ast_errors stringlengths 0 3.2k | d_id int64 44 121k | id int64 70 338k | n_whitespaces int64 3 14k | path stringlengths 8 134 | n_words int64 4 4.82k | n_identifiers int64 1 131 | random_cut stringlengths 16 15.8k | commit_message stringlengths 2 15.3k | fun_name stringlengths 1 84 | commit_id stringlengths 40 40 | repo stringlengths 3 28 | file_name stringlengths 5 79 | ast_levels int64 6 31 | nloc int64 1 548 | url stringlengths 31 59 | complexity int64 1 66 | token_counts int64 6 2.13k | n_ast_errors int64 0 28 | vocab_size int64 4 1.11k | n_ast_nodes int64 15 19.2k | language stringclasses 1
value | documentation dict | code stringlengths 101 62.2k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
@sympify_method_args | 48,788 | 198,089 | 34 | sympy/core/expr.py | 12 | 7 | def _imaginary_unit_as_coefficient(arg):
if getattr(arg, 'is_real', True):
return None
else:
return arg.as_coefficient( | move _imaginary_unit_as_coefficient to sympy.core.expr | _imaginary_unit_as_coefficient | bad8e3c1d614a05a0b1c6a05c21720f8751f0f2b | sympy | expr.py | 11 | 5 | https://github.com/sympy/sympy.git | 2 | 29 | 1 | 11 | 54 | Python | {
"docstring": " Helper to extract symbolic coefficient for imaginary unit ",
"language": "en",
"n_whitespaces": 9,
"n_words": 8,
"vocab_size": 8
} | def _imaginary_unit_as_coefficient(arg):
if getattr(arg, 'is_real', True):
return None
else:
return arg.as_coefficient(S.ImaginaryUnit)
@sympify_method_args |
83,198 | 279,959 | 100 | keras/optimizers/optimizer_experimental/optimizer.py | 19 | 8 | def from_config(cls, config, custom_objects=None):
if "learning_rate" in config:
if isinstance(config["learning_rate"], dict):
config["learning_rate"] = learning_rate_schedule.deserialize(
config["learning_rate"], custom_objects=custom_objects
| Some changes on the new optimizer:
1. Include `custom_objects` in `from_config` for deserializing custom learning rate.
2. Handle the error of seeing unrecognized variable with a better error message.
PiperOrigin-RevId: 476505974 | from_config | 51a6050b936ec87cd684fc1a052f79785ec9aaec | keras | optimizer.py | 14 | 7 | https://github.com/keras-team/keras.git | 3 | 52 | 0 | 18 | 88 | Python | {
"docstring": "Creates an optimizer from its config.\n\n This method is the reverse of `get_config`, capable of instantiating the\n same optimizer from the config dictionary.\n\n Args:\n config: A Python dictionary, typically the output of get_config.\n custom_objects: A Py... | def from_config(cls, config, custom_objects=None):
if "learning_rate" in config:
if isinstance(config["learning_rate"], dict):
config["learning_rate"] = learning_rate_schedule.deserialize(
config["learning_rate"], custom_objects=custom_objects
... | |
117,113 | 320,283 | 363 | src/paperless_mail/tests/test_parsers_live.py | 81 | 32 | def test_generate_pdf_from_mail(self):
mail = self.parser.get_parsed(os.path.join(self.SAMPLE_FILES, "html.eml"))
pdf_path = os.path.join(self.parser.tempdir, "html.eml.pdf")
with open(pdf_path, "wb") as file:
file.write(self.parser.generate_pdf_from_mail(mail))
c... | add test comments | test_generate_pdf_from_mail | 4aa318598fd0dc6c5d4e08dd2a13e7bf614511ec | paperless-ngx | test_parsers_live.py | 12 | 30 | https://github.com/paperless-ngx/paperless-ngx.git | 1 | 176 | 0 | 70 | 291 | Python | {
"docstring": "\n GIVEN:\n - Fresh start\n WHEN:\n - pdf generation from simple eml file is requested\n THEN:\n - gotenberg is called and the resulting file is returned and look as expected.\n ",
"language": "en",
"n_whitespaces": 91,
"n_words": 29,
... | def test_generate_pdf_from_mail(self):
mail = self.parser.get_parsed(os.path.join(self.SAMPLE_FILES, "html.eml"))
pdf_path = os.path.join(self.parser.tempdir, "html.eml.pdf")
with open(pdf_path, "wb") as file:
file.write(self.parser.generate_pdf_from_mail(mail))
c... | |
53,380 | 212,750 | 460 | DemoPrograms/Demo_Desktop_Widget_Drive_Usage_Gauges.py | 100 | 33 | def new(self, degree=0, color=None):
(center_x, center_y, angle, inner_radius, outer_radius,
outer_color, pointer_color, origin_color, line_width) = self.all
pointer_color = color or pointer_color
if self.figure != []:
for figure in self.figu... | More demo programs updates 🤦♂️ wow.....I thought for sure these were checked in.... | new | 430d1bc77fcdc0969a66ff370ec5e7e590423c83 | PySimpleGUI | Demo_Desktop_Widget_Drive_Usage_Gauges.py | 13 | 19 | https://github.com/PySimpleGUI/PySimpleGUI.git | 4 | 238 | 0 | 61 | 354 | Python | {
"docstring": "\n Draw new pointer by angle, erase old pointer if exist\n degree defined as clockwise from negative x-axis.\n ",
"language": "en",
"n_whitespaces": 51,
"n_words": 17,
"vocab_size": 16
} | def new(self, degree=0, color=None):
(center_x, center_y, angle, inner_radius, outer_radius,
outer_color, pointer_color, origin_color, line_width) = self.all
pointer_color = color or pointer_color
if self.figure != []:
for figure in self.figu... | |
10,241 | 50,918 | 610 | modules/image/object_detection/yolov3_darknet53_vehicles/processor.py | 172 | 48 | def postprocess(paths, images, data_out, score_thresh, label_names, output_dir, handle_id, visualization=True):
results = data_out.copy_to_cpu()
lod = data_out.lod()[0]
check_dir(output_dir)
if paths:
assert type(paths) is list, "type(paths) is not list."
if handle_id < len(paths)... | update yolov3_darknet53_vehicles (#1957)
* update yolov3_darknet53_vehicles
* update gpu config
* update
* add clean func
* update save inference model | postprocess | 7a847a39b1da6e6867031f52f713d92391b9729d | PaddleHub | processor.py | 19 | 50 | https://github.com/PaddlePaddle/PaddleHub.git | 13 | 380 | 0 | 107 | 611 | Python | {
"docstring": "\n postprocess the lod_tensor produced by Executor.run\n\n Args:\n paths (list[str]): The paths of images.\n images (list(numpy.ndarray)): images data, shape of each is [H, W, C]\n data_out (lod_tensor): data output of predictor.\n output_dir (str): The path to store ... | def postprocess(paths, images, data_out, score_thresh, label_names, output_dir, handle_id, visualization=True):
results = data_out.copy_to_cpu()
lod = data_out.lod()[0]
check_dir(output_dir)
if paths:
assert type(paths) is list, "type(paths) is not list."
if handle_id < len(paths)... | |
@pytest.fixture(params=_index_or_series_objs.keys()) | 40,068 | 167,616 | 102 | pandas/conftest.py | 59 | 28 | def series_with_multilevel_index() -> Series:
arrays = [
["bar", "bar", "baz", "baz", "qux", "qux", "foo", "foo"],
["one", "two", "one", "two", "one", "two", "one", "two"],
]
tuples = zip(*arrays)
index = MultiIndex.from_tuples(tuples)
da | TYP: misc return type annotations (#47558) | series_with_multilevel_index | f538568afc2c76c2d738d32e3544cf9fe6742960 | pandas | conftest.py | 10 | 14 | https://github.com/pandas-dev/pandas.git | 1 | 92 | 1 | 45 | 249 | Python | {
"docstring": "\n Fixture with a Series with a 2-level MultiIndex.\n ",
"language": "en",
"n_whitespaces": 15,
"n_words": 8,
"vocab_size": 6
} | def series_with_multilevel_index() -> Series:
arrays = [
["bar", "bar", "baz", "baz", "qux", "qux", "foo", "foo"],
["one", "two", "one", "two", "one", "two", "one", "two"],
]
tuples = zip(*arrays)
index = MultiIndex.from_tuples(tuples)
data = np.random.randn(8)
ser = Series(... |
106,436 | 307,668 | 46 | homeassistant/components/group/__init__.py | 10 | 3 | def _async_stop(self) -> None:
if self._async_unsub_state_changed:
self._async_unsub_state_changed()
self._async_unsub_state_ch | Improve type hints in group (#78350) | _async_stop | 5cccb248307d138a33c353544c57dc997b4fe917 | core | __init__.py | 9 | 8 | https://github.com/home-assistant/core.git | 2 | 23 | 0 | 10 | 41 | Python | {
"docstring": "Unregister the group from Home Assistant.\n\n This method must be run in the event loop.\n ",
"language": "en",
"n_whitespaces": 29,
"n_words": 15,
"vocab_size": 14
} | def _async_stop(self) -> None:
if self._async_unsub_state_changed:
self._async_unsub_state_changed()
self._async_unsub_state_changed = None
| |
@pytest.fixture(scope="session") | 11,567 | 56,814 | 129 | tests/conftest.py | 51 | 12 | def test_database_connection_url(generate_test_database_connection_url):
url = generate_test_database_connection_url
if url is None:
yield None
else:
# TODO: https://github.com/PrefectHQ/orion/issues/2045
# Also temporarily override the environment variable, so that child
... | :facepalm: I got bitten by the async fixture context issue. Fixed and added comments to help future developers. | test_database_connection_url | ef032ee4a8f5d357a6e8dadf4021177ccc71f767 | prefect | conftest.py | 14 | 10 | https://github.com/PrefectHQ/prefect.git | 2 | 56 | 1 | 39 | 122 | Python | {
"docstring": "\n Update the setting for the database connection url to the generated value from\n `generate_test_database_connection_url`\n\n This _must_ be separate from the generation of the test url because async fixtures\n are run in a separate context from the test suite.\n ",
"language": "en"... | def test_database_connection_url(generate_test_database_connection_url):
url = generate_test_database_connection_url
if url is None:
yield None
else:
# TODO: https://github.com/PrefectHQ/orion/issues/2045
# Also temporarily override the environment variable, so that child
... |
27,941 | 125,665 | 84 | python/ray/tune/examples/optuna_define_by_run_example.py | 50 | 9 | def define_by_run_func(trial) -> Optional[Dict[str, Any]]:
# This param is not used in the objective function.
activation = trial.suggest_categorical("activation", ["relu", "tanh"])
trial.suggest_float("width", 0, 20)
trial.suggest_float("height", -100, 100)
# Define-by-run allows for conditio... | [air/tuner/docs] Update docs for Tuner() API 2a: Tune examples (non-docs) (#26931)
Splitting up #26884: This PR includes changes to use Tuner() instead of tune.run() for all examples included in python/ray/tune/examples
Signed-off-by: xwjiang2010 <xwjiang2010@gmail.com>
Signed-off-by: Kai Fricke <kai@anyscale.com>... | define_by_run_func | 8d7b865614f3635def12c42b653f8acd8b4ae56a | ray | optuna_define_by_run_example.py | 10 | 18 | https://github.com/ray-project/ray.git | 2 | 72 | 0 | 46 | 127 | Python | {
"docstring": "Define-by-run function to create the search space.\n\n Ensure no actual computation takes place here. That should go into\n the trainable passed to ``Tuner`` (in this example, that's\n ``easy_objective``).\n\n For more information, see https://optuna.readthedocs.io/en/stable\\\n/tutorial/1... | def define_by_run_func(trial) -> Optional[Dict[str, Any]]:
# This param is not used in the objective function.
activation = trial.suggest_categorical("activation", ["relu", "tanh"])
trial.suggest_float("width", 0, 20)
trial.suggest_float("height", -100, 100)
# Define-by-run allows for conditio... | |
43,616 | 181,843 | 142 | tpot/base.py | 34 | 16 | def _compile_to_sklearn(self, expr):
sklearn_pipeline_str = generate_pipeline_code(
expr_to_tree(expr, self._pset), self.operators
)
sklearn_pipeline = eval(sklearn_pipeline_str, self.operators_context)
sklearn_pipeline.memory = self._memory
if self.random_st... | Revert "Deployed 7ccda9a with MkDocs version: 1.3.0"
This reverts commit bd9629c40e01241766197119b581a99409b07068. | _compile_to_sklearn | 388616b6247ca4ea8de4e2f340d6206aee523541 | tpot | base.py | 11 | 11 | https://github.com/EpistasisLab/tpot.git | 2 | 61 | 0 | 30 | 97 | Python | {
"docstring": "Compile a DEAP pipeline into a sklearn pipeline.\n\n Parameters\n ----------\n expr: DEAP individual\n The DEAP pipeline to be compiled\n\n Returns\n -------\n sklearn_pipeline: sklearn.pipeline.Pipeline\n ",
"language": "en",
"n_whitespa... | def _compile_to_sklearn(self, expr):
sklearn_pipeline_str = generate_pipeline_code(
expr_to_tree(expr, self._pset), self.operators
)
sklearn_pipeline = eval(sklearn_pipeline_str, self.operators_context)
sklearn_pipeline.memory = self._memory
if self.random_st... | |
47,902 | 196,402 | 189 | sympy/matrices/repmatrix.py | 49 | 13 | def equals(self, other, failing_expression=False):
if self.shape != getattr(other, 'shape', None):
retu | Moved imports to higher level | equals | 59d22b6bb7287613d598611027f640d068ca5748 | sympy | repmatrix.py | 13 | 12 | https://github.com/sympy/sympy.git | 7 | 93 | 0 | 32 | 141 | Python | {
"docstring": "Applies ``equals`` to corresponding elements of the matrices,\n trying to prove that the elements are equivalent, returning True\n if they are, False if any pair is not, and None (or the first\n failing expression if failing_expression is True) if it cannot\n be decided if ... | def equals(self, other, failing_expression=False):
if self.shape != getattr(other, 'shape', None):
return False
rv = True
for i in range(self.rows):
for j in range(self.cols):
ans = self[i, j].equals(other[i, j], failing_expression)
... | |
73,623 | 251,177 | 44 | mitmproxy/addons/blocklist.py | 8 | 6 | def load(self, loader):
loader.add_option(
"b | use Python 3.9+ typing | load | fdde9ba3b3caaa2654048cec0af07bfcc3a6a3f8 | mitmproxy | blocklist.py | 8 | 11 | https://github.com/mitmproxy/mitmproxy.git | 1 | 23 | 0 | 8 | 37 | Python | {
"docstring": "\n Block matching requests and return an empty response with the specified HTTP status.\n Option syntax is \"/flow-filter/status-code\", where flow-filter describes\n which requests this rule should be applied to and status-code is the HTTP status code to return for\n ... | def load(self, loader):
loader.add_option(
"block_list", Sequence[str], [],
)
| |
1,691 | 9,778 | 59 | gensim/models/translation_matrix.py | 24 | 15 | def train(self, tagged_docs):
m1 = [self.source_lang_vec.dv[item.tags].flatten() for item in tagged_docs]
m2 = [self.ta | Replace np.multiply with np.square and copyedit in translation_matrix.py (#3374)
* Replace np.multiply with np.square and copyedit
* Copyedit translation_matrix.py
Co-authored-by: Michael Penkov <m@penkov.dev> | train | 77c3a7ff5254346146d0e9eedf8e84fb6d577878 | gensim | translation_matrix.py | 12 | 5 | https://github.com/RaRe-Technologies/gensim.git | 3 | 76 | 0 | 17 | 116 | Python | {
"docstring": "Build the translation matrix to map from the source model's vectors to target model's vectors\n\n Parameters\n ----------\n tagged_docs : list of :class:`~gensim.models.doc2vec.TaggedDocument`, Documents\n that will be used for training, both the source language documen... | def train(self, tagged_docs):
m1 = [self.source_lang_vec.dv[item.tags].flatten() for item in tagged_docs]
m2 = [self.target_lang_vec.dv[item.tags].flatten() for item in tagged_docs]
self.translation_matrix = np.linalg.lstsq(m2, m1, -1)[0]
return self.translation_matrix
| |
12,993 | 62,568 | 35 | .venv/lib/python3.8/site-packages/pip/_vendor/html5lib/serializer.py | 20 | 11 | def serialize(input, tree="etree", encoding=None, **serializer_opts):
# XXX: Should we cache this?
walker = treewalkers.getTreeWalker(tree)
s = HTMLSerializer(**serializer_opts)
return s.render(walker(input), encoding)
| upd; format | serialize | f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | transferlearning | serializer.py | 9 | 4 | https://github.com/jindongwang/transferlearning.git | 1 | 44 | 0 | 19 | 73 | Python | {
"docstring": "Serializes the input token stream using the specified treewalker\n\n :arg input: the token stream to serialize\n\n :arg tree: the treewalker to use\n\n :arg encoding: the encoding to use\n\n :arg serializer_opts: any options to pass to the\n :py:class:`html5lib.serializer.HTMLSerial... | def serialize(input, tree="etree", encoding=None, **serializer_opts):
# XXX: Should we cache this?
walker = treewalkers.getTreeWalker(tree)
s = HTMLSerializer(**serializer_opts)
return s.render(walker(input), encoding)
| |
1,853 | 10,563 | 83 | jina/parsers/__init__.py | 28 | 13 | def set_client_cli_parser(parser=None):
if not parser:
from jina.parsers.base import set_base_parser
parser = set_base_parser()
from jina.parsers.peapods.runtimes.remote import mixin_client_gateway_parser
from jina.parsers.client import (
mixin_client_features_parser,
... | refactor: use absolute imports (#4167) | set_client_cli_parser | cea300655ed8be70d74c390ca12e8b09fb741665 | jina | __init__.py | 10 | 13 | https://github.com/jina-ai/jina.git | 2 | 64 | 0 | 23 | 99 | Python | {
"docstring": "Set the parser for the cli client\n\n :param parser: an optional existing parser to build upon\n :return: the parser\n ",
"language": "en",
"n_whitespaces": 28,
"n_words": 19,
"vocab_size": 15
} | def set_client_cli_parser(parser=None):
if not parser:
from jina.parsers.base import set_base_parser
parser = set_base_parser()
from jina.parsers.peapods.runtimes.remote import mixin_client_gateway_parser
from jina.parsers.client import (
mixin_client_features_parser,
... | |
5,141 | 27,924 | 111 | saleor/graphql/discount/mutations/sale_create.py | 36 | 17 | def send_sale_toggle_notification(info, instance, catalogue):
manager = info.context.plugins
now = datetime.now(pytz.utc)
start_date = instance.start_date
end_date = instance.end_date
if (start_date and start_date <= now) and (not end_date or not end_date <= now):
... | New event for starting and ending sales (#10110)
* Add sale started and sale ended webhooks
* Add started_notification_sent and ended_notification_sent flags to Sale model
* Add sale_webhook_schedule
* Add send_sale_started_and_sale_ended_notifications discount task
* Add tests for discount tasks
* Move... | send_sale_toggle_notification | 67492396aa41d068cac82e8fa328f218b5951d13 | saleor | sale_create.py | 12 | 9 | https://github.com/saleor/saleor.git | 5 | 79 | 0 | 26 | 128 | Python | {
"docstring": "Send a notification about starting or ending sale if it hasn't been sent yet.\n\n Send the notification when the start date is before the current date and the\n sale is not already finished.\n ",
"language": "en",
"n_whitespaces": 54,
"n_words": 33,
"vocab_size": 25
} | def send_sale_toggle_notification(info, instance, catalogue):
manager = info.context.plugins
now = datetime.now(pytz.utc)
start_date = instance.start_date
end_date = instance.end_date
if (start_date and start_date <= now) and (not end_date or not end_date <= now):
... | |
@bcoo_todense_p.def_impl | 26,536 | 119,028 | 11 | jax/experimental/sparse/bcoo.py | 10 | 9 | def bcoo_todense(data, indices, *, spinfo):
return bcoo_todense_p.bind(jnp.asarray(data), jnp.asarray(indices), spinfo=spin | [sparse] generalize metadata argument in BCOO primitives | bcoo_todense | 2c20d82776fea482aaf52e18ebad4f7fce5c3a81 | jax | bcoo.py | 9 | 2 | https://github.com/google/jax.git | 1 | 35 | 1 | 10 | 61 | Python | {
"docstring": "Convert batched sparse matrix to a dense matrix.\n\n Args:\n data : array of shape ``batch_dims + (nse,) + block_dims``.\n indices : array of shape ``batch_dims + (n_sparse, nse)``\n spinfo : BCOOInfo. In particular, this includes the shape\n of the matrix, which is equal to ``batch_dim... | def bcoo_todense(data, indices, *, spinfo):
return bcoo_todense_p.bind(jnp.asarray(data), jnp.asarray(indices), spinfo=spinfo)
@bcoo_todense_p.def_impl |
30,685 | 135,648 | 48 | rllib/utils/actor_manager.py | 16 | 10 | def ignore_ray_errors(self) -> Iterator[ResultOrError]:
return self._Iterator(
[r for r in self.result_or_errors if not isinstance(r.ge | Refactor ActorManager to store underlying remote actors in dict. (#29953)
Signed-off-by: Jun Gong <jungong@anyscale.com> | ignore_ray_errors | b84dac2609bd587c43ed17bb6fa18fb7241a41de | ray | actor_manager.py | 14 | 10 | https://github.com/ray-project/ray.git | 3 | 38 | 0 | 16 | 61 | Python | {
"docstring": "Return an iterator over the results, skipping only Ray errors.\n\n Similar to ignore_errors, but only skips Errors raised from the\n Ray framework. This is useful for application that wants to handle\n errors from user code differently.\n ",
"language": "en",
"n_whitesp... | def ignore_ray_errors(self) -> Iterator[ResultOrError]:
return self._Iterator(
[r for r in self.result_or_errors if not isinstance(r.get(), RayError)]
)
| |
@dataclasses.dataclass | 117,906 | 321,782 | 70 | qutebrowser/utils/usertypes.py | 21 | 7 | def certificate_was_accepted(self) -> None:
if not self.is_overridable():
return False
if self._certificate_accepted is None:
raise ValueError("No decision taken yet")
return self._certificate_accepted
| lint: Fix remaining pylint issues | certificate_was_accepted | ec8eebf99640d5a73072d05e73c6ea9b2ebea556 | qutebrowser | usertypes.py | 10 | 7 | https://github.com/qutebrowser/qutebrowser.git | 3 | 34 | 1 | 17 | 67 | Python | {
"docstring": "Check whether the certificate was accepted by the user.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 8
} | def certificate_was_accepted(self) -> None:
if not self.is_overridable():
return False
if self._certificate_accepted is None:
raise ValueError("No decision taken yet")
return self._certificate_accepted
@dataclasses.dataclass |
35,292 | 153,191 | 65 | modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py | 11 | 6 | def mask(self, row_indices, col_indices):
| FIX-#3675: Expand virtual partitioning utility (#3886)
Co-authored-by: mvashishtha <mahesh@ponder.io>
Co-authored-by: jeffreykennethli <jkli@ponder.io>
Co-authored-by: Anatoly Myachev <anatoly.myachev@intel.com>
Co-authored-by: Vasily Litvinov <vasilij.n.litvinov@intel.com>
Co-authored-by: Alexey Prutskov <alexey.... | mask | 8d1004fdbdaa05700613c8e6287641a732acf606 | modin | virtual_partition.py | 12 | 6 | https://github.com/modin-project/modin.git | 1 | 30 | 0 | 11 | 47 | Python | {
"docstring": "\n Create (synchronously) a mask that extracts the indices provided.\n\n Parameters\n ----------\n row_indices : list-like, slice or label\n The row labels for the rows to extract.\n col_indices : list-like, slice or label\n The column labels fo... | def mask(self, row_indices, col_indices):
return (
self.force_materialization()
.list_of_partitions_to_combine[0]
.mask(row_indices, col_indices)
)
| |
48,898 | 198,386 | 92 | sympy/integrals/intpoly.py | 46 | 20 | def left_integral3D(facets, index, expr, vertices, hp_param, degree):
value = S.Zero
facet = facets[index]
x0 = vertices[fac | Cleanup loops and ranges | left_integral3D | 7d773eb18daaef3c54f34d1ac6cbc5b83a5bb16c | sympy | intpoly.py | 14 | 10 | https://github.com/sympy/sympy.git | 2 | 103 | 0 | 37 | 149 | Python | {
"docstring": "Computes the left integral of Eq 10 in Chin et al.\n\n Explanation\n ===========\n\n For the 3D case, this is the sum of the integral values over constituting\n line segments of the face (which is accessed by facets[index]) multiplied\n by the distance between the first point of facet a... | def left_integral3D(facets, index, expr, vertices, hp_param, degree):
value = S.Zero
facet = facets[index]
x0 = vertices[facet[0]]
facet_len = len(facet)
for i, fac in enumerate(facet):
side = (vertices[fac], vertices[facet[(i + 1) % facet_len]])
value += distance_to_side(x0, si... | |
6,017 | 32,887 | 111 | src/transformers/models/deberta/modeling_tf_deberta.py | 32 | 21 | def xdropout(self, inputs):
mask = tf.cast(
1
- tf.compat.v1.distributions.Bernoulli(probs=1.0 - self.drop_prob).sample(sample_shape=shape_list(inputs)),
tf.bool,
| TF: XLA-trainable DeBERTa v2 (#18546)
* fix deberta issues
* add different code paths for gpu and tpu
* shorter gpu take along axis
* Stable Dropout without tf cond
* variable must be float | xdropout | 34aad0dac000508015d09ed7cf7c88adb5a0e308 | transformers | modeling_tf_deberta.py | 16 | 11 | https://github.com/huggingface/transformers.git | 2 | 105 | 0 | 27 | 143 | Python | {
"docstring": "\n Applies dropout to the inputs, as vanilla dropout, but also scales the remaining elements up by 1/drop_prob.\n ",
"language": "en",
"n_whitespaces": 32,
"n_words": 17,
"vocab_size": 16
} | def xdropout(self, inputs):
mask = tf.cast(
1
- tf.compat.v1.distributions.Bernoulli(probs=1.0 - self.drop_prob).sample(sample_shape=shape_list(inputs)),
tf.bool,
)
scale = tf.convert_to_tensor(1.0 / (1 - self.drop_prob), dtype=tf.float32)
if ... | |
26,500 | 118,955 | 122 | lib/tests/streamlit/legacy_add_rows_test.py | 35 | 17 | def test_deltas_that_melt_dataframes(self):
deltas = self._get_deltas_that_melt_dataframe | Remove legacy "`add_rows` coalescing" from ForwardMsgQueue (#4485)
Removes the `add_rows` legacy DataFrame concatenation implementation _from Python_. (To be clear: `add_rows` still works for legacy DataFrames, but the logic is frontend-only now. This is already how Arrow DataFrame concatenation is implemented.)
##... | test_deltas_that_melt_dataframes | 0f76064dbb9b9405173effe7f872aa8a8dba69cc | streamlit | legacy_add_rows_test.py | 13 | 8 | https://github.com/streamlit/streamlit.git | 2 | 74 | 0 | 30 | 116 | Python | {
"docstring": "Some element types require that their dataframes are\n 'melted' (https://pandas.pydata.org/docs/reference/api/pandas.melt.html)\n before being sent to the frontend. Test that the melting occurs.\n ",
"language": "en",
"n_whitespaces": 43,
"n_words": 21,
"vocab_size": 19
} | def test_deltas_that_melt_dataframes(self):
deltas = self._get_deltas_that_melt_dataframes()
for delta in deltas:
el = delta(DATAFRAME)
el._legacy_add_rows(NEW_ROWS)
df_proto = _get_data_frame(self.get_delta_from_queue())
# Test that the add_ro... | |
45,948 | 188,973 | 1,294 | psutil/_pslinux.py | 326 | 47 | def sensors_temperatures():
ret = collections.defaultdict(list)
basenames = glob.glob('/sys/class/hwmon/hwmon*/temp*_*')
# CentOS has an intermediate /device directory:
# https://github.com/giampaolo/psutil/issues/971
# https://github.com/nicolargo/glances/issues/1060
basenames.extend(glob.... | [Linux] cat/bcat utils refactoring (#2053) | sensors_temperatures | 46cb6c212a870b36bd0af17c48dd29f53468734b | psutil | _pslinux.py | 21 | 72 | https://github.com/giampaolo/psutil.git | 21 | 563 | 0 | 150 | 928 | Python | {
"docstring": "Return hardware (CPU and others) temperatures as a dict\n including hardware name, label, current, max and critical\n temperatures.\n\n Implementation notes:\n - /sys/class/hwmon looks like the most recent interface to\n retrieve this info, and this implementation relies on it\n ... | def sensors_temperatures():
ret = collections.defaultdict(list)
basenames = glob.glob('/sys/class/hwmon/hwmon*/temp*_*')
# CentOS has an intermediate /device directory:
# https://github.com/giampaolo/psutil/issues/971
# https://github.com/nicolargo/glances/issues/1060
basenames.extend(glob.... | |
15,901 | 72,541 | 223 | wagtail/admin/views/pages/workflow.py | 68 | 36 | def preview_revision_for_task(request, page_id, task_id):
| Reformat with black | preview_revision_for_task | d10f15e55806c6944827d801cd9c2d53f5da4186 | wagtail | workflow.py | 15 | 24 | https://github.com/wagtail/wagtail.git | 3 | 140 | 0 | 57 | 221 | Python | {
"docstring": "Preview the revision linked to the in-progress TaskState of a specified Task. This enables pages in moderation\n to be edited and new TaskStates linked to the new revisions created, with preview links remaining valid",
"language": "en",
"n_whitespaces": 36,
"n_words": 34,
"vocab_size": 28
} | def preview_revision_for_task(request, page_id, task_id):
page = get_object_or_404(Page, id=page_id)
task = get_object_or_404(Task, id=task_id).specific
try:
task_state = TaskState.objects.get(
page_revision__page=page, task=task, status=TaskState.STATUS_IN_PROGRESS
)
e... | |
56,492 | 221,726 | 94 | python3.10.4/Lib/contextlib.py | 44 | 9 | def push_async_callback(self, callback, /, *args, **kwds):
_exit_wrapper = self._create_async_cb_wrapper(callback, *args, **kwds)
# We changed the signature, so using @wraps is not appropriate, but
# setti | add python 3.10.4 for windows | push_async_callback | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | XX-Net | contextlib.py | 9 | 5 | https://github.com/XX-net/XX-Net.git | 1 | 45 | 0 | 39 | 73 | Python | {
"docstring": "Registers an arbitrary coroutine function and arguments.\n\n Cannot suppress exceptions.\n ",
"language": "en",
"n_whitespaces": 24,
"n_words": 10,
"vocab_size": 10
} | def push_async_callback(self, callback, /, *args, **kwds):
_exit_wrapper = self._create_async_cb_wrapper(callback, *args, **kwds)
# We changed the signature, so using @wraps is not appropriate, but
# setting __wrapped__ may still help with introspection.
_exit_wrapper.__wrapped... | |
13,285 | 63,394 | 789 | .venv/lib/python3.8/site-packages/pip/_vendor/pyparsing.py | 135 | 35 | def scanString(self, instring, maxMatches=_MAX_INT, overlap=False):
if not self.streamlined:
self.streamline()
for e in self.ignoreExprs:
e.streamline()
if not self.keepTabs:
instring = _ustr(instring).expandtabs()
instrlen = len(instring)
... | upd; format | scanString | f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | transferlearning | pyparsing.py | 20 | 41 | https://github.com/jindongwang/transferlearning.git | 13 | 217 | 0 | 80 | 354 | Python | {
"docstring": "\n Scan the input string for expression matches. Each match will return the\n matching tokens, start location, and end location. May be called with optional\n ``maxMatches`` argument, to clip scanning after 'n' matches are found. If\n ``overlap`` is specified, then overl... | def scanString(self, instring, maxMatches=_MAX_INT, overlap=False):
if not self.streamlined:
self.streamline()
for e in self.ignoreExprs:
e.streamline()
if not self.keepTabs:
instring = _ustr(instring).expandtabs()
instrlen = len(instring)
... | |
35,932 | 154,339 | 83 | modin/core/execution/dask/implementations/pandas_on_dask/partitioning/partition.py | 18 | 10 | def add_to_apply_calls(self, func, *args, length=None, width=None, **kwargs):
return PandasOnDaskDataframePartition(
self._data,
call_queue=self.call_queue + [[func, args, kwargs]],
length=length,
width=width,
)
| PERF-#4794: Compute caches in `_propagate_index_objs` (#4888)
Co-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>
Signed-off-by: Myachev <anatoly.myachev@intel.com> | add_to_apply_calls | 39b36eb2a2e3bf3d612933e1c78545a8bb28cde4 | modin | partition.py | 11 | 7 | https://github.com/modin-project/modin.git | 1 | 54 | 0 | 18 | 76 | Python | {
"docstring": "\n Add a function to the call queue.\n\n Parameters\n ----------\n func : callable\n Function to be added to the call queue.\n *args : iterable\n Additional positional arguments to be passed in `func`.\n length : distributed.Future or int... | def add_to_apply_calls(self, func, *args, length=None, width=None, **kwargs):
return PandasOnDaskDataframePartition(
self._data,
call_queue=self.call_queue + [[func, args, kwargs]],
length=length,
width=width,
)
| |
6,208 | 34,178 | 141 | src/transformers/feature_extraction_utils.py | 48 | 18 | def to_json_string(self) -> str:
dictionary = self.to_dict()
for key, value in dictionary.items():
if isinstance(value, np.ndarray):
dictionary[key] = value.tolist()
# make sure private name "_processor_class" is correctly
# saved as "processor_clas... | [ASR pipeline] correct with lm pipeline (#15200)
* [ASR pipeline] correct with lm pipeline
* improve error | to_json_string | 497346d07ec39da3a7f38a7e0a67a4906c141ea3 | transformers | feature_extraction_utils.py | 12 | 15 | https://github.com/huggingface/transformers.git | 4 | 85 | 0 | 40 | 142 | Python | {
"docstring": "\n Serializes this instance to a JSON string.\n\n Returns:\n `str`: String containing all the attributes that make up this feature_extractor instance in JSON format.\n ",
"language": "en",
"n_whitespaces": 56,
"n_words": 23,
"vocab_size": 20
} | def to_json_string(self) -> str:
dictionary = self.to_dict()
for key, value in dictionary.items():
if isinstance(value, np.ndarray):
dictionary[key] = value.tolist()
# make sure private name "_processor_class" is correctly
# saved as "processor_clas... | |
5,070 | 26,810 | 357 | saleor/core/permissions/__init__.py | 125 | 28 | def one_of_permissions_or_auth_filter_required(context, permissions):
if not permissions:
return True
authorization_filters = [
p for p in permissions if isinstance(p, AuthorizationFilters)
]
permissions = [p for p in permissions if not isinstance(p, AuthorizationFilters)]
gra... | Include permissions in schema descriptions of protected fields (#9428)
* POC Generate permission description for queries
* Use PermissionField for app queries
* Rename functions checking object ownership
* Switch to PermissionsField in more fields
* CR fixes
* Add missing descriptions | one_of_permissions_or_auth_filter_required | f0a988e798dd86befbbf7a0eda1bc1a8cc94dda2 | saleor | __init__.py | 16 | 29 | https://github.com/saleor/saleor.git | 14 | 172 | 0 | 76 | 278 | Python | {
"docstring": "Determine whether user or app has rights to perform an action.\n\n The `context` parameter is the Context instance associated with the request.\n ",
"language": "en",
"n_whitespaces": 28,
"n_words": 22,
"vocab_size": 21
} | def one_of_permissions_or_auth_filter_required(context, permissions):
if not permissions:
return True
authorization_filters = [
p for p in permissions if isinstance(p, AuthorizationFilters)
]
permissions = [p for p in permissions if not isinstance(p, AuthorizationFilters)]
gra... | |
33,344 | 144,928 | 45 | python/ray/_private/runtime_env/_clonevirtualenv.py | 19 | 8 | def _dirmatch(path, matchwith):
matchlen = len(matchwith)
if (path.startswith(matchwith)
| [runtime env] Support clone `virtualenv` from an existing `virtualenv` (#22309)
Before this PR, we can't run ray in virtualenv, cause `runtime_env` does not support create a new virtualenv from an existing virtualenv.
More details:https://github.com/ray-project/ray/pull/21801#discussion_r796848499
Co-authored-b... | _dirmatch | 4c73560b313821fbfbb8c943e02c8b298b7c1731 | ray | _clonevirtualenv.py | 11 | 6 | https://github.com/ray-project/ray.git | 3 | 45 | 0 | 18 | 73 | Python | {
"docstring": "Check if path is within matchwith's tree.\n >>> _dirmatch('/home/foo/bar', '/home/foo/bar')\n True\n >>> _dirmatch('/home/foo/bar/', '/home/foo/bar')\n True\n >>> _dirmatch('/home/foo/bar/etc', '/home/foo/bar')\n True\n >>> _dirmatch('/home/foo/bar2', '/home/foo/bar')\n False\n... | def _dirmatch(path, matchwith):
matchlen = len(matchwith)
if (path.startswith(matchwith)
and path[matchlen:matchlen + 1] in [os.sep, '']):
return True
return False
| |
70,270 | 244,173 | 79 | mmdet/models/dense_heads/tood_head.py | 37 | 13 | def deform_sampling(self, feat, offset):
# it is an equivalent implementation of bilinear interpolation
b, c, h, w = feat.shape
weight = feat.new_ones(c, 1, 1, 1)
y = deform_conv2d(feat, offset, weight, 1, 0, 1, c, c)
return y
| [Fix] Avoid invalid bbox after deform_sampling (#7567)
* Avoid invalid bbox after deform_sampling
* replace in-place opertion with torch.where, update docstring
* Update | deform_sampling | b403751bd409795cf63fcc6aa7ee280326358bac | mmdetection | tood_head.py | 8 | 5 | https://github.com/open-mmlab/mmdetection.git | 1 | 57 | 0 | 30 | 79 | Python | {
"docstring": "Sampling the feature x according to offset.\n\n Args:\n feat (Tensor): Feature\n offset (Tensor): Spatial offset for feature sampling\n ",
"language": "en",
"n_whitespaces": 54,
"n_words": 18,
"vocab_size": 15
} | def deform_sampling(self, feat, offset):
# it is an equivalent implementation of bilinear interpolation
b, c, h, w = feat.shape
weight = feat.new_ones(c, 1, 1, 1)
y = deform_conv2d(feat, offset, weight, 1, 0, 1, c, c)
return y
| |
17,285 | 81,965 | 694 | awxkit/awxkit/api/pages/page.py | 171 | 47 | def page_identity(self, response, request_json=None):
request_path = response.request.path_url
if request_path == '/migrations_notran/':
raise exc.IsMigrating('You have been redirected to the migration-in-progress page.')
request_method = response.request.method.lower()
... | Register pages for the Instance peers and install bundle endpoints
This includes exposing a new interface for Page objects, Page.bytes,
to return the full bytestring contents of the response. | page_identity | 68a44529b6b77d2d43d7099b654560bfd8bbf518 | awx | page.py | 13 | 44 | https://github.com/ansible/awx.git | 15 | 337 | 0 | 104 | 536 | Python | {
"docstring": "Takes a `requests.Response` and\n returns a new __item_class__ instance if the request method is not a get, or returns\n a __class__ instance if the request path is different than the caller's `endpoint`.\n ",
"language": "en",
"n_whitespaces": 56,
"n_words": 32,
"vocab... | def page_identity(self, response, request_json=None):
request_path = response.request.path_url
if request_path == '/migrations_notran/':
raise exc.IsMigrating('You have been redirected to the migration-in-progress page.')
request_method = response.request.method.lower()
... | |
21,442 | 102,077 | 108 | lib/sysinfo.py | 33 | 16 | def _installed_conda(self):
if not self._is_conda:
return None
with Popen("conda list", shell=True, stdout=PIPE, stderr=PIPE) as conda:
stdout, stderr = conda.communicate()
if stderr:
return "Could not get package list"
installed = stdout.deco... | Allow decoding errors | _installed_conda | 48c886b3dce3d3117ad16edaf35c8abd28dc51f5 | faceswap | sysinfo.py | 12 | 9 | https://github.com/deepfakes/faceswap.git | 3 | 73 | 0 | 28 | 128 | Python | {
"docstring": " str: The list of installed Conda packages within Faceswap's scope. ",
"language": "en",
"n_whitespaces": 11,
"n_words": 10,
"vocab_size": 10
} | def _installed_conda(self):
if not self._is_conda:
return None
with Popen("conda list", shell=True, stdout=PIPE, stderr=PIPE) as conda:
stdout, stderr = conda.communicate()
if stderr:
return "Could not get package list"
installed = stdout.deco... | |
7,193 | 39,296 | 86 | recommenders/models/sasrec/model.py | 30 | 14 | def embedding(self, input_seq):
seq_embeddings = self.item_embedding_layer(input_seq)
seq_embeddings = seq_embeddings * (self.embedding_dim ** 0.5)
# FIXME
positional_seq = tf.expand_dims(tf.range(tf.shape(input_seq)[1]), 0)
| doc | embedding | d38dffc30c18e9e3280863b32dcc71d01757b181 | recommenders | model.py | 13 | 7 | https://github.com/microsoft/recommenders.git | 1 | 86 | 0 | 22 | 132 | Python | {
"docstring": "Compute the sequence and positional embeddings.\n\n Args:\n input_seq (tf.Tensor): Input sequence\n \n Returns:\n tf.Tensor, tf.Tensor:\n - Sequence embeddings.\n - Positional embeddings.\n \n ",
"language": "en",
"n_wh... | def embedding(self, input_seq):
seq_embeddings = self.item_embedding_layer(input_seq)
seq_embeddings = seq_embeddings * (self.embedding_dim ** 0.5)
# FIXME
positional_seq = tf.expand_dims(tf.range(tf.shape(input_seq)[1]), 0)
positional_seq = tf.tile(positional_seq, [tf... | |
78,648 | 266,902 | 808 | lib/ansible/utils/display.py | 223 | 36 | def display(self, msg, color=None, stderr=False, screen_only=False, log_only=False, newline=True):
nocolor = msg
if not log_only:
has_newline = msg.endswith(u'\n')
if has_newline:
msg2 = msg[:-1]
else:
msg2 = msg
... | Remove obsolete Python 2.x controller code. | display | 6f445ca6e5c9c8b85ccc5062e00508c69ca26fde | ansible | display.py | 16 | 34 | https://github.com/ansible/ansible.git | 13 | 229 | 0 | 128 | 385 | Python | {
"docstring": " Display a message to the user\n\n Note: msg *must* be a unicode string to prevent UnicodeError tracebacks.\n ",
"language": "en",
"n_whitespaces": 32,
"n_words": 17,
"vocab_size": 15
} | def display(self, msg, color=None, stderr=False, screen_only=False, log_only=False, newline=True):
nocolor = msg
if not log_only:
has_newline = msg.endswith(u'\n')
if has_newline:
msg2 = msg[:-1]
else:
msg2 = msg
... | |
78,254 | 265,983 | 105 | netbox/extras/views.py | 23 | 13 | def get_queryset(self, request):
queryset = SavedFilter.objects.all()
user = request.user
if user.is_superuser:
return queryset
if user.is_anonymous:
return queryset.filter(shared=True)
| Closes #9623: Implement saved filters (#10801)
* Initial work on saved filters
* Return only enabled/shared filters
* Add tests
* Clean up filtering of usable SavedFilters | get_queryset | 484efdaf75f267a43f9321b938fda1bc967b9e53 | netbox | views.py | 11 | 10 | https://github.com/netbox-community/netbox.git | 3 | 62 | 0 | 18 | 101 | Python | {
"docstring": "\n Return only shared SavedFilters, or those owned by the current user, unless\n this is a superuser.\n ",
"language": "en",
"n_whitespaces": 38,
"n_words": 16,
"vocab_size": 16
} | def get_queryset(self, request):
queryset = SavedFilter.objects.all()
user = request.user
if user.is_superuser:
return queryset
if user.is_anonymous:
return queryset.filter(shared=True)
return queryset.filter(
Q(shared=True) | Q(user=u... | |
77,779 | 264,666 | 264 | netbox/extras/api/views.py | 64 | 36 | def list(self, request):
| Save old JobResults | list | f13a00b2dd33bffc3048c861b494096df457f212 | netbox | views.py | 18 | 18 | https://github.com/netbox-community/netbox.git | 4 | 135 | 0 | 54 | 222 | Python | {
"docstring": "\n Compile all reports and their related results (if any). Result data is deferred in the list view.\n ",
"language": "en",
"n_whitespaces": 32,
"n_words": 17,
"vocab_size": 17
} | def list(self, request):
report_list = []
report_content_type = ContentType.objects.get(app_label='extras', model='report')
results = {
r.name: r
for r in JobResult.objects.filter(
obj_type=report_content_type,
status__in=JobResult... | |
78,253 | 265,967 | 121 | netbox/extras/filtersets.py | 38 | 12 | def _usable(self, queryset, name, value):
user = self.request.user if self.request else None
if not user or user.is_anonymous:
if value:
return queryset.filter(enabled=True, shared=True)
return queryset.filter(Q(enabled=False) | Q(shared=False))
| Closes #9623: Implement saved filters (#10801)
* Initial work on saved filters
* Return only enabled/shared filters
* Add tests
* Clean up filtering of usable SavedFilters | _usable | 484efdaf75f267a43f9321b938fda1bc967b9e53 | netbox | filtersets.py | 15 | 9 | https://github.com/netbox-community/netbox.git | 6 | 127 | 0 | 27 | 199 | Python | {
"docstring": "\n Return only SavedFilters that are both enabled and are shared (or belong to the current user).\n ",
"language": "en",
"n_whitespaces": 31,
"n_words": 16,
"vocab_size": 15
} | def _usable(self, queryset, name, value):
user = self.request.user if self.request else None
if not user or user.is_anonymous:
if value:
return queryset.filter(enabled=True, shared=True)
return queryset.filter(Q(enabled=False) | Q(shared=False))
i... | |
14,040 | 65,853 | 12 | erpnext/education/api.py | 23 | 11 | def get_current_enrollment(student, academic_year=None):
current_academic_year = academic_year or frappe.defaul | style: format code with black | get_current_enrollment | 494bd9ef78313436f0424b918f200dab8fc7c20b | erpnext | api.py | 11 | 19 | https://github.com/frappe/erpnext.git | 3 | 55 | 0 | 21 | 85 | Python | {
"docstring": "\n\t\tselect\n\t\t\tname as program_enrollment, student_name, program, student_batch_name as student_batch,\n\t\t\tstudent_category, academic_term, academic_year\n\t\tfrom\n\t\t\t`tabProgram Enrollment`\n\t\twhere\n\t\t\tstudent = %s and academic_year = %s\n\t\torder by creation",
"language": "en",
... | def get_current_enrollment(student, academic_year=None):
current_academic_year = academic_year or frappe.defaults.get_defaults().academic_year
program_enrollment_list = frappe.db.sql(
,
(student, current_academic_year),
as_dict=1,
)
if program_enrollment_list:
return program_enrollment_list[0]
else:
ret... | |
@keras_export("keras.applications.inception_resnet_v2.preprocess_input") | 83,430 | 280,749 | 443 | keras/applications/inception_resnet_v2.py | 180 | 28 | def inception_resnet_block(x, scale, block_type, block_idx, activation="relu"):
if block_type == "block35":
branch_0 = conv2d_bn(x, 32, 1)
branch_1 = conv2d_bn(x, 32, 1)
branch_1 = conv2d_bn(branch_1, 32, 3)
branch_2 = conv2d_bn(x, 32, 1)
branch_2 = conv2d_bn(branch_2, 4... | Removes the serialization of lambdas Keras tests where necessary and adds SafeModeScope all other lambda-based serialization tests.
PiperOrigin-RevId: 495432774 | inception_resnet_block | e52c89c7d1bd52d1f0db0da86a72322ba72c1dc1 | keras | inception_resnet_v2.py | 14 | 44 | https://github.com/keras-team/keras.git | 6 | 336 | 1 | 93 | 520 | Python | {
"docstring": "Adds an Inception-ResNet block.\n\n This function builds 3 types of Inception-ResNet blocks mentioned\n in the paper, controlled by the `block_type` argument (which is the\n block name used in the official TF-slim implementation):\n - Inception-ResNet-A: `block_type='block35'`\n - Incep... | def inception_resnet_block(x, scale, block_type, block_idx, activation="relu"):
if block_type == "block35":
branch_0 = conv2d_bn(x, 32, 1)
branch_1 = conv2d_bn(x, 32, 1)
branch_1 = conv2d_bn(branch_1, 32, 3)
branch_2 = conv2d_bn(x, 32, 1)
branch_2 = conv2d_bn(branch_2, 4... |
19,814 | 100,317 | 152 | lib/gui/analysis/stats.py | 38 | 14 | def _get_calculations(self):
for selection in self._selections:
if selection == "raw":
continue
logger.debug("Calculating: %s", selection)
method = getattr(self, f"_calc_{selection}")
raw_keys = [key for key in self._stats if key.startswit... | 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 -... | _get_calculations | c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf | faceswap | stats.py | 15 | 10 | https://github.com/deepfakes/faceswap.git | 6 | 79 | 0 | 28 | 156 | Python | {
"docstring": " Perform the required calculations and populate :attr:`stats`. ",
"language": "en",
"n_whitespaces": 8,
"n_words": 7,
"vocab_size": 7
} | def _get_calculations(self):
for selection in self._selections:
if selection == "raw":
continue
logger.debug("Calculating: %s", selection)
method = getattr(self, f"_calc_{selection}")
raw_keys = [key for key in self._stats if key.startswit... | |
36,917 | 157,377 | 809 | ldm/models/diffusion/dpm_solver/dpm_solver.py | 228 | 37 | def multistep_dpm_solver_second_update(self, x, model_prev_list, t_prev_list, t, solver_type="dpm_solver"):
if solver_type not in ['dpm_solver', 'taylor']:
raise ValueError("'solver_type' must be either 'dpm_solver' or 'taylor', got {}".format(solver_type))
ns = self.noise_schedule
... | release more models | multistep_dpm_solver_second_update | ca86da3a30c4e080d4db8c25fca73de843663cb4 | stablediffusion | dpm_solver.py | 25 | 43 | https://github.com/Stability-AI/stablediffusion.git | 7 | 449 | 0 | 88 | 681 | Python | {
"docstring": "\n Multistep solver DPM-Solver-2 from time `t_prev_list[-1]` to time `t`.\n Args:\n x: A pytorch tensor. The initial value at time `s`.\n model_prev_list: A list of pytorch tensor. The previous computed model values.\n t_prev_list: A list of pytorch tenso... | def multistep_dpm_solver_second_update(self, x, model_prev_list, t_prev_list, t, solver_type="dpm_solver"):
if solver_type not in ['dpm_solver', 'taylor']:
raise ValueError("'solver_type' must be either 'dpm_solver' or 'taylor', got {}".format(solver_type))
ns = self.noise_schedule
... | |
41,599 | 175,317 | 64 | Lib/enum.py | 25 | 17 | def global_enum(cls, update_str=False):
if issubclass(cls, Flag):
cls.__repr__ = global_flag_repr
else:
cls.__repr__ = global_enum_repr
if not issubclass(cls, ReprEnum) or update_str:
cls.__str__ = global_str
sys.modules[cls.__module__].__dict__.updat | bpo-40066: [Enum] update str() and format() output (GH-30582)
Undo rejected PEP-663 changes:
- restore `repr()` to its 3.10 status
- restore `str()` to its 3.10 status
New changes:
- `IntEnum` and `IntFlag` now leave `__str__` as the original `int.__str__` so that str() and format() return the same result
... | global_enum | acf7403f9baea3ae1119fc6b4a3298522188bf96 | cpython | enum.py | 10 | 9 | https://github.com/python/cpython.git | 4 | 65 | 0 | 20 | 104 | Python | {
"docstring": "\n decorator that makes the repr() of an enum member reference its module\n instead of its class; also exports all members to the enum's module's\n global namespace\n ",
"language": "en",
"n_whitespaces": 39,
"n_words": 26,
"vocab_size": 23
} | def global_enum(cls, update_str=False):
if issubclass(cls, Flag):
cls.__repr__ = global_flag_repr
else:
cls.__repr__ = global_enum_repr
if not issubclass(cls, ReprEnum) or update_str:
cls.__str__ = global_str
sys.modules[cls.__module__].__dict__.update(cls.__members__)
r... | |
80,939 | 272,022 | 584 | keras/engine/training_v1.py | 101 | 28 | def create_training_target(self, target, run_eagerly=False):
if self.has_training_target():
raise ValueError(
"The training_target field for the _TrainingEndpoint "
"instance has already been populated"
)
if run_eagerly:
# When... | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | create_training_target | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | training_v1.py | 17 | 35 | https://github.com/keras-team/keras.git | 7 | 172 | 0 | 64 | 276 | Python | {
"docstring": "Create training_target instance and update the self.training_target.\n\n Note that the input target should just be a tensor or None, and\n corresponding training target will be created based on the output and\n loss_fn.\n\n Args:\n target: the target tensor for the... | def create_training_target(self, target, run_eagerly=False):
if self.has_training_target():
raise ValueError(
"The training_target field for the _TrainingEndpoint "
"instance has already been populated"
)
if run_eagerly:
# When... | |
8,117 | 43,999 | 130 | tests/models/test_dag.py | 45 | 23 | def test_set_task_instance_state(run_id, execution_date, session, dag_maker):
start_date = datetime_tz(2020, 1, 1)
with dag_maker("test_set_task_instance_state", start_date=start_date, session=session) as dag:
task_1 = DummyOperator(task_id="task_1")
task_2 = DummyOperator(task_id="ta | Use `DagRun.run_id` instead of `execution_date` when updating state of TIs(UI & REST API) (#18724)
We can now use run_id as well as execution_date to update states
of task instances
Co-authored-by: Tzu-ping Chung <uranusjr@gmail.com>
Co-authored-by: Ash Berlin-Taylor <ash_github@firemirror.com> | test_set_task_instance_state | 2b4bf7fe67fc656ceb7bdaad36453b7a5b83ef04 | airflow | test_dag.py | 12 | 39 | https://github.com/apache/airflow.git | 2 | 321 | 0 | 38 | 188 | Python | {
"docstring": "Test that set_task_instance_state updates the TaskInstance state and clear downstream failed",
"language": "en",
"n_whitespaces": 10,
"n_words": 11,
"vocab_size": 11
} | def test_set_task_instance_state(run_id, execution_date, session, dag_maker):
start_date = datetime_tz(2020, 1, 1)
with dag_maker("test_set_task_instance_state", start_date=start_date, session=session) as dag:
task_1 = DummyOperator(task_id="task_1")
task_2 = DummyOperator(task_id="task_2"... | |
95,433 | 296,453 | 260 | homeassistant/components/roon/config_flow.py | 56 | 22 | async def async_step_link(self, user_input=None):
errors = {}
if user_input is not None:
# Do not authenticate if the host is already configured
self._async_abort_entries_match({CONF_HOST: self._host})
try:
info = await authenticate(
... | Improve roon integraton (#66000)
* Update to new library, revise discovery to work with new library, specify port to work with new library.
* Move user gui to fallback.
* Revise tests.
* Handle old config.
* Improve debugging, refresh faster on load.
* Remove duplicate.
* Bump library version.
* F... | async_step_link | 23264c8fd4a3f8bcff5961ed11cab6388d3c67a4 | core | config_flow.py | 14 | 16 | https://github.com/home-assistant/core.git | 4 | 107 | 0 | 46 | 182 | Python | {
"docstring": "Handle linking and authenticting with the roon server.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | async def async_step_link(self, user_input=None):
errors = {}
if user_input is not None:
# Do not authenticate if the host is already configured
self._async_abort_entries_match({CONF_HOST: self._host})
try:
info = await authenticate(
... | |
54,138 | 215,744 | 24 | tests/pytests/unit/utils/win_dacl/test_get_sid_string.py | 12 | 10 | def test_get_sid_string_none():
sid_obj = sa | Add tests, migrate some tests to pytest | test_get_sid_string_none | 3bb43882e727b1d36abe2e501759c9c5e9048ecf | salt | test_get_sid_string.py | 10 | 4 | https://github.com/saltstack/salt.git | 1 | 39 | 0 | 11 | 66 | Python | {
"docstring": "\n Validate getting a null sid (S-1-0-0) when a null sid is passed\n ",
"language": "en",
"n_whitespaces": 19,
"n_words": 12,
"vocab_size": 9
} | def test_get_sid_string_none():
sid_obj = salt.utils.win_dacl.get_sid(None)
assert isinstance(sid_obj, pywintypes.SIDType)
assert salt.utils.win_dacl.get_sid_string(sid_obj) == "S-1-0-0"
| |
118,175 | 322,461 | 31 | paddlenlp/datasets/dataset.py | 10 | 8 | def read(self, filename, split='train'):
label_list = self.get_labels()
vocab_info = self.get_vocab()
| [cblue] support converting labels of multi-tasks | read | ba3ea1cffa14d8fddb4d61239d691eba1d711a1d | PaddleNLP | dataset.py | 8 | 40 | https://github.com/PaddlePaddle/PaddleNLP.git | 12 | 260 | 0 | 9 | 46 | Python | {
"docstring": "\n Returns a dataset containing all the examples that can be read from the file path.\n\n If `self.lazy` is False, this eagerly reads all instances from `self._read()`\n and returns a `MapDataset`.\n\n If `self.lazy` is True, this returns an `IterDataset`, which internally\... | def read(self, filename, split='train'):
label_list = self.get_labels()
vocab_info = self.get_vocab()
| |
16,279 | 74,629 | 47 | wagtail/core/tests/test_whitelist.py | 12 | 9 | def test_no_rule_for_attr(self):
tag = self.soup.b
fn = attribute_rule({"snowman": "barbec | Reformat with black | test_no_rule_for_attr | d10f15e55806c6944827d801cd9c2d53f5da4186 | wagtail | test_whitelist.py | 11 | 5 | https://github.com/wagtail/wagtail.git | 1 | 38 | 0 | 11 | 70 | Python | {
"docstring": "\n Test that attribute_rule() drops attributes for\n which no rule has been defined.\n ",
"language": "en",
"n_whitespaces": 34,
"n_words": 12,
"vocab_size": 12
} | def test_no_rule_for_attr(self):
tag = self.soup.b
fn = attribute_rule({"snowman": "barbecue"})
fn(tag)
self.assertEqual(str(tag), "<b>baz</b>")
| |
@DeveloperAPI | 29,861 | 132,902 | 477 | python/ray/util/check_serialize.py | 103 | 26 | def _inspect_generic_serialization(base_obj, depth, parent, failure_set):
assert not inspect.isfunction(base_obj)
functions = inspect.getmembers(base_obj, predicate=inspect.isfunction)
found = False
with _printer.indent():
for name, obj in functions:
serializable, _ = inspect_se... | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | _inspect_generic_serialization | 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | ray | check_serialize.py | 14 | 37 | https://github.com/ray-project/ray.git | 11 | 184 | 1 | 60 | 302 | Python | {
"docstring": "Adds the first-found non-serializable element to the failure_set.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 7
} | def _inspect_generic_serialization(base_obj, depth, parent, failure_set):
assert not inspect.isfunction(base_obj)
functions = inspect.getmembers(base_obj, predicate=inspect.isfunction)
found = False
with _printer.indent():
for name, obj in functions:
serializable, _ = inspect_se... |
49,752 | 200,643 | 863 | sympy/combinatorics/perm_groups.py | 287 | 20 | def is_dihedral(self):
r
if self._is_dihedral is not None:
return self._is_dihedral
order = self.order()
if order % 2 == 1:
self._is_dihedral = False
return False
if or | Add a `PermutationGroup.is_dihedral` property | is_dihedral | 624e6f073d5d20e78484f5a0b477469f83678b88 | sympy | perm_groups.py | 12 | 75 | https://github.com/sympy/sympy.git | 18 | 314 | 0 | 131 | 508 | Python | {
"docstring": "\n Return ``True`` if the group is dihedral.\n\n Examples\n ========\n\n >>> from sympy.combinatorics.perm_groups import PermutationGroup\n >>> from sympy.combinatorics.permutations import Permutation\n >>> from sympy.combinatorics.named_groups import Symmetri... | def is_dihedral(self):
r
if self._is_dihedral is not None:
return self._is_dihedral
order = self.order()
if order % 2 == 1:
self._is_dihedral = False
return False
if order == 2:
self._is_dihedral = True
return True
... | |
78,343 | 266,230 | 45 | netbox/dcim/signals.py | 14 | 12 | def extend_rearport_cable_paths(instance, created, **kwargs):
if created:
rearport = instance.rear_port
for cablepath in CablePath.objects.filter(_nodes__contains=rearport):
| Fixes #10969: Update cable paths ending at associated rear port when creating new front ports | extend_rearport_cable_paths | 4e27e8d3dd2cbfe3279bda3631ca92a7facdd334 | netbox | signals.py | 11 | 5 | https://github.com/netbox-community/netbox.git | 3 | 38 | 0 | 14 | 62 | Python | {
"docstring": "\n When a new FrontPort is created, add it to any CablePaths which end at its corresponding RearPort.\n ",
"language": "en",
"n_whitespaces": 24,
"n_words": 17,
"vocab_size": 17
} | def extend_rearport_cable_paths(instance, created, **kwargs):
if created:
rearport = instance.rear_port
for cablepath in CablePath.objects.filter(_nodes__contains=rearport):
cablepath.retrace()
| |
19,840 | 100,345 | 1,104 | lib/gui/utils.py | 281 | 50 | def _load_images_to_cache(self, image_files, frame_dims, thumbnail_size):
logger.debug("Number image_files: %s, frame_dims: %s, thumbnail_size: %s",
len(image_files), frame_dims, thumbnail_size)
num_images = (frame_dims[0] // thumbnail_size) * (frame_dims[1] // thumbnail_si... | 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 -... | _load_images_to_cache | c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf | faceswap | utils.py | 17 | 61 | https://github.com/deepfakes/faceswap.git | 13 | 488 | 0 | 176 | 811 | Python | {
"docstring": " Load preview images to the image cache.\n\n Load new images and append to cache, filtering the cache the number of thumbnails that will\n fit inside the display panel.\n\n Parameters\n ----------\n image_files: list\n A list of new image files that have ... | def _load_images_to_cache(self, image_files, frame_dims, thumbnail_size):
logger.debug("Number image_files: %s, frame_dims: %s, thumbnail_size: %s",
len(image_files), frame_dims, thumbnail_size)
num_images = (frame_dims[0] // thumbnail_size) * (frame_dims[1] // thumbnail_si... | |
79,173 | 267,897 | 25 | test/lib/ansible_test/_internal/commands/integration/coverage.py | 11 | 7 | def target_profile(self) -> t.Optional[PosixProfile]:
retur | ansible-test - Use more native type hints. (#78435)
* ansible-test - Use more native type hints.
Simple search and replace to switch from comments to native type hints for return types of functions with no arguments.
* ansible-test - Use more native type hints.
Conversion of simple single-line function annota... | target_profile | 3eb0485dd92c88cc92152d3656d94492db44b183 | ansible | coverage.py | 10 | 3 | https://github.com/ansible/ansible.git | 2 | 33 | 0 | 11 | 51 | Python | {
"docstring": "The POSIX target profile, if it uses a different Python interpreter than the controller, otherwise None.",
"language": "en",
"n_whitespaces": 15,
"n_words": 16,
"vocab_size": 16
} | def target_profile(self) -> t.Optional[PosixProfile]:
return t.cast(PosixProfile, self.profiles[0]) if self.profiles else None
| |
85,817 | 286,444 | 2,754 | openbb_terminal/portfolio/portfolio_model.py | 512 | 71 | def preprocess_transactions(self):
p_bar = tqdm(range(14), desc="Preprocessing transactions")
try:
# 0. If optional fields not in the transactions add missing
optional_fields = [
"Sector",
"Industry",
"Country",
... | Portfolio menu bug fixes (#3204)
* normalized way moving average is treated and prevent huge exception prompt
* changed descriptions on docs
* change to check_positive_float
* add integration tests
* fix linting
* add more integration tests
* add more integration tests
* fix linting
* add some ... | preprocess_transactions | f9086d6f38cf5de4bf3e44be0b4ccd332dbaca46 | OpenBBTerminal | portfolio_model.py | 23 | 137 | https://github.com/OpenBB-finance/OpenBBTerminal.git | 14 | 838 | 0 | 267 | 1,446 | Python | {
"docstring": "Method to preprocess, format and compute auxiliary fields.\n\n Preprocessing steps:\n 0. If optional fields not in the transactions add missing\n 1. Convert Date to datetime\n 2. Sort transactions by date\n 3. Capitalize Ticker and Type [of instrument... | def preprocess_transactions(self):
p_bar = tqdm(range(14), desc="Preprocessing transactions")
try:
# 0. If optional fields not in the transactions add missing
optional_fields = [
"Sector",
"Industry",
"Country",
... | |
79,831 | 269,013 | 39 | keras/optimizers/optimizer_v2/optimizer_v2.py | 27 | 7 | def _var_key(var):
# pylint: disable=protected-access
# Get the distributed variable if it exists.
if hasattr(var, "_distributed_container"):
var = var._distributed_container()
if getattr(var, "_in_g | Support checkpointing ShardedVariables in optimizer slot variables.
PiperOrigin-RevId: 429577423 | _var_key | 75d70a610dffe927d89ceb400d79bb7f9027b26e | keras | optimizer_v2.py | 10 | 6 | https://github.com/keras-team/keras.git | 3 | 39 | 0 | 23 | 69 | Python | {
"docstring": "Key for representing a primary variable, for looking up slots.\n\n In graph mode the name is derived from the var shared name.\n In eager mode the name is derived from the var unique id.\n If distribution strategy exists, get the primary variable first.\n\n Args:\n var: the variable.\n\n Retur... | def _var_key(var):
# pylint: disable=protected-access
# Get the distributed variable if it exists.
if hasattr(var, "_distributed_container"):
var = var._distributed_container()
if getattr(var, "_in_graph_mode", False):
return var._shared_name
return var._unique_id
| |
76,836 | 261,492 | 57 | sklearn/ensemble/tests/test_stacking.py | 26 | 19 | def test_stacking_classifier_base_regressor():
X_train, X_test, y_train, y_test = train_test_split(
scale(X_iris), y_iris, stratify=y_iris, random_state=42
)
clf = StackingClassifier(estimators=[("ridge", Ridge())])
clf.fit(X_train, y_train)
clf.predict(X_test)
clf.predict_proba(X_t... | ENH StackingClassifier allows regressors in its first layer (#24538)
Co-authored-by: Tom Dupré la Tour <tom.duprelatour.10@gmail.com>
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> | test_stacking_classifier_base_regressor | b1807ff8ead319a08294beeaae90c3f03b2bb8ac | scikit-learn | test_stacking.py | 13 | 9 | https://github.com/scikit-learn/scikit-learn.git | 1 | 79 | 0 | 25 | 121 | Python | {
"docstring": "Check that a regressor can be used as the first layer in `StackingClassifier`.",
"language": "en",
"n_whitespaces": 12,
"n_words": 13,
"vocab_size": 13
} | def test_stacking_classifier_base_regressor():
X_train, X_test, y_train, y_test = train_test_split(
scale(X_iris), y_iris, stratify=y_iris, random_state=42
)
clf = StackingClassifier(estimators=[("ridge", Ridge())])
clf.fit(X_train, y_train)
clf.predict(X_test)
clf.predict_proba(X_t... | |
23,079 | 108,151 | 580 | lib/matplotlib/backends/backend_svg.py | 145 | 27 | def _get_style_dict(self, gc, rgbFace):
attrib = {}
forced_alpha = gc.get_forced_alpha()
if gc.get_hatch() is not None:
attrib['fill'] = "url(#%s)" % self._get_hatch(gc, rgbFace)
if (rgbFace is not None and len(rgbFace) == 4 and rgbFace[3] != 1.0
... | Deprecate functions in backends | _get_style_dict | ec410abbb3a721e31f3aaa61e9e4f941467e35e1 | matplotlib | backend_svg.py | 17 | 37 | https://github.com/matplotlib/matplotlib.git | 21 | 342 | 0 | 76 | 558 | Python | {
"docstring": "Generate a style string from the GraphicsContext and rgbFace.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 9
} | def _get_style_dict(self, gc, rgbFace):
attrib = {}
forced_alpha = gc.get_forced_alpha()
if gc.get_hatch() is not None:
attrib['fill'] = "url(#%s)" % self._get_hatch(gc, rgbFace)
if (rgbFace is not None and len(rgbFace) == 4 and rgbFace[3] != 1.0
... | |
25,734 | 116,362 | 348 | tests/unit/test_executor.py | 85 | 28 | def test_union(self, mock_handler):
self.set_handler(mock_handler, name='pg', tables={'tasks': self.df})
# --- use predictor ---
predictor = {
'name': 'task_model',
'predict': 'p',
'dtypes': {
'p': dtype.float,
'a': dtype.inte... | union command
#2852 | test_union | 61f6f6c3c8154fa0629df8a016d449ceded99879 | mindsdb | test_executor.py | 14 | 35 | https://github.com/mindsdb/mindsdb.git | 1 | 201 | 0 | 53 | 346 | Python | {
"docstring": "\n SELECT a as a1, b as target\n FROM pg.tasks\n UNION {union}\n SELECT model.a as a2, model.p as target2\n FROM pg.tasks as t\n JOIN mindsdb.task_model as model\n WHERE t.a=1 \n ",
"language": "en",... | def test_union(self, mock_handler):
self.set_handler(mock_handler, name='pg', tables={'tasks': self.df})
# --- use predictor ---
predictor = {
'name': 'task_model',
'predict': 'p',
'dtypes': {
'p': dtype.float,
'a': dtype.inte... | |
8,522 | 45,252 | 89 | tests/utils/test_db_cleanup.py | 21 | 13 | def test_run_cleanup_tables(self, clean_table_mock, table_names):
base_kwargs = dict(
| Add `db clean` CLI command for purging old data (#20838)
CLI command to delete old rows from airflow metadata database.
Notes:
* Must supply "purge before date".
* Can optionally provide table list.
* Dry run will only print the number of rows meeting criteria.
* If not dry run, will require the user to confirm b... | test_run_cleanup_tables | c75774d3a31efe749f55ba16e782737df9f53af4 | airflow | test_db_cleanup.py | 9 | 8 | https://github.com/apache/airflow.git | 2 | 52 | 0 | 21 | 79 | Python | {
"docstring": "\n ``_cleanup_table`` should be called for each table in subset if one\n is provided else should be called for all tables.\n ",
"language": "en",
"n_whitespaces": 42,
"n_words": 20,
"vocab_size": 16
} | def test_run_cleanup_tables(self, clean_table_mock, table_names):
base_kwargs = dict(
clean_before_timestamp=None,
dry_run=None,
verbose=None,
)
run_cleanup(**base_kwargs, table_names=table_names)
assert clean_table_mock.call_count == len(tabl... | |
8,455 | 45,040 | 21 | tests/models/test_xcom.py | 7 | 6 | def test_set_serialize_call_old_signature(self, get_import, session):
serialize_watcher = | Add params dag_id, task_id etc to XCom.serialize_value (#19505)
When implementing a custom XCom backend, in order to store XCom objects organized by dag_id, run_id etc, we need to pass those params to `serialize_value`. | test_set_serialize_call_old_signature | 56285eee04285d8b6fac90911248d7e9dd5504d8 | airflow | test_xcom.py | 8 | 16 | https://github.com/apache/airflow.git | 1 | 82 | 0 | 7 | 26 | Python | {
"docstring": "\n When XCom.serialize_value takes only param ``value``, other kwargs should be ignored.\n ",
"language": "en",
"n_whitespaces": 26,
"n_words": 11,
"vocab_size": 11
} | def test_set_serialize_call_old_signature(self, get_import, session):
serialize_watcher = MagicMock()
| |
69,715 | 241,856 | 152 | scipy/stats/_stats_py.py | 63 | 17 | def gmean(a, axis=0, dtype=None, weights=None):
if not isinstance(a, np.ndarray):
# if not an ndarray object attempt to convert it
log_a = np.log(np.array(a, dtype=dtype))
elif dtype:
# Must change the default dtype allowing array type
if isinstance(a, np.ma.MaskedArray):
... | ENH: stats: add `axis` tuple and `nan_policy` to `gmean` (#14657)
* ENH: stats: add `axis` tuple and `nan_policy` to `gmean`
Co-authored-by: Pamphile ROY <roy.pamphile@gmail.com> | gmean | 465da5496a8dda099646e9d5947f24dfc0ec44e9 | scipy | _stats_py.py | 17 | 13 | https://github.com/scipy/scipy.git | 5 | 147 | 0 | 45 | 228 | Python | {
"docstring": "Compute the geometric mean along the specified axis.\n\n Return the geometric average of the array elements.\n That is: n-th root of (x1 * x2 * ... * xn)\n\n Parameters\n ----------\n a : array_like\n Input array or object that can be converted to an array.\n axis : int or No... | def gmean(a, axis=0, dtype=None, weights=None):
if not isinstance(a, np.ndarray):
# if not an ndarray object attempt to convert it
log_a = np.log(np.array(a, dtype=dtype))
elif dtype:
# Must change the default dtype allowing array type
if isinstance(a, np.ma.MaskedArray):
... | |
50,868 | 204,741 | 47 | django/core/serializers/base.py | 15 | 5 | def handle_m2m_field(self, obj, field):
raise NotImplementedError(
"subclasses of Serializer must provide a handle_m2m_field() method"
)
| Refs #33476 -- Reformatted code with Black. | handle_m2m_field | 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | django | base.py | 8 | 4 | https://github.com/django/django.git | 1 | 15 | 0 | 15 | 27 | Python | {
"docstring": "\n Called to handle a ManyToManyField.\n ",
"language": "en",
"n_whitespaces": 20,
"n_words": 5,
"vocab_size": 5
} | def handle_m2m_field(self, obj, field):
raise NotImplementedError(
"subclasses of Serializer must provide a handle_m2m_field() method"
)
| |
25,818 | 116,724 | 209 | mindsdb/integrations/handlers/hana_handler/hana_handler.py | 61 | 20 | def check_connection(self) -> StatusResponse:
response = StatusResponse(False)
need_to_close = self.is_connected is False
try:
connection = self.connect()
with connection.cursor() as cur:
cur.execute('SELECT * FROM SYS.M_DATABASE')
r... | feat: add sap hana integration | check_connection | db6291bc6a2cbea0154bd41c3abff3f6cfb7bc8a | mindsdb | hana_handler.py | 13 | 20 | https://github.com/mindsdb/mindsdb.git | 6 | 103 | 0 | 42 | 188 | Python | {
"docstring": "\n Check the connection of the SAP HANA database\n :return: success status and error message if error occurs\n ",
"language": "en",
"n_whitespaces": 39,
"n_words": 17,
"vocab_size": 15
} | def check_connection(self) -> StatusResponse:
response = StatusResponse(False)
need_to_close = self.is_connected is False
try:
connection = self.connect()
with connection.cursor() as cur:
cur.execute('SELECT * FROM SYS.M_DATABASE')
r... | |
47,454 | 195,867 | 185 | sympy/matrices/common.py | 90 | 18 | def extract(self, rowsList, colsList):
r
if not is_sequence(rowsList) or not is_sequence(colsList):
rais | Improved documentation formatting | extract | cda8dfe6f45dc5ed394c2f5cda706cd6c729f713 | sympy | common.py | 12 | 56 | https://github.com/sympy/sympy.git | 15 | 136 | 0 | 49 | 208 | Python | {
"docstring": "Return a submatrix by specifying a list of rows and columns.\n Negative indices can be given. All indices must be in the range\n $-n \\le i < n$ where $n$ is the number of rows or columns.\n\n Examples\n ========\n\n >>> from sympy import Matrix\n >>> m = Matr... | def extract(self, rowsList, colsList):
r
if not is_sequence(rowsList) or not is_sequence(colsList):
raise TypeError("rowsList and colsList must be iterable")
# ensure rowsList and colsList are lists of integers
if rowsList and all(isinstance(i, bool) for i in rowsList):
... | |
48,217 | 196,850 | 144 | sympy/integrals/integrals.py | 48 | 16 | def integrate(*args, meijerg=None, conds='piecewise', risch=None, heurisch=None, manual=None, **kwargs):
doit_flags = {
'deep': False,
'meijerg': meijerg,
'conds': conds,
'risch': risch,
'heurisch': heurisch,
'manual': manual
}
integral = Integral(*ar... | Fix a few docstring formatting issues | integrate | 1eeb01e15f06c6692a5bfd6fd2d2a3002d864a07 | sympy | integrals.py | 14 | 16 | https://github.com/sympy/sympy.git | 4 | 119 | 0 | 43 | 190 | Python | {
"docstring": "integrate(f, var, ...)\n\n Explanation\n ===========\n\n Compute definite or indefinite integral of one or more variables\n using Risch-Norman algorithm and table lookup. This procedure is\n able to handle elementary algebraic and transcendental functions\n and also a huge class of s... | def integrate(*args, meijerg=None, conds='piecewise', risch=None, heurisch=None, manual=None, **kwargs):
doit_flags = {
'deep': False,
'meijerg': meijerg,
'conds': conds,
'risch': risch,
'heurisch': heurisch,
'manual': manual
}
integral = Integral(*ar... | |
45,535 | 186,624 | 84 | certbot-apache/certbot_apache/_internal/augeasparser.py | 23 | 14 | def parsed_paths(self) -> List[str]:
res_paths: List[str] = []
paths = self.parser.existing_paths
for directory | Add typing to certbot.apache (#9071)
* Add typing to certbot.apache
Co-authored-by: Adrien Ferrand <ferrand.ad@gmail.com> | parsed_paths | 7d9e9a49005de7961e84d2a7c608db57dbab3046 | certbot | augeasparser.py | 14 | 16 | https://github.com/certbot/certbot.git | 3 | 57 | 0 | 20 | 89 | Python | {
"docstring": "\n Returns a list of file paths that have currently been parsed into the parser\n tree. The returned list may include paths with wildcard characters, for\n example: ['/etc/apache2/conf.d/*.load']\n\n This is typically called on the root node of the ParserNode tree.\n\n ... | def parsed_paths(self) -> List[str]:
res_paths: List[str] = []
paths = self.parser.existing_paths
for directory in paths:
for filename in paths[directory]:
res_paths.append(os.path.join(directory, filename))
return res_paths
| |
77,592 | 264,082 | 142 | PyInstaller/building/utils.py | 45 | 14 | def _check_guts_toc_mtime(attr_name, old_toc, new_toc, last_build, pyc=False):
for dest_name, src_name, typecode in old_toc:
if misc.mtime(src_name) > last_build:
| building: clean up the _check_guts_* helpers | _check_guts_toc_mtime | 21655572a6af55cefb05d0b0afbeb0b0db39ea19 | pyinstaller | utils.py | 15 | 11 | https://github.com/pyinstaller/pyinstaller.git | 6 | 82 | 0 | 34 | 131 | Python | {
"docstring": "\n Rebuild is required if mtimes of files listed in old TOC are newer than last_build.\n\n If pyc=True, check for .py files as well.\n\n Use this for calculated/analysed values read from cache.\n ",
"language": "en",
"n_whitespaces": 44,
"n_words": 31,
"vocab_size": 29
} | def _check_guts_toc_mtime(attr_name, old_toc, new_toc, last_build, pyc=False):
for dest_name, src_name, typecode in old_toc:
if misc.mtime(src_name) > last_build:
logger.info("Building because %s changed", src_name)
return True
elif pyc and typecode == 'PYMODULE':
... | |
25,826 | 116,753 | 213 | mindsdb/integrations/handlers/teradata_handler/teradata_handler.py | 65 | 20 | def check_connection(self) -> StatusResponse:
response = StatusResponse(False)
need_to_close = self.is_co | feat: add teradata integration | check_connection | 47c5e0ac2d89807f8ff7239d423a3d346bd39a1e | mindsdb | teradata_handler.py | 13 | 20 | https://github.com/mindsdb/mindsdb.git | 6 | 103 | 0 | 44 | 188 | Python | {
"docstring": "\n Check the connection of the Teradata database\n :return: success status and error message if error occurs\n ",
"language": "en",
"n_whitespaces": 38,
"n_words": 16,
"vocab_size": 14
} | def check_connection(self) -> StatusResponse:
response = StatusResponse(False)
need_to_close = self.is_connected is False
try:
connection = self.connect()
with connection.cursor() as cur:
cur.execute('SELECT 1 FROM (SELECT 1 AS "dual") AS "dual"... | |
5,969 | 32,666 | 148 | utils/prepare_for_doc_test.py | 79 | 22 | def process_doc_file(code_file, add_new_line=True):
with open(code_file, "r", encoding="utf-8", newline="\n") as f:
code = f.read()
# fmt: off
splits = code.split("```")
if len(splits) % 2 != 1:
raise ValueError("The number of occurrences of ``` should be an even number.")
spl... | Add a check regarding the number of occurrences of ``` (#18389)
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> | process_doc_file | bd6d1b430080aaf7d9a15f908b95631242da3fb0 | transformers | prepare_for_doc_test.py | 14 | 13 | https://github.com/huggingface/transformers.git | 5 | 132 | 0 | 57 | 236 | Python | {
"docstring": "\n Process given file.\n\n Args:\n code_file (`str` or `os.PathLike`): The file in which we want to style the docstring.\n ",
"language": "en",
"n_whitespaces": 35,
"n_words": 18,
"vocab_size": 18
} | def process_doc_file(code_file, add_new_line=True):
with open(code_file, "r", encoding="utf-8", newline="\n") as f:
code = f.read()
# fmt: off
splits = code.split("```")
if len(splits) % 2 != 1:
raise ValueError("The number of occurrences of ``` should be an even number.")
spl... | |
20,661 | 101,241 | 330 | plugins/extract/align/_base.py | 82 | 28 | def finalize(self, batch):
for face, landmarks in zip(batch["detected_faces"], batch["landmarks"]):
if not isinstance(landmarks, np.ndarray):
landmarks = np.array(landmarks)
face._landmarks_xy = landmarks
logger.trace("Item out: %s", {key: val.shape if ... | lib.align updates:
- alignments.py
- Add typed dicts for imported alignments
- Explicitly check for presence of thumb value in alignments dict
- linting
- detected_face.py
- Typing
- Linting
- Legacy support for pre-aligned face
- Update dependencies to new property names | finalize | 5e73437be47f2410439a3c6716de96354e6a0c94 | faceswap | _base.py | 13 | 18 | https://github.com/deepfakes/faceswap.git | 7 | 174 | 0 | 66 | 280 | Python | {
"docstring": " Finalize the output from Aligner\n\n This should be called as the final task of each `plugin`.\n\n Pairs the detected faces back up with their original frame before yielding each frame.\n\n Parameters\n ----------\n batch : dict\n The final ``dict`` from ... | def finalize(self, batch):
for face, landmarks in zip(batch["detected_faces"], batch["landmarks"]):
if not isinstance(landmarks, np.ndarray):
landmarks = np.array(landmarks)
face._landmarks_xy = landmarks
logger.trace("Item out: %s", {key: val.shape if ... | |
52,763 | 209,670 | 49 | scapy/layers/dcerpc.py | 27 | 8 | def find_dcerpc_interface(name):
try:
return next(x for x in DCE_RPC_INTERFACES.values() if x.name == name)
except StopItera | [MS-RPCE] and [MS-SMB] major update (#3683)
* Various fixes regarding DCE/RPC build
* DCE/RPC sessions
* Cleanup unused code
* Add missing GSS_WRAP algo names
* Add find_dcerpc_interface
* Split SMB client and server
* Missing StrFixedLenFieldUtf16
* Remove unfinished smbserver feature
* Friend... | find_dcerpc_interface | ca10c5cf00425d0178998ec0b006cbb65ddbfb54 | scapy | dcerpc.py | 12 | 5 | https://github.com/secdev/scapy.git | 4 | 35 | 0 | 27 | 62 | Python | {
"docstring": "\n Find an interface object through the name in the IDL\n ",
"language": "en",
"n_whitespaces": 17,
"n_words": 10,
"vocab_size": 9
} | def find_dcerpc_interface(name):
try:
return next(x for x in DCE_RPC_INTERFACES.values() if x.name == name)
except StopIteration:
raise AttributeError("Unknown interface !")
# --- NDR fields - [C706] chap 14
| |
43,806 | 182,367 | 194 | tests/test_animator.py | 86 | 16 | def test_animatable():
animatable = AnimateTest()
# Fake wall-clock time
time = 100.0
# Object that does the animation
animation = SimpleAnimation(
animatable,
"bar",
time,
3.0,
start_value=Animatable(20.0),
end_value=Animatable(50.0),
... | fix and test for animator | test_animatable | 8be6ea91f6e8a8d24d385975f1a5a7714cf27894 | textual | test_animator.py | 11 | 23 | https://github.com/Textualize/textual.git | 1 | 170 | 0 | 49 | 222 | Python | {
"docstring": "Test SimpleAnimation works with the Animatable protocol",
"language": "en",
"n_whitespaces": 6,
"n_words": 7,
"vocab_size": 7
} | def test_animatable():
animatable = AnimateTest()
# Fake wall-clock time
time = 100.0
# Object that does the animation
animation = SimpleAnimation(
animatable,
"bar",
time,
3.0,
start_value=Animatable(20.0),
end_value=Animatable(50.0),
... | |
53,068 | 211,340 | 650 | ppdet/metrics/map_utils.py | 125 | 38 | def update(self, bbox, score, label, gt_box, gt_label, difficult=None):
if difficult is None:
difficult = np.zeros_like(gt_label)
# record class gt count
for gtl, diff in zip(gt_label, difficult):
if self.evaluate_difficult or int(diff) == 0:
sel... | Refactor rbox (#6704)
* refactor rbox
* modify the code of save results
* fix some problem
* add .gitignore in dataset/dota
* fix test anno path | update | e55e41945d42db787a0f7c557d53d06a6b24536b | PaddleDetection | map_utils.py | 19 | 31 | https://github.com/PaddlePaddle/PaddleDetection.git | 15 | 303 | 0 | 81 | 450 | Python | {
"docstring": "\n Update metric statics from given prediction and ground\n truth infomations.\n ",
"language": "en",
"n_whitespaces": 32,
"n_words": 10,
"vocab_size": 10
} | def update(self, bbox, score, label, gt_box, gt_label, difficult=None):
if difficult is None:
difficult = np.zeros_like(gt_label)
# record class gt count
for gtl, diff in zip(gt_label, difficult):
if self.evaluate_difficult or int(diff) == 0:
sel... | |
16,182 | 73,936 | 77 | wagtail/core/permission_policies/collections.py | 20 | 12 | def _get_permission_objects_for_actions(self, actions):
permission_codenames = [
"%s_%s" % (action, self.model_name) for action in actions
]
return Permission.objects.filter(
content_ty | Reformat with black | _get_permission_objects_for_actions | d10f15e55806c6944827d801cd9c2d53f5da4186 | wagtail | collections.py | 10 | 7 | https://github.com/wagtail/wagtail.git | 2 | 42 | 0 | 20 | 66 | Python | {
"docstring": "\n Get a queryset of the Permission objects for the given actions\n ",
"language": "en",
"n_whitespaces": 26,
"n_words": 11,
"vocab_size": 10
} | def _get_permission_objects_for_actions(self, actions):
permission_codenames = [
"%s_%s" % (action, self.model_name) for action in actions
]
return Permission.objects.filter(
content_type=self._content_type, codename__in=permission_codenames
)
| |
117,569 | 321,163 | 411 | qutebrowser/browser/webengine/webview.py | 99 | 31 | def createWindow(self, wintype):
debug_type = debug.qenum_key(QWebEnginePage, wintype)
background = config.val.tabs.background
log.webview.debug("createWindow with type {}, background {}".format(
debug_type, background))
if wintype == QWebEnginePage.WebWindowType.W... | Run scripts/dev/rewrite_enums.py | createWindow | 0877fb0d78635692e481c8bde224fac5ad0dd430 | qutebrowser | webview.py | 14 | 25 | https://github.com/qutebrowser/qutebrowser.git | 7 | 172 | 0 | 60 | 287 | Python | {
"docstring": "Called by Qt when a page wants to create a new window.\n\n This function is called from the createWindow() method of the\n associated QWebEnginePage, each time the page wants to create a new\n window of the given type. This might be the result, for example, of a\n JavaScrip... | def createWindow(self, wintype):
debug_type = debug.qenum_key(QWebEnginePage, wintype)
background = config.val.tabs.background
log.webview.debug("createWindow with type {}, background {}".format(
debug_type, background))
if wintype == QWebEnginePage.WebWindowType.W... | |
75,856 | 259,662 | 40 | sklearn/ensemble/_gb.py | 12 | 11 | def predict(self, X):
raw_predictions = self.decision_function(X)
encode | DEP loss_ attribute in gradient boosting (#23079) | predict | 0d669dc419524eff7f45032f4c18253e627a055b | scikit-learn | _gb.py | 9 | 4 | https://github.com/scikit-learn/scikit-learn.git | 1 | 39 | 0 | 11 | 63 | Python | {
"docstring": "Predict class for X.\n\n Parameters\n ----------\n X : {array-like, sparse matrix} of shape (n_samples, n_features)\n The input samples. Internally, it will be converted to\n ``dtype=np.float32`` and if a sparse matrix is provided\n to a sparse ``c... | def predict(self, X):
raw_predictions = self.decision_function(X)
encoded_labels = self._loss._raw_prediction_to_decision(raw_predictions)
return self.classes_.take(encoded_labels, axis=0)
| |
42,319 | 177,255 | 29 | networkx/algorithms/operators/all.py | 17 | 6 | def union_all(graphs, rename=()):
R = None
| Make all.py generator friendly (#5984)
* Make compose_all generator friendly
* Make disjoint_union_all and intersection_all generator friendly
* Refactor disjoint_union_all to yield relabeled graphs
* Make union_all generator friendly
* Fix intersection_all
* Fix union_all signature
* Allow passing a... | union_all | 50ff08de69c6e9541cd6c029bede5dabf56cfe73 | networkx | all.py | 8 | 66 | https://github.com/networkx/networkx.git | 8 | 194 | 0 | 16 | 35 | Python | {
"docstring": "Returns the union of all graphs.\n\n The graphs must be disjoint, otherwise an exception is raised.\n\n Parameters\n ----------\n graphs : iterable\n Iterable of NetworkX graphs\n\n rename : iterable , optional\n Node names of graphs can be changed by specifying the tuple\n ... | def union_all(graphs, rename=()):
R = None
seen_nodes = set()
# rename graph to obtain disjoint node labels | |
76,685 | 261,192 | 123 | sklearn/ensemble/_hist_gradient_boosting/tests/test_gradient_boosting.py | 63 | 26 | def test_unknown_category_that_are_negative():
rng = np.random.RandomState(42)
| FIX Treat gradient boosting categoricals outside the bounds as unknown during predict (#24283) | test_unknown_category_that_are_negative | 072b481600c48662fd4893fdce461113becd207a | scikit-learn | test_gradient_boosting.py | 12 | 14 | https://github.com/scikit-learn/scikit-learn.git | 1 | 157 | 0 | 53 | 238 | Python | {
"docstring": "Check that unknown categories that are negative does not error.\n\n Non-regression test for #24274.\n ",
"language": "en",
"n_whitespaces": 20,
"n_words": 14,
"vocab_size": 13
} | def test_unknown_category_that_are_negative():
rng = np.random.RandomState(42)
n_samples = 1000
X = np.c_[rng.rand(n_samples), rng.randint(4, size=n_samples)]
y = np.zeros(shape=n_samples)
y[X[:, 1] % 2 == 0] = 1
hist = HistGradientBoostingRegressor(
random_state=0,
categor... | |
38,909 | 161,098 | 764 | ppg_extractor/encoder/encoder_layer.py | 225 | 32 | def forward(self, x_input, mask, cache=None):
if isinstance(x_input, tuple):
x, pos_emb = x_input[0], x_input[1]
else:
x, pos_emb = x_input, None
# whether to use macaron style
if self.feed_forward_macaron is not None:
| Init ppg extractor and ppg2mel (#375)
* Init ppg extractor and ppg2mel
* add preprocess and training
* FIx known issues
* Update __init__.py
Allow to gen audio
* Fix length issue
* Fix bug of preparing fid
* Fix sample issues
* Add UI usage of PPG-vc | forward | b617a87ee40ab384767a27335313c2c65ee094ec | MockingBird | encoder_layer.py | 14 | 53 | https://github.com/babysor/MockingBird.git | 19 | 449 | 0 | 80 | 699 | Python | {
"docstring": "Compute encoded features.\n\n :param torch.Tensor x_input: encoded source features, w/o pos_emb\n tuple((batch, max_time_in, size), (1, max_time_in, size))\n or (batch, max_time_in, size)\n :param torch.Tensor mask: mask for x (batch, max_time_in)\n :param torch.Tens... | def forward(self, x_input, mask, cache=None):
if isinstance(x_input, tuple):
x, pos_emb = x_input[0], x_input[1]
else:
x, pos_emb = x_input, None
# whether to use macaron style
if self.feed_forward_macaron is not None:
residual = x
... | |
46,502 | 191,364 | 58 | tests/unit_tests/test_prompt.py | 21 | 8 | def test_prompt_invalid_template_format() -> None:
template = "This is a {foo} test."
input_variables = ["foo"]
with pytest.raises(ValueError):
| initial commit | test_prompt_invalid_template_format | 18aeb720126a68201c7e3b5a617139c27c779496 | langchain | test_prompt.py | 11 | 8 | https://github.com/hwchase17/langchain.git | 1 | 37 | 0 | 20 | 69 | Python | {
"docstring": "Test initializing a prompt with invalid template format.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | def test_prompt_invalid_template_format() -> None:
template = "This is a {foo} test."
input_variables = ["foo"]
with pytest.raises(ValueError):
Prompt(
input_variables=input_variables, template=template, template_format="bar"
)
| |
73,140 | 249,805 | 205 | tests/rest/admin/test_user.py | 48 | 13 | def test_medium_does_not_exist(self) -> None:
# test for unknown medium
url = "/_synapse/admin/v1/threepid/publickey/users/unknown-key"
channel = self.make_request(
"GET",
url,
access_token=self.admin_user_tok,
)
self.assertEqual(404... | Add an Admin API endpoint for looking up users based on 3PID (#14405) | test_medium_does_not_exist | a3623af74e0af0d2f6cbd37b47dc54a1acd314d5 | synapse | test_user.py | 10 | 19 | https://github.com/matrix-org/synapse.git | 1 | 110 | 0 | 28 | 178 | Python | {
"docstring": "Tests that both a lookup for a medium that does not exist and a user that\n doesn't exist with that third party ID returns a 404",
"language": "en",
"n_whitespaces": 32,
"n_words": 26,
"vocab_size": 19
} | def test_medium_does_not_exist(self) -> None:
# test for unknown medium
url = "/_synapse/admin/v1/threepid/publickey/users/unknown-key"
channel = self.make_request(
"GET",
url,
access_token=self.admin_user_tok,
)
self.assertEqual(404... | |
@dataclass | 121,103 | 337,646 | 282 | src/accelerate/utils/dataclasses.py | 88 | 19 | def deepspeed_config_process(self, prefix="", mismatches=None, config=None, must_match=True, **kwargs):
mismatches = [] if mismatches is None else mismatches
if config is None:
config = self.deepspeed_config
for key, value in config.items():
if isinstance(value, ... | DeepSpeed Revamp (#405)
* deepspeed revamp
* Update dataclasses.py
* Update deepspeed.py
* quality
* fixing code
* quality
* FIx imports
* saving 16bit model in zero stage 3
1. Saving 16bit model in zero stage 3
2. zero init in stage 3 support using HFDeepSpeedConfig
* quality
* adding test and fixing bugs
... | deepspeed_config_process | 1703b79a797dab765996764707186def7533d8fd | accelerate | dataclasses.py | 14 | 17 | https://github.com/huggingface/accelerate.git | 7 | 137 | 1 | 68 | 228 | Python | {
"docstring": "Process the DeepSpeed config with the values from the kwargs.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 8
} | def deepspeed_config_process(self, prefix="", mismatches=None, config=None, must_match=True, **kwargs):
mismatches = [] if mismatches is None else mismatches
if config is None:
config = self.deepspeed_config
for key, value in config.items():
if isinstance(value, ... |
83,169 | 279,889 | 125 | keras/engine/training.py | 27 | 10 | def get_metrics_result(self):
# Collect metrics to return
return_metrics = {}
for metric in self.metrics:
result = metric.r | Expose Model get_metrics_result on Keras Model as a public API
PiperOrigin-RevId: 475681912 | get_metrics_result | 8cf91871ce167d63069c99120f8580a4976a59d0 | keras | training.py | 13 | 9 | https://github.com/keras-team/keras.git | 3 | 50 | 0 | 22 | 84 | Python | {
"docstring": "Returns the model's metrics values as a dict.\n\n If any of the metric result is a dict (containing multiple metrics),\n each of them gets added to the top level returned dict of this method.\n\n Returns:\n A `dict` containing values of the metrics listed in `self.metrics... | def get_metrics_result(self):
# Collect metrics to return
return_metrics = {}
for metric in self.metrics:
result = metric.result()
if isinstance(result, dict):
return_metrics.update(result)
else:
return_metrics[metric.n... | |
55,539 | 218,899 | 593 | python3.10.4/Lib/lib2to3/refactor.py | 95 | 23 | def refactor_docstring(self, input, filename):
result = []
block = None
block_lineno = None
indent = None
lineno = 0
for line in input.splitlines(keepends=True):
lineno += 1
if line.lstrip().startswith(self.PS1):
if block i... | add python 3.10.4 for windows | refactor_docstring | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | XX-Net | refactor.py | 18 | 31 | https://github.com/XX-net/XX-Net.git | 9 | 211 | 0 | 47 | 333 | Python | {
"docstring": "Refactors a docstring, looking for doctests.\n\n This returns a modified version of the input string. It looks\n for doctests, which start with a \">>>\" prompt, and may be\n continued with \"...\" prompts, as long as the \"...\" is indented\n the same as the \">>>\".\n\n ... | def refactor_docstring(self, input, filename):
result = []
block = None
block_lineno = None
indent = None
lineno = 0
for line in input.splitlines(keepends=True):
lineno += 1
if line.lstrip().startswith(self.PS1):
if block i... | |
8,643 | 45,557 | 419 | tests/utils/test_edgemodifier.py | 89 | 23 | def test_complex_reversed_dag(self, test_complex_taskgroup_dag, complex_dag_expected_edges):
(
dag,
group,
(
group_dm1,
group_dm2,
group_dm3,
dm_in1,
dm_in2,
dm_in3,
... | EdgeModifier refactoring (#21404) | test_complex_reversed_dag | ace8c6e942ff5554639801468b971915b7c0e9b9 | airflow | test_edgemodifier.py | 10 | 30 | https://github.com/apache/airflow.git | 1 | 150 | 0 | 50 | 210 | Python | {
"docstring": "Tests the complex reversed dag with a TaskGroup and a Label",
"language": "en",
"n_whitespaces": 10,
"n_words": 11,
"vocab_size": 10
} | def test_complex_reversed_dag(self, test_complex_taskgroup_dag, complex_dag_expected_edges):
(
dag,
group,
(
group_dm1,
group_dm2,
group_dm3,
dm_in1,
dm_in2,
dm_in3,
... | |
118,121 | 322,323 | 80 | paddlenlp/ops/faster_transformer/sample/plato_inference.py | 30 | 12 | def postprocess_response(token_ids, tokenizer):
eos_pos = len(token_ids)
for i, tok_id in enumerate(token_ids):
if tok_id == tokenizer.sep_token_id:
eos_pos = i
break
token_ids = token_ids[:eos_pos]
tokens = tokenizer.convert_ids_to_tokens(token_ids)
tokens = tok... | FasterUnifiedTransformer/PLATO support dy2sta (#1717)
* support ut dy2sta
* use jit load | postprocess_response | 4c36ef9e41ea6b0e43935bdf6b2f1b4a1f8de809 | PaddleNLP | plato_inference.py | 10 | 10 | https://github.com/PaddlePaddle/PaddleNLP.git | 3 | 60 | 0 | 22 | 98 | Python | {
"docstring": "Post-process the decoded sequence. Truncate from the first <eos>.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 8
} | def postprocess_response(token_ids, tokenizer):
eos_pos = len(token_ids)
for i, tok_id in enumerate(token_ids):
if tok_id == tokenizer.sep_token_id:
eos_pos = i
break
token_ids = token_ids[:eos_pos]
tokens = tokenizer.convert_ids_to_tokens(token_ids)
tokens = tok... | |
121,193 | 338,219 | 201 | src/accelerate/accelerator.py | 66 | 16 | def clip_grad_norm_(self, parameters, max_norm, norm_type=2):
if self.distributed_type == DistributedType.FSDP:
self.unscale_gradients()
parameters = [p for p in parameters]
for model in self._models:
if parameters == [p for p in model.parameters()]:
... | Return unclipped gradient from grad_clip_norm_ (#756) | clip_grad_norm_ | 693d46826e32507376d44f99967df4710886c984 | accelerate | accelerator.py | 14 | 11 | https://github.com/huggingface/accelerate.git | 7 | 101 | 0 | 48 | 156 | Python | {
"docstring": "\n Should be used in place of `torch.nn.utils.clip_grad_norm_`.\n\n Returns:\n `torch.Tensor`: Total norm of the parameter gradients (viewed as a single vector).\n\n Example:\n\n ```python\n >>> from accelerate import Accelerator\n\n >>> accelerator... | def clip_grad_norm_(self, parameters, max_norm, norm_type=2):
if self.distributed_type == DistributedType.FSDP:
self.unscale_gradients()
parameters = [p for p in parameters]
for model in self._models:
if parameters == [p for p in model.parameters()]:
... | |
56,689 | 222,663 | 399 | python3.10.4/Lib/distutils/command/build_clib.py | 108 | 15 | def check_library_list(self, libraries):
if not isinstance(libraries, list):
raise DistutilsSetupError(
"'libraries' option must be a list of tuples")
for lib in libraries:
if not isinstance(lib, tuple) and len(lib) != 2:
raise Distutil... | add python 3.10.4 for windows | check_library_list | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | XX-Net | build_clib.py | 14 | 20 | https://github.com/XX-net/XX-Net.git | 10 | 113 | 0 | 65 | 199 | Python | {
"docstring": "Ensure that the list of libraries is valid.\n\n `library` is presumably provided as a command option 'libraries'.\n This method checks that it is a list of 2-tuples, where the tuples\n are (library_name, build_info_dict).\n\n Raise DistutilsSetupError if the structure is in... | def check_library_list(self, libraries):
if not isinstance(libraries, list):
raise DistutilsSetupError(
"'libraries' option must be a list of tuples")
for lib in libraries:
if not isinstance(lib, tuple) and len(lib) != 2:
raise Distutil... | |
3,366 | 20,431 | 563 | pipenv/patched/notpip/_vendor/pygments/lexer.py | 130 | 16 | def _process_new_state(cls, new_state, unprocessed, processed):
if isinstance(new_state, str):
# an existing state
if new_state == '#pop':
return -1
elif new_state in unprocessed:
return (new_state,)
elif new_state == '#pus... | check point progress on only bringing in pip==22.0.4 (#4966)
* vendor in pip==22.0.4
* updating vendor packaging version
* update pipdeptree to fix pipenv graph with new version of pip.
* Vendoring of pip-shims 0.7.0
* Vendoring of requirementslib 1.6.3
* Update pip index safety restrictions patch for p... | _process_new_state | f3166e673fe8d40277b804d35d77dcdb760fc3b3 | pipenv | lexer.py | 15 | 30 | https://github.com/pypa/pipenv.git | 11 | 177 | 0 | 69 | 288 | Python | {
"docstring": "Preprocess the state transition action of a token definition.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 9
} | def _process_new_state(cls, new_state, unprocessed, processed):
if isinstance(new_state, str):
# an existing state
if new_state == '#pop':
return -1
elif new_state in unprocessed:
return (new_state,)
elif new_state == '#pus... | |
75,661 | 259,226 | 169 | sklearn/preprocessing/tests/test_encoders.py | 89 | 25 | def test_ohe_infrequent_two_levels_user_cats():
X_train = np.array(
[["a"] * 5 + ["b"] * 20 + ["c"] * 10 + ["d"] * 3], dtyp | ENH Adds infrequent categories to OneHotEncoder (#16018)
* ENH Completely adds infrequent categories
* STY Linting
* STY Linting
* DOC Improves wording
* DOC Lint
* BUG Fixes
* CLN Address comments
* CLN Address comments
* DOC Uses math to description float min_frequency
* DOC Adds comment r... | test_ohe_infrequent_two_levels_user_cats | 7f0006c8aad1a09621ad19c3db19c3ff0555a183 | scikit-learn | test_encoders.py | 16 | 18 | https://github.com/scikit-learn/scikit-learn.git | 2 | 203 | 0 | 67 | 332 | Python | {
"docstring": "Test that the order of the categories provided by a user is respected.",
"language": "en",
"n_whitespaces": 12,
"n_words": 13,
"vocab_size": 12
} | def test_ohe_infrequent_two_levels_user_cats():
X_train = np.array(
[["a"] * 5 + ["b"] * 20 + ["c"] * 10 + ["d"] * 3], dtype=object
).T
ohe = OneHotEncoder(
categories=[["c", "d", "a", "b"]],
sparse=False,
handle_unknown="infrequent_if_exist",
max_categories=2,
... | |
76,200 | 260,354 | 119 | sklearn/decomposition/_sparse_pca.py | 34 | 14 | def fit(self, X, y=None):
self._v | MAINT Use _validate_params in SparsePCA and MiniBatchSparsePCA (#23710)
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr> | fit | db6123fe40400828918037f3fae949bfcc4d9d05 | scikit-learn | _sparse_pca.py | 10 | 11 | https://github.com/scikit-learn/scikit-learn.git | 2 | 85 | 0 | 24 | 135 | Python | {
"docstring": "Fit the model from data in X.\n\n Parameters\n ----------\n X : array-like of shape (n_samples, n_features)\n Training vector, where `n_samples` is the number of samples\n and `n_features` is the number of features.\n\n y : Ignored\n Not use... | def fit(self, X, y=None):
self._validate_params()
random_state = check_random_state(self.random_state)
X = self._validate_data(X)
self.mean_ = X.mean(axis=0)
X = X - self.mean_
if self.n_components is None:
n_components = X.shape[1]
else:
... | |
11,200 | 55,077 | 74 | tests/cli/test_profile.py | 21 | 11 | def test_create_profile():
invoke_and_assert(
["profile", "create", "foo"],
expected_output=(
f
),
)
profiles = load_profiles()
assert profiles["foo"] == Profile(
name="foo", settings={}, source=PREFECT_PROFI | Add tests for profile CLI | test_create_profile | 808660dd04465fc796a34e835467e8ae1f2449b3 | prefect | test_profile.py | 11 | 21 | https://github.com/PrefectHQ/prefect.git | 1 | 52 | 0 | 20 | 89 | Python | {
"docstring": "\n Created profile 'foo'.\n\n Switch to your new profile with:\n\n prefect profile use 'foo'\n\n Or, to use it for a single command, include the `-p` option:\n\n prefect -p 'foo' config view\n ",
"language": "en",
"n_whitesp... | def test_create_profile():
invoke_and_assert(
["profile", "create", "foo"],
expected_output=(
f
),
)
profiles = load_profiles()
assert profiles["foo"] == Profile(
name="foo", settings={}, source=PREFECT_PROFILES_PATH.value()
)
| |
23,693 | 109,648 | 160 | lib/matplotlib/tests/test_axes.py | 97 | 21 | def test_mixed_errorbar_polar_caps():
fig = plt.figure()
ax = plt.subplot(111, projection='polar')
# symmetric errorbars
th_sym = [1, 2, 3]
r_sym = [0.9]*3
ax.errorbar(th_sym, r_sym, xerr=0.35, yerr=0.2, fmt="o")
# long errorbars
th_long = [np.pi/2 + .1, np.pi + .1]
r_long = [... | Curved polar errorbars
- uses _interpolation_steps
- prefers transform MarkerStyle in init over _transform property
- adjusted what's new
- added more tests for overlapping, asymmetric and long errorbars
- combine all tests to a single figure
- remove overlappnig since it does not work same on all platforms
- r... | test_mixed_errorbar_polar_caps | 907f78dbf959c0609ab484c59e840eea3eafee31 | matplotlib | test_axes.py | 11 | 17 | https://github.com/matplotlib/matplotlib.git | 1 | 273 | 0 | 72 | 348 | Python | {
"docstring": "\n Mix several polar errorbar use cases in a single test figure.\n\n It is advisable to position individual points off the grid. If there are\n problems with reproducibility of this test, consider removing grid.\n ",
"language": "en",
"n_whitespaces": 46,
"n_words": 33,
"vocab_size... | def test_mixed_errorbar_polar_caps():
fig = plt.figure()
ax = plt.subplot(111, projection='polar')
# symmetric errorbars
th_sym = [1, 2, 3]
r_sym = [0.9]*3
ax.errorbar(th_sym, r_sym, xerr=0.35, yerr=0.2, fmt="o")
# long errorbars
th_long = [np.pi/2 + .1, np.pi + .1]
r_long = [... | |
41,701 | 176,114 | 46 | tests/test_eval_model.py | 11 | 3 | def test_edgeql_for_01(self):
self.assert_test_query(
r,
{(1, 1), (2, 2), (3, 3)},
)
| Pull assert_data_shape out of testbase.server and use it for model tests (#3315) | test_edgeql_for_01 | 20ca6e2fa7bab2adc8c37d8c42049076c692782e | edgedb | test_eval_model.py | 9 | 7 | https://github.com/edgedb/edgedb.git | 1 | 33 | 0 | 11 | 46 | Python | {
"docstring": "\n FOR X IN {1,2,3} UNION ((SELECT X), (SELECT X));\n ",
"language": "en",
"n_whitespaces": 32,
"n_words": 9,
"vocab_size": 9
} | def test_edgeql_for_01(self):
self.assert_test_query(
r,
{(1, 1), (2, 2), (3, 3)},
)
| |
117,320 | 320,737 | 78 | qutebrowser/browser/downloadview.py | 17 | 13 | def on_clicked(self, index):
if not index.isValid():
return
item = self._model().data(index, downloads.ModelRole.item)
if item.done and item.successful:
item.open_file()
item.remove()
| mypy: Upgrade to PyQt5-stubs 5.15.6.0
For some unknown reason, those new stubs cause a *lot* of things now to be
checked by mypy which formerly probably got skipped due to Any being implied
somewhere.
The stubs themselves mainly improved, with a couple of regressions too.
In total, there were some 337 (!) new mypy e... | on_clicked | a20bb67a878b2e68abf8268c1b0a27f018d01352 | qutebrowser | downloadview.py | 10 | 7 | https://github.com/qutebrowser/qutebrowser.git | 4 | 54 | 0 | 16 | 91 | Python | {
"docstring": "Handle clicking of an item.\n\n Args:\n index: The QModelIndex of the clicked item.\n ",
"language": "en",
"n_whitespaces": 38,
"n_words": 13,
"vocab_size": 11
} | def on_clicked(self, index):
if not index.isValid():
return
item = self._model().data(index, downloads.ModelRole.item)
if item.done and item.successful:
item.open_file()
item.remove()
| |
@add_start_docstrings(
"""
XLM-RoBERTa-xlarge Model transformer with a sequence classification/regression head on top (a linear layer on top
of the pooled output) e.g. for GLUE tasks.
""",
XLM_ROBERTA_XL_START_DOCSTRING,
) | 6,311 | 34,690 | 44 | src/transformers/models/xlm_roberta_xl/modeling_xlm_roberta_xl.py | 27 | 6 | def _tie_weights(self):
# To tie those two weights if they get disconnec | Add support for XLM-R XL and XXL models by modeling_xlm_roberta_xl.py (#13727)
* add xlm roberta xl
* add convert xlm xl fairseq checkpoint to pytorch
* fix init and documents for xlm-roberta-xl
* fix indention
* add test for XLM-R xl,xxl
* fix model hub name
* fix some stuff
* up
* correct ini... | _tie_weights | e09473a817c5e5871e11cc81004355ef30250502 | transformers | modeling_xlm_roberta_xl.py | 8 | 2 | https://github.com/huggingface/transformers.git | 1 | 14 | 1 | 27 | 38 | Python | {
"docstring": "\n XLM-RoBERTa-xlarge Model transformer with a sequence classification/regression head on top (a linear layer on top\n of the pooled output) e.g. for GLUE tasks.\n ",
"language": "en",
"n_whitespaces": 33,
"n_words": 23,
"vocab_size": 21
} | def _tie_weights(self):
# To tie those two weights if they get disconnected (on TPU or when the bias is resized)
self.bias = self.decoder.bias
@add_start_docstrings(
,
XLM_ROBERTA_XL_START_DOCSTRING,
) |
3,071 | 19,706 | 23 | pipenv/installers.py | 9 | 5 | def matches_minor(self, other):
re | Issue 4993 Add standard pre commit hooks and apply linting. (#4994)
* Add .pre-commit-config.yaml to the project and exclude tests (for now). This does not include the MyPy linting that pip does but does include everything else. | matches_minor | 9a3b3ce70621af6f9adaa9eeac9cf83fa149319c | pipenv | installers.py | 8 | 2 | https://github.com/pypa/pipenv.git | 1 | 28 | 0 | 9 | 43 | Python | {
"docstring": "Check whether this version matches the other in (major, minor).",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | def matches_minor(self, other):
return (self.major, self.minor) == (other.major, other.minor)
| |
25,781 | 116,582 | 73 | mindsdb/integrations/handlers/lightwood_handler/tests/test_lightwood_handler.py | 24 | 15 | def test_04_query_predictor_single_where_condition(self):
time.sleep(120) # TODO
query = f
response = self.handler.native_query(query)
self.assertTrue(response.type == RESPONSE_TYPE.TABLE)
self.assertTrue(len(response.data_frame) == 1)
self.assertTrue(response.data_frame... | test fix | test_04_query_predictor_single_where_condition | b999051fd8153a1d3624471cac5483867116f985 | mindsdb | test_lightwood_handler.py | 11 | 12 | https://github.com/mindsdb/mindsdb.git | 1 | 83 | 0 | 21 | 143 | Python | {
"docstring": "\n SELECT target\n from {self.test_model_1}\n WHERE sqft=100\n ",
"language": "en",
"n_whitespaces": 47,
"n_words": 6,
"vocab_size": 6
} | def test_04_query_predictor_single_where_condition(self):
time.sleep(120) # TODO
query = f
response = self.handler.native_query(query)
self.assertTrue(response.type == RESPONSE_TYPE.TABLE)
self.assertTrue(len(response.data_frame) == 1)
self.assertTrue(response.data_frame... |
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