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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
23,671 | 109,612 | 271 | lib/matplotlib/axes/_base.py | 77 | 22 | def set_aspect(self, aspect, adjustable=None, anchor=None, share=False):
if cbook._str_equal(aspect, 'equal'):
aspect = 1
if not cbook._str_equal(aspect, 'auto'):
aspect = float(aspect) # raise ValueError if | Update _base.py | set_aspect | 9d616615417eac104e12f2915f3fe875177bb2e4 | matplotlib | _base.py | 14 | 20 | https://github.com/matplotlib/matplotlib.git | 10 | 146 | 0 | 50 | 232 | Python | {
"docstring": "\n Set the aspect ratio of the axes scaling, i.e. y/x-scale.\n\n Parameters\n ----------\n aspect : {'auto', 'equal'} or float\n Possible values:\n\n - 'auto': fill the position rectangle with data.\n - 'equal': same as ``aspect=1``, i.e. sa... | def set_aspect(self, aspect, adjustable=None, anchor=None, share=False):
if cbook._str_equal(aspect, 'equal'):
aspect = 1
if not cbook._str_equal(aspect, 'auto'):
aspect = float(aspect) # raise ValueError if necessary
if aspect<0:
raise Value... | |
50,145 | 202,525 | 144 | tests/custom_pk/tests.py | 59 | 12 | def test_pk_attributes(self):
# pk can be used as a substitute for the primary key.
# The primary key can be accessed via the pk property on the model.
e = Employee.objects.get(pk=123)
self.ass | Refs #33476 -- Reformatted code with Black. | test_pk_attributes | 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | django | tests.py | 10 | 8 | https://github.com/django/django.git | 1 | 51 | 0 | 44 | 89 | Python | {
"docstring": "\n pk and attribute name are available on the model\n No default id attribute is added\n ",
"language": "en",
"n_whitespaces": 37,
"n_words": 15,
"vocab_size": 14
} | def test_pk_attributes(self):
# pk can be used as a substitute for the primary key.
# The primary key can be accessed via the pk property on the model.
e = Employee.objects.get(pk=123)
self.assertEqual(e.pk, 123)
# Or we can use the real attribute name for the primary ke... | |
11,152 | 54,803 | 294 | src/prefect/client.py | 95 | 12 | async def __aenter__(self):
if self._closed:
# httpx.AsyncClient does not allow reuse so we will not either.
raise RuntimeError(
"The client cannot be started again after closing. "
| Disable lifespan management during logging | __aenter__ | 05b92d7c7f6cf21c5d6033df7242c331fc66b92e | prefect | client.py | 14 | 16 | https://github.com/PrefectHQ/prefect.git | 5 | 80 | 0 | 65 | 145 | Python | {
"docstring": "\n Start the client.\n\n If the client is already started, this will raise an exception.\n\n If the client is already closed, this will raise an exception. Use a new client\n instance instead.\n ",
"language": "en",
"n_whitespaces": 67,
"n_words": 31,
"vocab_... | async def __aenter__(self):
if self._closed:
# httpx.AsyncClient does not allow reuse so we will not either.
raise RuntimeError(
"The client cannot be started again after closing. "
"Retrieve a new client with `get_client()` instead."
... | |
31,501 | 138,659 | 665 | rllib/agents/qmix/qmix.py | 224 | 42 | def training_iteration(self) -> ResultDict:
# Sample n batches from n workers.
new_sample_batches = synchronous_parallel_sample(
worker_set=self.workers, concat=False
)
for batch in new_sample_batches:
# Update counters.
self._counters[NUM_EN... | [RLlib] QMIX training iteration function and new replay buffer API. (#24164) | training_iteration | 627b9f2e888b05434bb67f547b390409f26538e7 | ray | qmix.py | 13 | 46 | https://github.com/ray-project/ray.git | 6 | 238 | 0 | 139 | 397 | Python | {
"docstring": "QMIX training iteration function.\n\n - Sample n MultiAgentBatches from n workers synchronously.\n - Store new samples in the replay buffer.\n - Sample one training MultiAgentBatch from the replay buffer.\n - Learn on the training batch.\n - Update the target network... | def training_iteration(self) -> ResultDict:
# Sample n batches from n workers.
new_sample_batches = synchronous_parallel_sample(
worker_set=self.workers, concat=False
)
for batch in new_sample_batches:
# Update counters.
self._counters[NUM_EN... | |
@cli.command()
@click.option("--gh-token", envvar=["GH_TOKEN", "GITHUB_TOKEN"], required=True) | 72,929 | 249,457 | 105 | scripts-dev/release.py | 27 | 11 | def _announce() -> None:
current_version = get_package_version()
tag_name = f"v{current_version}"
click.echo(
f
| Extend the release script to wait for GitHub Actions to finish and to be usable as a guide for the whole process. (#13483) | _announce | c7b18d9d44c90acfd4ceaec1fa2f8275e03f14af | synapse | release.py | 11 | 31 | https://github.com/matrix-org/synapse.git | 2 | 42 | 1 | 22 | 147 | Python | {
"docstring": "Generate markdown to announce the release.\nHi everyone. Synapse {current_version} has just been released.\n\n[notes](https://github.com/matrix-org/synapse/releases/tag/{tag_name}) | \\\n[docker](https://hub.docker.com/r/matrixdotorg/synapse/tags?name={tag_name}) | \\\n[debs](https://packages.matrix.o... | def _announce() -> None:
current_version = get_package_version()
tag_name = f"v{current_version}"
click.echo(
f
)
if "rc" in tag_name:
click.echo(
)
else:
click.echo(
)
@cli.command()
@click.option("--gh-token", envvar=[... |
53,460 | 212,852 | 154 | PySimpleGUI.py | 45 | 15 | def update(self, value=None, visible=None):
| Completed switching all elements over to the new way of handling visiblity | update | ed2bc288ff17344f6406c49623036620f18e65bb | PySimpleGUI | PySimpleGUI.py | 12 | 12 | https://github.com/PySimpleGUI/PySimpleGUI.git | 6 | 98 | 0 | 32 | 158 | Python | {
"docstring": "\n Changes some of the settings for the Output Element. Must call `Window.Read` or `Window.Finalize` prior\n\n Changes will not be visible in your window until you call window.read or window.refresh.\n\n If you change visibility, your element may MOVE. If you want it to remain sta... | def update(self, value=None, visible=None):
if not self._widget_was_created(): # if widget hasn't been created yet, then don't allow
return
if value is not None:
self._TKOut.output.delete('1.0', tk.END)
self._TKOut.output.insert(tk.END, value)
if vi... | |
34,801 | 150,631 | 111 | freqtrade/freqai/prediction_models/RLPredictionModel.py | 39 | 8 | def example(self):
result = getattr(self, "_example", None)
if result is None:
# No example batch was found, so get one from the `.train` dataset
result = next(iter(self.train))
# And cache it for next time
self._example = result
return re... | callback function and TDQN model added | example | 01232e9a1f8e28e3611e38af3816edb026600767 | freqtrade | RLPredictionModel.py | 13 | 6 | https://github.com/freqtrade/freqtrade.git | 2 | 39 | 0 | 32 | 68 | Python | {
"docstring": "Get and cache an example batch of `inputs, labels` for plotting.",
"language": "en",
"n_whitespaces": 10,
"n_words": 11,
"vocab_size": 11
} | def example(self):
result = getattr(self, "_example", None)
if result is None:
# No example batch was found, so get one from the `.train` dataset
result = next(iter(self.train))
# And cache it for next time
self._example = result
return re... | |
50,635 | 204,114 | 151 | django/contrib/gis/measure.py | 39 | 7 | def unit_attname(cls, unit_str):
lower = unit_str.lower()
if unit_str in cls.UNITS:
return unit_str
elif lower in cls.UNITS:
return lower
elif lower in cls.LALIAS:
return cls.LALIAS[lower]
else:
raise Exception(
... | Refs #33476 -- Reformatted code with Black. | unit_attname | 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | django | measure.py | 12 | 12 | https://github.com/django/django.git | 4 | 56 | 0 | 28 | 93 | Python | {
"docstring": "\n Retrieve the unit attribute name for the given unit string.\n For example, if the given unit string is 'metre', return 'm'.\n Raise an exception if an attribute cannot be found.\n ",
"language": "en",
"n_whitespaces": 59,
"n_words": 30,
"vocab_size": 22
} | def unit_attname(cls, unit_str):
lower = unit_str.lower()
if unit_str in cls.UNITS:
return unit_str
elif lower in cls.UNITS:
return lower
elif lower in cls.LALIAS:
return cls.LALIAS[lower]
else:
raise Exception(
... | |
30,776 | 135,932 | 63 | rllib/tests/test_nn_framework_import_errors.py | 30 | 15 | def test_dont_import_tf_error():
# Do n | [RLlib] AlgorithmConfigs: Make None a valid value for methods to set properties; Use new `NotProvided` singleton, instead, to indicate no changes wanted on that property. (#30020) | test_dont_import_tf_error | 087548031bcf22dd73364b58acb70e61a49f2427 | ray | test_nn_framework_import_errors.py | 13 | 6 | https://github.com/ray-project/ray.git | 2 | 58 | 0 | 28 | 108 | Python | {
"docstring": "Check error being thrown, if tf not installed but configured.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | def test_dont_import_tf_error():
# Do not import tf for testing purposes.
os.environ["RLLIB_TEST_NO_TF_IMPORT"] = "1"
config = ppo.PPOConfig().environment("CartPole-v1")
for _ in framework_iterator(config, frameworks=("tf", "tf2")):
with pytest.raises(ImportError, match="However, no instal... | |
54,870 | 217,655 | 78 | python3.10.4/Lib/hmac.py | 13 | 9 | def _current(self):
if self._hmac:
return self._hmac
else:
h = self._outer.copy()
| add python 3.10.4 for windows | _current | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | XX-Net | hmac.py | 13 | 7 | https://github.com/XX-net/XX-Net.git | 2 | 40 | 0 | 11 | 69 | Python | {
"docstring": "Return a hash object for the current state.\n\n To be used only internally with digest() and hexdigest().\n ",
"language": "en",
"n_whitespaces": 31,
"n_words": 17,
"vocab_size": 17
} | def _current(self):
if self._hmac:
return self._hmac
else:
h = self._outer.copy()
h.update(self._inner.digest())
return h
| |
13,559 | 64,064 | 12 | erpnext/patches/v13_0/delete_old_sales_reports.py | 16 | 8 | def delete_links_from_desktop_icons(report):
desktop_icons = frappe.db.get_values("Desktop Icon", {"_report": report}, ["name"])
for desktop_icon in desktop_icons:
frappe.delete_doc("Desktop Icon", desktop_icon[0]) | fix: broken patches (backport #29067) (#29406)
* chore: patch fixes
(cherry picked from commit 8b5b146f6d2720587a16f78a8d47840be8dca2b7)
# Conflicts:
# erpnext/patches/v13_0/make_homepage_products_website_items.py
* fix: remove desktop icons while deleting sales reports
(cherry picked from commit 5f72026c... | delete_links_from_desktop_icons | f469ec87d94d4639ff4eb99a45496721c4779bf3 | erpnext | delete_old_sales_reports.py | 11 | 4 | https://github.com/frappe/erpnext.git | 2 | 42 | 0 | 15 | 73 | Python | {
"docstring": " Check for one or multiple Desktop Icons and delete ",
"language": "en",
"n_whitespaces": 10,
"n_words": 9,
"vocab_size": 9
} | def delete_links_from_desktop_icons(report):
desktop_icons = frappe.db.get_values("Desktop Icon", {"_report": report}, ["name"])
for desktop_icon in desktop_icons:
frappe.delete_doc("Desktop Icon", desktop_icon[0]) | |
4,761 | 24,519 | 143 | ppstructure/table/table_master_match.py | 64 | 18 | def get_bboxes_list(end2end_result, structure_master_result):
# end2end
e | add SLANet | get_bboxes_list | ddaa2c2552e19635cd6cdf38619f1f176c358f89 | PaddleOCR | table_master_match.py | 10 | 16 | https://github.com/PaddlePaddle/PaddleOCR.git | 2 | 93 | 0 | 37 | 159 | Python | {
"docstring": "\n This function is use to convert end2end results and structure master results to\n List of xyxy bbox format and List of xywh bbox format\n :param end2end_result: bbox's format is xyxy\n :param structure_master_result: bbox's format is xywh\n :return: 4 kind list of bbox ()\n ",
"... | def get_bboxes_list(end2end_result, structure_master_result):
# end2end
end2end_xyxy_list = []
end2end_xywh_list = []
for end2end_item in end2end_result:
src_bbox = end2end_item['bbox']
end2end_xyxy_list.append(src_bbox)
xywh_bbox = xyxy2xywh(src_bbox)
end2end_xywh_l... | |
3,424 | 20,557 | 145 | pipenv/patched/notpip/_vendor/pyparsing/core.py | 134 | 46 | def autoname_elements() -> None:
for name, var in sys._getframe().f_back.f_locals.items():
if isinstance(var, ParserElement) and not var.customName:
var.set_name(name)
dbl_quoted_string = Combine(
Regex(r'"(?:[^"\n\r\\]|(?:"")|(?:\\(?:[^x]|x[0-9a-fA-F]+)))*') + '"'
).set_name("string ... | 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... | autoname_elements | f3166e673fe8d40277b804d35d77dcdb760fc3b3 | pipenv | core.py | 13 | 8 | https://github.com/pypa/pipenv.git | 4 | 45 | 0 | 87 | 339 | Python | {
"docstring": "\n Utility to simplify mass-naming of parser elements, for\n generating railroad diagram with named subdiagrams.\n ",
"language": "en",
"n_whitespaces": 24,
"n_words": 14,
"vocab_size": 14
} | def autoname_elements() -> None:
for name, var in sys._getframe().f_back.f_locals.items():
if isinstance(var, ParserElement) and not var.customName:
var.set_name(name)
dbl_quoted_string = Combine(
Regex(r'"(?:[^"\n\r\\]|(?:"")|(?:\\(?:[^x]|x[0-9a-fA-F]+)))*') + '"'
).set_name("string ... | |
21,486 | 102,171 | 58 | tools/test/test_gen_backend_stubs.py | 30 | 4 | def test_valid_zero_ops_doesnt_require_backend_dispatch_key(self) -> None:
yaml_str =
# External codegen on a yaml file with no operators is effectively a no-op,
| Revert "Revert D32498569: allow external backend codegen to toggle whether to generate out= and inplace kernels" (#69950)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69950
This reverts commit f6cad53443704dfe5a20cc62bee14d91e3bffcaa.
Test Plan: Imported from OSS
Reviewed By: albanD
Diff... | test_valid_zero_ops_doesnt_require_backend_dispatch_key | bb5b4cceb6f737448eaaa6817cd773b6f4b0e77d | pytorch | test_gen_backend_stubs.py | 7 | 6 | https://github.com/pytorch/pytorch.git | 1 | 16 | 0 | 27 | 32 | Python | {
"docstring": "\\\nbackend: BAD_XLA\ncpp_namespace: torch_xla\nsupported:",
"language": "en",
"n_whitespaces": 2,
"n_words": 6,
"vocab_size": 6
} | def test_valid_zero_ops_doesnt_require_backend_dispatch_key(self) -> None:
yaml_str =
# External codegen on a yaml file with no operators is effectively a no-op,
# so there's no reason to parse the backend
self.assert_success_from_gen_backend_stubs(yaml_str)
| |
1,809 | 9,995 | 322 | tests/distributed/test_remote_peas/test_remote_peas.py | 132 | 41 | async def test_pseudo_remote_peas_topologies(gateway, head, worker):
worker_port = random_port()
head_port = random_port()
port_expose = random_port()
graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}'
if head == 'remote':
pods_addresses = f'{{"pod0": ["{HOST}:{h... | feat: star routing (#3900)
* feat(proto): adjust proto for star routing (#3844)
* feat(proto): adjust proto for star routing
* feat(proto): generate proto files
* feat(grpc): refactor grpclet interface (#3846)
* feat: refactor connection pool for star routing (#3872)
* feat(k8s): add more labels to k8s ... | test_pseudo_remote_peas_topologies | 933415bfa1f9eb89f935037014dfed816eb9815d | jina | test_remote_peas.py | 12 | 33 | https://github.com/jina-ai/jina.git | 4 | 210 | 0 | 85 | 316 | Python | {
"docstring": "\n g(l)-h(l)-w(l) - works\n g(l)-h(l)-w(r) - works - head connects to worker via localhost\n g(l)-h(r)-w(r) - works - head (inside docker) connects to worker via dockerhost\n g(l)-h(r)-w(l) - doesn't work remote head need remote worker\n g(r)-... - doesn't work, as distributed parser no... | async def test_pseudo_remote_peas_topologies(gateway, head, worker):
worker_port = random_port()
head_port = random_port()
port_expose = random_port()
graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}'
if head == 'remote':
pods_addresses = f'{{"pod0": ["{HOST}:{h... | |
1,728 | 9,848 | 217 | jina/peapods/peas/__init__.py | 50 | 19 | async def async_wait_start_success(self):
import asyncio
_timeout = self.args.timeout_ready
if _timeout <= 0:
_timeout = None
else:
_timeout /= 1e3
timeout_ns = 1e9 * _timeout if _timeout else None
now = time.time_ns()
while time... | feat: star routing (#3900)
* feat(proto): adjust proto for star routing (#3844)
* feat(proto): adjust proto for star routing
* feat(proto): generate proto files
* feat(grpc): refactor grpclet interface (#3846)
* feat: refactor connection pool for star routing (#3872)
* feat(k8s): add more labels to k8s ... | async_wait_start_success | 933415bfa1f9eb89f935037014dfed816eb9815d | jina | __init__.py | 13 | 17 | https://github.com/jina-ai/jina.git | 6 | 102 | 0 | 34 | 168 | Python | {
"docstring": "\n Wait for the `Pea` to start successfully in a non-blocking manner\n ",
"language": "en",
"n_whitespaces": 26,
"n_words": 11,
"vocab_size": 11
} | async def async_wait_start_success(self):
import asyncio
_timeout = self.args.timeout_ready
if _timeout <= 0:
_timeout = None
else:
_timeout /= 1e3
timeout_ns = 1e9 * _timeout if _timeout else None
now = time.time_ns()
while time... | |
23,550 | 109,359 | 55 | lib/matplotlib/offsetbox.py | 16 | 9 | def set_fontsize(self, s=None):
if s is None:
s = mpl.rcParams["legend.fontsize"]
self.prop = FontProperties(size=s)
self.stale = True
| Get rcParams from mpl | set_fontsize | 438d30b227b1fef7e8733578f851e76a8e360f24 | matplotlib | offsetbox.py | 10 | 5 | https://github.com/matplotlib/matplotlib.git | 2 | 38 | 0 | 13 | 64 | Python | {
"docstring": "\n Set the fontsize in points.\n\n If *s* is not given, reset to :rc:`legend.fontsize`.\n ",
"language": "en",
"n_whitespaces": 35,
"n_words": 13,
"vocab_size": 13
} | def set_fontsize(self, s=None):
if s is None:
s = mpl.rcParams["legend.fontsize"]
self.prop = FontProperties(size=s)
self.stale = True
| |
29,858 | 132,899 | 233 | python/ray/util/actor_pool.py | 71 | 25 | def get_next(self, timeout=None):
if not s | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | get_next | 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | ray | actor_pool.py | 12 | 18 | https://github.com/ray-project/ray.git | 6 | 133 | 0 | 54 | 218 | Python | {
"docstring": "Returns the next pending result in order.\n\n This returns the next result produced by submit(), blocking for up to\n the specified timeout until it is available.\n\n Returns:\n The next result.\n\n Raises:\n TimeoutError if the timeout is reached.\n\n... | def get_next(self, timeout=None):
if not self.has_next():
raise StopIteration("No more results to get")
if self._next_return_index >= self._next_task_index:
raise ValueError(
"It is not allowed to call get_next() after " "get_next_unordered()."
... | |
3,716 | 21,185 | 259 | pipenv/environment.py | 44 | 26 | def expand_egg_links(self) -> None:
prefixes = [
Path(prefix)
for prefix in self.base_paths["libdirs"].split(os.pathsep)
if vistir.path.is_in_path(prefix, self.prefix.as_posix())
]
for loc in prefixes:
if not loc.exists():
... | Convert type comments to type annotations | expand_egg_links | 4b996c0fa85824b323ad9eff3364dbe2213ebb4c | pipenv | environment.py | 16 | 21 | https://github.com/pypa/pipenv.git | 8 | 120 | 0 | 31 | 200 | Python | {
"docstring": "\n Expand paths specified in egg-link files to prevent pip errors during\n reinstall\n ",
"language": "en",
"n_whitespaces": 34,
"n_words": 12,
"vocab_size": 12
} | def expand_egg_links(self) -> None:
prefixes = [
Path(prefix)
for prefix in self.base_paths["libdirs"].split(os.pathsep)
if vistir.path.is_in_path(prefix, self.prefix.as_posix())
]
for loc in prefixes:
if not loc.exists():
... | |
17,698 | 83,638 | 56 | zerver/tests/test_link_embed.py | 22 | 10 | def test_page_with_og(self) -> None:
| preview: Use a dataclass for the embed data.
This is significantly cleaner than passing around `Dict[str, Any]` all
of the time. | test_page_with_og | 327ff9ea0f5e4712a34d767fee55a549cc1d3f39 | zulip | test_link_embed.py | 9 | 14 | https://github.com/zulip/zulip.git | 1 | 46 | 0 | 19 | 79 | Python | {
"docstring": "<html>\n <head>\n <meta property=\"og:title\" content=\"The Rock\" />\n <meta property=\"og:type\" content=\"video.movie\" />\n <meta property=\"og:url\" content=\"http://www.imdb.com/title/tt0117500/\" />\n <meta property=\"og:image\" content=\"http://ia.m... | def test_page_with_og(self) -> None:
html = b
parser = OpenGraphParser(html, "text/html; charset=UTF-8")
result = parser.extract_data()
self.assertEqual(result.title, "The Rock")
self.assertEqual(result.description, "The Rock film")
| |
48,207 | 196,831 | 120 | sympy/core/expr.py | 26 | 9 | def is_rational_function(self, *syms):
if self in _illegal:
return False
if syms:
syms = set(map(sympify, syms))
else:
syms = self.free_symbols
if not syms:
return True
return self._eval_is_rational_function(syms)... | Moved definition of illegal | is_rational_function | 117f9554466e08aa4178137ad65fae1f2d49b340 | sympy | expr.py | 12 | 10 | https://github.com/sympy/sympy.git | 4 | 50 | 0 | 19 | 83 | Python | {
"docstring": "\n Test whether function is a ratio of two polynomials in the given\n symbols, syms. When syms is not given, all free symbols will be used.\n The rational function does not have to be in expanded or in any kind of\n canonical form.\n\n This function returns False for... | def is_rational_function(self, *syms):
if self in _illegal:
return False
if syms:
syms = set(map(sympify, syms))
else:
syms = self.free_symbols
if not syms:
return True
return self._eval_is_rational_function(syms)... | |
48,713 | 197,838 | 39 | sympy/polys/numberfields/primes.py | 11 | 14 | def reduce_alg_num(self, a):
elt = self.ZK.parent.element_from_alg_num(a)
red = self.reduce_element(elt)
return a.field_element(list(reversed(red.QQ_col.f | Improve `PrimeIdeal` reduction methods. | reduce_alg_num | af44b30d68265acb25340374b648e198fb5570e7 | sympy | primes.py | 14 | 4 | https://github.com/sympy/sympy.git | 1 | 47 | 0 | 10 | 78 | Python | {
"docstring": "\n Reduce an :py:class:`~.AlgebraicNumber` to a \"small representative\"\n modulo this prime ideal.\n\n Parameters\n ==========\n\n elt : :py:class:`~.AlgebraicNumber`\n The element to be reduced.\n\n Returns\n =======\n\n :py:class:`~... | def reduce_alg_num(self, a):
elt = self.ZK.parent.element_from_alg_num(a)
red = self.reduce_element(elt)
return a.field_element(list(reversed(red.QQ_col.flat())))
| |
118,204 | 322,610 | 452 | paddlenlp/taskflow/task.py | 79 | 24 | def _auto_joiner(self, short_results, input_mapping, is_dict=False):
concat_results = []
elem_type = {} if is_dict else []
for k, vs in input_mapping.items():
single_results = elem_type
for v in vs:
if len(single_results) == 0:
... | Update Taskflow word_segmentation and ner tasks (#1666)
* Add AutoSplitter & AutoJoiner
* codestyle fix
* unify auto joiner
* add comments
* add sentence split mode
* update params
* add paddle version check
* add wordtag for word_segmentation
* add wordtag for word_segmentation
* add ner-la... | _auto_joiner | 1e2ee01dade0d4076ba98aa613c3eb150c615abb | PaddleNLP | task.py | 21 | 23 | https://github.com/PaddlePaddle/PaddleNLP.git | 9 | 159 | 0 | 59 | 252 | Python | {
"docstring": "\n Join the short results automatically and generate the final results to match with the user inputs.\n Args:\n short_results (List[dict] / List[List[str]] / List[str]): input raw texts.\n input_mapping (dict): cutting length.\n is_dict (bool): whether th... | def _auto_joiner(self, short_results, input_mapping, is_dict=False):
concat_results = []
elem_type = {} if is_dict else []
for k, vs in input_mapping.items():
single_results = elem_type
for v in vs:
if len(single_results) == 0:
... | |
80,043 | 269,373 | 125 | keras/applications/efficientnet_weight_update_util.py | 66 | 9 | def get_variable_names_from_ckpt(path_ckpt, use_ema=True):
v_all = tf.train.list_variables(path_ckpt)
# keep name only
v_name_all = [x[0] for x in v_all]
if use_ema:
v_name_all = [x for x in v_name_all if "ExponentialMovingAverage" in x]
else:
v_name_all = [
x for ... | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | get_variable_names_from_ckpt | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | efficientnet_weight_update_util.py | 13 | 11 | https://github.com/keras-team/keras.git | 9 | 80 | 0 | 32 | 130 | Python | {
"docstring": "Get list of tensor names from checkpoint.\n\n Args:\n path_ckpt: str, path to the ckpt files\n use_ema: Bool, whether to use ExponentialMovingAverage result or not.\n Returns:\n List of variable names from checkpoint.\n ",
"language": "en",
"n_whitespaces": 55,
"n_words":... | def get_variable_names_from_ckpt(path_ckpt, use_ema=True):
v_all = tf.train.list_variables(path_ckpt)
# keep name only
v_name_all = [x[0] for x in v_all]
if use_ema:
v_name_all = [x for x in v_name_all if "ExponentialMovingAverage" in x]
else:
v_name_all = [
x for ... | |
48,925 | 198,418 | 103 | sympy/solvers/deutils.py | 38 | 14 | def ode_order(expr, func):
| Improve loop performance in solvers | ode_order | bd9f607176c58dfba01e27c05c2b7d49ff97c901 | sympy | deutils.py | 17 | 11 | https://github.com/sympy/sympy.git | 6 | 103 | 0 | 26 | 161 | Python | {
"docstring": "\n Returns the order of a given differential\n equation with respect to func.\n\n This function is implemented recursively.\n\n Examples\n ========\n\n >>> from sympy import Function\n >>> from sympy.solvers.deutils import ode_order\n >>> from sympy.abc import x\n >>> f, g =... | def ode_order(expr, func):
a = Wild('a', exclude=[func])
if expr.match(a):
return 0
if isinstance(expr, Derivative):
if expr.args[0] == func:
return len(expr.variables)
else:
return max(ode_order(arg, func) for arg in expr.args[0].args) + len(expr.variab... | |
91,035 | 291,932 | 866 | homeassistant/components/discord/notify.py | 170 | 53 | async def async_send_message(self, message, **kwargs):
nextcord.VoiceClient.warn_nacl = False
discord_bot = nextcord.Client()
images = None
embedding = None
if ATTR_TARGET not in kwargs:
_LOGGER.error("No target specified")
return None
d... | Replace discord.py with nextcord (#66540)
* Replace discord.py with nextcord
* Typing tweak
* Another pip check decrease :) | async_send_message | cb03db8df4bf8b50945b36a4b0debcaaed1190a8 | core | notify.py | 18 | 51 | https://github.com/home-assistant/core.git | 19 | 347 | 0 | 102 | 564 | Python | {
"docstring": "Login to Discord, send message to channel(s) and log out.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 9
} | async def async_send_message(self, message, **kwargs):
nextcord.VoiceClient.warn_nacl = False
discord_bot = nextcord.Client()
images = None
embedding = None
if ATTR_TARGET not in kwargs:
_LOGGER.error("No target specified")
return None
d... | |
@pytest.fixture(
params=[
(
Interval(left=0, right=5, inclusive="right"),
IntervalDtype("int64", inclusive="right"),
),
(
Interval(left=0.1, right=0.5, inclusive="right"),
IntervalDtype("float64", inclusive="right"),
),
(Period(... | 40,065 | 167,613 | 290 | pandas/conftest.py | 78 | 24 | def rand_series_with_duplicate_datetimeindex() -> Series:
dates = [
datetime(2000, 1, 2),
datetime(2000, 1, 2),
datetime(2000, 1, 2),
datetime(2000, 1, 3),
datetime(2000, 1, 3),
datetime(2000, 1, 3),
datetime(2000, 1, 4),
datetime(2000, 1, 4),
... | TYP: misc return type annotations (#47558) | rand_series_with_duplicate_datetimeindex | f538568afc2c76c2d738d32e3544cf9fe6742960 | pandas | conftest.py | 13 | 17 | https://github.com/pandas-dev/pandas.git | 1 | 120 | 1 | 43 | 360 | Python | {
"docstring": "\n Fixture for Series with a DatetimeIndex that has duplicates.\n ",
"language": "en",
"n_whitespaces": 16,
"n_words": 9,
"vocab_size": 9
} | def rand_series_with_duplicate_datetimeindex() -> Series:
dates = [
datetime(2000, 1, 2),
datetime(2000, 1, 2),
datetime(2000, 1, 2),
datetime(2000, 1, 3),
datetime(2000, 1, 3),
datetime(2000, 1, 3),
datetime(2000, 1, 4),
datetime(2000, 1, 4),
... |
12,285 | 60,770 | 18 | .venv/lib/python3.8/site-packages/pip/_internal/locations/base.py | 9 | 4 | def get_major_minor_version():
# typ | upd; format | get_major_minor_version | f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | transferlearning | base.py | 9 | 2 | https://github.com/jindongwang/transferlearning.git | 1 | 15 | 0 | 9 | 31 | Python | {
"docstring": "\n Return the major-minor version of the current Python as a string, e.g.\n \"3.7\" or \"3.10\".\n ",
"language": "en",
"n_whitespaces": 25,
"n_words": 15,
"vocab_size": 14
} | def get_major_minor_version():
# type: () -> str
return "{}.{}".format(*sys.version_info)
| |
70,501 | 244,731 | 1,066 | tests/test_models/test_dense_heads/test_ssd_head.py | 232 | 61 | def test_ssd_head_loss(self):
s = 300
img_metas = [{
'img_shape': (s, s, 3),
'scale_factor': 1,
}]
cfg = Config(
dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
... | Update SSD and PISA-SSD model config | test_ssd_head_loss | 9d7511d8c35df1f9c13b17eb770136859bf370be | mmdetection | test_ssd_head.py | 15 | 64 | https://github.com/open-mmlab/mmdetection.git | 2 | 471 | 0 | 154 | 677 | Python | {
"docstring": "Tests ssd head loss when truth is empty and non-empty.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | def test_ssd_head_loss(self):
s = 300
img_metas = [{
'img_shape': (s, s, 3),
'scale_factor': 1,
}]
cfg = Config(
dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
... | |
20,129 | 100,671 | 394 | tools/alignments/jobs.py | 160 | 24 | def _legacy_check(self) -> None:
if self._min_size > 0 or self._arguments.extract_every_n != 1:
logger.warning("This alignments file was generated with the legacy extraction method.")
logger.warning("You should run this extraction job, but with 'min_size' set to 0 and "
... | Alignments tool - Replace 'extract-large' with 'min-size' | _legacy_check | a9908b46f77dc66ac7efe7100ea0eed4b1f2b460 | faceswap | jobs.py | 12 | 26 | https://github.com/deepfakes/faceswap.git | 7 | 143 | 0 | 103 | 256 | Python | {
"docstring": " Check whether the alignments file was created with the legacy extraction method.\n\n If so, force user to re-extract all faces if any options have been specified, otherwise\n raise the appropriate warnings and set the legacy options.\n ",
"language": "en",
"n_whitespaces": 58... | def _legacy_check(self) -> None:
if self._min_size > 0 or self._arguments.extract_every_n != 1:
logger.warning("This alignments file was generated with the legacy extraction method.")
logger.warning("You should run this extraction job, but with 'min_size' set to 0 and "
... | |
48,106 | 196,688 | 18 | sympy/stats/crv_types.py | 15 | 6 | def FisherZ(name, d1, d2):
r
return rv(name, FisherZDistribution, (d1, d2))
#-------------------------------------------------------------------------------
# Frechet distribution ----- | Documentation cleanup 5 | FisherZ | 9ad8ab9fe58051cf11626ba6654852fcfec60147 | sympy | crv_types.py | 8 | 61 | https://github.com/sympy/sympy.git | 1 | 24 | 0 | 15 | 36 | Python | {
"docstring": "\n Create a Continuous Random Variable with an Fisher's Z distribution.\n\n Explanation\n ===========\n\n The density of the Fisher's Z distribution is given by\n\n .. math::\n f(x) := \\frac{2d_1^{d_1/2} d_2^{d_2/2}} {\\mathrm{B}(d_1/2, d_2/2)}\n \\frac{e^{d_1z}}{... | def FisherZ(name, d1, d2):
r
return rv(name, FisherZDistribution, (d1, d2))
#-------------------------------------------------------------------------------
# Frechet distribution ---------------------------------------------------------
| |
6,828 | 37,529 | 177 | src/transformers/trainer_pt_utils.py | 60 | 17 | def find_batch_size(tensors):
if isinstance(tensors, (list, tuple)):
for t in tensors:
result = find_batch_size(t)
if result is not None:
return result
elif isinstance(tensors, Mapping):
for key, value in tensors.items():
result = find_bat... | Replace dict/BatchEncoding instance checks by Mapping (#17014)
* Replace dict/BatchEncoding instance checks by Mapping
* Typo | find_batch_size | 18df440709f1b19d1c5617c0d987c5ff8fd0915d | transformers | trainer_pt_utils.py | 13 | 15 | https://github.com/huggingface/transformers.git | 11 | 126 | 0 | 31 | 192 | Python | {
"docstring": "\n Find the first dimension of a tensor in a nested list/tuple/dict of tensors.\n ",
"language": "en",
"n_whitespaces": 20,
"n_words": 13,
"vocab_size": 11
} | def find_batch_size(tensors):
if isinstance(tensors, (list, tuple)):
for t in tensors:
result = find_batch_size(t)
if result is not None:
return result
elif isinstance(tensors, Mapping):
for key, value in tensors.items():
result = find_bat... | |
6,842 | 37,632 | 35 | src/transformers/models/yolos/feature_extraction_yolos.py | 14 | 11 | def post_process_segmentation(self, outputs, target_sizes, threshold=0.9, mask_threshold=0.5):
out_logits, raw_masks = outputs.logits, outputs.pred_masks
preds = []
| Add YOLOS (#16848)
* First draft
* Add YolosForObjectDetection
* Make forward pass work
* Add mid position embeddings
* Add interpolation of position encodings
* Add expected values
* Add YOLOS to tests
* Add integration test
* Support tiny model as well
* Support all models in conversion sc... | post_process_segmentation | 1ac698744c4dbdf1495d303246d08ffacdf4f5b8 | transformers | feature_extraction_yolos.py | 8 | 16 | https://github.com/huggingface/transformers.git | 2 | 196 | 0 | 13 | 51 | Python | {
"docstring": "\n Converts the output of [`DetrForSegmentation`] into image segmentation predictions. Only supports PyTorch.\n\n Parameters:\n outputs ([`DetrSegmentationOutput`]):\n Raw outputs of the model.\n target_sizes (`torch.Tensor` of shape `(batch_size, 2)`... | def post_process_segmentation(self, outputs, target_sizes, threshold=0.9, mask_threshold=0.5):
out_logits, raw_masks = outputs.logits, outputs.pred_masks
preds = []
| |
47,707 | 196,207 | 114 | sympy/combinatorics/subsets.py | 14 | 12 | def iterate_graycode(self, k):
unranked_code = GrayCode.unrank(self.superset_size,
| Updated import locations | iterate_graycode | 498015021131af4dbb07eb110e5badaba8250c7b | sympy | subsets.py | 12 | 5 | https://github.com/sympy/sympy.git | 1 | 41 | 0 | 14 | 64 | Python | {
"docstring": "\n Helper function used for prev_gray and next_gray.\n It performs ``k`` step overs to get the respective Gray codes.\n\n Examples\n ========\n\n >>> from sympy.combinatorics import Subset\n >>> a = Subset([1, 2, 3], [1, 2, 3, 4])\n >>> a.iterate_grayco... | def iterate_graycode(self, k):
unranked_code = GrayCode.unrank(self.superset_size,
(self.rank_gray + k) % self.cardinality)
return Subset.subset_from_bitlist(self.superset,
unranked_code)
| |
81,150 | 273,879 | 32 | keras/layers/rnn/gru_lstm_utils.py | 17 | 15 | def is_sequence_right_padded(mask):
max_seq_length = tf.shape(mask)[1]
count_of_true = tf.reduce_sum(tf.cast(mask, tf.int32), axis=1)
right_padded_mask = tf.sequence_mask(count_of_true, maxlen=max_seq_length)
| Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | is_sequence_right_padded | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | gru_lstm_utils.py | 11 | 5 | https://github.com/keras-team/keras.git | 1 | 64 | 0 | 15 | 100 | Python | {
"docstring": "Check the mask tensor and see if it right padded.\n\n For cuDNN kernel, it uses the sequence length param to skip the tailing\n timestep. If the data is left padded, or not a strict right padding (has\n masked value in the middle of the sequence), then cuDNN kernel won't be work\n properly... | def is_sequence_right_padded(mask):
max_seq_length = tf.shape(mask)[1]
count_of_true = tf.reduce_sum(tf.cast(mask, tf.int32), axis=1)
right_padded_mask = tf.sequence_mask(count_of_true, maxlen=max_seq_length)
return tf.reduce_all(tf.equal(mask, right_padded_mask))
| |
71,154 | 246,321 | 385 | tests/rest/client/test_third_party_rules.py | 49 | 17 | def _send_event_over_federation(self) -> None:
body = {
"pdus": [
{
"sender": self.user_id,
"type": EventTypes.Message,
"state_key": "",
"content": {"body": "hello world", "msgtype": "m.text"},
... | Tests: replace mocked Authenticator with the real thing (#11913)
If we prepopulate the test homeserver with a key for a remote homeserver, we
can make federation requests to it without having to stub out the
authenticator. This has two advantages:
* means that what we are testing is closer to reality (ie, we now... | _send_event_over_federation | c3db7a0b59d48b8872bc24096f9a2467ef35f703 | synapse | test_third_party_rules.py | 14 | 25 | https://github.com/matrix-org/synapse.git | 1 | 120 | 0 | 44 | 211 | Python | {
"docstring": "Send a dummy event over federation and check that the request succeeds.",
"language": "en",
"n_whitespaces": 11,
"n_words": 12,
"vocab_size": 12
} | def _send_event_over_federation(self) -> None:
body = {
"pdus": [
{
"sender": self.user_id,
"type": EventTypes.Message,
"state_key": "",
"content": {"body": "hello world", "msgtype": "m.text"},
... | |
19,876 | 100,391 | 88 | plugins/train/trainer/_base.py | 26 | 15 | def _print_loss(self, loss):
output = ", ".join([f"Loss {side}: {side_loss:.5f}"
for side, side_loss in zip(("A", "B"), loss)])
timestamp = time.strftime("%H:%M:%S")
output = f"[{timestamp}] [#{self._model.iterations:05d}] {output}"
| 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 -... | _print_loss | c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf | faceswap | _base.py | 14 | 6 | https://github.com/deepfakes/faceswap.git | 2 | 55 | 0 | 23 | 132 | Python | {
"docstring": " Outputs the loss for the current iteration to the console.\n\n Parameters\n ----------\n loss: list\n The loss for each side. List should contain 2 ``floats`` side \"a\" in position 0 and\n side \"b\" in position `.\n ",
"language": "en",
"n_whit... | def _print_loss(self, loss):
output = ", ".join([f"Loss {side}: {side_loss:.5f}"
for side, side_loss in zip(("A", "B"), loss)])
timestamp = time.strftime("%H:%M:%S")
output = f"[{timestamp}] [#{self._model.iterations:05d}] {output}"
print(f"\r{output}... | |
56,285 | 221,238 | 41 | python3.10.4/Lib/calendar.py | 16 | 9 | def itermonthdays2(self, year, month):
for i, d in enumerate(self.itermonthdays(year, mont | add python 3.10.4 for windows | itermonthdays2 | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | XX-Net | calendar.py | 10 | 3 | https://github.com/XX-net/XX-Net.git | 2 | 37 | 0 | 16 | 57 | Python | {
"docstring": "\n Like itermonthdates(), but will yield (day number, weekday number)\n tuples. For days outside the specified month the day number is 0.\n ",
"language": "en",
"n_whitespaces": 43,
"n_words": 21,
"vocab_size": 20
} | def itermonthdays2(self, year, month):
for i, d in enumerate(self.itermonthdays(year, month), self.firstweekday):
yield d, i % 7
| |
99,493 | 300,633 | 36 | tests/helpers/test_template.py | 17 | 11 | def test_distance_function_return_none_if_invalid_state(hass):
hass.states.async_set("test.object_2", "happy", {"latitude": 10})
tpl = template.Template("{{ distance(states.test.object_2) | round }}", hass)
with pytes | Fail template functions when no default specified (#71687) | test_distance_function_return_none_if_invalid_state | 4885331509eeffe50f42d76b234996467b06170f | core | test_template.py | 10 | 5 | https://github.com/home-assistant/core.git | 1 | 45 | 0 | 17 | 83 | Python | {
"docstring": "Test distance function return None if invalid state.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | def test_distance_function_return_none_if_invalid_state(hass):
hass.states.async_set("test.object_2", "happy", {"latitude": 10})
tpl = template.Template("{{ distance(states.test.object_2) | round }}", hass)
with pytest.raises(TemplateError):
tpl.async_render()
| |
elif sys.version_info[:2] >= (3, 7):sys | 3,609 | 20,890 | 25 | pipenv/patched/notpip/_vendor/typing_extensions.py | 13 | 7 | def Concatenate(self, parameters):
return _con | 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... | Concatenate | f3166e673fe8d40277b804d35d77dcdb760fc3b3 | pipenv | typing_extensions.py | 7 | 2 | https://github.com/pypa/pipenv.git | 1 | 15 | 2 | 13 | 48 | Python | {
"docstring": "Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a\n higher order function which adds, removes or transforms parameters of a\n callable.\n\n For example::\n\n Callable[Concatenate[int, P], int]\n\n See PEP 612 for detailed information.\n ... | def Concatenate(self, parameters):
return _concatenate_getitem(self, parameters)
# 3.7-8
elif sys.version_info[:2] >= (3, 7): |
26,587 | 119,349 | 116 | tests/ann_test.py | 55 | 19 | def compute_recall(result_neighbors, ground_truth_neighbors) -> float:
| [JAX] Move ann.ann_recall back to tests.
The function is simple enough for users to implement their own on the host.
PiperOrigin-RevId: 430696789 | compute_recall | 8372b98c4856b6b2363b7bb28abdb4579440a656 | jax | ann_test.py | 16 | 25 | https://github.com/google/jax.git | 5 | 105 | 0 | 37 | 164 | Python | {
"docstring": "Computes the recall of an approximate nearest neighbor search.\n\n Args:\n result_neighbors: int32 numpy array of the shape [num_queries,\n neighbors_per_query] where the values are the indices of the dataset.\n ground_truth_neighbors: int32 numpy array of with shape [num_queries,\n g... | def compute_recall(result_neighbors, ground_truth_neighbors) -> float:
assert len(
result_neighbors.shape) == 2, "shape = [num_queries, neighbors_per_query]"
assert len(ground_truth_neighbors.shape
) == 2, "shape = [num_queries, ground_truth_neighbors_per_query]"
assert result_neighbors.shape... | |
39,469 | 163,635 | 108 | pandas/core/arrays/datetimes.py | 30 | 15 | def isocalendar(self) -> DataFrame:
from pandas import DataFrame
values = self._local_timestamps()
sarray = fields.build_isocalendar_sarray(values)
iso_calendar_df = DataFrame(
sarray, columns=["year", "week", "day"], dtype="UInt32"
)
if self._hasna:... | EA interface: rename ExtensionArray._hasnans to ._hasna (#45519) | isocalendar | a0b40c0f2ad73420a54e48ec4f564b9667e3f452 | pandas | datetimes.py | 11 | 44 | https://github.com/pandas-dev/pandas.git | 2 | 64 | 0 | 26 | 109 | Python | {
"docstring": "\n Returns a DataFrame with the year, week, and day calculated according to\n the ISO 8601 standard.\n\n .. versionadded:: 1.1.0\n\n Returns\n -------\n DataFrame\n with columns year, week and day\n\n See Also\n --------\n Times... | def isocalendar(self) -> DataFrame:
from pandas import DataFrame
values = self._local_timestamps()
sarray = fields.build_isocalendar_sarray(values)
iso_calendar_df = DataFrame(
sarray, columns=["year", "week", "day"], dtype="UInt32"
)
if self._hasna:... | |
70,002 | 243,180 | 264 | src/PIL/Image.py | 71 | 17 | def putpixel(self, xy, value):
if self.readonly:
self._copy()
self.load()
if self.pyaccess:
return self.pyaccess.putpixel(xy, value)
if (
self.mode in ("P", "PA")
and isinstance(value, (list, tuple))
and len(value) i... | Allow RGB and RGBA values for PA image putpixel | putpixel | a37593f004247ebf69d5582524da6dc5143cb023 | Pillow | Image.py | 14 | 18 | https://github.com/python-pillow/Pillow.git | 9 | 142 | 0 | 49 | 225 | Python | {
"docstring": "\n Modifies the pixel at the given position. The color is given as\n a single numerical value for single-band images, and a tuple for\n multi-band images. In addition to this, RGB and RGBA tuples are\n accepted for P and PA images.\n\n Note that this method is relati... | def putpixel(self, xy, value):
if self.readonly:
self._copy()
self.load()
if self.pyaccess:
return self.pyaccess.putpixel(xy, value)
if (
self.mode in ("P", "PA")
and isinstance(value, (list, tuple))
and len(value) i... | |
99,301 | 300,441 | 293 | tests/components/template/test_switch.py | 55 | 14 | async def test_available_template_with_entities(hass):
await setup.async_setup_component(
hass,
"switch",
{
"switch": {
"platform": "template",
"switches": {
"test_template_switch": {
**OPTIMISTIC_SW... | Tweak template switch tests (#71738) | test_available_template_with_entities | 11cc1feb853bcfd9633ebfc44eae142c10a7f983 | core | test_switch.py | 17 | 26 | https://github.com/home-assistant/core.git | 1 | 123 | 0 | 34 | 224 | Python | {
"docstring": "Test availability templates with values from other entities.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | async def test_available_template_with_entities(hass):
await setup.async_setup_component(
hass,
"switch",
{
"switch": {
"platform": "template",
"switches": {
"test_template_switch": {
**OPTIMISTIC_SW... | |
84,345 | 282,896 | 1,278 | bots/etf/tops.py | 247 | 84 | def etfs_disc_command(sort=""):
# Debug
i | Discord bot massive improvement (#1481)
* allow logs feature flag
* Adding log collection md
* upload last log at startup
* additions/refractor
* refactor
* lint/black ++
* disc
* TimeRotating Logger and upload to s3
* corrected regex error
* makeup for config
* logging/disc/sia/etf/++
... | etfs_disc_command | 50cafd500ece43df98e3cf076d81084b2806ea03 | OpenBBTerminal | tops.py | 18 | 98 | https://github.com/OpenBB-finance/OpenBBTerminal.git | 10 | 599 | 0 | 146 | 945 | Python | {
"docstring": "Displays ETF's Top Gainers/Decliners, Most Active [Wall Street Journal]",
"language": "en",
"n_whitespaces": 9,
"n_words": 9,
"vocab_size": 9
} | def etfs_disc_command(sort=""):
# Debug
if cfg.DEBUG:
logger.debug("etfs")
df_etfs = wsj_model.etf_movers(sort, export=True)
if df_etfs.empty:
raise Exception("No available data found")
df_etfs.set_index(" ", inplace=True)
prfx = "Top"
if sort == "active":
pr... | |
35,584 | 153,753 | 75 | modin/core/execution/ray/implementations/pandas_on_ray/partitioning/partition.py | 15 | 12 | def get(self):
| FEAT-#4371: Add logging to Modin (#4372)
Co-authored-by: Devin Petersohn <devin.petersohn@gmail.com>
Co-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>
Co-authored-by: Anatoly Myachev <anatoliimyachev@mail.com>
Co-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>
Signed-off-by: Naren Krish... | get | 49fc2cf3733f20ac6cf8a7c61e42ef7aa5cf4b03 | modin | partition.py | 10 | 8 | https://github.com/modin-project/modin.git | 2 | 50 | 0 | 13 | 101 | Python | {
"docstring": "\n Get the object wrapped by this partition out of the Plasma store.\n\n Returns\n -------\n pandas.DataFrame\n The object from the Plasma store.\n ",
"language": "en",
"n_whitespaces": 68,
"n_words": 21,
"vocab_size": 16
} | def get(self):
logger = get_logger()
logger.debug(f"ENTER::Partition.get::{self._identity}")
if len(self.call_queue):
self.drain_call_queue()
result = ray.get(self.oid)
logger.debug(f"EXIT::Partition.get::{self._identity}")
return result
| |
@pytest.fixture | 9,197 | 47,660 | 243 | tests/sensors/test_external_task_sensor.py | 111 | 36 | def dag_bag_ext():
clear_db_runs()
dag_bag = DagBag(dag_folder=DEV_NULL, include_examples=False)
dag_0 = DAG("dag_0", start_date=DEFAULT_DATE, schedule_interval=None)
task_a_0 = EmptyOperator(task_id="task_a_0", dag=dag_0)
task_b_0 = ExternalTaskMarker(
task_id="task_b_0", external_da... | Replace usage of `DummyOperator` with `EmptyOperator` (#22974)
* Replace usage of `DummyOperator` with `EmptyOperator` | dag_bag_ext | 49e336ae0302b386a2f47269a6d13988382d975f | airflow | test_external_task_sensor.py | 10 | 35 | https://github.com/apache/airflow.git | 2 | 290 | 1 | 69 | 460 | Python | {
"docstring": "\n Create a DagBag with DAGs looking like this. The dotted lines represent external dependencies\n set up using ExternalTaskMarker and ExternalTaskSensor.\n\n dag_0: task_a_0 >> task_b_0\n |\n |\n dag_1: ---> task_... | def dag_bag_ext():
clear_db_runs()
dag_bag = DagBag(dag_folder=DEV_NULL, include_examples=False)
dag_0 = DAG("dag_0", start_date=DEFAULT_DATE, schedule_interval=None)
task_a_0 = EmptyOperator(task_id="task_a_0", dag=dag_0)
task_b_0 = ExternalTaskMarker(
task_id="task_b_0", external_da... |
@image_comparison(['constrained_layout4.png']) | 22,615 | 107,160 | 93 | lib/matplotlib/tests/test_constrainedlayout.py | 34 | 16 | def test_constrained_layout3():
fig, axs = plt.subplots(2, 2, layout="constrained")
for nn, ax in enumerate(axs.flat):
pcm = example_pcolor(ax, fontsize=24)
if nn == 3:
pad = 0.08
else:
pad = 0.02 # default
fig.colorbar(pcm, ax=ax, pad=pad)
@image... | ENH: implement and use base layout_engine for more flexible layout. | test_constrained_layout3 | ec4dfbc3c83866f487ff0bc9c87b0d43a1c02b22 | matplotlib | test_constrainedlayout.py | 11 | 9 | https://github.com/matplotlib/matplotlib.git | 3 | 74 | 1 | 30 | 127 | Python | {
"docstring": "Test constrained_layout for colorbars with subplots",
"language": "en",
"n_whitespaces": 5,
"n_words": 6,
"vocab_size": 6
} | def test_constrained_layout3():
fig, axs = plt.subplots(2, 2, layout="constrained")
for nn, ax in enumerate(axs.flat):
pcm = example_pcolor(ax, fontsize=24)
if nn == 3:
pad = 0.08
else:
pad = 0.02 # default
fig.colorbar(pcm, ax=ax, pad=pad)
@image... |
40,114 | 167,771 | 21 | pandas/core/groupby/groupby.py | 7 | 9 | def indices(self) -> dict[Hashable, npt.NDArray[np.intp]]:
return self.grouper.indi | TYP: more return annotations in core/ (#47618)
* TYP: more return annotations in core/
* from __future__ import annotations
* more __future__ | indices | f65417656ba8c59438d832b6e2a431f78d40c21c | pandas | groupby.py | 7 | 5 | https://github.com/pandas-dev/pandas.git | 1 | 26 | 0 | 7 | 41 | Python | {
"docstring": "\n Dict {group name -> group indices}.\n ",
"language": "en",
"n_whitespaces": 21,
"n_words": 6,
"vocab_size": 6
} | def indices(self) -> dict[Hashable, npt.NDArray[np.intp]]:
return self.grouper.indices
| |
12,773 | 61,950 | 146 | .venv/lib/python3.8/site-packages/pip/_vendor/distlib/database.py | 42 | 13 | def get_hash(self, data, hasher=None):
if | upd; format | get_hash | f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | transferlearning | database.py | 12 | 12 | https://github.com/jindongwang/transferlearning.git | 3 | 89 | 0 | 25 | 151 | Python | {
"docstring": "\n Get the hash of some data, using a particular hash algorithm, if\n specified.\n\n :param data: The data to be hashed.\n :type data: bytes\n :param hasher: The name of a hash implementation, supported by hashlib,\n or ``None``. Examples of val... | def get_hash(self, data, hasher=None):
if hasher is None:
hasher = self.hasher
if hasher is None:
hasher = hashlib.md5
prefix = ''
else:
hasher = getattr(hashlib, hasher)
prefix = '%s=' % self.hasher
digest = hasher(dat... | |
30,656 | 135,565 | 173 | rllib/utils/tests/test_actor_manager.py | 63 | 23 | def test_async_call_same_actor_multiple_times(self):
actors = [Actor.remote(i, maybe_crash=False) for i in range(4)]
manager = FaultTolerantActorManager(actors=actors)
# 2 asynchronous call to actor 0.
num_of_calls = manager.foreach_actor_async(
lambda w: w.call(),
... | [RLlib] Introduce FaultTolerantActorManager (#29703)
Signed-off-by: Jun Gong <jungong@anyscale.com> | test_async_call_same_actor_multiple_times | d329147ae28c57b290f6b932f9f3044523f67c4e | ray | test_actor_manager.py | 11 | 11 | https://github.com/ray-project/ray.git | 3 | 107 | 0 | 51 | 168 | Python | {
"docstring": "Test multiple asynchronous remote calls to the same actor.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 9
} | def test_async_call_same_actor_multiple_times(self):
actors = [Actor.remote(i, maybe_crash=False) for i in range(4)]
manager = FaultTolerantActorManager(actors=actors)
# 2 asynchronous call to actor 0.
num_of_calls = manager.foreach_actor_async(
lambda w: w.call(),
... | |
20,731 | 101,313 | 389 | scripts/fsmedia.py | 119 | 19 | def _load(self):
data = {}
if not self._is_extract:
if not self.have_alignments_file:
return data
data = super()._load()
return data
skip_existing = hasattr(self._args, 'skip_existing') and self._args.skip_existing
skip_faces ... | bugfix: debug landmarks | _load | 9e503bdaa2bfe2baaea50ad2e4bf742f309d9d10 | faceswap | fsmedia.py | 14 | 24 | https://github.com/deepfakes/faceswap.git | 15 | 171 | 0 | 73 | 290 | Python | {
"docstring": " Override the parent :func:`~lib.align.Alignments._load` to handle skip existing\n frames and faces on extract.\n\n If skip existing has been selected, existing alignments are loaded and returned to the\n calling script.\n\n Returns\n -------\n dict\n ... | def _load(self):
data = {}
if not self._is_extract:
if not self.have_alignments_file:
return data
data = super()._load()
return data
skip_existing = hasattr(self._args, 'skip_existing') and self._args.skip_existing
skip_faces ... | |
@log_start_end(log=logger) | 85,189 | 285,147 | 24 | openbb_terminal/stocks/discovery/yahoofinance_model.py | 9 | 7 | def get_gtech() -> pd.DataFrame:
return get_df(
"https://finance.y | Fixed bad yfinance urls (#2282) | get_gtech | bd12c203a0585dab6ca3ff81c3b4500e088b41d6 | OpenBBTerminal | yahoofinance_model.py | 8 | 11 | https://github.com/OpenBB-finance/OpenBBTerminal.git | 1 | 14 | 1 | 9 | 40 | Python | {
"docstring": "Get technology stocks with revenue and earnings growth in excess of 25%. [Source: Yahoo Finance]\n\n Returns\n -------\n pd.DataFrame\n Growth technology stocks\n ",
"language": "en",
"n_whitespaces": 40,
"n_words": 21,
"vocab_size": 19
} | def get_gtech() -> pd.DataFrame:
return get_df(
"https://finance.yahoo.com/screener/predefined/growth_technology_stocks"
)
@log_start_end(log=logger) |
@require_torch | 6,455 | 35,457 | 100 | tests/encoder_decoder/test_modeling_encoder_decoder.py | 30 | 21 | def test_bert2gpt2_summarization(self):
model = EncoderDecoderModel.from_pretrained("patrickvonplaten/bert2gpt2-cnn_dailymail-fp16")
model.to(torch_device)
tokenizer_in = AutoTokenizer.from_pretrained("bert-base-case | [Test refactor 1/5] Per-folder tests reorganization (#15725)
* Per-folder tests reorganization
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org> | test_bert2gpt2_summarization | 29c10a41d04f855c433a6cde7797b325651417d2 | transformers | test_modeling_encoder_decoder.py | 12 | 11 | https://github.com/huggingface/transformers.git | 1 | 89 | 1 | 23 | 162 | Python | {
"docstring": "(CNN)Sigma Alpha Epsilon is under fire for a video showing party-bound fraternity members singing a racist chant. SAE's national chapter suspended the students, but University of Oklahoma President David Boren took it a step further, saying the university's affiliation with the fraternity is permanent... | def test_bert2gpt2_summarization(self):
model = EncoderDecoderModel.from_pretrained("patrickvonplaten/bert2gpt2-cnn_dailymail-fp16")
model.to(torch_device)
tokenizer_in = AutoTokenizer.from_pretrained("bert-base-cased")
tokenizer_out = AutoTokenizer.from_pretrained("../gpt2")
A... |
5,294 | 30,056 | 106 | saleor/permission/management.py | 27 | 8 | def _get_builtin_permissions(opts): # noqa: D205, D212
perms = []
for action in opts.default_permissions:
perms.append(
(
get_permission_codename(action, opts),
"Can %s %s" % (action, opts.verbose_name_raw),
)
)
| Move create_permission post migrate signal | _get_builtin_permissions | 3981ae09888569eafe9cbb3a0c659dd337028fa4 | saleor | management.py | 13 | 10 | https://github.com/saleor/saleor.git | 2 | 43 | 0 | 25 | 70 | Python | {
"docstring": "\n Return (codename, name) for all autogenerated permissions.\n By default, this is ('add', 'change', 'delete', 'view')\n ",
"language": "en",
"n_whitespaces": 25,
"n_words": 15,
"vocab_size": 15
} | def _get_builtin_permissions(opts): # noqa: D205, D212
perms = []
for action in opts.default_permissions:
perms.append(
(
get_permission_codename(action, opts),
"Can %s %s" % (action, opts.verbose_name_raw),
)
)
return perms
| |
121,117 | 337,787 | 84 | src/accelerate/accelerator.py | 16 | 9 | def accumulate(self, model):
self._do_sync()
if self.sync_gradients:
context = contextl | Introduce automatic gradient accumulation wrapper + fix a few test issues (#484)
* Have accelerator handle gradient accumulation
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> | accumulate | 86ce737d7fc94f8000dbd5e13021d0411bb4204a | accelerate | accelerator.py | 10 | 8 | https://github.com/huggingface/accelerate.git | 2 | 37 | 0 | 14 | 67 | Python | {
"docstring": "\n A context manager that will lightly wrap around and perform gradient accumulation automatically\n\n Args:\n model (`torch.nn.Module`):\n PyTorch Module that was prepared with `Accelerator.prepare`\n ",
"language": "en",
"n_whitespaces": 71,
"n_wo... | def accumulate(self, model):
self._do_sync()
if self.sync_gradients:
context = contextlib.nullcontext
else:
context = self.no_sync
with context(model):
yield
| |
56,951 | 223,525 | 118 | python3.10.4/Lib/email/_header_value_parser.py | 48 | 13 | def get_attribute(value):
attribute = Attribute()
if value and value[0] in CFWS_LEADER:
token, value = get_cfws(value)
attribute.append(token)
if value and value[0] in ATTRIBUTE_ENDS:
raise errors.H | add python 3.10.4 for windows | get_attribute | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | XX-Net | _header_value_parser.py | 12 | 14 | https://github.com/XX-net/XX-Net.git | 7 | 99 | 0 | 25 | 163 | Python | {
"docstring": " [CFWS] 1*attrtext [CFWS]\n\n This version of the BNF makes the CFWS explicit, and as usual we use a\n value terminal for the actual run of characters. The RFC equivalent of\n attrtext is the token characters, with the subtraction of '*', \"'\", and '%'.\n We include tab in the excluded s... | def get_attribute(value):
attribute = Attribute()
if value and value[0] in CFWS_LEADER:
token, value = get_cfws(value)
attribute.append(token)
if value and value[0] in ATTRIBUTE_ENDS:
raise errors.HeaderParseError(
"expected token but found '{}'".format(value))
t... | |
@pytest.fixture | 35,948 | 154,378 | 282 | modin/pandas/test/test_io.py | 82 | 21 | def eval_to_file(modin_obj, pandas_obj, fn, extension, **fn_kwargs):
with ensure_clean_dir() as dirname:
unique_filename_modin = get_unique_filename(
extension=extension, data_dir=dirname
)
unique_filename_pandas = get_unique_filename(
extension=extension, data_d... | TEST-#4879: Use pandas `ensure_clean()` in place of `io_tests_data` (#4881)
Signed-off-by: Karthik Velayutham <vkarthik@ponder.io> | eval_to_file | 5086a9ea37bc37e6e58da0ceaf5864b16cc8e0ed | modin | test_io.py | 14 | 20 | https://github.com/modin-project/modin.git | 3 | 104 | 1 | 63 | 176 | Python | {
"docstring": "Helper function to test `to_<extension>` methods.\n\n Args:\n modin_obj: Modin DataFrame or Series to test `to_<extension>` method.\n pandas_obj: Pandas DataFrame or Series to test `to_<extension>` method.\n fn: name of the method, that should be tested.\n extension: Ext... | def eval_to_file(modin_obj, pandas_obj, fn, extension, **fn_kwargs):
with ensure_clean_dir() as dirname:
unique_filename_modin = get_unique_filename(
extension=extension, data_dir=dirname
)
unique_filename_pandas = get_unique_filename(
extension=extension, data_d... |
50,522 | 203,731 | 70 | django/contrib/contenttypes/fields.py | 16 | 9 | def _is_matching_generic_foreign_key(self, field):
return (
isinstance(field, GenericForeignKey)
and field.ct_field == self.content_type_field_name
and field.fk_field == self.object_id_field_name
)
| Refs #33476 -- Reformatted code with Black. | _is_matching_generic_foreign_key | 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | django | fields.py | 10 | 6 | https://github.com/django/django.git | 3 | 33 | 0 | 14 | 52 | Python | {
"docstring": "\n Return True if field is a GenericForeignKey whose content type and\n object id fields correspond to the equivalent attributes on this\n GenericRelation.\n ",
"language": "en",
"n_whitespaces": 51,
"n_words": 22,
"vocab_size": 22
} | def _is_matching_generic_foreign_key(self, field):
return (
isinstance(field, GenericForeignKey)
and field.ct_field == self.content_type_field_name
and field.fk_field == self.object_id_field_name
)
| |
20,628 | 101,207 | 102 | lib/align/alignments.py | 25 | 13 | def hashes_to_frame(self):
if not self._hashes_to_frame:
logger.debug("Generating hashes to frame")
for frame_name, val in self._data.items():
for idx, face in enumerate(val["faces"]):
sel | 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 | hashes_to_frame | 5e73437be47f2410439a3c6716de96354e6a0c94 | faceswap | alignments.py | 17 | 7 | https://github.com/deepfakes/faceswap.git | 4 | 67 | 0 | 23 | 112 | Python | {
"docstring": " dict: The SHA1 hash of the face mapped to the frame(s) and face index within the frame\n that the hash corresponds to. The structure of the dictionary is:\n\n {**SHA1_hash** (`str`): {**filename** (`str`): **face_index** (`int`)}}.\n\n Notes\n -----\n This method is... | def hashes_to_frame(self):
if not self._hashes_to_frame:
logger.debug("Generating hashes to frame")
for frame_name, val in self._data.items():
for idx, face in enumerate(val["faces"]):
self._hashes_to_frame.setdefault(face["hash"], {})[frame_n... | |
117,338 | 320,770 | 466 | qutebrowser/completion/completiondelegate.py | 90 | 55 | def _get_textdoc(self, index):
assert self._opt is not None
# FIXME we probably should do eliding here. See
# qcommonstyle.cpp:viewItemDrawText
# https://github.com/qutebrowser/qutebrowser/issues/118
text_option = QTextOption()
if self._opt.features & QStyleOptio... | 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... | _get_textdoc | a20bb67a878b2e68abf8268c1b0a27f018d01352 | qutebrowser | completiondelegate.py | 19 | 33 | https://github.com/qutebrowser/qutebrowser.git | 7 | 292 | 0 | 68 | 469 | Python | {
"docstring": "Create the QTextDocument of an item.\n\n Args:\n index: The QModelIndex of the item to draw.\n ",
"language": "en",
"n_whitespaces": 40,
"n_words": 15,
"vocab_size": 13
} | def _get_textdoc(self, index):
assert self._opt is not None
# FIXME we probably should do eliding here. See
# qcommonstyle.cpp:viewItemDrawText
# https://github.com/qutebrowser/qutebrowser/issues/118
text_option = QTextOption()
if self._opt.features & QStyleOptio... | |
1,585 | 9,296 | 159 | reconstruction/ostec/external/face_detector/detect_face.py | 34 | 11 | def feed(self, *args):
assert len(args) != 0
self.terminals = [] | initialize ostec | feed | 7375ee364e0df2a417f92593e09557f1b2a3575a | insightface | detect_face.py | 16 | 11 | https://github.com/deepinsight/insightface.git | 4 | 65 | 0 | 32 | 107 | Python | {
"docstring": "Set the input(s) for the next operation by replacing the terminal nodes.\n The arguments can be either layer names or the actual layers.\n ",
"language": "en",
"n_whitespaces": 37,
"n_words": 23,
"vocab_size": 20
} | def feed(self, *args):
assert len(args) != 0
self.terminals = []
for fed_layer in args:
if isinstance(fed_layer, str):
try:
fed_layer = self.layers[fed_layer]
except KeyError:
raise KeyError('Unknown lay... | |
80,862 | 271,843 | 315 | keras/engine/training_utils_v1.py | 101 | 16 | def unpack_iterator_input(iterator):
try:
next_element = iterator.get_next()
except tf.errors.OutOfRangeError:
raise RuntimeError(
"Your dataset iterator ran out of data; "
"Make sure that your dataset can generate "
"required number of samples."
... | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | unpack_iterator_input | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | training_utils_v1.py | 14 | 26 | https://github.com/keras-team/keras.git | 5 | 105 | 0 | 67 | 180 | Python | {
"docstring": "Convert a dataset iterator to a tuple of tensors `x, y, sample_weights`.\n\n Args:\n iterator: Instance of a dataset iterator.\n\n Returns:\n Tuple of tensors `x, y, weights`. `y` and `weights` entry may be None.\n ",
"language": "en",
"n_whitespaces": 52,
"n_words": 33,
"vo... | def unpack_iterator_input(iterator):
try:
next_element = iterator.get_next()
except tf.errors.OutOfRangeError:
raise RuntimeError(
"Your dataset iterator ran out of data; "
"Make sure that your dataset can generate "
"required number of samples."
... | |
26,798 | 120,211 | 11 | tests/mesh_utils_test.py | 9 | 3 | def mock_2x2x4_devices(one_device_per_chip):
return mock_devices(2, 2, 4, 'TPU v4', one_device_pe | [mesh_utils] Support creating device meshes for hybrid networks
Also makes some NFCs to other mesh_utils code.
PiperOrigin-RevId: 442581767 | mock_2x2x4_devices | 3f9e45e0c5b035de27b14588cd3b4cfd5f3c1f04 | jax | mesh_utils_test.py | 8 | 2 | https://github.com/google/jax.git | 1 | 19 | 0 | 9 | 31 | Python | {
"docstring": "Hard-coded reproduction of jax.devices() output on 2x2x4.",
"language": "en",
"n_whitespaces": 6,
"n_words": 7,
"vocab_size": 7
} | def mock_2x2x4_devices(one_device_per_chip):
return mock_devices(2, 2, 4, 'TPU v4', one_device_per_chip)
| |
1,079 | 6,855 | 61 | ludwig/export.py | 31 | 15 | def export_triton(model_path, output_path="model_repository", model_name="ludwig_model", model_version=1, **kwargs):
logger.info(f"Model path: {model_path}")
logger.info(f"Output path: {output_path}" | Adding new export for Triton (#2078)
* Adding new export for triton. Fixes for load model for neuropod export, add output dict format
* Adding test for triton. Fix to cast int to string for os.path.join. Added annotation for neurpod
* Minor tweaks to config.pbtxt output
* Remove logger that is not being us... | export_triton | 698a0e0f1ed95d20116dc51aa9c6a7ed48446deb | ludwig | export.py | 9 | 10 | https://github.com/ludwig-ai/ludwig.git | 1 | 90 | 0 | 27 | 170 | Python | {
"docstring": "Exports a model in torchscript format with config for Triton serving.\n\n # Inputs\n\n :param model_path: (str) filepath to pre-trained model.\n :param output_path: (str, default: `'model_repository'`) directory to store the\n triton models.\n :param model_name: (str, default: `'lu... | def export_triton(model_path, output_path="model_repository", model_name="ludwig_model", model_version=1, **kwargs):
logger.info(f"Model path: {model_path}")
logger.info(f"Output path: {output_path}")
logger.info(f"Model name: {model_name}")
logger.info(f"Model version: {model_version}")
logger... | |
17,983 | 85,389 | 327 | src/sentry/eventstore/models.py | 93 | 24 | def tags(self) -> Sequence[Tuple[str, str]]:
tags_key_column = self._get_column_name(Columns.TAGS_KEY)
tags_value_column = self._get_column_name(Columns.TAGS_VALUE)
if tags_key_column in self._snuba_data and tags_value_column in self._snuba_data:
keys = self._snuba_data[tag... | feat(perf_issues): Add `GroupEvent` and split some functionality in `Event` into a base class. (#38143)
Since we can now have events with multiple groups, we can no longer rely on the `Event.group`
property. This pr adds in a `GroupEvent` subclass that should be passed around wherever we expect an
event to have a si... | tags | 6aaaf5089b2c39757883179df5a8512db3b0c716 | sentry | models.py | 15 | 23 | https://github.com/getsentry/sentry.git | 11 | 145 | 0 | 67 | 229 | Python | {
"docstring": "\n Tags property uses tags from snuba if loaded otherwise falls back to\n nodestore.\n ",
"language": "en",
"n_whitespaces": 35,
"n_words": 13,
"vocab_size": 13
} | def tags(self) -> Sequence[Tuple[str, str]]:
tags_key_column = self._get_column_name(Columns.TAGS_KEY)
tags_value_column = self._get_column_name(Columns.TAGS_VALUE)
if tags_key_column in self._snuba_data and tags_value_column in self._snuba_data:
keys = self._snuba_data[tag... | |
77,934 | 264,988 | 116 | netbox/dcim/tests/test_models.py | 38 | 12 | def test_cable_validates_compatible_types(self):
# An interface cannot be connected to a power port
cable = Cable(a_terminations=[self.interface1, self.interface2], b_terminations=[self.interface3])
with self.assertRaises(ValidationError):
cable.clean()
# TODO: Remove t... | Clean up tests | test_cable_validates_compatible_types | 6280398bc17211bbc5b321039144c1eb0461f4a9 | netbox | test_models.py | 11 | 4 | https://github.com/netbox-community/netbox.git | 1 | 43 | 0 | 26 | 81 | Python | {
"docstring": "\n The clean method should have a check to ensure only compatible port types can be connected by a cable\n \n # A cable cannot connect a front port to its corresponding rear port\n # ",
"language": "en",
"n_whitespaces": 63,
"n_words": 33,
"vocab_size": 26
} | def test_cable_validates_compatible_types(self):
# An interface cannot be connected to a power port
cable = Cable(a_terminations=[self.interface1, self.interface2], b_terminations=[self.interface3])
with self.assertRaises(ValidationError):
cable.clean()
# TODO: Remove t... | |
81,490 | 275,865 | 766 | keras/saving/hdf5_format.py | 235 | 55 | def save_model_to_hdf5(model, filepath, overwrite=True, include_optimizer=True):
if h5py is None:
raise ImportError(
"`save_model()` using h5 format requires h5py. Could not "
"import h5py."
)
# TODO(psv) Add warning when we save models that contain non-serializabl... | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | save_model_to_hdf5 | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | hdf5_format.py | 18 | 54 | https://github.com/keras-team/keras.git | 16 | 290 | 0 | 164 | 490 | Python | {
"docstring": "Saves a model to a HDF5 file.\n\n The saved model contains:\n - the model's configuration (topology)\n - the model's weights\n - the model's optimizer's state (if any)\n\n Thus the saved model can be reinstantiated in\n the exact same state, without any of the code\n u... | def save_model_to_hdf5(model, filepath, overwrite=True, include_optimizer=True):
if h5py is None:
raise ImportError(
"`save_model()` using h5 format requires h5py. Could not "
"import h5py."
)
# TODO(psv) Add warning when we save models that contain non-serializabl... | |
270 | 2,278 | 299 | packages/syft/src/syft/core/node/common/node_manager/user_manager.py | 79 | 24 | def set(self, **kwargs) -> None: # nosec
attributes = {}
user_id = kwargs["u | replaced all methods of usermanager class,
working login
Co-Authored By: Ionesio | set | 066545e8a88e842aa7d0a5d57bac88716001bced | PySyft | user_manager.py | 11 | 41 | https://github.com/OpenMined/PySyft.git | 10 | 205 | 0 | 55 | 351 | Python | {
"docstring": "Updates the information for the given user id.\n\n Args:\n user_id (str): unique id of the user in the database.\n email (str, optional): email of the user. Defaults to \"\".\n password (str, optional): password of the user. Defaults to \"\".\n role (... | def set(self, **kwargs) -> None: # nosec
attributes = {}
user_id = kwargs["user_id"]
user = self.first(id_int=int(user_id))
if not user:
raise UserNotFoundError
for k, v in kwargs.items():
if k in user.__attr_searchable__:
attrib... | |
18,963 | 92,964 | 336 | tests/sentry/snuba/metrics/fields/test_base.py | 62 | 31 | def test_get_entity_and_validate_dependency_tree_of_a_single_entity_derived_metric(self):
use_case_id = UseCaseKey.RELEASE_HEALTH
expected_derived_metrics_entities = {
SessionMRI.ALL.value: "metrics_counters",
SessionMRI.ALL_USER.value: "metrics_sets",
Sessio... | fix(snuba): Add appropriate `UseCaseKey` for indexer [TET-146] (#36308)
* fix(snuba): Add appropriate `UseCaseKey` for indexer
Update indexer invocation call to have the appropriate
`UseCaseKey` depending on use case.
In `src/sentry/sentry_metrics/indexer/base.py::StringIndexer`
when using `resolve` and `rever... | test_get_entity_and_validate_dependency_tree_of_a_single_entity_derived_metric | cd803d173c72b64d06c0687170bf9a945d0b503c | sentry | test_base.py | 14 | 25 | https://github.com/getsentry/sentry.git | 2 | 180 | 0 | 47 | 292 | Python | {
"docstring": "\n Tests that ensures that get_entity method works expected in the sense that:\n - Since it is the first function that is called by the query_builder, validation is\n applied there to ensure that if it is an instance of a SingleEntityDerivedMetric,\n then it is composed of ... | def test_get_entity_and_validate_dependency_tree_of_a_single_entity_derived_metric(self):
use_case_id = UseCaseKey.RELEASE_HEALTH
expected_derived_metrics_entities = {
SessionMRI.ALL.value: "metrics_counters",
SessionMRI.ALL_USER.value: "metrics_sets",
Sessio... | |
76,202 | 260,356 | 83 | sklearn/decomposition/_sparse_pca.py | 23 | 13 | def transform(self, X):
check_is_fitted(self)
X = self._validate_data(X, reset=False)
X = X - self.mean_
U = ridge_regression(
self.components_.T, X.T, self.ridge_alpha, solver="cholesky"
)
return U
| 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> | transform | db6123fe40400828918037f3fae949bfcc4d9d05 | scikit-learn | _sparse_pca.py | 10 | 8 | https://github.com/scikit-learn/scikit-learn.git | 1 | 55 | 0 | 18 | 87 | Python | {
"docstring": "Least Squares projection of the data onto the sparse components.\n\n To avoid instability issues in case the system is under-determined,\n regularization can be applied (Ridge regression) via the\n `ridge_alpha` parameter.\n\n Note that Sparse PCA components orthogonality i... | def transform(self, X):
check_is_fitted(self)
X = self._validate_data(X, reset=False)
X = X - self.mean_
U = ridge_regression(
self.components_.T, X.T, self.ridge_alpha, solver="cholesky"
)
return U
| |
77,797 | 264,756 | 233 | netbox/utilities/utils.py | 117 | 27 | def serialize_object(obj, extra=None):
json_str = serialize('json', [obj])
print(json_str)
data = json.loads(json_str)[0]['fields']
# Exclude any MPTTModel fields
if issubclass(obj.__class__, MPTTModel):
for field in ['level', 'lft', 'rght', 'tree_id']:
data.pop | Extend Cable model to support multiple A/B terminations | serialize_object | 4bb9b6ee2639db683b70d6ddbee055497e0a3647 | netbox | utils.py | 12 | 18 | https://github.com/netbox-community/netbox.git | 11 | 167 | 0 | 86 | 285 | Python | {
"docstring": "\n Return a generic JSON representation of an object using Django's built-in serializer. (This is used for things like\n change logging, not the REST API.) Optionally include a dictionary to supplement the object data. A list of keys\n can be provided to exclude them from the returned diction... | def serialize_object(obj, extra=None):
json_str = serialize('json', [obj])
print(json_str)
data = json.loads(json_str)[0]['fields']
# Exclude any MPTTModel fields
if issubclass(obj.__class__, MPTTModel):
for field in ['level', 'lft', 'rght', 'tree_id']:
data.pop(field)
... | |
88,520 | 289,378 | 405 | tests/components/history/test_init.py | 112 | 20 | async def test_statistics_during_period(recorder_mock, hass, hass_ws_client, caplog):
now = dt_util.utcnow()
await async_setup_component(hass, "history", {})
client = await hass_ws_client()
# Test the WS API works and issues a warning
await client.send_json(
{
"id": 1,
... | Ensure recorder test fixture is setup before hass fixture (#80528)
* Ensure recorder test fixture is setup before hass fixture
* Adjust more tests | test_statistics_during_period | 31a787558fd312331b55e5c2c4b33341fc3601fc | core | test_init.py | 14 | 37 | https://github.com/home-assistant/core.git | 1 | 173 | 0 | 76 | 319 | Python | {
"docstring": "Test history/statistics_during_period forwards to recorder.",
"language": "en",
"n_whitespaces": 4,
"n_words": 5,
"vocab_size": 5
} | async def test_statistics_during_period(recorder_mock, hass, hass_ws_client, caplog):
now = dt_util.utcnow()
await async_setup_component(hass, "history", {})
client = await hass_ws_client()
# Test the WS API works and issues a warning
await client.send_json(
{
"id": 1,
... | |
16,427 | 75,606 | 104 | wagtail/search/management/commands/update_index.py | 24 | 8 | def queryset_chunks(self, qs, chunk_size=DEFAULT_CHUNK_SIZE):
i = 0 | Reformat with black | queryset_chunks | d10f15e55806c6944827d801cd9c2d53f5da4186 | wagtail | update_index.py | 14 | 8 | https://github.com/wagtail/wagtail.git | 3 | 44 | 0 | 21 | 73 | Python | {
"docstring": "\n Yield a queryset in chunks of at most ``chunk_size``. The chunk yielded\n will be a list, not a queryset. Iterating over the chunks is done in a\n transaction so that the order and count of items in the queryset\n remains stable.\n ",
"language": "en",
"n_whit... | def queryset_chunks(self, qs, chunk_size=DEFAULT_CHUNK_SIZE):
i = 0
while True:
items = list(qs[i * chunk_size :][:chunk_size])
if not items:
break
yield items
i += 1
| |
19,211 | 95,431 | 229 | src/sentry/search/events/builder.py | 45 | 15 | def flattened_having(self) -> List[Condition]:
flattened: List[Condition] = []
boolean_conditions: List[BooleanCondition] = []
for condition in self.having:
if isinstance(condition, Condition):
flattened.append(condition)
elif isinstance(conditio... | fix(snql): Add aggregations to select in auto_aggregation (#31061)
- This is to fix an issue for queries that have the uniq aggregation in
the HAVING clause, and is not selected.
- Previously we would not add the aggregation to the select clause in
these cases
- Now anything in the having clause will get... | flattened_having | 2a4da479b2d4a2faa901701f4c73ff823236e9e8 | sentry | builder.py | 14 | 20 | https://github.com/getsentry/sentry.git | 8 | 116 | 0 | 30 | 184 | Python | {
"docstring": "Return self.having as a flattened list ignoring boolean operators\n This is because self.having can have a mix of BooleanConditions and Conditions. And each BooleanCondition can in\n turn be a mix of either type.\n ",
"language": "en",
"n_whitespaces": 54,
"n_words": 33,
"... | def flattened_having(self) -> List[Condition]:
flattened: List[Condition] = []
boolean_conditions: List[BooleanCondition] = []
for condition in self.having:
if isinstance(condition, Condition):
flattened.append(condition)
elif isinstance(conditio... | |
39,468 | 163,634 | 211 | pandas/core/arrays/datetimelike.py | 64 | 27 | def _add_timedelta_arraylike(self, other):
# overridden by PeriodArray
if len(self) != len(other):
raise ValueError("cannot add indices of unequal length")
if isinstance(other, np.ndarray):
| EA interface: rename ExtensionArray._hasnans to ._hasna (#45519) | _add_timedelta_arraylike | a0b40c0f2ad73420a54e48ec4f564b9667e3f452 | pandas | datetimelike.py | 10 | 15 | https://github.com/pandas-dev/pandas.git | 5 | 122 | 0 | 57 | 191 | Python | {
"docstring": "\n Add a delta of a TimedeltaIndex\n\n Returns\n -------\n Same type as self\n ",
"language": "en",
"n_whitespaces": 48,
"n_words": 12,
"vocab_size": 11
} | def _add_timedelta_arraylike(self, other):
# overridden by PeriodArray
if len(self) != len(other):
raise ValueError("cannot add indices of unequal length")
if isinstance(other, np.ndarray):
# ndarray[timedelta64]; wrap in TimedeltaIndex for op
from ... | |
80,737 | 271,248 | 1,164 | keras/engine/functional.py | 488 | 55 | def _map_graph_network(inputs, outputs):
# "depth" is number of layers between output Node and the Node.
# Nodes are ordered from inputs -> outputs.
nodes_in_decreasing_depth, layer_indices = _build_map(outputs)
network_nodes = {
_make_node_key(node.layer.name, node.layer._inbound_nodes.ind... | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | _map_graph_network | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | functional.py | 21 | 65 | https://github.com/keras-team/keras.git | 20 | 470 | 0 | 245 | 792 | Python | {
"docstring": "Validates a network's topology and gather its layers and nodes.\n\n Args:\n inputs: List of input tensors.\n outputs: List of outputs tensors.\n\n Returns:\n A tuple `(nodes, nodes_by_depth, layers, layers_by_depth)`.\n - nodes: list of Node instances.\n - nodes_by_depth... | def _map_graph_network(inputs, outputs):
# "depth" is number of layers between output Node and the Node.
# Nodes are ordered from inputs -> outputs.
nodes_in_decreasing_depth, layer_indices = _build_map(outputs)
network_nodes = {
_make_node_key(node.layer.name, node.layer._inbound_nodes.ind... | |
28,513 | 127,723 | 138 | python/ray/data/dataset.py | 40 | 18 | def default_batch_format(self) -> Type:
# noqa: E501
import pandas as pd
import pyarrow as pa
schema = self.schema()
assert isinstance(schema, | [Datasets] Add `Dataset.default_batch_format` (#28434)
Participants in the PyTorch UX study couldn't understand how the "native" batch format works. This PR introduces a method Dataset.native_batch_format that tells users exactly what the native batch format is, so users don't have to guess. | default_batch_format | 206e847694cba414dc4664e4ae02b20e10e3f25d | ray | dataset.py | 10 | 72 | https://github.com/ray-project/ray.git | 4 | 79 | 0 | 32 | 124 | Python | {
"docstring": "Return this dataset's default batch format.\n\n The default batch format describes what batches of data look like. To learn more\n about batch formats, read\n :ref:`writing user-defined functions <transform_datasets_writing_udfs>`.\n\n Example:\n\n If your datase... | def default_batch_format(self) -> Type:
# noqa: E501
import pandas as pd
import pyarrow as pa
schema = self.schema()
assert isinstance(schema, (type, PandasBlockSchema, pa.Schema))
if isinstance(schema, type):
return list
if isinstance(schema, (Pa... | |
@pytest.mark.parametrize("Tree", REG_TREES.values())
@pytest.mark.parametrize(
"old_criterion, new_criterion",
[
("mse", "squared_error"),
("mae", "absolute_error"),
],
) | 75,740 | 259,378 | 282 | sklearn/tree/tests/test_tree.py | 159 | 40 | def test_decision_tree_regressor_sample_weight_consistency(criterion):
tree_params = dict(criterion=criterion)
tree = DecisionTreeRegressor(**tree_params, random_state=42)
for kind in ["zeros", "ones"]:
check_sample_weights_invariance(
"DecisionTreeRegressor_" + criterion, tree, kin... | MNT fix typo in tree test name (#22943) | test_decision_tree_regressor_sample_weight_consistency | f89a40bd92004368dee38ea76a1b9eaddaff4d7a | scikit-learn | test_tree.py | 12 | 22 | https://github.com/scikit-learn/scikit-learn.git | 2 | 212 | 1 | 123 | 431 | Python | {
"docstring": "Test that the impact of sample_weight is consistent.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | def test_decision_tree_regressor_sample_weight_consistency(criterion):
tree_params = dict(criterion=criterion)
tree = DecisionTreeRegressor(**tree_params, random_state=42)
for kind in ["zeros", "ones"]:
check_sample_weights_invariance(
"DecisionTreeRegressor_" + criterion, tree, kin... |
52,020 | 207,608 | 110 | tests/admin_views/tests.py | 24 | 9 | def test_with_fk_to_field(self):
response = self.client.get(
reverse("admin:auth_user_changelist") + "?q=joe&%s=id" % TO_FIELD_V | Refs #33476 -- Reformatted code with Black. | test_with_fk_to_field | 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | django | tests.py | 12 | 10 | https://github.com/django/django.git | 1 | 46 | 0 | 22 | 83 | Python | {
"docstring": "\n The to_field GET parameter is preserved when a search is performed.\n Refs #10918.\n ",
"language": "en",
"n_whitespaces": 35,
"n_words": 13,
"vocab_size": 12
} | def test_with_fk_to_field(self):
response = self.client.get(
reverse("admin:auth_user_changelist") + "?q=joe&%s=id" % TO_FIELD_VAR
)
self.assertContains(response, "\n1 user\n")
self.assertContains(
response,
'<input type="hidden" name="%s" val... | |
46,351 | 190,450 | 27 | fastai/torch_core.py | 15 | 7 | def remove_module_load(state_dict):
new_state_dict = OrderedDict()
fo | Upgrading to support latest Pytorch version | remove_module_load | 4fc3616712edb19179b17dd270ad6cf63abf99c2 | DeOldify | torch_core.py | 11 | 4 | https://github.com/jantic/DeOldify.git | 2 | 34 | 0 | 12 | 57 | Python | {
"docstring": "create new OrderedDict that does not contain `module.`",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | def remove_module_load(state_dict):
new_state_dict = OrderedDict()
for k, v in state_dict.items(): new_state_dict[k[7:]] = v
return new_state_dict
| |
@add_start_docstrings(
"The bare LayoutLMv3 Model transformer outputting raw hidden-states without any specific head on top.",
LAYOUTLMV3_START_DOCSTRING,
) | 6,073 | 33,182 | 54 | src/transformers/models/layoutlmv3/modeling_tf_layoutlmv3.py | 31 | 9 | def serving(self, inputs):
output = self.call(inputs)
return self.serving_output(output)
LAYOUTLMV3_START_DOCSTRING = r
LAYOUTLMV3_INPUTS_DOCSTRING = r
@add_start_docstrings(
"The bare LayoutLMv3 Model transformer outputting raw hidden-states w | [LayoutLMv3] Add TensorFlow implementation (#18678)
Co-authored-by: Esben Toke Christensen <esben.christensen@visma.com>
Co-authored-by: Lasse Reedtz <lasse.reedtz@visma.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> | serving | de8548ebf3242305d0f9792dacb6f86b196a3a33 | transformers | modeling_tf_layoutlmv3.py | 8 | 3 | https://github.com/huggingface/transformers.git | 1 | 23 | 1 | 28 | 67 | Python | {
"docstring": "\n Method used for serving the model.\n\n Args:\n inputs (`Dict[str, tf.Tensor]`):\n The input of the saved model as a dictionary of tensors.\n \n This model inherits from [`TFPreTrainedModel`]. Check the superclass documentation for the generic method... | def serving(self, inputs):
output = self.call(inputs)
return self.serving_output(output)
LAYOUTLMV3_START_DOCSTRING = r
LAYOUTLMV3_INPUTS_DOCSTRING = r
@add_start_docstrings(
"The bare LayoutLMv3 Model transformer outputting raw hidden-states without any specific head on top.",
LA... |
107,305 | 308,556 | 40 | homeassistant/components/sisyphus/media_player.py | 8 | 9 | def media_image_url(self):
if self._table.active_track:
return self._table.active_track.get_th | Sisyphus: Fix bad super call (#63327)
Co-authored-by: Franck Nijhof <git@frenck.dev> | media_image_url | 9f0805f51293851096d7ece48f48a041e4a809e0 | core | media_player.py | 11 | 4 | https://github.com/home-assistant/core.git | 2 | 34 | 0 | 7 | 57 | Python | {
"docstring": "Return the URL for a thumbnail image of the current track.",
"language": "en",
"n_whitespaces": 10,
"n_words": 11,
"vocab_size": 10
} | def media_image_url(self):
if self._table.active_track:
return self._table.active_track.get_thumbnail_url(Track.ThumbnailSize.LARGE)
return super().media_image_url
| |
@pytest.mark.parametrize(
"ongoing_requests",
[[7, 1, 8, 4], [8, 1, 8, 4], [6, 1, 8, 4], [0, 1, 8, 4]]) | 28,953 | 129,433 | 385 | python/ray/serve/tests/test_autoscaling_policy.py | 107 | 26 | def test_fluctuating_ongoing_requests(delay_s):
config = AutoscalingConfig(
min_replicas=1,
max_replicas=10,
target_num_ongoing_requests_per_replica=50,
upscale_delay_s=delay_s,
downscale_delay_s=delay_s)
policy = BasicAutoscalingPolicy(config)
if delay_s > 0:... | [Serve] Serve Autoscaling Release tests (#21208) | test_fluctuating_ongoing_requests | 75b3080834bceb184e9ba19e21511eb0ea19955b | ray | test_autoscaling_policy.py | 14 | 31 | https://github.com/ray-project/ray.git | 6 | 155 | 1 | 55 | 301 | Python | {
"docstring": "\n Simulates a workload that switches between too many and too few\n ongoing requests.\n ",
"language": "en",
"n_whitespaces": 23,
"n_words": 13,
"vocab_size": 12
} | def test_fluctuating_ongoing_requests(delay_s):
config = AutoscalingConfig(
min_replicas=1,
max_replicas=10,
target_num_ongoing_requests_per_replica=50,
upscale_delay_s=delay_s,
downscale_delay_s=delay_s)
policy = BasicAutoscalingPolicy(config)
if delay_s > 0:... |
10,583 | 52,487 | 78 | modules/audio/svs/diffsinger/utils/audio.py | 47 | 7 | def librosa_pad_lr(x, fsize, fshift, pad_sides=1): | Add Diffsinger Module (#2120)
* add diffsinger
* update README
* update README | librosa_pad_lr | 7eef3bfde63d03acbd1fc9a15a5e56bef47c0ef7 | PaddleHub | audio.py | 13 | 7 | https://github.com/PaddlePaddle/PaddleHub.git | 2 | 46 | 0 | 32 | 105 | Python | {
"docstring": "compute right padding (final frame) or both sides padding (first and final frames)\n ",
"language": "en",
"n_whitespaces": 16,
"n_words": 13,
"vocab_size": 12
} | def librosa_pad_lr(x, fsize, fshift, pad_sides=1):
assert pad_sides in (1, 2)
# return int(fsize // 2)
pad = (x.shape[0] // fshift + 1) * fshift - x.shape[0]
if pad_sides == 1:
return 0, pad
else:
return pad // 2, pad // 2 + pad % 2
# Conversions | |
27,112 | 122,164 | 55 | jax/tools/colab_tpu.py | 37 | 14 | def setup_tpu(tpu_driver_version='tpu_driver-0.2'):
global TPU_DRIVER_MODE
if not TPU_DRIVER_MODE:
colab_tpu_addr = os.environ['COLAB_TPU_ADDR'].split(':')[0]
url = f | Pin default jax.tools.colab_tpu.setup_tpu driver version.
Prior to this change, we were defaulting to the TPU nightly driver
version. We should instead pin to the version associated with the
default jaxlib version that Colab uses. | setup_tpu | 0cc4066bb7bf758a5ba8c5def9c2c32a1c98fb89 | jax | colab_tpu.py | 13 | 9 | https://github.com/google/jax.git | 2 | 64 | 0 | 32 | 125 | Python | {
"docstring": "Sets up Colab to run on TPU.\n\n Note: make sure the Colab Runtime is set to Accelerator: TPU.\n\n Args\n ----\n tpu_driver_version : (str) specify the version identifier for the tpu driver.\n Defaults to \"tpu_driver-0.2\", which can be used with jaxlib 0.3.20. Set to\n \"tpu_driver_nightly... | def setup_tpu(tpu_driver_version='tpu_driver-0.2'):
global TPU_DRIVER_MODE
if not TPU_DRIVER_MODE:
colab_tpu_addr = os.environ['COLAB_TPU_ADDR'].split(':')[0]
url = f'http://{colab_tpu_addr}:8475/requestversion/{tpu_driver_version}'
requests.post(url)
TPU_DRIVER_MODE = 1
# The following is re... | |
71,987 | 247,899 | 133 | tests/storage/databases/main/test_lock.py | 49 | 16 | def test_timeout_lock(self):
lock = self.get_success(self.store.try_acquire_lock("name", "key"))
assert lock is not None
self.get_success(lock.__aenter__())
# We simulate the process getting stuck by cancelling the looping call
# that keeps the lock active.
| Add type hints for `tests/unittest.py`. (#12347)
In particular, add type hints for get_success and friends, which are then helpful in a bunch of places. | test_timeout_lock | f0b03186d96305fd44d74a89bf4230beec0c5c31 | synapse | test_lock.py | 11 | 9 | https://github.com/matrix-org/synapse.git | 1 | 95 | 0 | 38 | 166 | Python | {
"docstring": "Test that we time out locks if they're not updated for ages",
"language": "en",
"n_whitespaces": 11,
"n_words": 12,
"vocab_size": 12
} | def test_timeout_lock(self):
lock = self.get_success(self.store.try_acquire_lock("name", "key"))
assert lock is not None
self.get_success(lock.__aenter__())
# We simulate the process getting stuck by cancelling the looping call
# that keeps the lock active.
lo... | |
81,454 | 275,725 | 81 | keras/preprocessing/image.py | 33 | 11 | def random_brightness(x, brightness_range, scale=True):
if len(brightness_range) != 2:
raise ValueError(
"`brightness_range should be tuple or list of two floats. "
"Received: %s" % (brightness_range,)
)
u = np.random.uniform(brightness_range[0], bri | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | random_brightness | 84afc5193d38057e2e2badf9c889ea87d80d8fbf | keras | image.py | 12 | 8 | https://github.com/keras-team/keras.git | 2 | 58 | 0 | 33 | 92 | Python | {
"docstring": "Performs a random brightness shift.\n\n Deprecated: `tf.keras.preprocessing.image.random_brightness` does not operate\n on tensors and is not recommended for new code. Prefer\n `tf.keras.layers.RandomBrightness` which provides equivalent functionality as\n a preprocessing layer. For more i... | def random_brightness(x, brightness_range, scale=True):
if len(brightness_range) != 2:
raise ValueError(
"`brightness_range should be tuple or list of two floats. "
"Received: %s" % (brightness_range,)
)
u = np.random.uniform(brightness_range[0], brightness_range[1]... | |
107,962 | 309,255 | 23 | tests/util/test_async.py | 14 | 5 | def test_check_loop_sync(caplog):
hasync.check_loop()
assert "Detected block | Warn on`time.sleep` in event loop (#63766)
Co-authored-by: Martin Hjelmare <marhje52@gmail.com> | test_check_loop_sync | dc58bc375ae203e3d394225f9c3a5a14d43cb2f3 | core | test_async.py | 7 | 3 | https://github.com/home-assistant/core.git | 1 | 18 | 0 | 14 | 34 | Python | {
"docstring": "Test check_loop does nothing when called from thread.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | def test_check_loop_sync(caplog):
hasync.check_loop()
assert "Detected blocking call inside the event loop" not in caplog.text
| |
28,641 | 128,240 | 279 | python/ray/serve/_private/deployment_state.py | 70 | 20 | def update(self) -> bool:
try:
# Add or remove DeploymentReplica instances in self._replicas.
# This should be the only place we adjust total number of replicas
# we manage.
running_replicas_changed = self._scale_deployment_replicas()
# Chec... | [Serve] add alpha gRPC support (#28175) | update | 65d0c0aa48be8f9f7faae857d3ab71444997755a | ray | deployment_state.py | 17 | 24 | https://github.com/ray-project/ray.git | 3 | 72 | 0 | 56 | 138 | Python | {
"docstring": "Attempts to reconcile this deployment to match its goal state.\n\n This is an asynchronous call; it's expected to be called repeatedly.\n\n Also updates the internal DeploymentStatusInfo based on the current\n state of the system.\n\n Returns true if this deployment was suc... | def update(self) -> bool:
try:
# Add or remove DeploymentReplica instances in self._replicas.
# This should be the only place we adjust total number of replicas
# we manage.
running_replicas_changed = self._scale_deployment_replicas()
# Chec... | |
50,095 | 202,382 | 165 | tests/csrf_tests/tests.py | 48 | 18 | def test_https_malformed_host(self):
req = self._get_request(method="POST")
req._is_secure_override = True
req.META["HTTP_HOST"] = "@malformed"
req.META["HTTP_REFERER"] = "https://www.evil.org/somepage"
req.META["S | Refs #33476 -- Reformatted code with Black. | test_https_malformed_host | 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | django | tests.py | 10 | 15 | https://github.com/django/django.git | 1 | 99 | 0 | 41 | 176 | Python | {
"docstring": "\n CsrfViewMiddleware generates a 403 response if it receives an HTTPS\n request with a bad host.\n ",
"language": "en",
"n_whitespaces": 37,
"n_words": 15,
"vocab_size": 14
} | def test_https_malformed_host(self):
req = self._get_request(method="POST")
req._is_secure_override = True
req.META["HTTP_HOST"] = "@malformed"
req.META["HTTP_REFERER"] = "https://www.evil.org/somepage"
req.META["SERVER_PORT"] = "443"
mw = CsrfViewMiddleware(toke... | |
594 | 3,894 | 63 | airbyte-integrations/connectors/source-orb/source_orb/source.py | 24 | 18 | def stream_slices(self, **kwargs) -> Iterable[Optional[Mapping[str, Any]]]:
# TODO: self.authenticator should optionally pull from sel | 🎉 New Source: Orb (#9985)
* V1 of source_orb connector
* add boostrap.md file
* add clause on Pagination to bootstrap.md
* add SUMMARY documentation
* add lookback_window_days connector parameter
* Add support for start_date parameter
* Add ability to transform record in order to un-nest IDs
* Ad... | stream_slices | 1e0ac30ebdcfce55a5644bcd486044da45c93dd6 | airbyte | source.py | 12 | 11 | https://github.com/airbytehq/airbyte.git | 2 | 57 | 0 | 24 | 93 | Python | {
"docstring": "\n This stream is sliced per `customer_id`. This has two implications:\n (1) State can be checkpointed after processing each slice\n (2) The other parameters (e.g. request_params, path) can be dependent on this slice.\n\n This allows us to pull data on a per customer_id bas... | def stream_slices(self, **kwargs) -> Iterable[Optional[Mapping[str, Any]]]:
# TODO: self.authenticator should optionally pull from self._session.auth
customers_stream = Customers(authenticator=self._session.auth)
for customer in customers_stream.read_records(sync_mode=SyncMode.full_refr... | |
82,567 | 278,476 | 526 | keras/utils/metrics_utils.py | 193 | 24 | def ragged_assert_compatible_and_get_flat_values(values, mask=None):
if isinstance(values, list):
is_all_ragged = all(isinstance(rt, tf.RaggedTensor) for rt in values)
is_any_ragged = any(isinstance(rt, tf.RaggedTensor) for rt in values)
else:
is_all_ragged = isinstance(values, tf.R... | resolve line-too-long in utils | ragged_assert_compatible_and_get_flat_values | 80ee2fa4e1db2dda14370110830db82be3eb97b7 | keras | metrics_utils.py | 16 | 36 | https://github.com/keras-team/keras.git | 14 | 244 | 0 | 107 | 405 | Python | {
"docstring": "If ragged, it checks the compatibility and then returns the flat_values.\n\n Note: If two tensors are dense, it does not check their compatibility.\n Note: Although two ragged tensors with different ragged ranks could have\n identical overall rank and dimension sizes and hence ... | def ragged_assert_compatible_and_get_flat_values(values, mask=None):
if isinstance(values, list):
is_all_ragged = all(isinstance(rt, tf.RaggedTensor) for rt in values)
is_any_ragged = any(isinstance(rt, tf.RaggedTensor) for rt in values)
else:
is_all_ragged = isinstance(values, tf.R... | |
2,286 | 12,428 | 124 | jina/orchestrate/deployments/__init__.py | 25 | 12 | def update_sandbox_args(self):
if self.is_sandbox:
host, port = HubIO.deploy_public_sandbox(self.args)
self._sandbox_deployed = True
self.first_pod_args.host = host
self.first_pod_args.port = port
if self.head_args:
self.pod_ar... | fix: do not deploy sandbox on init (#4844) | update_sandbox_args | 7c4c39a9d82c58ef2493c21a288c755901a9594e | jina | __init__.py | 13 | 9 | https://github.com/jina-ai/jina.git | 3 | 67 | 0 | 16 | 112 | Python | {
"docstring": "Update args of all its pods based on the host and port returned by Hubble",
"language": "en",
"n_whitespaces": 14,
"n_words": 15,
"vocab_size": 15
} | def update_sandbox_args(self):
if self.is_sandbox:
host, port = HubIO.deploy_public_sandbox(self.args)
self._sandbox_deployed = True
self.first_pod_args.host = host
self.first_pod_args.port = port
if self.head_args:
self.pod_ar... | |
37,328 | 158,146 | 44 | d2l/mxnet.py | 21 | 5 | def download_all():
for name in DATA_HUB:
download(name)
DATA_HUB['kaggle_house_train'] = (
DATA_URL + 'kaggle_house_pred_train.csv',
'585e9cc93e70b39160e7921475f9bcd7d31219ce')
DATA_HUB['kaggle_house_test'] = (
DATA_URL + 'kaggle_house | [PaddlePaddle] Merge master into Paddle branch (#1186)
* change 15.2 title in chinese version (#1109)
change title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘
* 修改部分语义表述 (#1105)
* Update r0.17.5 (#1120)
* Bump versions in installation
* 94行typo: （“bert.mall”）->（“bert.small”） (#1129)
* line 313: "b... | download_all | b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2 | d2l-zh | mxnet.py | 9 | 3 | https://github.com/d2l-ai/d2l-zh.git | 2 | 14 | 0 | 17 | 72 | Python | {
"docstring": "Download all files in the DATA_HUB.\n\n Defined in :numref:`sec_kaggle_house`",
"language": "en",
"n_whitespaces": 11,
"n_words": 9,
"vocab_size": 8
} | def download_all():
for name in DATA_HUB:
download(name)
DATA_HUB['kaggle_house_train'] = (
DATA_URL + 'kaggle_house_pred_train.csv',
'585e9cc93e70b39160e7921475f9bcd7d31219ce')
DATA_HUB['kaggle_house_test'] = (
DATA_URL + 'kaggle_house_pred_test.csv',
'fa19780a7b011d9b009e8bff8e99922... | |
55,519 | 218,873 | 46 | python3.10.4/Lib/lib2to3/pytree.py | 14 | 5 | def generate_matches(self, nodes):
r = {}
if nodes and self.match(nodes[0], r):
yield 1, r
| add python 3.10.4 for windows | generate_matches | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | XX-Net | pytree.py | 9 | 4 | https://github.com/XX-net/XX-Net.git | 3 | 31 | 0 | 13 | 51 | Python | {
"docstring": "\n Generator yielding all matches for this pattern.\n\n Default implementation for non-wildcard patterns.\n ",
"language": "en",
"n_whitespaces": 34,
"n_words": 12,
"vocab_size": 11
} | def generate_matches(self, nodes):
r = {}
if nodes and self.match(nodes[0], r):
yield 1, r
| |
15,953 | 73,139 | 31 | wagtail/contrib/modeladmin/helpers/permission.py | 10 | 7 | def user_can_delete_obj(self, user, obj):
perm_codenam | Reformat with black | user_can_delete_obj | d10f15e55806c6944827d801cd9c2d53f5da4186 | wagtail | permission.py | 9 | 3 | https://github.com/wagtail/wagtail.git | 1 | 27 | 0 | 10 | 45 | Python | {
"docstring": "\n Return a boolean to indicate whether `user` is permitted to 'delete'\n a specific `self.model` instance.\n ",
"language": "en",
"n_whitespaces": 37,
"n_words": 15,
"vocab_size": 13
} | def user_can_delete_obj(self, user, obj):
perm_codename = self.get_perm_codename("delete")
return self.user_has_specific_permission(user, perm_codename)
| |
20,823 | 101,409 | 69 | tools/preview/preview.py | 18 | 9 | def _busy_indicator_trace(self, *args) -> None:
logger.trace("Busy indicator trace: %s", args) # type: ignor | Bugfix: convert - Gif Writer
- Fix non-launch error on Gif Writer
- convert plugins - linting
- convert/fs_media/preview/queue_manager - typing
- Change convert items from dict to Dataclass | _busy_indicator_trace | 1022651eb8a7741014f5d2ec7cbfe882120dfa5f | faceswap | preview.py | 10 | 13 | https://github.com/deepfakes/faceswap.git | 2 | 40 | 0 | 18 | 72 | Python | {
"docstring": " Show or hide busy indicator based on whether the preview is updating.\n\n Parameters\n ----------\n args: unused\n Required for tkinter event, but unused\n ",
"language": "en",
"n_whitespaces": 62,
"n_words": 22,
"vocab_size": 21
} | def _busy_indicator_trace(self, *args) -> None:
logger.trace("Busy indicator trace: %s", args) # type: ignore
if self._busy_tkvar.get():
self._start_busy_indicator()
else:
self._stop_busy_indicator()
| |
46,056 | 189,448 | 356 | manim/mobject/svg/code_mobject.py | 41 | 20 | def _gen_html_string(self):
self.html_string = _hilite_me(
self.code_string,
self.language,
self.style,
self.insert_line_no,
"border:solid gray;bor | Hide more private methods from the docs. (#2468)
* hide privs from text_mobject.py
* hide privs from tex_mobject.py
* hide privs from code_mobject.py
* hide privs from svg_mobject.py
* remove SVGPath and utils from __init__.py
* don't import string_to_numbers
* hide privs from geometry.py
* hide p... | gen_html_string | 902e7eb4f0147b5882a613b67467e38a1d47f01e | manim | code_mobject.py | 16 | 25 | https://github.com/ManimCommunity/manim.git | 2 | 103 | 0 | 37 | 170 | Python | {
"docstring": "Function to generate html string with code highlighted and stores in variable html_string.",
"language": "en",
"n_whitespaces": 12,
"n_words": 13,
"vocab_size": 13
} | def _gen_html_string(self):
self.html_string = _hilite_me(
self.code_string,
self.language,
self.style,
self.insert_line_no,
"border:solid gray;border-width:.1em .1em .1em .8em;padding:.2em .6em;",
self.file_path,
self.... | |
4,155 | 22,074 | 49 | pipenv/patched/pip/_vendor/requests/cookies.py | 14 | 6 | def __getstate__(self):
state = self.__di | Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir. | __getstate__ | cd5a9683be69c86c8f3adcd13385a9bc5db198ec | pipenv | cookies.py | 9 | 4 | https://github.com/pypa/pipenv.git | 1 | 23 | 0 | 13 | 44 | Python | {
"docstring": "Unlike a normal CookieJar, this class is pickleable.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | def __getstate__(self):
state = self.__dict__.copy()
# remove the unpickleable RLock object
state.pop("_cookies_lock")
return state
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.