3.0, 4.0], "bytes_item": b"abc", "bytes_list": [b"abc", b"1234"], }, # Row two. { "int_item": 2, "int_list": [3, 3, 4], "float_item": 2.0, "float_list": [2.0, 2.0, 3.0], "bytes_item": b"def", "bytes_list": [b"def", b"1234"], }, ] ) # Write the TFRecords. ds.write_tfrecords(tmp_path) # Read the TFRecords. readback_ds = ray.data.read_tfrecords(tmp_path) assert ds.take() == readback_ds.take()

9fab504fe776f96fecf85e12ea006264cbe92f4a

test_dataset_tfrecords.py

[Datasets] Add writer for TFRecords. (#29448) This PR enables users to write TFRecords from datasets. In particular, the master branch already includes an API for reading TFRecords from datasets. Users have requested the ability to write these datasets back to TFRecords.

ray

python/ray/data/tests/test_dataset_tfrecords.py

Python

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

test_uninstall_from_sentry

def test_uninstall_from_sentry(self): self.login_as(self.user) with self.tasks(): config_id = "my_config_id" responses.add( responses.DELETE, f"{VercelClient.base_url}{VercelClient.UNINSTALL % config_id}", json={}, ) path = ( f"/api/0/organizations/{self.organization.slug}/integrations/{self.integration.id}/" ) response = self.client.delete(path, format="json") assert response.status_code == 204 assert ( len( OrganizationIntegration.objects.filter( integration=self.integration, status=ObjectStatus.VISIBLE, ) ) == 1 ) response = self.client.delete( path=self.url, data=PRIMARY_UNINSTALL_RESPONSE, content_type="application/json", ) assert response.status_code == 204 integration = Integration.objects.get(id=self.integration.id) assert integration.metadata == { "access_token": "my_access_token2", "installation_id": "my_config_id2", "installation_type": "team", "webhook_id": "my_webhook_id2", "configurations": { "my_config_id2": { "access_token": "my_access_token2", "webhook_id": "my_webhook_id2", "organization_id": self.second_org.id, } }, } with self.tasks(): config_id = "my_config_id2" responses.add( responses.DELETE, f"{VercelClient.base_url}{VercelClient.UNINSTALL % config_id}", json={}, ) path = ( f"/api/0/organizations/{self.second_org.slug}/integrations/{self.integration.id}/" ) response = self.client.delete(path, format="json") assert response.status_code == 204 assert ( len( OrganizationIntegration.objects.filter( integration=self.integration, status=ObjectStatus.VISIBLE, ) ) == 0 ) response = self.client.delete( path=self.url, data=NONPRIMARY_UNINSTALL_RESPONSE, content_type="application/json", ) assert response.status_code == 204 assert not Integration.objects.filter(id=self.integration.id).exists()

8201e74ec3d81e89354905c946e62436f0247602

test_uninstall.py

ref(integrations): Update Vercel endpoints (#36150) This PR updates the endpoints we reach to in the Vercel integration. It seems to work just fine without changes as the payloads returned from vercel haven't updated, but we'll need to specify API Scopes so they don't receive 403s. This also refactored the pagination code to loop 100 at a time, indefinitely I had previously tried to consolidate the project webhooks in this PR, but I'll be doing that separately.

sentry

tests/sentry/integrations/vercel/test_uninstall.py

Python

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

check_connection

def check_connection(self) -> StatusResponse: response = StatusResponse(False) try: session = self.connect() # TODO: change the healthcheck session.execute('SELECT release_version FROM system.local').one() response.success = True except Exception as e: log.error(f'Error connecting to Scylla {self.connection_args["keyspace"]}, {e}!') response.error_message = e if response.success is False and self.is_connected is True: self.is_connected = False return response

f1fb699f88f8644d46afa9a2786a934510b05b79

scylla_handler.py

Impl handler

mindsdb

mindsdb/integrations/handlers/scylla_handler/scylla_handler.py

Python

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

downgrade

def downgrade(): conn = op.get_bind() if conn.dialect.name == "mysql": op.alter_column( table_name=TABLE_NAME, column_name=COLUMN_NAME, type_=mysql.TIMESTAMP(), nullable=False )

69f6f9e01b6df76c3c8fa266d460324163957887

a66efa278eea_add_precision_to_execution_date_in_mysql.py

Autogenerate migration reference doc (#21601) * document airflow version in each alembic migration module and use this to autogen the doc * update each migration module to have the same description used in migration ref (so it can be used in autogen)

airflow

airflow/migrations/versions/a66efa278eea_add_precision_to_execution_date_in_mysql.py

Python

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

setraw

def setraw(fd, when=termios.TCSAFLUSH): mode = termios.tcgetattr(fd) mode[tty.IFLAG] = mode[tty.IFLAG] & ~(termios.BRKINT | termios.ICRNL | termios.INPCK | termios.ISTRIP | termios.IXON) # mode[tty.OFLAG] = mode[tty.OFLAG] & ~(termios.OPOST) mode[tty.CFLAG] = mode[tty.CFLAG] & ~(termios.CSIZE | termios.PARENB) mode[tty.CFLAG] = mode[tty.CFLAG] | termios.CS8 mode[tty.LFLAG] = mode[tty.LFLAG] & ~(termios.ECHO | termios.ICANON | termios.IEXTEN | termios.ISIG) mode[tty.CC][termios.VMIN] = 1 mode[tty.CC][termios.VTIME] = 0 termios.tcsetattr(fd, when, mode)

5797d06aecb1ff620483f6c3ff4bd6d30356332f

pause.py

Use customized setraw to prevent output issues (#78060)

ansible

lib/ansible/plugins/action/pause.py

Python

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

get_student_attendance

def get_student_attendance(student_group, date): student_attendance = frappe.db.sql( , (student_group, date), as_dict=1, ) return student_attendance

494bd9ef78313436f0424b918f200dab8fc7c20b

student_batch_wise_attendance.py

style: format code with black

erpnext

erpnext/education/report/student_batch_wise_attendance/student_batch_wise_attendance.py

Python

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

test_legend_auto5

def test_legend_auto5(): fig, axs = plt.subplots(ncols=2, figsize=(9.6, 4.8)) leg_bboxes = [] for ax, loc in zip(axs.flat, ("center", "best")): # An Ellipse patch at the top, a U-shaped Polygon patch at the # bottom and a ring-like Wedge patch: the correct placement of # the legend should be in the center. for _patch in [ mpatches.Ellipse( xy=(0.5, 0.9), width=0.8, height=0.2, fc="C1"), mpatches.Polygon(np.array([ [0, 1], [0, 0], [1, 0], [1, 1], [0.9, 1.0], [0.9, 0.1], [0.1, 0.1], [0.1, 1.0], [0.1, 1.0]]), fc="C1"), mpatches.Wedge((0.5, 0.5), 0.5, 0, 360, width=0.05, fc="C0") ]: ax.add_patch(_patch) ax.plot([0.1, 0.9], [0.9, 0.9], label="A segment") # sthg to label leg = ax.legend(loc=loc) fig.canvas.draw() leg_bboxes.append( leg.get_window_extent().transformed(ax.transAxes.inverted())) assert_allclose(leg_bboxes[1].bounds, leg_bboxes[0].bounds) @image_comparison(['legend_various_labels'], remove_text=True)

d8bb1a52316c38434e526412c27d9c4b01960084

@image_comparison(['legend_various_labels'], remove_text=True)

test_legend.py

ENH: rely on non-rectangular patch paths rather than bboxes for legend auto-placing (fix #9580) (#9598) * use path rather than bbox for non rectangular patches * Add tests * Add a short breadcrumb note in api_changes

matplotlib

lib/matplotlib/tests/test_legend.py

Python

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

sort_accounts

def sort_accounts(accounts, is_root=False, key="name"): def compare_accounts(a, b): if re.split(r"\W+", a[key])[0].isdigit(): # if chart of accounts is numbered, then sort by number return int(a[key] > b[key]) - int(a[key] < b[key]) elif is_root: if a.report_type != b.report_type and a.report_type == "Balance Sheet": return -1 if a.root_type != b.root_type and a.root_type == "Asset": return -1 if a.root_type == "Liability" and b.root_type == "Equity": return -1 if a.root_type == "Income" and b.root_type == "Expense": return -1 else: # sort by key (number) or name return int(a[key] > b[key]) - int(a[key] < b[key]) return 1 accounts.sort(key=functools.cmp_to_key(compare_accounts))

494bd9ef78313436f0424b918f200dab8fc7c20b

financial_statements.py

style: format code with black

erpnext

erpnext/accounts/report/financial_statements.py

Python

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

look_at

def look_at(eye, center, world_up): batch_size = center.shape[0] vector_degeneracy_cutoff = 1e-6 forward = center - eye forward_norm = np.linalg.norm(forward, axis=1, keepdims=True) forward = np.divide(forward, forward_norm) to_side = np.cross(forward, world_up) to_side_norm = np.linalg.norm(to_side, axis=1, keepdims=True) to_side = np.divide(to_side, to_side_norm) cam_up = np.cross(to_side, forward) w_column = np.array( batch_size * [[0., 0., 0., 1.]], dtype=np.float32) # [batch_size, 4] w_column = np.reshape(w_column, [batch_size, 4, 1]) view_rotation = np.stack( [to_side, cam_up, -forward, np.zeros_like(to_side, dtype=np.float32)], axis=1) # [batch_size, 4, 3] matrix view_rotation = np.concatenate( [view_rotation, w_column], axis=2) # [batch_size, 4, 4] identity_batch = np.tile(np.expand_dims(np.eye(3), 0), [batch_size, 1, 1]) view_translation = np.concatenate([identity_batch, np.expand_dims(-eye, 2)], 2) view_translation = np.concatenate( [view_translation, np.reshape(w_column, [batch_size, 1, 4])], 1) camera_matrices = np.matmul(view_rotation, view_translation) return camera_matrices

7375ee364e0df2a417f92593e09557f1b2a3575a

ganfit_camera.py

initialize ostec

insightface

reconstruction/ostec/utils/ganfit_camera.py

Python

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

on_train_batch_end

def on_train_batch_end(self, batch, logs=None): # For backwards compatibility. self.on_batch_end(batch, logs=logs)

f3cafc77c269f7ecbf80bb4cf4b54e28c153f4e6

callbacks.py

resolve line-too-long in root directory

keras

keras/callbacks.py

Python

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

pop_up

def pop_up(self, text='', move=True): self.edit.setText(text) self.edit.setSelection(0, len(text)) self.edit.setFocus(Qt.PopupFocusReason) if move: cursor_pos = QCursor.pos() # move OK button below cursor btn = self.button_box.buttons()[0] self.adjustSize() btn.adjustSize() offset = btn.mapToGlobal(btn.pos()) - self.pos() offset += QPoint(btn.size().width()/4, btn.size().height()/2) cursor_pos.setX(max(0, cursor_pos.x() - offset.x())) cursor_pos.setY(max(0, cursor_pos.y() - offset.y())) parent_bottom_right = self.parentWidget().geometry() max_x = parent_bottom_right.x() + parent_bottom_right.width() - self.sizeHint().width() max_y = parent_bottom_right.y() + parent_bottom_right.height() - self.sizeHint().height() max_global = self.parentWidget().mapToGlobal(QPoint(max_x, max_y)) if cursor_pos.x() > max_global.x(): cursor_pos.setX(max_global.x()) if cursor_pos.y() > max_global.y(): cursor_pos.setY(max_global.y()) self.move(cursor_pos) return trimmed(self.edit.text()) if self.exec_() else None

0c377fc2588ad0f57b3060c26f2d4f891c68276f

labelDialog.py

move "OK" button below cursor when opening label dialog (#893) The intent for this change is to allow faster labeling when there are streaks of the same label occasionally, but not consistently enough to enable "default label" mode. With this PR the user can simply click again to confirm the previous selection, without having to aim for the OK button, or move either hand to the ENTER button. The alignment and position change of the buttons is for two reasons: - it covers less of the drawn shape, easing verification of the label to be selected - the alignment wasn't taken into account for offset calculation. It works if the dialog is shown, but that causes the dialog to briefly flicker in the old position. Presumably an `adjustSize` or similar is needed on more widgets, but I was unable to figure out which.

labelImg

libs/labelDialog.py

Python

https://github.com/heartexlabs/labelImg.git

create_pseudo_labeled_data

def create_pseudo_labeled_data(args, infer_input, infer_output, eval_result, id2label, next_data_dir): dataset = datasets.concatenate_datasets([infer_input, infer_output], axis=1) if args.do_filter_by_confidence: dataset = dataset.filter(lambda example: example["probability"] > args.confidence_threshold) if args.do_filter_by_val_performance: assert eval_result >= 0.0 and eval_result <= 1.0 num_selected_rows = int(eval_result * len(dataset)) print(num_selected_rows) dataset = dataset.sort("probability", reverse=True) dataset = dataset.select(range(num_selected_rows)) dataset = dataset.remove_columns(["label", "probability"]) dataset = dataset.rename_column("prediction", "label") dataset = dataset.map(lambda example: {"label": id2label[example["label"]]}) dataset = dataset.shuffle(seed=args.seed) pseudo_labeled_data_file = os.path.join(next_data_dir, f"train_pseudo.{args.data_file_extension}") if args.data_file_extension == "csv": dataset.to_csv(pseudo_labeled_data_file, index=False) else: dataset.to_json(pseudo_labeled_data_file)

34ef029dc04bb94b4e280e02ef3e82dacf1b9dfc

selftraining.py

Add self training code for text classification (#16738) * Add self-training code for text-classification * Add self-training code for text-classification * Add self-training code for text-classification * Add self-training code for text-classification * Add self-training code for text-classification * Delete strata

transformers

examples/research_projects/self-training-text-classification/selftraining.py

Python

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

jacobi_symbol

def jacobi_symbol(m, n): r m, n = as_int(m), as_int(n) if n < 0 or not n % 2: raise ValueError("n should be an odd positive integer") if m < 0 or m > n: m %= n if not m: return int(n == 1) if n == 1 or m == 1: return 1 if igcd(m, n) != 1: return 0 j = 1 while m != 0: while m % 2 == 0 and m > 0: m >>= 1 if n % 8 in [3, 5]: j = -j m, n = n, m if m % 4 == n % 4 == 3: j = -j m %= n return j

d7614cda8f6b341df8515c65244a415b0bf2fc6f

residue_ntheory.py

jacobi_symbol: remove dead code paths Fixes #23443 The first part of the code was never reached `m %= n` The later `n != 1` condition never matched either since the gcd calculation prevented that from ever happening. ```python if igcd(m, n) != 1: return 0 ``` https://en.wikipedia.org/wiki/Jacobi_symbol#Implementation_in_Lua

sympy

sympy/ntheory/residue_ntheory.py

Python

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

_topk

def _topk(self, scores): k = self.max_per_img shape_fm = paddle.shape(scores) shape_fm.stop_gradient = True cat, height, width = shape_fm[1], shape_fm[2], shape_fm[3] # batch size is 1 scores_r = paddle.reshape(scores, [cat, -1]) topk_scores, topk_inds = paddle.topk(scores_r, k) topk_ys = topk_inds // width topk_xs = topk_inds % width topk_score_r = paddle.reshape(topk_scores, [-1]) topk_score, topk_ind = paddle.topk(topk_score_r, k) k_t = paddle.full(paddle.shape(topk_ind), k, dtype='int64') topk_clses = paddle.cast(paddle.floor_divide(topk_ind, k_t), 'float32') topk_inds = paddle.reshape(topk_inds, [-1]) topk_ys = paddle.reshape(topk_ys, [-1, 1]) topk_xs = paddle.reshape(topk_xs, [-1, 1]) topk_inds = paddle.gather(topk_inds, topk_ind) topk_ys = paddle.gather(topk_ys, topk_ind) topk_xs = paddle.gather(topk_xs, topk_ind) return topk_score, topk_inds, topk_clses, topk_ys, topk_xs

5e02a81af77a9a4ecd1e394430c4396b48bc76fd

layers.py

remove one line redundant code (#6424)

PaddleDetection

ppdet/modeling/layers.py

Python

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

latitude

def latitude(self) -> float | None: if ( self.extra_state_attributes is not None and ATTR_LATITUDE in self.extra_state_attributes ): latitude: float = self.extra_state_attributes[ATTR_LATITUDE] return latitude return None

bcae6d604e2967c7475f0caa4b1b5e4e76ab88bf

schema_discovery.py

Improve MQTT type hints part 8 (#81034) * Improve typing device_tracker discovery * Improve typing device_tracker yaml * Add test source_type attribute * Follow up comment * Initialize at `__init__` not at class level. * Use full name for return variable * Correct import, remove assert * Use AsyncSeeCallback

core

homeassistant/components/mqtt/device_tracker/schema_discovery.py

Python

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

test_false_values_displayed

def test_false_values_displayed(self): response = self.get(4) self.assertContains(response, "<dd>False</dd>", count=3, html=True)

d10f15e55806c6944827d801cd9c2d53f5da4186

test_page_modeladmin.py

Reformat with black

wagtail

wagtail/contrib/modeladmin/tests/test_page_modeladmin.py

Python

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

call

def call(self, inputs, **kwargs): # pylint:disable=unused-argument # Compute the axes along which to reduce the mean / variance input_shape = K.int_shape(inputs) layer_size = input_shape[self.axis] if self.partial in (0.0, 1.0): mean_square = K.mean(K.square(inputs), axis=self.axis, keepdims=True) else: partial_size = int(layer_size * self.partial) partial_x, _ = tf.split( # pylint:disable=redundant-keyword-arg,no-value-for-parameter inputs, [partial_size, layer_size - partial_size], axis=self.axis) mean_square = K.mean(K.square(partial_x), axis=self.axis, keepdims=True) recip_square_root = tf.math.rsqrt(mean_square + self.epsilon) output = self.scale * inputs * recip_square_root + self.offset return output

c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf

normalization_tf.py

Update code to support Tensorflow versions up to 2.8 (#1213) * Update maximum tf version in setup + requirements * - bump max version of tf version in launcher - standardise tf version check * update keras get_custom_objects for tf>2.6 * bugfix: force black text in GUI file dialogs (linux) * dssim loss - Move to stock tf.ssim function * Update optimizer imports for compatibility * fix logging for tf2.8 * Fix GUI graphing for TF2.8 * update tests * bump requirements.txt versions * Remove limit on nvidia-ml-py * Graphing bugfixes - Prevent live graph from displaying if data not yet available * bugfix: Live graph. Collect loss labels correctly * fix: live graph - swallow inconsistent loss errors * Bugfix: Prevent live graph from clearing during training * Fix graphing for AMD

faceswap

lib/model/normalization/normalization_tf.py

Python

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

test_to_python

def test_to_python(self): table = self.block.to_python(self.db_data) self.assertIsInstance(table, TypedTable) self.assertEqual(len(table.columns), 2) self.assertEqual(table.columns[0]["heading"], "Country") self.assertEqual(table.columns[1]["heading"], "Description") rows = list(table.rows) self.assertEqual(len(rows), 2) self.assertEqual( [block.value for block in rows[0]], ["nl", "A small country with stroopwafels"], ) self.assertEqual( [block.value for block in rows[1]], ["fr", "A large country with baguettes"] )

d10f15e55806c6944827d801cd9c2d53f5da4186

tests.py

Reformat with black

wagtail

wagtail/contrib/typed_table_block/tests.py

Python

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

_format_maybe_minus_and_locale

def _format_maybe_minus_and_locale(self, fmt, arg): return self.fix_minus(locale.format_string(fmt, (arg,), True) if self._useLocale else fmt % arg)

88cb4c9d0aa1e790fc4689ca7e68725bf851bf63

ticker.py

Properly capitalize "Unicode". See e.g. https://en.wikipedia.org/wiki/Unicode, https://docs.python.org/3/howto/unicode.html. Also associated minor doc cleanups.

matplotlib

lib/matplotlib/ticker.py

Python

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

create_session

def create_session(self, loop): session = ClientSession(loop=loop, json_serialize=json_dumps) # Setting directly on `session` will raise deprecation warning object.__setattr__(session, "_request", self.match_request) return session

da027fa3905d36b91beefd456cb546f891617eab

aiohttp.py

JSON serialize NamedTuple subclasses with aiohttp (#74971)

core

tests/test_util/aiohttp.py

Python

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

last

def last(self): for obj in (self.reverse() if self.ordered else self.order_by("-pk"))[:1]: return obj

9c19aff7c7561e3a82978a272ecdaad40dda5c00

query.py

Refs #33476 -- Reformatted code with Black.

django

django/db/models/query.py

Python

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

create_view

def create_view(self, request): kwargs = {"model_admin": self} view_class = self.create_view_class return view_class.as_view(**kwargs)(request)

d10f15e55806c6944827d801cd9c2d53f5da4186

options.py

Reformat with black

wagtail

wagtail/contrib/modeladmin/options.py

Python

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

_create_index

def _create_index(instance, table_name, index_name): table = Table(table_name, Base.metadata) _LOGGER.debug("Looking up index %s for table %s", index_name, table_name) # Look up the index object by name from the table is the models index_list = [idx for idx in table.indexes if idx.name == index_name] if not index_list: _LOGGER.debug("The index %s no longer exists", index_name) return index = index_list[0] _LOGGER.debug("Creating %s index", index_name) _LOGGER.warning( "Adding index `%s` to database. Note: this can take several " "minutes on large databases and slow computers. Please " "be patient!", index_name, ) try: with session_scope(session=instance.get_session()) as session: connection = session.connection() index.create(connection) except (InternalError, ProgrammingError, OperationalError) as err: raise_if_exception_missing_str(err, ["already exists", "duplicate"]) _LOGGER.warning( "Index %s already exists on %s, continuing", index_name, table_name ) _LOGGER.debug("Finished creating %s", index_name)

41ab12cb88741807a246bb296762d7c683a30b58

migration.py

Don't use shared session during recorder migration (#65672)

core

homeassistant/components/recorder/migration.py

Python

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

squeeze

def squeeze(self, axis=None): axis = range(self._AXIS_LEN) if axis is None else (self._get_axis_number(axis),) return self.iloc[ tuple( 0 if i in axis and len(a) == 1 else slice(None) for i, a in enumerate(self.axes) ) ] # ---------------------------------------------------------------------- # Rename

244f747bb63f45c1c439193f0672c6162853b168

generic.py

make series axis parameter docs consistent (#47109) * make series docs consistent add series unused param info to DF docs * fix trailing whitespace * fix docs build * add unused * add or update docs for all series methods * small fix * fix line length * fix param order * fix param order * add * add backticks to None and fix space Co-authored-by: uncjackg <[email protected]>

pandas

pandas/core/generic.py

Python

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

filename

def filename(self): if self.buildver: buildver = '-' + self.buildver else: buildver = '' pyver = '.'.join(self.pyver) abi = '.'.join(self.abi) arch = '.'.join(self.arch) # replace - with _ as a local version separator version = self.version.replace('-', '_') return '%s-%s%s-%s-%s-%s.whl' % (self.name, version, buildver, pyver, abi, arch)

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

wheel.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_vendor/distlib/wheel.py

Python

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

async_internal_added_to_hass

async def async_internal_added_to_hass(self) -> None: await super().async_internal_added_to_hass() state = await self.async_get_last_state() if state is not None and state.attributes.get(ATTR_SKIPPED_VERSION) is not None: self.__skipped_version = state.attributes[ATTR_SKIPPED_VERSION]

073fb40b79cf8aa06790fdceb23b6857db888c99

__init__.py

Add update entity platform (#68248) Co-authored-by: Glenn Waters <[email protected]>

core

homeassistant/components/update/__init__.py

Python

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

generate_export_pipeline_code

def generate_export_pipeline_code(pipeline_tree, operators): steps = _process_operator(pipeline_tree, operators) # number of steps in a pipeline num_step = len(steps) if num_step > 1: pipeline_text = "make_pipeline(\n{STEPS}\n)".format( STEPS=_indent(",\n".join(steps), 4) ) # only one operator (root = True) else: pipeline_text = "{STEPS}".format(STEPS=_indent(",\n".join(steps), 0)) return pipeline_text

388616b6247ca4ea8de4e2f340d6206aee523541

export_utils.py

Revert "Deployed 7ccda9a with MkDocs version: 1.3.0" This reverts commit bd9629c40e01241766197119b581a99409b07068.

tpot

tpot/export_utils.py

Python

https://github.com/EpistasisLab/tpot.git

OutputString

def OutputString(self, attrs=None): # Build up our result # result = [] append = result.append # First, the key=value pair append("%s=%s" % (self.key, self.coded_value)) # Now add any defined attributes if attrs is None: attrs = self._reserved items = sorted(self.items()) for key, value in items: if value == "": continue if key not in attrs: continue if key == "expires" and isinstance(value, int): append("%s=%s" % (self._reserved[key], _getdate(value))) elif key == "max-age" and isinstance(value, int): append("%s=%d" % (self._reserved[key], value)) elif key == "comment" and isinstance(value, str): append("%s=%s" % (self._reserved[key], _quote(value))) elif key in self._flags: if value: append(str(self._reserved[key])) else: append("%s=%s" % (self._reserved[key], value)) # Return the result return _semispacejoin(result) __class_getitem__ = classmethod(types.GenericAlias) # # Pattern for finding cookie # # This used to be strict parsing based on the RFC2109 and RFC2068 # specifications. I have since discovered that MSIE 3.0x doesn't # follow the character rules outlined in those specs. As a # result, the parsing rules here are less strict. # _LegalKeyChars = r"\w\d!#%&'~_`><@,:/\$\*\+\-\.\^\|\)\(\?\}\{\=" _LegalValueChars = _LegalKeyChars + r'\[\]' _CookiePattern = re.compile(r + _LegalKeyChars + r + _LegalValueChars + r, re.ASCII | re.VERBOSE) # re.ASCII may be removed if safe. # At long last, here is the cookie class. Using this class is almost just like # using a dictionary. See this module's docstring for example usage. #

8198943edd73a363c266633e1aa5b2a9e9c9f526

cookies.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/http/cookies.py

Python

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

validate_cycler

def validate_cycler(s): if isinstance(s, str): # TODO: We might want to rethink this... # While I think I have it quite locked down, it is execution of # arbitrary code without sanitation. # Combine this with the possibility that rcparams might come from the # internet (future plans), this could be downright dangerous. # I locked it down by only having the 'cycler()' function available. # UPDATE: Partly plugging a security hole. # I really should have read this: # https://nedbatchelder.com/blog/201206/eval_really_is_dangerous.html # We should replace this eval with a combo of PyParsing and # ast.literal_eval() try: _DunderChecker().visit(ast.parse(s)) s = eval(s, {'cycler': cycler, '__builtins__': {}}) except BaseException as e: raise ValueError(f"{s!r} is not a valid cycler construction: {e}" ) from e # Should make sure what comes from the above eval() # is a Cycler object. if isinstance(s, Cycler): cycler_inst = s else: raise ValueError(f"Object is not a string or Cycler instance: {s!r}") unknowns = cycler_inst.keys - (set(_prop_validators) | set(_prop_aliases)) if unknowns: raise ValueError("Unknown artist properties: %s" % unknowns) # Not a full validation, but it'll at least normalize property names # A fuller validation would require v0.10 of cycler. checker = set() for prop in cycler_inst.keys: norm_prop = _prop_aliases.get(prop, prop) if norm_prop != prop and norm_prop in cycler_inst.keys: raise ValueError(f"Cannot specify both {norm_prop!r} and alias " f"{prop!r} in the same prop_cycle") if norm_prop in checker: raise ValueError(f"Another property was already aliased to " f"{norm_prop!r}. Collision normalizing {prop!r}.") checker.update([norm_prop]) # This is just an extra-careful check, just in case there is some # edge-case I haven't thought of. assert len(checker) == len(cycler_inst.keys) # Now, it should be safe to mutate this cycler for prop in cycler_inst.keys: norm_prop = _prop_aliases.get(prop, prop) cycler_inst.change_key(prop, norm_prop) for key, vals in cycler_inst.by_key().items(): _prop_validators[key](vals) return cycler_inst

22a44db48c1b7659837092c5b01a59eb1d004fc6

rcsetup.py

Use repr in error messages

matplotlib

lib/matplotlib/rcsetup.py

Python

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

addslashes

def addslashes(value): return value.replace("\\", "\\\\").replace('"', '\\"').replace("'", "\\'") @register.filter(is_safe=True) @stringfilter

9c19aff7c7561e3a82978a272ecdaad40dda5c00

@register.filter(is_safe=True) @stringfilter

defaultfilters.py

Refs #33476 -- Reformatted code with Black.

django

django/template/defaultfilters.py

Python

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

get_data

def get_data(filters): lead_details = [] lead_filters = get_lead_filters(filters) for lead in frappe.get_all( "Lead", fields=["name", "lead_name", "company_name"], filters=lead_filters ): data = frappe.db.sql( , {"lead": lead.name, "limit": filters.get("no_of_interaction")}, ) for lead_info in data: lead_data = [lead.name, lead.lead_name, lead.company_name] + list(lead_info) lead_details.append(lead_data) return lead_details

494bd9ef78313436f0424b918f200dab8fc7c20b

prospects_engaged_but_not_converted.py

style: format code with black

erpnext

erpnext/crm/report/prospects_engaged_but_not_converted/prospects_engaged_but_not_converted.py

Python

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

choose

def choose(self, choices): from dask.array.routines import choose return choose(self, choices)

2820bae493a49cb1d0a6e376985c5473b8f04fa8

core.py

Don't include docs in ``Array`` methods, just refer to module docs (#9244) Co-authored-by: James Bourbeau <[email protected]>

dask

dask/array/core.py

Python

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

newer

def newer(self, source, target): if not os.path.exists(source): raise DistlibException("file '%r' does not exist" % os.path.abspath(source)) if not os.path.exists(target): return True return os.stat(source).st_mtime > os.stat(target).st_mtime

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

util.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_vendor/distlib/util.py

Python

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

filldedent

def filldedent(s, w=70, **kwargs): return '\n' + fill(dedent(str(s)).strip('\n'), width=w, **kwargs)

2047f4855577845b1b99e0926b887d313725a6e7

misc.py

Pass keyword arguments to filldedent() through to fill()

sympy

sympy/utilities/misc.py

Python

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

test_regex

def test_regex(self) -> None: # Some of the undocumented endpoints which are very similar to # some of the documented endpoints. assert find_openapi_endpoint("/users/me/presence") is None assert find_openapi_endpoint("/users/me/subscriptions/23") is None assert find_openapi_endpoint("/users/iago/subscriptions/23") is None assert find_openapi_endpoint("/messages/matches_narrow") is None # Making sure documented endpoints are matched correctly. assert ( find_openapi_endpoint("/users/23/subscriptions/21") == "/users/{user_id}/subscriptions/{stream_id}" ) assert ( find_openapi_endpoint("/users/[email protected]/presence") == "/users/{user_id_or_email}/presence" ) assert find_openapi_endpoint("/users/[email protected]") == "/users/{email}" assert find_openapi_endpoint("/messages/23") == "/messages/{message_id}" assert find_openapi_endpoint("/realm/emoji/realm_emoji_1") == "/realm/emoji/{emoji_name}"

b0ce4f1bce8031881addecb1e86073483517f392

test_openapi.py

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

zulip

zerver/tests/test_openapi.py

Python

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

compare_total

def compare_total(self, other, context=None): other = _convert_other(other, raiseit=True) # if one is negative and the other is positive, it's easy if self._sign and not other._sign: return _NegativeOne if not self._sign and other._sign: return _One sign = self._sign # let's handle both NaN types self_nan = self._isnan() other_nan = other._isnan() if self_nan or other_nan: if self_nan == other_nan: # compare payloads as though they're integers self_key = len(self._int), self._int other_key = len(other._int), other._int if self_key < other_key: if sign: return _One else: return _NegativeOne if self_key > other_key: if sign: return _NegativeOne else: return _One return _Zero if sign: if self_nan == 1: return _NegativeOne if other_nan == 1: return _One if self_nan == 2: return _NegativeOne if other_nan == 2: return _One else: if self_nan == 1: return _One if other_nan == 1: return _NegativeOne if self_nan == 2: return _One if other_nan == 2: return _NegativeOne if self < other: return _NegativeOne if self > other: return _One if self._exp < other._exp: if sign: return _One else: return _NegativeOne if self._exp > other._exp: if sign: return _NegativeOne else: return _One return _Zero

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pydecimal.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/_pydecimal.py

Python

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

_override_cmds

def _override_cmds(self) -> None: self.options.version_cmd[0] = self.options.ctl self.options.restart_cmd[0] = self.options.ctl self.options.conftest_cmd[0] = self.options.ctl self.options.get_modules_cmd[0] = self.options.ctl self.options.get_includes_cmd[0] = self.options.ctl self.options.get_defines_cmd[0] = self.options.ctl

eed1afb8082518a5212a6d8016a4ccf44c5ad99e

configurator.py

certbot-apache: use httpd by default for CentOS/RHEL (#9402) * certbot-apache: use httpd for newer RHEL derived distros A change in RHEL 9 is causing apachectl to error out when used with additional arguments, resulting in certbot errors. The CentOS configurator now uses httpd instead for RHEL 9 (and later) derived distros. * Single CentOS class which uses the apache_bin option * soothe mypy * Always call super()._override_cmds()

certbot

certbot-apache/certbot_apache/_internal/configurator.py

Python

https://github.com/certbot/certbot.git

_get_files

def _get_files(self, files): # Older versions of fsspec doesn't support unstrip_protocol(). It # was only added relatively recently: # https://github.com/fsspec/filesystem_spec/pull/828

b240370bf83c88589d293b76b4a2409294e06f90

parquet_dispatcher.py

FEAT-#4733: Support fastparquet as engine for `read_parquet` (#4807) Signed-off-by: Karthik Velayutham <[email protected]>

modin

modin/core/io/column_stores/parquet_dispatcher.py

Python

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

get_wheel_cache_entry

def get_wheel_cache_entry(self, link, name): # type: (Link, Optional[str]) -> Optional[CacheEntry] if self._wheel_cache is None or self.preparer.require_hashes: return None return self._wheel_cache.get_cache_entry( link=link, package_name=name, supported_tags=get_supported(), )

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

factory.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/factory.py

Python

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

broadcast

async def broadcast(self, data): for channel in self.channels.values(): await channel.send(data)

9f6bba40af1a407f190a89f5c0c8b4e3f528ba46

channel.py

initial concept for replicate, basic leader and follower logic

freqtrade

freqtrade/rpc/replicate/channel.py

Python

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

_set_concurrent_future_state

def _set_concurrent_future_state(concurrent, source): assert source.done() if source.cancelled(): concurrent.cancel() if not concurrent.set_running_or_notify_cancel(): return exception = source.exception() if exception is not None: concurrent.set_exception(_convert_future_exc(exception)) else: result = source.result() concurrent.set_result(result)

8198943edd73a363c266633e1aa5b2a9e9c9f526

futures.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/asyncio/futures.py

Python

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

test_repeated_paginate_relations

def test_repeated_paginate_relations(self): expected_event_ids = [] for idx in range(10): channel = self._send_relation( RelationTypes.ANNOTATION, "m.reaction", chr(ord("a") + idx) ) self.assertEquals(200, channel.code, channel.json_body) expected_event_ids.append(channel.json_body["event_id"]) prev_token = "" found_event_ids: List[str] = [] for _ in range(20): from_token = "" if prev_token: from_token = "&from=" + prev_token channel = self.make_request( "GET", f"/_matrix/client/unstable/rooms/{self.room}/relations/{self.parent_id}?limit=1{from_token}", access_token=self.user_token, ) self.assertEquals(200, channel.code, channel.json_body) found_event_ids.extend(e["event_id"] for e in channel.json_body["chunk"]) next_batch = channel.json_body.get("next_batch") self.assertNotEquals(prev_token, next_batch) prev_token = next_batch if not prev_token: break # We paginated backwards, so reverse found_event_ids.reverse() self.assertEquals(found_event_ids, expected_event_ids) # Reset and try again, but convert the tokens to the legacy format. prev_token = "" found_event_ids = [] for _ in range(20): from_token = "" if prev_token: from_token = "&from=" + self._stream_token_to_relation_token(prev_token) channel = self.make_request( "GET", f"/_matrix/client/unstable/rooms/{self.room}/relations/{self.parent_id}?limit=1{from_token}", access_token=self.user_token, ) self.assertEquals(200, channel.code, channel.json_body) found_event_ids.extend(e["event_id"] for e in channel.json_body["chunk"]) next_batch = channel.json_body.get("next_batch") self.assertNotEquals(prev_token, next_batch) prev_token = next_batch if not prev_token: break # We paginated backwards, so reverse found_event_ids.reverse() self.assertEquals(found_event_ids, expected_event_ids)

df36945ff0e4a293a9dac0da07e2c94256835b32

test_relations.py

Support pagination tokens from /sync and /messages in the relations API. (#11952)

synapse

tests/rest/client/test_relations.py

Python

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

_delete_composed_index

def _delete_composed_index(self, model, fields, *args): first_field = model._meta.get_field(fields[0]) if first_field.get_internal_type() == "ForeignKey": constraint_names = self._constraint_names( model, [first_field.column], index=True ) if not constraint_names: self.execute( self._create_index_sql(model, fields=[first_field], suffix="") ) return super()._delete_composed_index(model, fields, *args)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

schema.py

Refs #33476 -- Reformatted code with Black.

django

django/db/backends/mysql/schema.py

Python

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

climate_adc_t3000_missing_fan_mode_states_fixture

def climate_adc_t3000_missing_fan_mode_states_fixture(client, climate_adc_t3000_state): data = copy.deepcopy(climate_adc_t3000_state) data["name"] = f"{data['name']} missing fan mode states" for value in data["values"]: if ( value["commandClassName"] == "Thermostat Fan Mode" and value["property"] == "mode" ): del value["metadata"]["states"] node = Node(client, data) client.driver.controller.nodes[node.node_id] = node return node @pytest.fixture(name="climate_danfoss_lc_13")

21aa07e3e58268d6ca1425cd05abcfd847b9872c

@pytest.fixture(name="climate_danfoss_lc_13")

conftest.py

Add Z-Wave thermostat fan entity (#65865) * Add Z-Wave thermostat fan entity * Fix failing test, increase number of entities to 27 * Add tests to improve coverage * Take back unrelated changes to climate.py * Clean up guard clauses, use info.primary_value, and make entity disabled by default * Fix tests * Add more tests for code coverage * Remove unused const * Remove speed parameter from overridden method since it was removed from entity * Address PR comments

core

tests/components/zwave_js/conftest.py

Python

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

get_basefile

def get_basefile(self, tex, fontsize, dpi=None): src = self._get_tex_source(tex, fontsize) + str(dpi) return os.path.join( self.texcache, hashlib.md5(src.encode('utf-8')).hexdigest())

4ea309aac5b6b638967d19107db297b5c7bde551

texmanager.py

Pick TeX cache name based on entire TeX source. This allows invalidating the cache when the source generation algorithm changes.

matplotlib

lib/matplotlib/texmanager.py

Python

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

get_dict_for_field

def get_dict_for_field(self, field_name): try: field = self.model._meta.get_field(field_name) except FieldDoesNotExist: field = None return { "label": self.get_field_label(field_name, field), "value": self.get_field_display_value(field_name, field), }

d10f15e55806c6944827d801cd9c2d53f5da4186

views.py

Reformat with black

wagtail

wagtail/contrib/modeladmin/views.py

Python

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

_upsample_2d

def _upsample_2d(self, hidden_states, weight=None, kernel=None, factor=2, gain=1): assert isinstance(factor, int) and factor >= 1 # Setup filter kernel. if kernel is None: kernel = [1] * factor # setup kernel kernel = torch.tensor(kernel, dtype=torch.float32) if kernel.ndim == 1: kernel = torch.outer(kernel, kernel) kernel /= torch.sum(kernel) kernel = kernel * (gain * (factor**2)) if self.use_conv: convH = weight.shape[2] convW = weight.shape[3] inC = weight.shape[1] pad_value = (kernel.shape[0] - factor) - (convW - 1) stride = (factor, factor) # Determine data dimensions. output_shape = ( (hidden_states.shape[2] - 1) * factor + convH, (hidden_states.shape[3] - 1) * factor + convW, ) output_padding = ( output_shape[0] - (hidden_states.shape[2] - 1) * stride[0] - convH, output_shape[1] - (hidden_states.shape[3] - 1) * stride[1] - convW, ) assert output_padding[0] >= 0 and output_padding[1] >= 0 num_groups = hidden_states.shape[1] // inC # Transpose weights. weight = torch.reshape(weight, (num_groups, -1, inC, convH, convW)) weight = torch.flip(weight, dims=[3, 4]).permute(0, 2, 1, 3, 4) weight = torch.reshape(weight, (num_groups * inC, -1, convH, convW)) inverse_conv = F.conv_transpose2d( hidden_states, weight, stride=stride, output_padding=output_padding, padding=0 ) output = upfirdn2d_native( inverse_conv, torch.tensor(kernel, device=inverse_conv.device), pad=((pad_value + 1) // 2 + factor - 1, pad_value // 2 + 1), ) else: pad_value = kernel.shape[0] - factor output = upfirdn2d_native( hidden_states, torch.tensor(kernel, device=hidden_states.device), up=factor, pad=((pad_value + 1) // 2 + factor - 1, pad_value // 2), ) return output

a73f8b725105b12a60a9b22918bda68f8b6d26c3

resnet.py

Clean up resnet.py file (#780) * clean up resnet.py * make style and quality * minor formatting

diffusers

src/diffusers/models/resnet.py

Python

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

_update_lines

def _update_lines(self, lines, new_line): code_matches = [x for x in re.finditer(_invisible_codes, new_line)] color_codes = [ code.string[code.span()[0] : code.span()[1]] for code in code_matches ] # Add color codes from earlier in the unwrapped line, and then track any new ones we add. new_line = "".join(self._active_codes) + new_line for code in color_codes: if code != _ansi_color_reset_code: self._active_codes.append(code) else: # A single reset code resets everything self._active_codes = [] # Always ensure each line is color terminted if any colors are # still active, otherwise colors will bleed into other cells on the console if len(self._active_codes) > 0: new_line = new_line + _ansi_color_reset_code lines.append(new_line)

adf24bfa9723b0621183bb27f0c889b813c06e8a

tabulate.py

[State Observability] Use a table format by default (#26159) NOTE: tabulate is copied/pasted to the codebase for table formatting. This PR changes the default layout to be the table format for both summary and list APIs.

ray

python/ray/_private/thirdparty/tabulate/tabulate.py

Python

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

score

def score(self, X, y, **fit_params): check_is_fitted(self) return self.estimator_.score(self.transform(X), y, **fit_params)

6e5ef2e9b8c64e6788428610ae884b9bf3d298a2

_rfe.py

MAINT solve long line reported by flake8 (#24065)

scikit-learn

sklearn/feature_selection/_rfe.py

Python

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

allowlist_svg

def allowlist_svg(dirty_xml): from lxml.html import clean allow_tags = [ 'xml', 'svg', 'circle', 'ellipse', 'line', 'path', 'polygon', 'polyline', 'rect' ] cleaner = clean.Cleaner( allow_tags=allow_tags, style=True, links=True, add_nofollow=False, page_structure=True, safe_attrs_only=False, remove_unknown_tags=False) clean_xml = cleaner.clean_html(dirty_xml) return clean_xml

53f6308186aa131946e196b0409f3d732ec9e007

uploader.py

fix: DEV-2236: Stored XSS via SVG file (#2273) * user uploaded content rendered as plain text or known image only * allow list for svg in progress * allow list for svg basic pass * add error handling * add to file processing re: code review * rm uneeded code * add env var to disable svg cleaning * add test * update env setting * rm lxml string methods * Update uploader.py * Update base.py Co-authored-by: Max Tkachenko <[email protected]>

label-studio

label_studio/data_import/uploader.py

Python

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

test_save_periodic_pipeline

def test_save_periodic_pipeline(): tpot_obj = TPOTClassifier( random_state=42, population_size=1, offspring_size=2, generations=1, verbosity=0, config_dict='TPOT light' ) tpot_obj.fit(training_features, training_target) with closing(StringIO()) as our_file: tpot_obj.log_file_ = our_file tpot_obj.verbosity = 3 tpot_obj._last_pipeline_write = datetime.now() sleep(0.11) tpot_obj._output_best_pipeline_period_seconds = 0.1 tmpdir = mkdtemp() + '/' tpot_obj.periodic_checkpoint_folder = tmpdir # reset _pareto_front to rasie exception tpot_obj._pareto_front = None tpot_obj._save_periodic_pipeline(1) our_file.seek(0) assert_in('Failed saving periodic pipeline, exception', our_file.read()) #clean up rmtree(tmpdir)

388616b6247ca4ea8de4e2f340d6206aee523541

tpot_tests.py

Revert "Deployed 7ccda9a with MkDocs version: 1.3.0" This reverts commit bd9629c40e01241766197119b581a99409b07068.

tpot

tests/tpot_tests.py

Python

https://github.com/EpistasisLab/tpot.git

tzname

def tzname(self): if self._tzinfo is None: return None name = self._tzinfo.tzname(None) _check_tzname(name) return name

8198943edd73a363c266633e1aa5b2a9e9c9f526

datetime.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/datetime.py

Python

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

gcn_loss

def gcn_loss(self, gcn_data): gcn_pred, gt_labels = gcn_data gt_labels = gt_labels.reshape([-1]) loss = F.cross_entropy(gcn_pred, gt_labels) return loss

1f9400dd7374ce9cc47981372e324ff412e53ba3

det_drrg_loss.py

add drrg

PaddleOCR

ppocr/losses/det_drrg_loss.py

Python

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

add_never_cache_headers

def add_never_cache_headers(response): patch_response_headers(response, cache_timeout=-1) patch_cache_control( response, no_cache=True, no_store=True, must_revalidate=True, private=True )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

cache.py

Refs #33476 -- Reformatted code with Black.

django

django/utils/cache.py

Python

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

test_n_step_very_short_trajectory

def test_n_step_very_short_trajectory(self): gamma = 1.0 obs = np.arange(0, 2) actions = np.random.randint(-100, 300, size=(2,)) check_actions = actions.copy() rewards = [10.0, 100.0] next_obs = np.arange(1, 3) batch = SampleBatch( { SampleBatch.OBS: obs, SampleBatch.ACTIONS: actions, SampleBatch.REWARDS: rewards, SampleBatch.TERMINATEDS: [False, False], SampleBatch.TRUNCATEDS: [False, False], SampleBatch.NEXT_OBS: next_obs, } ) adjust_nstep(3, gamma, batch) check(batch[SampleBatch.OBS], [0, 1]) check(batch[SampleBatch.ACTIONS], check_actions) check(batch[SampleBatch.TERMINATEDS], [False, False]) check(batch[SampleBatch.TRUNCATEDS], [False, False]) check(batch[SampleBatch.REWARDS], [10.0 + gamma * 100.0, 100.0]) check(batch[SampleBatch.NEXT_OBS], [2, 2])

8e680c483ce326cefc62e44f68ab1a6948b1c3d2

test_postprocessing.py

[RLlib] gymnasium support (new `Env.reset()/step()/seed()/render()` APIs). (#28369)

ray

rllib/evaluation/tests/test_postprocessing.py

Python

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

_create_index_name

def _create_index_name(self, table_name, column_names, suffix=""): _, table_name = split_identifier(table_name) hash_suffix_part = "%s%s" % ( names_digest(table_name, *column_names, length=8), suffix, ) max_length = self.connection.ops.max_name_length() or 200 # If everything fits into max_length, use that name. index_name = "%s_%s_%s" % (table_name, "_".join(column_names), hash_suffix_part) if len(index_name) <= max_length: return index_name # Shorten a long suffix. if len(hash_suffix_part) > max_length / 3: hash_suffix_part = hash_suffix_part[: max_length // 3] other_length = (max_length - len(hash_suffix_part)) // 2 - 1 index_name = "%s_%s_%s" % ( table_name[:other_length], "_".join(column_names)[:other_length], hash_suffix_part, ) # Prepend D if needed to prevent the name from starting with an # underscore or a number (not permitted on Oracle). if index_name[0] == "_" or index_name[0].isdigit(): index_name = "D%s" % index_name[:-1] return index_name

9c19aff7c7561e3a82978a272ecdaad40dda5c00

schema.py

Refs #33476 -- Reformatted code with Black.

django

django/db/backends/base/schema.py

Python

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

approve

def approve(self, user=None, update=True, comment=""): if self.status != self.STATUS_IN_PROGRESS: raise PermissionDenied self.status = self.STATUS_APPROVED self.finished_at = timezone.now() self.finished_by = user self.comment = comment self.save() self.log_state_change_action(user, "approve") if update: self.workflow_state.update(user=user) task_approved.send( sender=self.specific.__class__, instance=self.specific, user=user ) return self

d10f15e55806c6944827d801cd9c2d53f5da4186

__init__.py

Reformat with black

wagtail

wagtail/core/models/__init__.py

Python

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

minimize

def minimize(self, loss, var_list, grad_loss=None, name=None, tape=None): grads_and_vars = self._compute_gradients( loss, var_list=var_list, grad_loss=grad_loss, tape=tape ) return self.apply_gradients(grads_and_vars, name=name)

84afc5193d38057e2e2badf9c889ea87d80d8fbf

optimizer_v2.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/optimizers/optimizer_v2/optimizer_v2.py

Python

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

test_render_config

def test_render_config(tmpdir): user_config_path = os.path.join(tmpdir, "config.yaml") input_features = [ number_feature(), number_feature(), category_feature(encoder={"vocab_size": 3}), category_feature(encoder={"vocab_size": 3}), ] output_features = [category_feature(decoder={"vocab_size": 3})] user_config = { INPUT_FEATURES: input_features, OUTPUT_FEATURES: output_features, } with open(user_config_path, "w") as f: yaml.dump(user_config, f) output_config_path = os.path.join(tmpdir, "rendered.yaml") _run_ludwig("render_config", config=user_config_path, output=output_config_path) rendered_config = load_yaml(output_config_path) assert len(rendered_config[INPUT_FEATURES]) == len(user_config[INPUT_FEATURES]) assert len(rendered_config[OUTPUT_FEATURES]) == len(user_config[OUTPUT_FEATURES]) assert TRAINER in rendered_config assert COMBINER in rendered_config assert PREPROCESSING in rendered_config

5a25d1f2a914c849cf978573c5993411151bc447

test_cli.py

Added tests for init_config and render_config CLI commands (#2551)

ludwig

tests/integration_tests/test_cli.py

Python

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

update_info

def update_info(self, info) -> None: for key in self._info_fields: value = getattr(self, key, None) idx = info.setdefault(self.name, {}) existing_value = idx.get(key) if key in idx and value is not None and existing_value != value: # frequency/name just warn if key in ["freq", "index_name"]: ws = attribute_conflict_doc % (key, existing_value, value) warnings.warn( ws, AttributeConflictWarning, stacklevel=find_stack_level() ) # reset idx[key] = None setattr(self, key, None) else: raise ValueError( f"invalid info for [{self.name}] for [{key}], " f"existing_value [{existing_value}] conflicts with " f"new value [{value}]" ) else: if value is not None or existing_value is not None: idx[key] = value

7d2f9b8d59908fbf57c6453bc41891efbfe981a6

pytables.py

TYP: some return annotations in pytables.py (#47512)

pandas

pandas/io/pytables.py

Python

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

split_dataset

def split_dataset(items, eval_split_max_size=None, eval_split_size=0.01): speakers = [item["speaker_name"] for item in items] is_multi_speaker = len(set(speakers)) > 1 if eval_split_size > 1: eval_split_size = int(eval_split_size) else: if eval_split_max_size: eval_split_size = min(eval_split_max_size, int(len(items) * eval_split_size)) else: eval_split_size = int(len(items) * eval_split_size) assert ( eval_split_size > 0 ), " [!] You do not have enough samples for the evaluation set. You can work around this setting the 'eval_split_size' parameter to a minimum of {}".format( 1 / len(items) ) np.random.seed(0) np.random.shuffle(items) if is_multi_speaker: items_eval = [] speakers = [item["speaker_name"] for item in items] speaker_counter = Counter(speakers) while len(items_eval) < eval_split_size: item_idx = np.random.randint(0, len(items)) speaker_to_be_removed = items[item_idx]["speaker_name"] if speaker_counter[speaker_to_be_removed] > 1: items_eval.append(items[item_idx]) speaker_counter[speaker_to_be_removed] -= 1 del items[item_idx] return items_eval, items return items[:eval_split_size], items[eval_split_size:]

1425a023fe4bc6bda8578295aeeeb02af78cc082

__init__.py

Make style and lint

TTS

TTS/tts/datasets/__init__.py

Python

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

center

def center(G, e=None, usebounds=False, weight=None): if usebounds is True and e is None and not G.is_directed(): return _extrema_bounding(G, compute="center", weight=weight) if e is None: e = eccentricity(G, weight=weight) radius = min(e.values()) p = [v for v in e if e[v] == radius] return p

28f78cfa9a386620ee1179582fda1db5ffc59f84

distance_measures.py

Add weight distance metrics (#5305) Adds the weight keyword argument to allow users to compute weighted distance metrics e.g. diameter, eccentricity, periphery, etc. The kwarg works in the same fashion as the weight param for shortest paths - i.e. if a string, look up with edge attr by key, if callable, compute the weight via the function. Default is None, meaning return unweighted result which is the current behavior. Co-authored-by: Dan Schult <[email protected]> Co-authored-by: Ross Barnowski <[email protected]>

networkx

networkx/algorithms/distance_measures.py

Python

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

infer_concrete_type_builder

def infer_concrete_type_builder(nn_module, share_types=True): concrete_type_builder = torch._C.ConcreteModuleTypeBuilder(type(nn_module)) if isinstance(nn_module, (torch.nn.ModuleDict)): concrete_type_builder.set_module_dict() if isinstance(nn_module, (torch.nn.ModuleList, torch.nn.Sequential)): concrete_type_builder.set_module_list() class_annotations = getattr(nn_module, '__annotations__', {}) if isinstance(nn_module, (torch.ao.quantization.QuantWrapper)): class_annotations = {} # Get user-annotated ignored attributes. user_annotated_ignored_attributes = getattr(nn_module, "__jit_ignored_attributes__", list()) concrete_type_builder.add_ignored_attributes(user_annotated_ignored_attributes) ignored_properties = jit_ignored_properties(nn_module) # try to infer the type from type annotation or from the object itself

8e6d1738a41cb28c36db3dc5e10fd812417673de

_recursive.py

Per-overload torch.ops API (#67254) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/67254 Fixes https://github.com/pytorch/pytorch/issues/65997 TODO: disallow `default` as an overload name for aten operators. BC breaking: `output = torch.ops._test.leaky_relu(self=torch.tensor(-1.0))` now fails with the error `TypeError: __call__() got multiple values for argument 'self'` since we call into `OpOverloadBundle`'s `__call__` method that has `self` bound to it as its first argument. cc ezyang gchanan Test Plan: Imported from OSS Reviewed By: albanD Differential Revision: D33262228 Pulled By: anjali411 fbshipit-source-id: 600dbf511514ea9b41aea3e6b1bc1102dab08909

pytorch

torch/jit/_recursive.py

Python

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

to_undirected

def to_undirected(self, as_view=False): graph_class = self.to_undirected_class() if as_view is True: return nx.graphviews.generic_graph_view(self, graph_class) # deepcopy when not a view G = graph_class() G.graph.update(deepcopy(self.graph)) G.add_nodes_from((n, deepcopy(d)) for n, d in self._node.items()) G.add_edges_from( (u, v, key, deepcopy(datadict)) for u, nbrs in self._adj.items() for v, keydict in nbrs.items() for key, datadict in keydict.items() ) return G

8f4c99debc9440728c5e85f8bffa5d26b232eb6f

multigraph.py

Multigraph docs update (#5389) * Updated MultiDiGraph documentation to include more examples of actually using parallel edges, and fixed references to things like G[u, v] where G[u, v, k] is required for a MultiDigraph. Have not made parallel changes in MultiGraph which should maybe also be made? Docs tests pass on my end; no code outside of comments was changed. -Peter Mawhorter * Updated docs for MultiGraph to add more multigraph-specific examples and fix a few places where untested examples were wrong. -Peter Mawhorter * [DOC] fix typo * add the right amount of separators Co-authored-by: Mridul Seth <[email protected]>

networkx

networkx/classes/multigraph.py

Python

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

rgb_to_hsv

def rgb_to_hsv(arr): arr = np.asarray(arr) # check length of the last dimension, should be _some_ sort of rgb if arr.shape[-1] != 3: raise ValueError("Last dimension of input array must be 3; " "shape {} was found.".format(arr.shape)) in_shape = arr.shape arr = np.array( arr, copy=False, dtype=np.promote_types(arr.dtype, np.float32), # Don't work on ints. ndmin=2, # In case input was 1D. ) out = np.zeros_like(arr) arr_max = arr.max(-1) ipos = arr_max > 0 delta = arr.ptp(-1) s = np.zeros_like(delta) s[ipos] = delta[ipos] / arr_max[ipos] ipos = delta > 0 # red is max idx = (arr[..., 0] == arr_max) & ipos out[idx, 0] = (arr[idx, 1] - arr[idx, 2]) / delta[idx] # green is max idx = (arr[..., 1] == arr_max) & ipos out[idx, 0] = 2. + (arr[idx, 2] - arr[idx, 0]) / delta[idx] # blue is max idx = (arr[..., 2] == arr_max) & ipos out[idx, 0] = 4. + (arr[idx, 0] - arr[idx, 1]) / delta[idx] out[..., 0] = (out[..., 0] / 6.0) % 1.0 out[..., 1] = s out[..., 2] = arr_max return out.reshape(in_shape)

9b6abd0b4933811e0a45c2535ab8fd107db65dd9

colors.py

DOC: improve grammar and consistency

matplotlib

lib/matplotlib/colors.py

Python

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

__len__

def __len__(self) -> int: # do a DFS to count the number of leaf nodes count = 0 stack = [self._data] while stack: node = stack.pop() if isinstance(node, NestedDict): node = node._data if isinstance(node, Mapping): stack.extend(node.values()) else: count += 1 return count

c8dbbf374661d89e620b472a8c62aa3ce3c6ce98

nested_dict.py

[RLlib] Introduction of Nested dict for RLModule construction (#29027) Signed-off-by: Kourosh Hakhamaneshi <[email protected]>

ray

rllib/utils/nested_dict.py

Python

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

generate_mask

def generate_mask(self, h, w, p, shift): # supporting sqaure. attn_mask = torch.zeros(h, w, p, p, p, p, dtype=torch.bool, device=self.relative_position_params.device) if self.type == 'W': return attn_mask s = p - shift attn_mask[-1, :, :s, :, s:, :] = True attn_mask[-1, :, s:, :, :s, :] = True attn_mask[:, -1, :, :s, :, s:] = True attn_mask[:, -1, :, s:, :, :s] = True attn_mask = rearrange(attn_mask, 'w1 w2 p1 p2 p3 p4 -> 1 1 (w1 w2) (p1 p2) (p3 p4)') return attn_mask

8deae077004f0332ca607fc3a5d568b1a4705bec

scunet_model_arch.py

Add ScuNET DeNoiser/Upscaler Q&D Implementation of ScuNET, thanks to our handy model loader. :P https://github.com/cszn/SCUNet

stable-diffusion-webui

modules/scunet_model_arch.py

Python

https://github.com/AUTOMATIC1111/stable-diffusion-webui.git

setup_tpu

def setup_tpu(tpu_driver_version='tpu_driver-0.2'): global TPU_DRIVER_MODE if not TPU_DRIVER_MODE: colab_tpu_addr = os.environ['COLAB_TPU_ADDR'].split(':')[0] url = f'http://{colab_tpu_addr}:8475/requestversion/{tpu_driver_version}' requests.post(url) TPU_DRIVER_MODE = 1 # The following is required to use TPU Driver as JAX's backend. config.FLAGS.jax_xla_backend = "tpu_driver" config.FLAGS.jax_backend_target = "grpc://" + os.environ['COLAB_TPU_ADDR']

0cc4066bb7bf758a5ba8c5def9c2c32a1c98fb89

colab_tpu.py

Pin default jax.tools.colab_tpu.setup_tpu driver version. Prior to this change, we were defaulting to the TPU nightly driver version. We should instead pin to the version associated with the default jaxlib version that Colab uses.

jax

jax/tools/colab_tpu.py

Python

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

check_connection

def check_connection(self, logger, config) -> Tuple[bool, any]: try: req = requests.get(RkiCovidStream.url_base + "germany") if req.status_code == 200: return True, None return False, req.reason except Exception: return False, "There is a problem in source check connection."

d6d52c5d99dd7ebbd966da79c1d890699a947f39

source.py

:tada: New Source: RKI (Robert Koch-Institut) Covid Public API (#11732) * Added source for RKI-covid-germany, updated spec.json, implemented source with check and discover method added germany.json. * implemented incremental method for germany history cases with date as parameters, updated streams, added cursor field for incremental streams. * main file added. * added Incidence source with date as parameter. Incremental stream. spec, source, schemas updated, added class GermanHistoryIncidence added. * Added a full-refresh stream for germany/age-group .Added incremental streams for deaths/:days, recovered/:days, frozen-incidence/:days, hospitalization/:days. Updated source.py methods. Updated sepc.json properties key. Updated configured_catalogue.json with required streams. Updated config.json * writting test unit test cases for incremental streams: german history cases and german history incidence. * Incremental streams for germanhistorydeaths, germanhistoryfrozenIncidence, germanhistoryhospitalization, germanhistoryrecovered. Fixing other test cases. * Added test stream for age group and germany. * changes in Readme and source.py. * IncrementalMixin added to class GermanyHistoryCases. AFter review IncrementalMixin will be implemented to all incremental classes. * Implemented Incremental mixin or GermanHistory Cases connector. * corrected changes. * adding integration test * comment acceptence test. * On path with master * updated the changes for PR request. * changed file source-rki-covid/integration_tests/configured_catalog.json * corrected flake and blackformatting. Build gradel. * Worked on the suggestions. * source_rki_covid/schemas/germany_age_groups.json * uodated abnormal_state.json * updated the schemas for german age groups and history hospitalization. * correct dockerfile and update airbyte_cdk version * run format * update python version * correct dockerfile build * add source in seed * update uuid for rki-covid source * change docker * add bash * auto-bump connector version * run seed file * correct doc * auto-bump connector version Co-authored-by: Marcos Marx Millnitz <[email protected]> Co-authored-by: Octavia Squidington III <[email protected]>

airbyte

airbyte-integrations/connectors/source-rki-covid/source_rki_covid/source.py

Python

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

get_heading

def get_heading(self, queryset, field): heading_override = self.export_headings.get(field) if heading_override: return force_str(heading_override) return force_str( label_for_field( field, model=self.model, model_admin=self.model_admin ).title() )

d10f15e55806c6944827d801cd9c2d53f5da4186

views.py

Reformat with black

wagtail

wagtail/contrib/modeladmin/views.py

Python

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

_nannumel_sparse

def _nannumel_sparse(x, **kwargs): n = _nannumel(x, **kwargs) # If all dimensions are contracted, this will just be a number, otherwise we # want to densify it. return n.todense() if hasattr(n, "todense") else n

8b95f983c232c1bd628e9cba0695d3ef229d290b

backends.py

Sparse array reductions (#9342)

dask

dask/array/backends.py

Python

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

_new_step

def _new_step(self): self.should_save = False self.should_evaluate = False self.should_log = False

44a290e94d1becd1f09fddc3d873f9e19c9d6919

trainer_callback.py

[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]>

PaddleNLP

paddlenlp/trainer/trainer_callback.py

Python

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

shuffle_group

def shuffle_group(df, cols, stage, k, npartitions, ignore_index, nfinal): if isinstance(cols, str): cols = [cols] if cols and cols[0] == "_partitions": ind = df[cols[0]] else: ind = hash_object_dispatch(df[cols] if cols else df, index=False) if nfinal and nfinal != npartitions: ind = ind % int(nfinal) c = ind.values typ = np.min_scalar_type(npartitions * 2) c = np.mod(c, npartitions).astype(typ, copy=False) np.floor_divide(c, k**stage, out=c) np.mod(c, k, out=c) return group_split_dispatch(df, c, k, ignore_index=ignore_index) @contextlib.contextmanager

510bbc380531cbf56a409f1ae68e6fd84a9599e6

@contextlib.contextmanager

shuffle.py

Update `pre-commit` version (#8691)

dask

dask/dataframe/shuffle.py

Python

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

unifi_dict

def unifi_dict(self) -> dict[str, Any]: return { "nvr": self.nvr.unifi_dict(), "cameras": [c.unifi_dict() for c in self.cameras.values()], "lights": [c.unifi_dict() for c in self.lights.values()], "sensors": [c.unifi_dict() for c in self.sensors.values()], "viewers": [c.unifi_dict() for c in self.viewers.values()], "liveviews": [c.unifi_dict() for c in self.liveviews.values()], "doorlocks": [c.unifi_dict() for c in self.doorlocks.values()], "chimes": [c.unifi_dict() for c in self.chimes.values()], } @dataclass

654c59c19414c52f95f56603c460f63edeb60959

@dataclass

conftest.py

Add diagnostics for UniFi Protect (#72280)

core

tests/components/unifiprotect/conftest.py

Python

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

get_attendance_list

def get_attendance_list(from_date, to_date, student_group, students_list): attendance_list = frappe.db.sql( , (student_group, from_date, to_date), as_dict=1, ) att_map = {} students_with_leave_application = get_students_with_leave_application( from_date, to_date, students_list ) for d in attendance_list: att_map.setdefault(d.student, frappe._dict()).setdefault(d.date, "") if students_with_leave_application.get( d.date ) and d.student in students_with_leave_application.get(d.date): att_map[d.student][d.date] = "Present" else: att_map[d.student][d.date] = d.status att_map = mark_holidays(att_map, from_date, to_date, students_list) return att_map

494bd9ef78313436f0424b918f200dab8fc7c20b

student_monthly_attendance_sheet.py

style: format code with black

erpnext

erpnext/education/report/student_monthly_attendance_sheet/student_monthly_attendance_sheet.py

Python

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

update_static

def update_static(): config = Config() logger = get_log('http') static_path = Path(config['paths']['static']) last_gui_version_lv = get_last_compatible_gui_version() current_gui_version_lv = get_current_gui_version() if last_gui_version_lv is False: return False if current_gui_version_lv is not None: if current_gui_version_lv >= last_gui_version_lv: return True logger.info(f'New version of GUI available ({last_gui_version_lv.vstring}). Downloading...') temp_dir = tempfile.mkdtemp(prefix='mindsdb_gui_files_') success = download_gui(temp_dir, last_gui_version_lv.vstring) if success is False: shutil.rmtree(temp_dir) return False temp_dir_for_rm = tempfile.mkdtemp(prefix='mindsdb_gui_files_') shutil.rmtree(temp_dir_for_rm) shutil.copytree(str(static_path), temp_dir_for_rm) shutil.rmtree(str(static_path)) shutil.copytree(temp_dir, str(static_path)) shutil.rmtree(temp_dir_for_rm) logger.info(f'GUI version updated to {last_gui_version_lv.vstring}') return True

9ce5a21dd6359fd7e8ebf78051ce9e97bd195ec9

initialize.py

ML handler supbrocess (#3377) * log -> logger dividing components: app initialize parse args set env.MINDSDB_CONFIG_PATH config requiers env.MINDSDB_CONFIG_PATH sets env.MINDSDB_DB_CON Config() - makes initialization log uses config initialize_log - makes initialization database uses env.MINDSDB_DB_CON have init() method file storage uses config * partial sync for model storage interfaces * ml handler in subprocess interface * fix delete model * fix: model with error in success status * fix: remove hf predictor * fix pg handler * MLHandlerPersistWrapper keeps wrapper process opened * predictor with error keeps 'success' status #3362 * lock for sending tasks to subprocess one by one * check target of predictor before run learn in subproccess * fix check target * fix: json_ai override and problem definition generation * fix None case * folder for ml handler tests * fix: add timeseries_settings key to learn_args * fixes in lw_handler * fix: del join_learn_process * tests for LW handler * finish unit test for LW * changes in tests: - set-project -> to base class - return of ml handler is dataframe - draft for project structure test * merge from staging * create_validation method to check learn params before send to subprocess fixes of HF fixed version of transformers in HF requirements Co-authored-by: Patricio Cerda Mardini <[email protected]>

mindsdb

mindsdb/api/http/initialize.py

Python

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

test_stream_admin_remove_others_from_public_stream

def test_stream_admin_remove_others_from_public_stream(self) -> None: result = self.attempt_unsubscribe_of_principal( query_count=15, target_users=[self.example_user("cordelia")], is_realm_admin=False, is_stream_admin=True, is_subbed=True, invite_only=False, target_users_subbed=True, ) json = self.assert_json_success(result) self.assert_length(json["removed"], 1) self.assert_length(json["not_removed"], 0)

803982e87254e3b1ebcb16ed795e224afceea3a3

test_subs.py

message_flags: Short-circuit if no messages changed. Omit sending an event, and updating the database, if there are no matching messages.

zulip

zerver/tests/test_subs.py

Python

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

test_conversation_part_has_conversation_id

def test_conversation_part_has_conversation_id(requests_mock): response_body = { "type": "conversation", "id": "151272900024304", "created_at": 1647365706, "updated_at": 1647366443, "conversation_parts": { "type": "conversation_part.list", "conversation_parts": [ {"type": "conversation_part", "id": "13740311965"}, {"type": "conversation_part", "id": "13740312024"}, ], "total_count": 2, }, } url = "https://api.intercom.io/conversations/151272900024304" requests_mock.get(url, json=response_body) stream1 = ConversationParts(authenticator=NoAuth()) record_count = 0 for record in stream1.read_records(sync_mode=SyncMode.incremental, stream_slice={"id": "151272900024304"}): assert record["conversation_id"] == "151272900024304" record_count += 1 assert record_count == 2

787daa9961b6b103e8d520c544277fc77c191dfb

unit_test.py

🎉 Source Intercom: Added conversation_id field to conversation_part records (#11206)

airbyte

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

Python

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

flatten

def flatten(data, levels=None, preserve_nulls=False, _ids=None): if _ids is None: _ids = set() if id(data) in _ids: raise RecursionError("Reference cycle detected. Check input list.") _ids.add(id(data)) ret = [] for element in data: if not preserve_nulls and element in (None, "None", "null"): # ignore null items continue elif is_iter(element): if levels is None: ret.extend(flatten(element, preserve_nulls=preserve_nulls, _ids=_ids)) elif levels >= 1: # decrement as we go down the stack ret.extend( flatten( element, levels=(int(levels) - 1), preserve_nulls=preserve_nulls, _ids=_ids, ) ) else: ret.append(element) else: ret.append(element) return ret

ec41b56baee98ade5e6e21083645da1ec21c4b86

data.py

detect reference cycles in flatten function

salt

salt/utils/data.py

Python

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

training_iteration

def training_iteration(self) -> ResultDict: # Some shortcuts. batch_size = self.config["train_batch_size"] # Collects SampleBatches in parallel and synchronously # from the Trainer's RolloutWorkers until we hit the # configured `train_batch_size`. sample_batches = [] num_env_steps = 0 num_agent_steps = 0 while (not self._by_agent_steps and num_env_steps < batch_size) or \ (self._by_agent_steps and num_agent_steps < batch_size): new_sample_batches = synchronous_parallel_sample(self.workers) sample_batches.extend(new_sample_batches) num_env_steps += sum(len(s) for s in new_sample_batches) num_agent_steps += sum( len(s) if isinstance(s, SampleBatch) else s.agent_steps() for s in new_sample_batches) self._counters[NUM_ENV_STEPS_SAMPLED] += num_env_steps self._counters[NUM_AGENT_STEPS_SAMPLED] += num_agent_steps # Combine all batches at once train_batch = SampleBatch.concat_samples(sample_batches) # Use simple optimizer (only for multi-agent or tf-eager; all other # cases should use the multi-GPU optimizer, even if only using 1 GPU). # TODO: (sven) rename MultiGPUOptimizer into something more # meaningful. if self.config.get("simple_optimizer") is True: train_results = train_one_step(self, train_batch) else: train_results = multi_gpu_train_one_step(self, train_batch) return train_results

853d10871c55cb741cb15212ef4ab42f158f968c

trainer.py

[RLlib] Issue 18499: PGTrainer with training_iteration fn does not support multi-GPU. (#21376)

ray

rllib/agents/trainer.py

Python

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

get_model

def get_model(self, app_label, model_name=None, require_ready=True): if require_ready: self.check_models_ready() else: self.check_apps_ready() if model_name is None: app_label, model_name = app_label.split(".") app_config = self.get_app_config(app_label) if not require_ready and app_config.models is None: app_config.import_models() return app_config.get_model(model_name, require_ready=require_ready)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

registry.py

Refs #33476 -- Reformatted code with Black.

django

django/apps/registry.py

Python

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

handle_groupme

def handle_groupme(request) -> bool: req = json.loads(request.decode("utf-8")) text = req.get("text").strip().lower() group_id = req.get("group_id").strip() if text[0] == "!": cmd = text[1:] full_cmd = cmd.split("/") group = full_cmd[0].split("-")[0] parents = {x.split("-")[0] for x in commands} if group in parents: if full_cmd[0] in commands: selected = commands[full_cmd[0]] if len(full_cmd) != len(selected.get("required", [])) + 1: syntax = get_syntax(selected, full_cmd[0]) send_message(f"Required syntax: {syntax}", group_id) return False other_args = {} for i, val in enumerate(full_cmd[1:]): req_name = list(selected.get("required", {}).keys())[i] required = selected.get("required", [])[req_name] if isinstance(required, List) and required != [True, False]: required = [str(x) for x in required] if isinstance(val, str) and req_name in ["ticker"]: val = val.upper() elif isinstance(val, str) and req_name == "raw": val = bool(val) if (isinstance(required, List) and val not in required) or ( isinstance(required, Pattern) and not required.match(val) ): syntax = get_syntax(selected, full_cmd[0]) send_message( f"{syntax}\nInvalid argument for: {req_name}", group_id ) get_arguments(selected, req_name, group_id) return False other_args[req_name] = val func = selected["function"] ShowView().groupme(func, group_id, cmd, **other_args) return True else: show_cmds = [] for command in commands: if group == command[: len(group)]: show_cmds.append(command) send_options("Valid commands: ", show_cmds, group_id) return False else: send_options("Valid categories: ", parents, group_id) return False return False

b8b3b49896b7553c8ad57e0f3fbb4464ecf24179

run_groupme.py

Groupme Bot (#1418) * Added groupme helpers * Began handling of user input * Expanded commands, improved bot * Completed dictionary * Eliminated redundancies * Added more * Added debuggers for server * Fixed bugs * Improved input handling and image sending * Fixed dd-est * Fixed dd commands * Added dps fix * Fixed feargreed * Fixed econ commands * Fixed gov commands * Fixed ta * Added docstrings * Added docstrings * black Co-authored-by: didierlopes.eth <[email protected]>

OpenBBTerminal

bots/groupme/run_groupme.py

Python

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

_fill

def _fill(strings, linelen=75): currpos = 0 lasti = 0 result = [] for i, s in enumerate(strings): length = len(s) if currpos + length < linelen: currpos += length + 1 else: result.append(b' '.join(strings[lasti:i])) lasti = i currpos = length result.append(b' '.join(strings[lasti:])) return b'\n'.join(result) # PDF strings are supposed to be able to include any eight-bit data, # except that unbalanced parens and backslashes must be escaped by a # backslash. However, sf bug #2708559 shows that the carriage return # character may get read as a newline; these characters correspond to # \gamma and \Omega in TeX's math font encoding. Escaping them fixes # the bug. _string_escape_regex = re.compile(br'([\\()\r\n])')

ec410abbb3a721e31f3aaa61e9e4f941467e35e1

backend_pdf.py

Deprecate functions in backends

matplotlib

lib/matplotlib/backends/backend_pdf.py

Python

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

plextv_resources_fixture

def plextv_resources_fixture(): return load_fixture("plex/plextv_resources_one_server.xml") @pytest.fixture(name="plextv_resources_two_servers", scope="session")

10195dc700770cdfdeaff79c53cf5d1d763f20c6

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

conftest.py

Improve server selection for Plex config flows (#63408)

core

tests/components/plex/conftest.py

Python

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

test_timeout_does_not_wait_for_completion_for_sync_flows

def test_timeout_does_not_wait_for_completion_for_sync_flows(self, tmp_path): if sys.version_info[1] == 11: pytest.xfail("The engine returns _after_ sleep finishes in Python 3.11") canary_file = tmp_path / "canary"

a7bd9cadd5038383449b0e75a87bb23a73b278d8

test_flows.py

Add support for Python 3.11 (#7304) Co-authored-by: Chris Guidry <[email protected]>

prefect

tests/test_flows.py

Python

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

inertia

def inertia(self): if self.is_rigidbody: return RigidBody.inertia.fget(self) return (self.central_inertia, self.masscenter)

f0ccc88c86f77f1c3e13d590d4506e49c8cb2a12

body.py

Add property docstrings

sympy

sympy/physics/mechanics/body.py

Python

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

test_event_ref

def test_event_ref(self): # Reset the event cache self.store._get_event_cache.clear() with LoggingContext("test") as ctx: # We keep hold of the event event though we never use it. event = self.get_success(self.store.get_event(self.event_id)) # noqa: F841 # We should have fetched the event from the DB self.assertEqual(ctx.get_resource_usage().evt_db_fetch_count, 1) # Reset the event cache self.store._get_event_cache.clear() with LoggingContext("test") as ctx: self.get_success(self.store.get_event(self.event_id)) # Since the event is still in memory we shouldn't have fetched it # from the DB self.assertEqual(ctx.get_resource_usage().evt_db_fetch_count, 0)

fcf951d5dc7ca8c4cb18aa9c1f5ccb005df3610a

test_events_worker.py

Track in memory events using weakrefs (#10533)

synapse

tests/storage/databases/main/test_events_worker.py

Python

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

_load_specials

def _load_specials(self, *args, **kwargs): super(KeyedVectors, self)._load_specials(*args, **kwargs) if hasattr(self, 'doctags'): self._upconvert_old_d2vkv() # fixup rename/consolidation into index_to_key of older index2word, index2entity if not hasattr(self, 'index_to_key'): self.index_to_key = self.__dict__.pop('index2word', self.__dict__.pop('index2entity', None)) # fixup rename into vectors of older syn0 if not hasattr(self, 'vectors'): self.vectors = self.__dict__.pop('syn0', None) self.vector_size = self.vectors.shape[1] # ensure at least a 'None' in 'norms' to force recalc if not hasattr(self, 'norms'): self.norms = None # ensure at least an empty 'expandos' if not hasattr(self, 'expandos'): self.expandos = {} # fixup rename of vocab into map if 'key_to_index' not in self.__dict__: self._upconvert_old_vocab() # ensure older instances have next_index if not hasattr(self, 'next_index'): self.next_index = len(self)

766b9e19585968d011649b53057fba3663eff551

keyedvectors.py

Ensure next_index available when loading old stored KeyedVectors models (#3117) * fix #3114: ensure next_index available * rm trailing whitespace

gensim

gensim/models/keyedvectors.py

Python

https://github.com/RaRe-Technologies/gensim.git

simple_test

def simple_test(self, feats, img_metas, rescale=False): outs = self.forward(feats) results_list = self.get_results( *outs, img_metas=img_metas, rescale=rescale) return results_list

9c5b3331ac8edbfa328922fbab45c382380da540

base_dense_head.py

Simplify api of one-stage detector

mmdetection

mmdet/models/dense_heads/base_dense_head.py

Python

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

test_http_server_aborts

def test_http_server_aborts(tctx, stream): server = Placeholder(Server) flow = Placeholder(HTTPFlow) playbook = Playbook(http.HttpLayer(tctx, HTTPMode.regular))

372a632161dee642d81542069507826e34466ba1