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aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unicode.py
|
python
|
_codepoint_is_ascii
|
(ch)
|
return ch < 128
|
Returns true if a codepoint is in the ASCII range
|
Returns true if a codepoint is in the ASCII range
|
[
"Returns",
"true",
"if",
"a",
"codepoint",
"is",
"in",
"the",
"ASCII",
"range"
] |
def _codepoint_is_ascii(ch):
"""
Returns true if a codepoint is in the ASCII range
"""
return ch < 128
|
[
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"(",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unicode.py#L409-L413
|
|
benoitsteiner/tensorflow-opencl
|
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
|
tensorflow/contrib/learn/python/learn/estimators/model_fn.py
|
python
|
ModelFnOps.estimator_spec
|
(self, default_serving_output_alternative_key=None)
|
return core_model_fn_lib.EstimatorSpec(
mode=core_mode,
predictions=self.predictions,
loss=self.loss,
train_op=self.train_op,
eval_metric_ops=_get_eval_metric_ops(),
export_outputs=export_outputs_dict,
training_chief_hooks=self.training_chief_hooks,
training_hooks=self.training_hooks,
scaffold=self.scaffold)
|
Creates an equivalent `EstimatorSpec`.
Args:
default_serving_output_alternative_key: Required for multiple heads. If
you have multiple entries in `output_alternatives` dict (comparable to
multiple heads), `EstimatorSpec` requires a default head that will be
used if a Servo request does not explicitly mention which head to infer
on. Pass the key of the output alternative here that you want to
designate as default. A separate ExportOutpout for this default head
wil be added to the export_outputs dict with the special key
signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY, unless there is
already an enry in output_alternatives with this special key.
Returns:
Instance of `EstimatorSpec` that is equivalent to this `ModelFnOps`
Raises:
ValueError: If problem type is unknown.
|
Creates an equivalent `EstimatorSpec`.
|
[
"Creates",
"an",
"equivalent",
"EstimatorSpec",
"."
] |
def estimator_spec(self, default_serving_output_alternative_key=None):
"""Creates an equivalent `EstimatorSpec`.
Args:
default_serving_output_alternative_key: Required for multiple heads. If
you have multiple entries in `output_alternatives` dict (comparable to
multiple heads), `EstimatorSpec` requires a default head that will be
used if a Servo request does not explicitly mention which head to infer
on. Pass the key of the output alternative here that you want to
designate as default. A separate ExportOutpout for this default head
wil be added to the export_outputs dict with the special key
signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY, unless there is
already an enry in output_alternatives with this special key.
Returns:
Instance of `EstimatorSpec` that is equivalent to this `ModelFnOps`
Raises:
ValueError: If problem type is unknown.
"""
def _scores(output_tensors):
scores = output_tensors.get(prediction_key.PredictionKey.SCORES)
if scores is None:
scores = output_tensors.get(prediction_key.PredictionKey.PROBABILITIES)
return scores
def _classes(output_tensors): # pylint: disable=missing-docstring
classes = output_tensors.get(prediction_key.PredictionKey.CLASSES)
if classes is None:
logging.warning(
'classes is None, Servo inference will not have class ids.')
return None
elif classes.dtype != dtypes.string:
# Servo classification can only serve string classes
logging.warning(
'classes is not string, Servo inference will not have class ids.')
return None
return classes
def _export_output(problem_type, predictions): # pylint: disable=missing-docstring
if problem_type == constants.ProblemType.LINEAR_REGRESSION:
return core_export_lib.RegressionOutput(_scores(predictions))
if (problem_type == constants.ProblemType.CLASSIFICATION or
problem_type == constants.ProblemType.LOGISTIC_REGRESSION):
return core_export_lib.ClassificationOutput(
scores=_scores(predictions), classes=_classes(predictions))
if problem_type == constants.ProblemType.UNSPECIFIED:
return core_export_lib.PredictOutput(predictions)
raise ValueError('Unknown problem_type=%s' % problem_type)
# Converts output_alternatives
export_outputs_dict = None
if self.output_alternatives:
output_alternatives = self.output_alternatives
# Adds default output_alternative if needed.
if (len(output_alternatives) > 1 and
signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY not in
output_alternatives):
output_alternatives = output_alternatives.copy()
output_alternatives[
signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY] = (
output_alternatives[default_serving_output_alternative_key])
export_outputs_dict = {key: _export_output(*val) for key, val in
output_alternatives.items()}
def _get_eval_metric_ops():
"""Returns self.eval_metric_ops without loss metric."""
result = {}
for key, value in six.iteritems(self.eval_metric_ops):
if key != metric_key.MetricKey.LOSS:
result[key] = value
return result
# Convert the contrib mode enum to the core mode enum.
# Note: mode already validated in __new__().
if self.mode == ModeKeys.TRAIN:
core_mode = core_model_fn_lib.ModeKeys.TRAIN
elif self.mode == ModeKeys.EVAL:
core_mode = core_model_fn_lib.ModeKeys.EVAL
elif self.mode == ModeKeys.INFER:
core_mode = core_model_fn_lib.ModeKeys.PREDICT
return core_model_fn_lib.EstimatorSpec(
mode=core_mode,
predictions=self.predictions,
loss=self.loss,
train_op=self.train_op,
eval_metric_ops=_get_eval_metric_ops(),
export_outputs=export_outputs_dict,
training_chief_hooks=self.training_chief_hooks,
training_hooks=self.training_hooks,
scaffold=self.scaffold)
|
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] |
https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/contrib/learn/python/learn/estimators/model_fn.py#L196-L291
|
|
vesoft-inc/nebula
|
25a06217ebaf169e1f0e5ff6a797ba6f0c41fc35
|
.linters/cpp/cpplint.py
|
python
|
GetHeaderGuardCPPVariable
|
(filename)
|
return re.sub(r'[^a-zA-Z0-9]', '_', file_path_from_root).upper() + '_'
|
Returns the CPP variable that should be used as a header guard.
Args:
filename: The name of a C++ header file.
Returns:
The CPP variable that should be used as a header guard in the
named file.
|
Returns the CPP variable that should be used as a header guard.
|
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"header",
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"."
] |
def GetHeaderGuardCPPVariable(filename):
"""Returns the CPP variable that should be used as a header guard.
Args:
filename: The name of a C++ header file.
Returns:
The CPP variable that should be used as a header guard in the
named file.
"""
# Restores original filename in case that cpplint is invoked from Emacs's
# flymake.
filename = re.sub(r'_flymake\.h$', '.h', filename)
filename = re.sub(r'/\.flymake/([^/]*)$', r'/\1', filename)
# Replace 'c++' with 'cpp'.
filename = filename.replace('C++', 'cpp').replace('c++', 'cpp')
fileinfo = FileInfo(filename)
file_path_from_root = fileinfo.RepositoryName()
def FixupPathFromRoot():
if _root_debug:
sys.stderr.write("\n_root fixup, _root = '%s', repository name = '%s'\n"
% (_root, fileinfo.RepositoryName()))
# Process the file path with the --root flag if it was set.
if not _root:
if _root_debug:
sys.stderr.write("_root unspecified\n")
return file_path_from_root
def StripListPrefix(lst, prefix):
# f(['x', 'y'], ['w, z']) -> None (not a valid prefix)
if lst[:len(prefix)] != prefix:
return None
# f(['a, 'b', 'c', 'd'], ['a', 'b']) -> ['c', 'd']
return lst[(len(prefix)):]
# root behavior:
# --root=subdir , lstrips subdir from the header guard
maybe_path = StripListPrefix(PathSplitToList(file_path_from_root),
PathSplitToList(_root))
if _root_debug:
sys.stderr.write(("_root lstrip (maybe_path=%s, file_path_from_root=%s," +
" _root=%s)\n") % (maybe_path, file_path_from_root, _root))
if maybe_path:
return os.path.join(*maybe_path)
# --root=.. , will prepend the outer directory to the header guard
full_path = fileinfo.FullName()
root_abspath = os.path.abspath(_root)
maybe_path = StripListPrefix(PathSplitToList(full_path),
PathSplitToList(root_abspath))
if _root_debug:
sys.stderr.write(("_root prepend (maybe_path=%s, full_path=%s, " +
"root_abspath=%s)\n") % (maybe_path, full_path, root_abspath))
if maybe_path:
return os.path.join(*maybe_path)
if _root_debug:
sys.stderr.write("_root ignore, returning %s\n" % (file_path_from_root))
# --root=FAKE_DIR is ignored
return file_path_from_root
file_path_from_root = FixupPathFromRoot()
return re.sub(r'[^a-zA-Z0-9]', '_', file_path_from_root).upper() + '_'
|
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https://github.com/vesoft-inc/nebula/blob/25a06217ebaf169e1f0e5ff6a797ba6f0c41fc35/.linters/cpp/cpplint.py#L2034-L2107
|
|
apple/turicreate
|
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
|
deps/src/libxml2-2.9.1/python/libxml2class.py
|
python
|
xmlDoc.newDocNodeEatName
|
(self, ns, name, content)
|
return __tmp
|
Creation of a new node element within a document. @ns and
@content are optional (None). NOTE: @content is supposed to
be a piece of XML CDATA, so it allow entities references,
but XML special chars need to be escaped first by using
xmlEncodeEntitiesReentrant(). Use xmlNewDocRawNode() if you
don't need entities support.
|
Creation of a new node element within a document.
|
[
"Creation",
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] |
def newDocNodeEatName(self, ns, name, content):
"""Creation of a new node element within a document. @ns and
@content are optional (None). NOTE: @content is supposed to
be a piece of XML CDATA, so it allow entities references,
but XML special chars need to be escaped first by using
xmlEncodeEntitiesReentrant(). Use xmlNewDocRawNode() if you
don't need entities support. """
if ns is None: ns__o = None
else: ns__o = ns._o
ret = libxml2mod.xmlNewDocNodeEatName(self._o, ns__o, name, content)
if ret is None:raise treeError('xmlNewDocNodeEatName() failed')
__tmp = xmlNode(_obj=ret)
return __tmp
|
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https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/deps/src/libxml2-2.9.1/python/libxml2class.py#L3556-L3568
|
|
crosslife/OpenBird
|
9e0198a1a2295f03fa1e8676e216e22c9c7d380b
|
cocos2d/tools/bindings-generator/clang/cindex.py
|
python
|
AccessSpecifierKind.get_all_kinds
|
()
|
return filter(None, AccessSpecifierKind._kinds)
|
Return all AccessSpecifierKind enumeration instances.
|
Return all AccessSpecifierKind enumeration instances.
|
[
"Return",
"all",
"AccessSpecifierKind",
"enumeration",
"instances",
"."
] |
def get_all_kinds():
"""Return all AccessSpecifierKind enumeration instances."""
return filter(None, AccessSpecifierKind._kinds)
|
[
"def",
"get_all_kinds",
"(",
")",
":",
"return",
"filter",
"(",
"None",
",",
"AccessSpecifierKind",
".",
"_kinds",
")"
] |
https://github.com/crosslife/OpenBird/blob/9e0198a1a2295f03fa1e8676e216e22c9c7d380b/cocos2d/tools/bindings-generator/clang/cindex.py#L424-L426
|
|
KratosMultiphysics/Kratos
|
0000833054ed0503424eb28205d6508d9ca6cbbc
|
applications/StructuralMechanicsApplication/python_scripts/structural_mechanics_analysis.py
|
python
|
StructuralMechanicsAnalysis.OutputSolutionStep
|
(self)
|
This function printed / writes output files after the solution of a step
|
This function printed / writes output files after the solution of a step
|
[
"This",
"function",
"printed",
"/",
"writes",
"output",
"files",
"after",
"the",
"solution",
"of",
"a",
"step"
] |
def OutputSolutionStep(self):
"""This function printed / writes output files after the solution of a step
"""
# In case of contact problem
if self.contact_problem:
# First we check if one of the output processes will print output in this step this is done to save computation in case none of them will print
is_output_step = False
for output_process in self._GetListOfOutputProcesses():
if output_process.IsOutputStep():
is_output_step = True
break
if is_output_step:
# Informing the output will be created
KratosMultiphysics.Logger.PrintWarning("StructuralMechanicsAnalysis", "STEP: ", self._GetSolver().GetComputingModelPart().ProcessInfo[KratosMultiphysics.STEP])
KratosMultiphysics.Logger.PrintWarning("StructuralMechanicsAnalysis", "TIME: ", self.time)
# Creating output
super().OutputSolutionStep()
|
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https://github.com/KratosMultiphysics/Kratos/blob/0000833054ed0503424eb28205d6508d9ca6cbbc/applications/StructuralMechanicsApplication/python_scripts/structural_mechanics_analysis.py#L51-L70
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/scikit-learn/py3/sklearn/decomposition/_pca.py
|
python
|
PCA._fit_full
|
(self, X, n_components)
|
return U, S, V
|
Fit the model by computing full SVD on X
|
Fit the model by computing full SVD on X
|
[
"Fit",
"the",
"model",
"by",
"computing",
"full",
"SVD",
"on",
"X"
] |
def _fit_full(self, X, n_components):
"""Fit the model by computing full SVD on X"""
n_samples, n_features = X.shape
if n_components == 'mle':
if n_samples < n_features:
raise ValueError("n_components='mle' is only supported "
"if n_samples >= n_features")
elif not 0 <= n_components <= min(n_samples, n_features):
raise ValueError("n_components=%r must be between 0 and "
"min(n_samples, n_features)=%r with "
"svd_solver='full'"
% (n_components, min(n_samples, n_features)))
elif n_components >= 1:
if not isinstance(n_components, numbers.Integral):
raise ValueError("n_components=%r must be of type int "
"when greater than or equal to 1, "
"was of type=%r"
% (n_components, type(n_components)))
# Center data
self.mean_ = np.mean(X, axis=0)
X -= self.mean_
U, S, V = linalg.svd(X, full_matrices=False)
# flip eigenvectors' sign to enforce deterministic output
U, V = svd_flip(U, V)
components_ = V
# Get variance explained by singular values
explained_variance_ = (S ** 2) / (n_samples - 1)
total_var = explained_variance_.sum()
explained_variance_ratio_ = explained_variance_ / total_var
singular_values_ = S.copy() # Store the singular values.
# Postprocess the number of components required
if n_components == 'mle':
n_components = \
_infer_dimension_(explained_variance_, n_samples, n_features)
elif 0 < n_components < 1.0:
# number of components for which the cumulated explained
# variance percentage is superior to the desired threshold
ratio_cumsum = stable_cumsum(explained_variance_ratio_)
n_components = np.searchsorted(ratio_cumsum, n_components) + 1
# Compute noise covariance using Probabilistic PCA model
# The sigma2 maximum likelihood (cf. eq. 12.46)
if n_components < min(n_features, n_samples):
self.noise_variance_ = explained_variance_[n_components:].mean()
else:
self.noise_variance_ = 0.
self.n_samples_, self.n_features_ = n_samples, n_features
self.components_ = components_[:n_components]
self.n_components_ = n_components
self.explained_variance_ = explained_variance_[:n_components]
self.explained_variance_ratio_ = \
explained_variance_ratio_[:n_components]
self.singular_values_ = singular_values_[:n_components]
return U, S, V
|
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"[",
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scikit-learn/py3/sklearn/decomposition/_pca.py#L423-L484
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/series.py
|
python
|
Series.keys
|
(self)
|
return self.index
|
Return alias for index.
Returns
-------
Index
Index of the Series.
|
Return alias for index.
|
[
"Return",
"alias",
"for",
"index",
"."
] |
def keys(self):
"""
Return alias for index.
Returns
-------
Index
Index of the Series.
"""
return self.index
|
[
"def",
"keys",
"(",
"self",
")",
":",
"return",
"self",
".",
"index"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/series.py#L1514-L1523
|
|
epam/Indigo
|
30e40b4b1eb9bae0207435a26cfcb81ddcc42be1
|
api/python/indigo/ml/mpp/datasets.py
|
python
|
MolDataset.process
|
(self)
|
Process graph data and set attributes to dataset
|
Process graph data and set attributes to dataset
|
[
"Process",
"graph",
"data",
"and",
"set",
"attributes",
"to",
"dataset"
] |
def process(self):
"Process graph data and set attributes to dataset"
df = pd.read_csv(config.file_name)
df = df.loc[df[config.target].notnull()]
data = dict(zip(df[config.smiles], df[config.target]))
self.graphs = []
self.labels = []
for smiles, label in data.items():
self.graphs.append(mol_to_graph(smiles))
self.labels.append(label)
self.gclasses = len(self.labels)
self.dim_nfeats = len(self.graphs[0].ndata["atomic"][0])
self.dim_efeats = len(self.graphs[0].edata["ord"][0])
self.labels = FloatTensor(self.labels)
|
[
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"=",
"FloatTensor",
"(",
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".",
"labels",
")"
] |
https://github.com/epam/Indigo/blob/30e40b4b1eb9bae0207435a26cfcb81ddcc42be1/api/python/indigo/ml/mpp/datasets.py#L16-L30
|
||
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
tools/strict_enum_value_checker/strict_enum_value_checker.py
|
python
|
StrictEnumValueChecker.CheckForFileDeletion
|
(self, affected_file)
|
return True
|
Emits a warning notification if file has been deleted
|
Emits a warning notification if file has been deleted
|
[
"Emits",
"a",
"warning",
"notification",
"if",
"file",
"has",
"been",
"deleted"
] |
def CheckForFileDeletion(self, affected_file):
"""Emits a warning notification if file has been deleted """
if not affected_file.NewContents():
self.EmitWarning("The file seems to be deleted in the changelist. If "
"your intent is to really delete the file, the code in "
"PRESUBMIT.py should be updated to remove the "
"|StrictEnumValueChecker| class.");
return False
return True
|
[
"def",
"CheckForFileDeletion",
"(",
"self",
",",
"affected_file",
")",
":",
"if",
"not",
"affected_file",
".",
"NewContents",
"(",
")",
":",
"self",
".",
"EmitWarning",
"(",
"\"The file seems to be deleted in the changelist. If \"",
"\"your intent is to really delete the file, the code in \"",
"\"PRESUBMIT.py should be updated to remove the \"",
"\"|StrictEnumValueChecker| class.\"",
")",
"return",
"False",
"return",
"True"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/strict_enum_value_checker/strict_enum_value_checker.py#L162-L170
|
|
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/protobuf/python/google/protobuf/internal/containers.py
|
python
|
RepeatedScalarFieldContainer.__delslice__
|
(self, start, stop)
|
Deletes the subset of items from between the specified indices.
|
Deletes the subset of items from between the specified indices.
|
[
"Deletes",
"the",
"subset",
"of",
"items",
"from",
"between",
"the",
"specified",
"indices",
"."
] |
def __delslice__(self, start, stop):
"""Deletes the subset of items from between the specified indices."""
del self._values[start:stop]
self._message_listener.Modified()
|
[
"def",
"__delslice__",
"(",
"self",
",",
"start",
",",
"stop",
")",
":",
"del",
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"_values",
"[",
"start",
":",
"stop",
"]",
"self",
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"_message_listener",
".",
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"(",
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] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/protobuf/python/google/protobuf/internal/containers.py#L325-L328
|
||
miyosuda/TensorFlowAndroidDemo
|
35903e0221aa5f109ea2dbef27f20b52e317f42d
|
jni-build/jni/include/tensorflow/contrib/distributions/python/ops/dirichlet_multinomial.py
|
python
|
DirichletMultinomial.validate_args
|
(self)
|
return self._validate_args
|
Boolean describing behavior on invalid input.
|
Boolean describing behavior on invalid input.
|
[
"Boolean",
"describing",
"behavior",
"on",
"invalid",
"input",
"."
] |
def validate_args(self):
"""Boolean describing behavior on invalid input."""
return self._validate_args
|
[
"def",
"validate_args",
"(",
"self",
")",
":",
"return",
"self",
".",
"_validate_args"
] |
https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/tensorflow/contrib/distributions/python/ops/dirichlet_multinomial.py#L186-L188
|
|
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/math_ops.py
|
python
|
cast
|
(x, dtype, name=None)
|
Casts a tensor to a new type.
The operation casts `x` (in case of `Tensor`) or `x.values`
(in case of `SparseTensor` or `IndexedSlices`) to `dtype`.
For example:
```python
x = tf.constant([1.8, 2.2], dtype=tf.float32)
tf.dtypes.cast(x, tf.int32) # [1, 2], dtype=tf.int32
```
The operation supports data types (for `x` and `dtype`) of
`uint8`, `uint16`, `uint32`, `uint64`, `int8`, `int16`, `int32`, `int64`,
`float16`, `float32`, `float64`, `complex64`, `complex128`, `bfloat16`.
In case of casting from complex types (`complex64`, `complex128`) to real
types, only the real part of `x` is returned. In case of casting from real
types to complex types (`complex64`, `complex128`), the imaginary part of the
returned value is set to `0`. The handling of complex types here matches the
behavior of numpy.
Args:
x: A `Tensor` or `SparseTensor` or `IndexedSlices` of numeric type. It could
be `uint8`, `uint16`, `uint32`, `uint64`, `int8`, `int16`, `int32`,
`int64`, `float16`, `float32`, `float64`, `complex64`, `complex128`,
`bfloat16`.
dtype: The destination type. The list of supported dtypes is the same as
`x`.
name: A name for the operation (optional).
Returns:
A `Tensor` or `SparseTensor` or `IndexedSlices` with same shape as `x` and
same type as `dtype`.
Raises:
TypeError: If `x` cannot be cast to the `dtype`.
|
Casts a tensor to a new type.
|
[
"Casts",
"a",
"tensor",
"to",
"a",
"new",
"type",
"."
] |
def cast(x, dtype, name=None):
"""Casts a tensor to a new type.
The operation casts `x` (in case of `Tensor`) or `x.values`
(in case of `SparseTensor` or `IndexedSlices`) to `dtype`.
For example:
```python
x = tf.constant([1.8, 2.2], dtype=tf.float32)
tf.dtypes.cast(x, tf.int32) # [1, 2], dtype=tf.int32
```
The operation supports data types (for `x` and `dtype`) of
`uint8`, `uint16`, `uint32`, `uint64`, `int8`, `int16`, `int32`, `int64`,
`float16`, `float32`, `float64`, `complex64`, `complex128`, `bfloat16`.
In case of casting from complex types (`complex64`, `complex128`) to real
types, only the real part of `x` is returned. In case of casting from real
types to complex types (`complex64`, `complex128`), the imaginary part of the
returned value is set to `0`. The handling of complex types here matches the
behavior of numpy.
Args:
x: A `Tensor` or `SparseTensor` or `IndexedSlices` of numeric type. It could
be `uint8`, `uint16`, `uint32`, `uint64`, `int8`, `int16`, `int32`,
`int64`, `float16`, `float32`, `float64`, `complex64`, `complex128`,
`bfloat16`.
dtype: The destination type. The list of supported dtypes is the same as
`x`.
name: A name for the operation (optional).
Returns:
A `Tensor` or `SparseTensor` or `IndexedSlices` with same shape as `x` and
same type as `dtype`.
Raises:
TypeError: If `x` cannot be cast to the `dtype`.
"""
base_type = dtypes.as_dtype(dtype).base_dtype
if isinstance(x,
(ops.Tensor, _resource_variable_type)) and base_type == x.dtype:
return x
with ops.name_scope(name, "Cast", [x]) as name:
if isinstance(x, sparse_tensor.SparseTensor):
values_cast = cast(x.values, base_type, name=name)
x = sparse_tensor.SparseTensor(x.indices, values_cast, x.dense_shape)
elif isinstance(x, ops.IndexedSlices):
values_cast = cast(x.values, base_type, name=name)
x = ops.IndexedSlices(values_cast, x.indices, x.dense_shape)
else:
# TODO(josh11b): If x is not already a Tensor, we could return
# ops.convert_to_tensor(x, dtype=dtype, ...) here, but that
# allows some conversions that cast() can't do, e.g. casting numbers to
# strings.
x = ops.convert_to_tensor(x, name="x")
if x.dtype.base_dtype != base_type:
x = gen_math_ops.cast(x, base_type, name=name)
if x.dtype.is_complex and base_type.is_floating:
logging.warn("Casting complex to real discards imaginary part.")
return x
|
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] |
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/math_ops.py#L648-L707
|
||
baidu-research/tensorflow-allreduce
|
66d5b855e90b0949e9fa5cca5599fd729a70e874
|
tensorflow/python/training/optimizer.py
|
python
|
Optimizer._assert_valid_dtypes
|
(self, tensors)
|
Asserts tensors are all valid types (see `_valid_dtypes`).
Args:
tensors: Tensors to check.
Raises:
ValueError: If any tensor is not a valid type.
|
Asserts tensors are all valid types (see `_valid_dtypes`).
|
[
"Asserts",
"tensors",
"are",
"all",
"valid",
"types",
"(",
"see",
"_valid_dtypes",
")",
"."
] |
def _assert_valid_dtypes(self, tensors):
"""Asserts tensors are all valid types (see `_valid_dtypes`).
Args:
tensors: Tensors to check.
Raises:
ValueError: If any tensor is not a valid type.
"""
valid_dtypes = self._valid_dtypes()
for t in tensors:
dtype = t.dtype.base_dtype
if dtype not in valid_dtypes:
raise ValueError(
"Invalid type %r for %s, expected: %s." % (
dtype, t.name, [v for v in valid_dtypes]))
|
[
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"_assert_valid_dtypes",
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https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/python/training/optimizer.py#L502-L517
|
||
eerolanguage/clang
|
91360bee004a1cbdb95fe5eb605ef243152da41b
|
bindings/python/clang/cindex.py
|
python
|
Config.set_compatibility_check
|
(check_status)
|
Perform compatibility check when loading libclang
The python bindings are only tested and evaluated with the version of
libclang they are provided with. To ensure correct behavior a (limited)
compatibility check is performed when loading the bindings. This check
will throw an exception, as soon as it fails.
In case these bindings are used with an older version of libclang, parts
that have been stable between releases may still work. Users of the
python bindings can disable the compatibility check. This will cause
the python bindings to load, even though they are written for a newer
version of libclang. Failures now arise if unsupported or incompatible
features are accessed. The user is required to test himself if the
features he is using are available and compatible between different
libclang versions.
|
Perform compatibility check when loading libclang
|
[
"Perform",
"compatibility",
"check",
"when",
"loading",
"libclang"
] |
def set_compatibility_check(check_status):
""" Perform compatibility check when loading libclang
The python bindings are only tested and evaluated with the version of
libclang they are provided with. To ensure correct behavior a (limited)
compatibility check is performed when loading the bindings. This check
will throw an exception, as soon as it fails.
In case these bindings are used with an older version of libclang, parts
that have been stable between releases may still work. Users of the
python bindings can disable the compatibility check. This will cause
the python bindings to load, even though they are written for a newer
version of libclang. Failures now arise if unsupported or incompatible
features are accessed. The user is required to test himself if the
features he is using are available and compatible between different
libclang versions.
"""
if Config.loaded:
raise Exception("compatibility_check must be set before before " \
"using any other functionalities in libclang.")
Config.compatibility_check = check_status
|
[
"def",
"set_compatibility_check",
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"if",
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"\"using any other functionalities in libclang.\"",
")",
"Config",
".",
"compatibility_check",
"=",
"check_status"
] |
https://github.com/eerolanguage/clang/blob/91360bee004a1cbdb95fe5eb605ef243152da41b/bindings/python/clang/cindex.py#L3319-L3340
|
||
naver/sling
|
5671cd445a2caae0b4dd0332299e4cfede05062c
|
webkit/Tools/Scripts/webkitpy/common/system/executive.py
|
python
|
Executive.kill_process
|
(self, pid)
|
Attempts to kill the given pid.
Will fail silently if pid does not exist or insufficient permisssions.
|
Attempts to kill the given pid.
Will fail silently if pid does not exist or insufficient permisssions.
|
[
"Attempts",
"to",
"kill",
"the",
"given",
"pid",
".",
"Will",
"fail",
"silently",
"if",
"pid",
"does",
"not",
"exist",
"or",
"insufficient",
"permisssions",
"."
] |
def kill_process(self, pid):
"""Attempts to kill the given pid.
Will fail silently if pid does not exist or insufficient permisssions."""
if sys.platform.startswith('win32'):
# We only use taskkill.exe on windows (not cygwin) because subprocess.pid
# is a CYGWIN pid and taskkill.exe expects a windows pid.
# Thankfully os.kill on CYGWIN handles either pid type.
task_kill_executable = os.path.join('C:', os.sep, 'WINDOWS', 'system32', 'taskkill.exe')
command = [task_kill_executable, "/f", "/t", "/pid", pid]
# taskkill will exit 128 if the process is not found. We should log.
self.run_command(command, error_handler=self.ignore_error)
return
# According to http://docs.python.org/library/os.html
# os.kill isn't available on Windows. python 2.5.5 os.kill appears
# to work in cygwin, however it occasionally raises EAGAIN.
retries_left = 10 if sys.platform == "cygwin" else 1
while retries_left > 0:
try:
retries_left -= 1
# Give processes one change to clean up quickly before exiting.
# Following up with a kill should have no effect if the process
# already exited, and forcefully kill it if SIGTERM wasn't enough.
os.kill(pid, signal.SIGTERM)
os.kill(pid, signal.SIGKILL)
except OSError, e:
if e.errno == errno.EAGAIN:
if retries_left <= 0:
_log.warn("Failed to kill pid %s. Too many EAGAIN errors." % pid)
continue
if e.errno == errno.ESRCH: # The process does not exist.
return
if e.errno == errno.EPIPE: # The process has exited already on cygwin
return
if e.errno == errno.ECHILD:
# Can't wait on a non-child process, but the kill worked.
return
if e.errno == errno.EACCES and sys.platform == 'cygwin':
# Cygwin python sometimes can't kill native processes.
return
raise
|
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] |
https://github.com/naver/sling/blob/5671cd445a2caae0b4dd0332299e4cfede05062c/webkit/Tools/Scripts/webkitpy/common/system/executive.py#L183-L223
|
||
albertz/openlierox
|
d316c14a8eb57848ef56e9bfa7b23a56f694a51b
|
tools/DedicatedServerVideo/gdata/Crypto/PublicKey/ElGamal.py
|
python
|
ElGamalobj.size
|
(self)
|
return number.size(self.p) - 1
|
Return the maximum number of bits that can be handled by this key.
|
Return the maximum number of bits that can be handled by this key.
|
[
"Return",
"the",
"maximum",
"number",
"of",
"bits",
"that",
"can",
"be",
"handled",
"by",
"this",
"key",
"."
] |
def size(self):
"Return the maximum number of bits that can be handled by this key."
return number.size(self.p) - 1
|
[
"def",
"size",
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"self",
")",
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"number",
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"size",
"(",
"self",
".",
"p",
")",
"-",
"1"
] |
https://github.com/albertz/openlierox/blob/d316c14a8eb57848ef56e9bfa7b23a56f694a51b/tools/DedicatedServerVideo/gdata/Crypto/PublicKey/ElGamal.py#L115-L117
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/pandas/py2/pandas/io/parsers.py
|
python
|
_read
|
(filepath_or_buffer, kwds)
|
return data
|
Generic reader of line files.
|
Generic reader of line files.
|
[
"Generic",
"reader",
"of",
"line",
"files",
"."
] |
def _read(filepath_or_buffer, kwds):
"""Generic reader of line files."""
encoding = kwds.get('encoding', None)
if encoding is not None:
encoding = re.sub('_', '-', encoding).lower()
kwds['encoding'] = encoding
compression = kwds.get('compression', 'infer')
compression = _infer_compression(filepath_or_buffer, compression)
filepath_or_buffer, _, compression, should_close = get_filepath_or_buffer(
filepath_or_buffer, encoding, compression)
kwds['compression'] = compression
if kwds.get('date_parser', None) is not None:
if isinstance(kwds['parse_dates'], bool):
kwds['parse_dates'] = True
# Extract some of the arguments (pass chunksize on).
iterator = kwds.get('iterator', False)
chunksize = _validate_integer('chunksize', kwds.get('chunksize', None), 1)
nrows = kwds.get('nrows', None)
# Check for duplicates in names.
_validate_names(kwds.get("names", None))
# Create the parser.
parser = TextFileReader(filepath_or_buffer, **kwds)
if chunksize or iterator:
return parser
try:
data = parser.read(nrows)
finally:
parser.close()
if should_close:
try:
filepath_or_buffer.close()
except ValueError:
pass
return data
|
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] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py2/pandas/io/parsers.py#L403-L445
|
|
rsummers11/CADLab
|
976ed959a0b5208bb4173127a7ef732ac73a9b6f
|
panreas_hnn/hed-globalweight/python/caffe/io.py
|
python
|
load_image
|
(filename, color=True)
|
return img
|
Load an image converting from grayscale or alpha as needed.
Parameters
----------
filename : string
color : boolean
flag for color format. True (default) loads as RGB while False
loads as intensity (if image is already grayscale).
Returns
-------
image : an image with type np.float32 in range [0, 1]
of size (H x W x 3) in RGB or
of size (H x W x 1) in grayscale.
|
Load an image converting from grayscale or alpha as needed.
|
[
"Load",
"an",
"image",
"converting",
"from",
"grayscale",
"or",
"alpha",
"as",
"needed",
"."
] |
def load_image(filename, color=True):
"""
Load an image converting from grayscale or alpha as needed.
Parameters
----------
filename : string
color : boolean
flag for color format. True (default) loads as RGB while False
loads as intensity (if image is already grayscale).
Returns
-------
image : an image with type np.float32 in range [0, 1]
of size (H x W x 3) in RGB or
of size (H x W x 1) in grayscale.
"""
img = skimage.img_as_float(skimage.io.imread(filename)).astype(np.float32)
if img.ndim == 2:
img = img[:, :, np.newaxis]
if color:
img = np.tile(img, (1, 1, 3))
elif img.shape[2] == 4:
img = img[:, :, :3]
return img
|
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https://github.com/rsummers11/CADLab/blob/976ed959a0b5208bb4173127a7ef732ac73a9b6f/panreas_hnn/hed-globalweight/python/caffe/io.py#L275-L299
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/AWSPythonSDK/1.5.8/docutils/transforms/references.py
|
python
|
Footnotes.number_footnotes
|
(self, startnum)
|
return startnum
|
Assign numbers to autonumbered footnotes.
For labeled autonumbered footnotes, copy the number over to
corresponding footnote references.
|
Assign numbers to autonumbered footnotes.
|
[
"Assign",
"numbers",
"to",
"autonumbered",
"footnotes",
"."
] |
def number_footnotes(self, startnum):
"""
Assign numbers to autonumbered footnotes.
For labeled autonumbered footnotes, copy the number over to
corresponding footnote references.
"""
for footnote in self.document.autofootnotes:
while True:
label = str(startnum)
startnum += 1
if label not in self.document.nameids:
break
footnote.insert(0, nodes.label('', label))
for name in footnote['names']:
for ref in self.document.footnote_refs.get(name, []):
ref += nodes.Text(label)
ref.delattr('refname')
assert len(footnote['ids']) == len(ref['ids']) == 1
ref['refid'] = footnote['ids'][0]
footnote.add_backref(ref['ids'][0])
self.document.note_refid(ref)
ref.resolved = 1
if not footnote['names'] and not footnote['dupnames']:
footnote['names'].append(label)
self.document.note_explicit_target(footnote, footnote)
self.autofootnote_labels.append(label)
return startnum
|
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/AWSPythonSDK/1.5.8/docutils/transforms/references.py#L499-L526
|
|
xiaolonw/caffe-video_triplet
|
c39ea1ad6e937ccf7deba4510b7e555165abf05f
|
python/caffe/io.py
|
python
|
Transformer.set_input_scale
|
(self, in_, scale)
|
Set the scale of preprocessed inputs s.t. the blob = blob * scale.
N.B. input_scale is done AFTER mean subtraction and other preprocessing
while raw_scale is done BEFORE.
Parameters
----------
in_ : which input to assign this scale factor
scale : scale coefficient
|
Set the scale of preprocessed inputs s.t. the blob = blob * scale.
N.B. input_scale is done AFTER mean subtraction and other preprocessing
while raw_scale is done BEFORE.
|
[
"Set",
"the",
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".",
"the",
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"subtraction",
"and",
"other",
"preprocessing",
"while",
"raw_scale",
"is",
"done",
"BEFORE",
"."
] |
def set_input_scale(self, in_, scale):
"""
Set the scale of preprocessed inputs s.t. the blob = blob * scale.
N.B. input_scale is done AFTER mean subtraction and other preprocessing
while raw_scale is done BEFORE.
Parameters
----------
in_ : which input to assign this scale factor
scale : scale coefficient
"""
self.__check_input(in_)
self.input_scale[in_] = scale
|
[
"def",
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"in_",
")",
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".",
"input_scale",
"[",
"in_",
"]",
"=",
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] |
https://github.com/xiaolonw/caffe-video_triplet/blob/c39ea1ad6e937ccf7deba4510b7e555165abf05f/python/caffe/io.py#L258-L270
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/lib/masked/timectrl.py
|
python
|
TimeCtrl.GetMxDateTime
|
(self, value=None)
|
return t
|
Returns the value of the control as an mx.DateTime, with the date
portion set to January 1, 1970.
|
Returns the value of the control as an mx.DateTime, with the date
portion set to January 1, 1970.
|
[
"Returns",
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".",
"DateTime",
"with",
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"date",
"portion",
"set",
"to",
"January",
"1",
"1970",
"."
] |
def GetMxDateTime(self, value=None):
"""
Returns the value of the control as an mx.DateTime, with the date
portion set to January 1, 1970.
"""
if value is None:
t = self.GetValue(as_mxDateTime=True)
else:
# Convert string 1st to wxDateTime, then use components, since
# mx' DateTime.Parser.TimeFromString() doesn't handle AM/PM:
wxdt = self.GetWxDateTime(value)
hour, minute, second = wxdt.GetHour(), wxdt.GetMinute(), wxdt.GetSecond()
t = DateTime.DateTime(1970,1,1) + DateTimeDelta(0, hour, minute, second)
return t
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/masked/timectrl.py#L783-L796
|
|
ycm-core/ycmd
|
fc0fb7e5e15176cc5a2a30c80956335988c6b59a
|
ycmd/completers/cs/cs_completer.py
|
python
|
CsharpSolutionCompleter.ServerIsHealthy
|
( self )
|
Check if our OmniSharp server is healthy (up and serving).
|
Check if our OmniSharp server is healthy (up and serving).
|
[
"Check",
"if",
"our",
"OmniSharp",
"server",
"is",
"healthy",
"(",
"up",
"and",
"serving",
")",
"."
] |
def ServerIsHealthy( self ):
""" Check if our OmniSharp server is healthy (up and serving)."""
if not self._ServerIsRunning():
return False
try:
return self._GetResponse( '/checkalivestatus', timeout = 3 )
except Exception:
return False
|
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] |
https://github.com/ycm-core/ycmd/blob/fc0fb7e5e15176cc5a2a30c80956335988c6b59a/ycmd/completers/cs/cs_completer.py#L835-L843
|
||
rdiankov/openrave
|
d1a23023fd4b58f077d2ca949ceaf1b91f3f13d7
|
python/databases/inversereachability.py
|
python
|
InverseReachabilityModel.classnormalizationconst
|
(classstd)
|
return quatconst+gaussconst
|
normalization const for the equation exp(dot(-0.5/bandwidth**2,r_[arccos(x[0])**2,x[1:]**2]))
|
normalization const for the equation exp(dot(-0.5/bandwidth**2,r_[arccos(x[0])**2,x[1:]**2]))
|
[
"normalization",
"const",
"for",
"the",
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"exp",
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"dot",
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"-",
"0",
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"[",
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":",
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] |
def classnormalizationconst(classstd):
"""normalization const for the equation exp(dot(-0.5/bandwidth**2,r_[arccos(x[0])**2,x[1:]**2]))"""
gaussconst = -0.5*(len(classstd)-1)*numpy.log(pi)-0.5*numpy.log(prod(classstd[1:]))
# normalization for the weights so that integrated volume is 1. this is necessary when comparing across different distributions?
quatconst = numpy.log(1.0/classstd[0]**2+0.3334)
return quatconst+gaussconst
|
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https://github.com/rdiankov/openrave/blob/d1a23023fd4b58f077d2ca949ceaf1b91f3f13d7/python/databases/inversereachability.py#L108-L113
|
|
tensorflow/tensorflow
|
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
|
tensorflow/python/ops/control_flow_state.py
|
python
|
_ZerosLikeV2
|
(op, index)
|
Branch of ZerosLike for TF2.
|
Branch of ZerosLike for TF2.
|
[
"Branch",
"of",
"ZerosLike",
"for",
"TF2",
"."
] |
def _ZerosLikeV2(op, index):
"""Branch of ZerosLike for TF2."""
val = op.outputs[index]
if val.dtype == dtypes.resource:
return array_ops.zeros(
gen_resource_variable_ops.variable_shape(val),
dtype=default_gradient.get_zeros_dtype(val))
if (isinstance(val.op.graph, control_flow_v2_func_graphs.WhileBodyFuncGraph)
and val.dtype != dtypes.variant):
# In while_v2 we do not want to add a `ZerosLike` op because that will
# trigger accumulation of `val`. Normally `ZerosLike` is preferred because
# it helps avoid creating extra nodes(possibly Consts) for the shape.
# For variants, we must use ZerosLike.
if val.shape.is_fully_defined():
return constant_op.constant(0, shape=val.shape.dims, dtype=val.dtype)
else:
# Note: Even though we add `Shape` in the default graph, while_v2 is smart
# enough to place it in the forward graph i.e. `val.graph`.
zeros_shape = array_ops.shape_internal(val, optimize=False)
return array_ops.zeros(zeros_shape, val.dtype)
else:
return array_ops.zeros_like(val, optimize=False)
|
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/ops/control_flow_state.py#L806-L827
|
||
zhaoweicai/cascade-rcnn
|
2252f46158ea6555868ca6fa5c221ea71d9b5e6c
|
scripts/cpp_lint.py
|
python
|
ResetNolintSuppressions
|
()
|
Resets the set of NOLINT suppressions to empty.
|
Resets the set of NOLINT suppressions to empty.
|
[
"Resets",
"the",
"set",
"of",
"NOLINT",
"suppressions",
"to",
"empty",
"."
] |
def ResetNolintSuppressions():
"Resets the set of NOLINT suppressions to empty."
_error_suppressions.clear()
|
[
"def",
"ResetNolintSuppressions",
"(",
")",
":",
"_error_suppressions",
".",
"clear",
"(",
")"
] |
https://github.com/zhaoweicai/cascade-rcnn/blob/2252f46158ea6555868ca6fa5c221ea71d9b5e6c/scripts/cpp_lint.py#L499-L501
|
||
nest/nest-simulator
|
f2623eb78518cdbd55e77e0ed486bf1111bcb62f
|
pynest/examples/hpc_benchmark.py
|
python
|
lambertwm1
|
(x)
|
return sp.lambertw(x, k=-1 if x < 0 else 0).real
|
Wrapper for LambertWm1 function
|
Wrapper for LambertWm1 function
|
[
"Wrapper",
"for",
"LambertWm1",
"function"
] |
def lambertwm1(x):
"""Wrapper for LambertWm1 function"""
# Using scipy to mimic the gsl_sf_lambert_Wm1 function.
return sp.lambertw(x, k=-1 if x < 0 else 0).real
|
[
"def",
"lambertwm1",
"(",
"x",
")",
":",
"# Using scipy to mimic the gsl_sf_lambert_Wm1 function.",
"return",
"sp",
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"x",
",",
"k",
"=",
"-",
"1",
"if",
"x",
"<",
"0",
"else",
"0",
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] |
https://github.com/nest/nest-simulator/blob/f2623eb78518cdbd55e77e0ed486bf1111bcb62f/pynest/examples/hpc_benchmark.py#L426-L429
|
|
rdkit/rdkit
|
ede860ae316d12d8568daf5ee800921c3389c84e
|
rdkit/ML/ScreenComposite.py
|
python
|
ScreenIt
|
(composite, indices, data, partialVote=0, voteTol=0.0, verbose=1, screenResults=None,
goodVotes=None, badVotes=None, noVotes=None)
|
return nGood, misCount, nSkipped, avgGood, avgBad, avgSkip, None
|
screens a set of data using a composite model and prints out
statistics about the screen.
#DOC
The work of doing the screening and processing the results is
handled by _DetailedScreen()_
**Arguments**
- composite: the composite model to be used
- data: the examples to be screened (a sequence of sequences)
it's assumed that the last element in each example is its "value"
- partialVote: (optional) toggles use of the threshold value in
the screnning.
- voteTol: (optional) the threshold to be used to decide whether or not a
given prediction should be kept
- verbose: (optional) sets degree of verbosity of the screening
- screenResults: (optional) the results of screening the results
(a sequence of 3-tuples in the format returned by
_CollectResults()_). If this is provided, the examples will not
be screened again.
- goodVotes,badVotes,noVotes: (optional) if provided these should
be lists (or anything supporting an _append()_ method) which
will be used to pass the screening results back.
**Returns**
a 7-tuple:
1) the number of good (correct) predictions
2) the number of bad (incorrect) predictions
3) the number of predictions skipped due to the _threshold_
4) the average confidence in the good predictions
5) the average confidence in the bad predictions
6) the average confidence in the skipped predictions
7) None
|
screens a set of data using a composite model and prints out
statistics about the screen.
#DOC
The work of doing the screening and processing the results is
handled by _DetailedScreen()_
|
[
"screens",
"a",
"set",
"of",
"data",
"using",
"a",
"composite",
"model",
"and",
"prints",
"out",
"statistics",
"about",
"the",
"screen",
".",
"#DOC",
"The",
"work",
"of",
"doing",
"the",
"screening",
"and",
"processing",
"the",
"results",
"is",
"handled",
"by",
"_DetailedScreen",
"()",
"_"
] |
def ScreenIt(composite, indices, data, partialVote=0, voteTol=0.0, verbose=1, screenResults=None,
goodVotes=None, badVotes=None, noVotes=None):
""" screens a set of data using a composite model and prints out
statistics about the screen.
#DOC
The work of doing the screening and processing the results is
handled by _DetailedScreen()_
**Arguments**
- composite: the composite model to be used
- data: the examples to be screened (a sequence of sequences)
it's assumed that the last element in each example is its "value"
- partialVote: (optional) toggles use of the threshold value in
the screnning.
- voteTol: (optional) the threshold to be used to decide whether or not a
given prediction should be kept
- verbose: (optional) sets degree of verbosity of the screening
- screenResults: (optional) the results of screening the results
(a sequence of 3-tuples in the format returned by
_CollectResults()_). If this is provided, the examples will not
be screened again.
- goodVotes,badVotes,noVotes: (optional) if provided these should
be lists (or anything supporting an _append()_ method) which
will be used to pass the screening results back.
**Returns**
a 7-tuple:
1) the number of good (correct) predictions
2) the number of bad (incorrect) predictions
3) the number of predictions skipped due to the _threshold_
4) the average confidence in the good predictions
5) the average confidence in the bad predictions
6) the average confidence in the skipped predictions
7) None
"""
if goodVotes is None:
goodVotes = []
if badVotes is None:
badVotes = []
if noVotes is None:
noVotes = []
if not partialVote:
voteTol = 0.0
DetailedScreen(indices, data, composite, voteTol, screenResults=screenResults,
goodVotes=goodVotes, badVotes=badVotes, noVotes=noVotes)
nGood = len(goodVotes)
goodAccum = 0.
for res, pred, conf, idx in goodVotes:
goodAccum += conf
misCount = len(badVotes)
badAccum = 0.
for res, pred, conf, idx in badVotes:
badAccum += conf
nSkipped = len(noVotes)
goodSkipped = 0
badSkipped = 0
skipAccum = 0.
for ans, pred, conf, idx in noVotes:
skipAccum += conf
if ans != pred:
badSkipped += 1
else:
goodSkipped += 1
nData = nGood + misCount + nSkipped
if verbose:
print('Total N Points:', nData)
if partialVote:
nCounted = nData - nSkipped
if verbose:
print('Misclassifications: %d (%%%4.2f)' % (misCount, 100. * float(misCount) / nCounted))
print('N Skipped: %d (%%%4.2f)' % (nSkipped, 100. * float(nSkipped) / nData))
print('\tGood Votes Skipped: %d (%%%4.2f)' %
(goodSkipped, 100. * float(goodSkipped) / nSkipped))
print('\tBad Votes Skipped: %d (%%%4.2f)' % (badSkipped, 100. * float(badSkipped) / nSkipped))
else:
if verbose:
print('Misclassifications: %d (%%%4.2f)' % (misCount, 100. * float(misCount) / nData))
print('Average Correct Vote Confidence: % 6.4f' % (goodAccum / (nData - misCount)))
print('Average InCorrect Vote Confidence: % 6.4f' % (badAccum / misCount))
avgGood = 0
avgBad = 0
avgSkip = 0
if nGood:
avgGood = goodAccum / nGood
if misCount:
avgBad = badAccum / misCount
if nSkipped:
avgSkip = skipAccum / nSkipped
return nGood, misCount, nSkipped, avgGood, avgBad, avgSkip, None
|
[
"def",
"ScreenIt",
"(",
"composite",
",",
"indices",
",",
"data",
",",
"partialVote",
"=",
"0",
",",
"voteTol",
"=",
"0.0",
",",
"verbose",
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"1",
",",
"screenResults",
"=",
"None",
",",
"goodVotes",
"=",
"None",
",",
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"None",
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"noVotes",
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"None",
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"goodVotes",
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"]",
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"None",
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"=",
"[",
"]",
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"noVotes",
"is",
"None",
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"noVotes",
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",",
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"goodVotes",
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"goodAccum",
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"=",
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")",
"goodSkipped",
"=",
"0",
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"skipAccum",
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"for",
"ans",
",",
"pred",
",",
"conf",
",",
"idx",
"in",
"noVotes",
":",
"skipAccum",
"+=",
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"pred",
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"badSkipped",
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"1",
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":",
"goodSkipped",
"+=",
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"nData",
"=",
"nGood",
"+",
"misCount",
"+",
"nSkipped",
"if",
"verbose",
":",
"print",
"(",
"'Total N Points:'",
",",
"nData",
")",
"if",
"partialVote",
":",
"nCounted",
"=",
"nData",
"-",
"nSkipped",
"if",
"verbose",
":",
"print",
"(",
"'Misclassifications: %d (%%%4.2f)'",
"%",
"(",
"misCount",
",",
"100.",
"*",
"float",
"(",
"misCount",
")",
"/",
"nCounted",
")",
")",
"print",
"(",
"'N Skipped: %d (%%%4.2f)'",
"%",
"(",
"nSkipped",
",",
"100.",
"*",
"float",
"(",
"nSkipped",
")",
"/",
"nData",
")",
")",
"print",
"(",
"'\\tGood Votes Skipped: %d (%%%4.2f)'",
"%",
"(",
"goodSkipped",
",",
"100.",
"*",
"float",
"(",
"goodSkipped",
")",
"/",
"nSkipped",
")",
")",
"print",
"(",
"'\\tBad Votes Skipped: %d (%%%4.2f)'",
"%",
"(",
"badSkipped",
",",
"100.",
"*",
"float",
"(",
"badSkipped",
")",
"/",
"nSkipped",
")",
")",
"else",
":",
"if",
"verbose",
":",
"print",
"(",
"'Misclassifications: %d (%%%4.2f)'",
"%",
"(",
"misCount",
",",
"100.",
"*",
"float",
"(",
"misCount",
")",
"/",
"nData",
")",
")",
"print",
"(",
"'Average Correct Vote Confidence: % 6.4f'",
"%",
"(",
"goodAccum",
"/",
"(",
"nData",
"-",
"misCount",
")",
")",
")",
"print",
"(",
"'Average InCorrect Vote Confidence: % 6.4f'",
"%",
"(",
"badAccum",
"/",
"misCount",
")",
")",
"avgGood",
"=",
"0",
"avgBad",
"=",
"0",
"avgSkip",
"=",
"0",
"if",
"nGood",
":",
"avgGood",
"=",
"goodAccum",
"/",
"nGood",
"if",
"misCount",
":",
"avgBad",
"=",
"badAccum",
"/",
"misCount",
"if",
"nSkipped",
":",
"avgSkip",
"=",
"skipAccum",
"/",
"nSkipped",
"return",
"nGood",
",",
"misCount",
",",
"nSkipped",
",",
"avgGood",
",",
"avgBad",
",",
"avgSkip",
",",
"None"
] |
https://github.com/rdkit/rdkit/blob/ede860ae316d12d8568daf5ee800921c3389c84e/rdkit/ML/ScreenComposite.py#L465-L577
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/psutil/_common.py
|
python
|
wrap_numbers
|
(input_dict, name)
|
Given an `input_dict` and a function `name`, adjust the numbers
which "wrap" (restart from zero) across different calls by adding
"old value" to "new value" and return an updated dict.
|
Given an `input_dict` and a function `name`, adjust the numbers
which "wrap" (restart from zero) across different calls by adding
"old value" to "new value" and return an updated dict.
|
[
"Given",
"an",
"input_dict",
"and",
"a",
"function",
"name",
"adjust",
"the",
"numbers",
"which",
"wrap",
"(",
"restart",
"from",
"zero",
")",
"across",
"different",
"calls",
"by",
"adding",
"old",
"value",
"to",
"new",
"value",
"and",
"return",
"an",
"updated",
"dict",
"."
] |
def wrap_numbers(input_dict, name):
"""Given an `input_dict` and a function `name`, adjust the numbers
which "wrap" (restart from zero) across different calls by adding
"old value" to "new value" and return an updated dict.
"""
with _wn.lock:
return _wn.run(input_dict, name)
|
[
"def",
"wrap_numbers",
"(",
"input_dict",
",",
"name",
")",
":",
"with",
"_wn",
".",
"lock",
":",
"return",
"_wn",
".",
"run",
"(",
"input_dict",
",",
"name",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/psutil/_common.py#L698-L704
|
||
Cocos-BCX/cocos-mainnet
|
68451c4d882c0efe871806394be473f5689bd982
|
programs/build_helpers/check_reflect.py
|
python
|
process_node
|
(path, node)
|
return
|
if node.tag == "TestCase":
if node.attrib.get("result", "UNKNOWN") != "passed":
failset.add(node)
return
if node.tag in ["TestResult", "TestSuite"]:
for child in node:
cpath = path+"/"+child.attrib["name"]
process_node(cpath, child)
return
|
if node.tag == "TestCase":
if node.attrib.get("result", "UNKNOWN") != "passed":
failset.add(node)
return
if node.tag in ["TestResult", "TestSuite"]:
for child in node:
cpath = path+"/"+child.attrib["name"]
process_node(cpath, child)
return
|
[
"if",
"node",
".",
"tag",
"==",
"TestCase",
":",
"if",
"node",
".",
"attrib",
".",
"get",
"(",
"result",
"UNKNOWN",
")",
"!",
"=",
"passed",
":",
"failset",
".",
"add",
"(",
"node",
")",
"return",
"if",
"node",
".",
"tag",
"in",
"[",
"TestResult",
"TestSuite",
"]",
":",
"for",
"child",
"in",
"node",
":",
"cpath",
"=",
"path",
"+",
"/",
"+",
"child",
".",
"attrib",
"[",
"name",
"]",
"process_node",
"(",
"cpath",
"child",
")",
"return"
] |
def process_node(path, node):
"""
if node.tag == "TestCase":
if node.attrib.get("result", "UNKNOWN") != "passed":
failset.add(node)
return
if node.tag in ["TestResult", "TestSuite"]:
for child in node:
cpath = path+"/"+child.attrib["name"]
process_node(cpath, child)
return
"""
#print("unknown node", node.tag)
print(node.tag)
return
|
[
"def",
"process_node",
"(",
"path",
",",
"node",
")",
":",
"#print(\"unknown node\", node.tag)",
"print",
"(",
"node",
".",
"tag",
")",
"return"
] |
https://github.com/Cocos-BCX/cocos-mainnet/blob/68451c4d882c0efe871806394be473f5689bd982/programs/build_helpers/check_reflect.py#L8-L22
|
|
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/third_party/pipeline/pipeline/pipeline.py
|
python
|
Pipeline.finalized
|
(self)
|
Finalizes this Pipeline after execution if it's a generator.
Default action as the root pipeline is to email the admins with the status.
Implementors be sure to call 'was_aborted' to find out if the finalization
that you're handling is for a success or error case.
|
Finalizes this Pipeline after execution if it's a generator.
|
[
"Finalizes",
"this",
"Pipeline",
"after",
"execution",
"if",
"it",
"s",
"a",
"generator",
"."
] |
def finalized(self):
"""Finalizes this Pipeline after execution if it's a generator.
Default action as the root pipeline is to email the admins with the status.
Implementors be sure to call 'was_aborted' to find out if the finalization
that you're handling is for a success or error case.
"""
if self.pipeline_id == self.root_pipeline_id:
self.send_result_email()
|
[
"def",
"finalized",
"(",
"self",
")",
":",
"if",
"self",
".",
"pipeline_id",
"==",
"self",
".",
"root_pipeline_id",
":",
"self",
".",
"send_result_email",
"(",
")"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/pipeline/pipeline/pipeline.py#L999-L1007
|
||
baidu-research/tensorflow-allreduce
|
66d5b855e90b0949e9fa5cca5599fd729a70e874
|
tensorflow/python/tools/optimize_for_inference_lib.py
|
python
|
ensure_graph_is_valid
|
(graph_def)
|
Makes sure that the graph is internally consistent.
Checks basic properties of the graph def and raises an exception if there are
input references to missing nodes, duplicated names, or other logic errors.
Args:
graph_def: Definition of a graph to be checked.
Raises:
ValueError: If the graph is incorrectly constructed.
|
Makes sure that the graph is internally consistent.
|
[
"Makes",
"sure",
"that",
"the",
"graph",
"is",
"internally",
"consistent",
"."
] |
def ensure_graph_is_valid(graph_def):
"""Makes sure that the graph is internally consistent.
Checks basic properties of the graph def and raises an exception if there are
input references to missing nodes, duplicated names, or other logic errors.
Args:
graph_def: Definition of a graph to be checked.
Raises:
ValueError: If the graph is incorrectly constructed.
"""
node_map = {}
for node in graph_def.node:
if node.name not in node_map.keys():
node_map[node.name] = node
else:
raise ValueError("Duplicate node names detected for ", node.name)
for node in graph_def.node:
for input_name in node.input:
input_node_name = node_name_from_input(input_name)
if input_node_name not in node_map.keys():
raise ValueError("Input for ", node.name, " not found: ", input_name)
|
[
"def",
"ensure_graph_is_valid",
"(",
"graph_def",
")",
":",
"node_map",
"=",
"{",
"}",
"for",
"node",
"in",
"graph_def",
".",
"node",
":",
"if",
"node",
".",
"name",
"not",
"in",
"node_map",
".",
"keys",
"(",
")",
":",
"node_map",
"[",
"node",
".",
"name",
"]",
"=",
"node",
"else",
":",
"raise",
"ValueError",
"(",
"\"Duplicate node names detected for \"",
",",
"node",
".",
"name",
")",
"for",
"node",
"in",
"graph_def",
".",
"node",
":",
"for",
"input_name",
"in",
"node",
".",
"input",
":",
"input_node_name",
"=",
"node_name_from_input",
"(",
"input_name",
")",
"if",
"input_node_name",
"not",
"in",
"node_map",
".",
"keys",
"(",
")",
":",
"raise",
"ValueError",
"(",
"\"Input for \"",
",",
"node",
".",
"name",
",",
"\" not found: \"",
",",
"input_name",
")"
] |
https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/python/tools/optimize_for_inference_lib.py#L119-L141
|
||
panda3d/panda3d
|
833ad89ebad58395d0af0b7ec08538e5e4308265
|
direct/src/showbase/Audio3DManager.py
|
python
|
Audio3DManager.getDropOffFactor
|
(self)
|
return self.audio_manager.audio3dGetDropOffFactor()
|
Exaggerate or diminish the effect of distance on sound. Default is 1.0
Valid range is 0 to 10
Faster drop off, use >1.0
Slower drop off, use <1.0
|
Exaggerate or diminish the effect of distance on sound. Default is 1.0
Valid range is 0 to 10
Faster drop off, use >1.0
Slower drop off, use <1.0
|
[
"Exaggerate",
"or",
"diminish",
"the",
"effect",
"of",
"distance",
"on",
"sound",
".",
"Default",
"is",
"1",
".",
"0",
"Valid",
"range",
"is",
"0",
"to",
"10",
"Faster",
"drop",
"off",
"use",
">",
"1",
".",
"0",
"Slower",
"drop",
"off",
"use",
"<1",
".",
"0"
] |
def getDropOffFactor(self):
"""
Exaggerate or diminish the effect of distance on sound. Default is 1.0
Valid range is 0 to 10
Faster drop off, use >1.0
Slower drop off, use <1.0
"""
return self.audio_manager.audio3dGetDropOffFactor()
|
[
"def",
"getDropOffFactor",
"(",
"self",
")",
":",
"return",
"self",
".",
"audio_manager",
".",
"audio3dGetDropOffFactor",
"(",
")"
] |
https://github.com/panda3d/panda3d/blob/833ad89ebad58395d0af0b7ec08538e5e4308265/direct/src/showbase/Audio3DManager.py#L76-L83
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/tools/python/src/Lib/lib-tk/Tkinter.py
|
python
|
Canvas.tag_bind
|
(self, tagOrId, sequence=None, func=None, add=None)
|
return self._bind((self._w, 'bind', tagOrId),
sequence, func, add)
|
Bind to all items with TAGORID at event SEQUENCE a call to function FUNC.
An additional boolean parameter ADD specifies whether FUNC will be
called additionally to the other bound function or whether it will
replace the previous function. See bind for the return value.
|
Bind to all items with TAGORID at event SEQUENCE a call to function FUNC.
|
[
"Bind",
"to",
"all",
"items",
"with",
"TAGORID",
"at",
"event",
"SEQUENCE",
"a",
"call",
"to",
"function",
"FUNC",
"."
] |
def tag_bind(self, tagOrId, sequence=None, func=None, add=None):
"""Bind to all items with TAGORID at event SEQUENCE a call to function FUNC.
An additional boolean parameter ADD specifies whether FUNC will be
called additionally to the other bound function or whether it will
replace the previous function. See bind for the return value."""
return self._bind((self._w, 'bind', tagOrId),
sequence, func, add)
|
[
"def",
"tag_bind",
"(",
"self",
",",
"tagOrId",
",",
"sequence",
"=",
"None",
",",
"func",
"=",
"None",
",",
"add",
"=",
"None",
")",
":",
"return",
"self",
".",
"_bind",
"(",
"(",
"self",
".",
"_w",
",",
"'bind'",
",",
"tagOrId",
")",
",",
"sequence",
",",
"func",
",",
"add",
")"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/lib-tk/Tkinter.py#L2282-L2289
|
|
francinexue/xuefu
|
b6ff79747a42e020588c0c0a921048e08fe4680c
|
ctpx/ctp2/ctptd.py
|
python
|
CtpTd.onRtnInstrumentStatus
|
(self, InstrumentStatusField)
|
合约交易状态通知
|
合约交易状态通知
|
[
"合约交易状态通知"
] |
def onRtnInstrumentStatus(self, InstrumentStatusField):
"""合约交易状态通知"""
pass
|
[
"def",
"onRtnInstrumentStatus",
"(",
"self",
",",
"InstrumentStatusField",
")",
":",
"pass"
] |
https://github.com/francinexue/xuefu/blob/b6ff79747a42e020588c0c0a921048e08fe4680c/ctpx/ctp2/ctptd.py#L367-L369
|
||
benoitsteiner/tensorflow-opencl
|
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
|
tensorflow/contrib/framework/python/ops/variables.py
|
python
|
variable
|
(name, shape=None, dtype=None, initializer=None,
regularizer=None, trainable=True, collections=None,
caching_device=None, device=None,
partitioner=None, custom_getter=None, use_resource=None)
|
Gets an existing variable with these parameters or creates a new one.
Args:
name: the name of the new or existing variable.
shape: shape of the new or existing variable.
dtype: type of the new or existing variable (defaults to `DT_FLOAT`).
initializer: initializer for the variable if one is created.
regularizer: a (Tensor -> Tensor or None) function; the result of
applying it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
trainable: If `True` also add the variable to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see `tf.Variable`).
collections: A list of collection names to which the Variable will be added.
If None it would default to `tf.GraphKeys.GLOBAL_VARIABLES`.
caching_device: Optional device string or function describing where the
Variable should be cached for reading. Defaults to the Variable's
device.
device: Optional device to place the variable. It can be an string or a
function that is called to get the device for the variable.
partitioner: Optional callable that accepts a fully defined `TensorShape`
and dtype of the `Variable` to be created, and returns a list of
partitions for each axis (currently only one axis can be partitioned).
custom_getter: Callable that allows overwriting the internal
get_variable method and has to have the same signature.
use_resource: If `True` use a ResourceVariable instead of a Variable.
Returns:
The created or existing variable.
|
Gets an existing variable with these parameters or creates a new one.
|
[
"Gets",
"an",
"existing",
"variable",
"with",
"these",
"parameters",
"or",
"creates",
"a",
"new",
"one",
"."
] |
def variable(name, shape=None, dtype=None, initializer=None,
regularizer=None, trainable=True, collections=None,
caching_device=None, device=None,
partitioner=None, custom_getter=None, use_resource=None):
"""Gets an existing variable with these parameters or creates a new one.
Args:
name: the name of the new or existing variable.
shape: shape of the new or existing variable.
dtype: type of the new or existing variable (defaults to `DT_FLOAT`).
initializer: initializer for the variable if one is created.
regularizer: a (Tensor -> Tensor or None) function; the result of
applying it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
trainable: If `True` also add the variable to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see `tf.Variable`).
collections: A list of collection names to which the Variable will be added.
If None it would default to `tf.GraphKeys.GLOBAL_VARIABLES`.
caching_device: Optional device string or function describing where the
Variable should be cached for reading. Defaults to the Variable's
device.
device: Optional device to place the variable. It can be an string or a
function that is called to get the device for the variable.
partitioner: Optional callable that accepts a fully defined `TensorShape`
and dtype of the `Variable` to be created, and returns a list of
partitions for each axis (currently only one axis can be partitioned).
custom_getter: Callable that allows overwriting the internal
get_variable method and has to have the same signature.
use_resource: If `True` use a ResourceVariable instead of a Variable.
Returns:
The created or existing variable.
"""
collections = list(collections if collections is not None
else [ops.GraphKeys.GLOBAL_VARIABLES])
# Remove duplicates
collections = set(collections)
getter = variable_scope.get_variable
if custom_getter is not None:
getter = functools.partial(custom_getter,
reuse=variable_scope.get_variable_scope().reuse)
with ops.device(device or ''):
return getter(name, shape=shape, dtype=dtype,
initializer=initializer,
regularizer=regularizer,
trainable=trainable,
collections=collections,
caching_device=caching_device,
partitioner=partitioner,
use_resource=use_resource)
|
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",",
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")"
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https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/contrib/framework/python/ops/variables.py#L167-L217
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/msw/_gdi.py
|
python
|
EnhMetaFile.IsOk
|
(*args, **kwargs)
|
return _gdi_.EnhMetaFile_IsOk(*args, **kwargs)
|
IsOk(self) -> bool
|
IsOk(self) -> bool
|
[
"IsOk",
"(",
"self",
")",
"-",
">",
"bool"
] |
def IsOk(*args, **kwargs):
"""IsOk(self) -> bool"""
return _gdi_.EnhMetaFile_IsOk(*args, **kwargs)
|
[
"def",
"IsOk",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_gdi_",
".",
"EnhMetaFile_IsOk",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/_gdi.py#L5540-L5542
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/dateutil/dateutil/parser/isoparser.py
|
python
|
isoparser.__init__
|
(self, sep=None)
|
:param sep:
A single character that separates date and time portions. If
``None``, the parser will accept any single character.
For strict ISO-8601 adherence, pass ``'T'``.
|
:param sep:
A single character that separates date and time portions. If
``None``, the parser will accept any single character.
For strict ISO-8601 adherence, pass ``'T'``.
|
[
":",
"param",
"sep",
":",
"A",
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"character",
"that",
"separates",
"date",
"and",
"time",
"portions",
".",
"If",
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"parser",
"will",
"accept",
"any",
"single",
"character",
".",
"For",
"strict",
"ISO",
"-",
"8601",
"adherence",
"pass",
"T",
"."
] |
def __init__(self, sep=None):
"""
:param sep:
A single character that separates date and time portions. If
``None``, the parser will accept any single character.
For strict ISO-8601 adherence, pass ``'T'``.
"""
if sep is not None:
if (len(sep) != 1 or ord(sep) >= 128 or sep in '0123456789'):
raise ValueError('Separator must be a single, non-numeric ' +
'ASCII character')
sep = sep.encode('ascii')
self._sep = sep
|
[
"def",
"__init__",
"(",
"self",
",",
"sep",
"=",
"None",
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":",
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"is",
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".",
"encode",
"(",
"'ascii'",
")",
"self",
".",
"_sep",
"=",
"sep"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/dateutil/dateutil/parser/isoparser.py#L43-L57
|
||
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/x86/toolchain/lib/python2.7/xml/sax/xmlreader.py
|
python
|
AttributesImpl.__init__
|
(self, attrs)
|
Non-NS-aware implementation.
attrs should be of the form {name : value}.
|
Non-NS-aware implementation.
|
[
"Non",
"-",
"NS",
"-",
"aware",
"implementation",
"."
] |
def __init__(self, attrs):
"""Non-NS-aware implementation.
attrs should be of the form {name : value}."""
self._attrs = attrs
|
[
"def",
"__init__",
"(",
"self",
",",
"attrs",
")",
":",
"self",
".",
"_attrs",
"=",
"attrs"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/xml/sax/xmlreader.py#L278-L282
|
||
ricardoquesada/Spidermonkey
|
4a75ea2543408bd1b2c515aa95901523eeef7858
|
config/check_spidermonkey_style.py
|
python
|
Include.section
|
(self, enclosing_inclname)
|
return 3
|
Identify which section inclname belongs to.
The section numbers are as follows.
0. Module header (e.g. jsfoo.h or jsfooinlines.h within jsfoo.cpp)
1. mozilla/Foo.h
2. <foo.h> or <foo>
3. jsfoo.h, prmjtime.h, etc
4. foo/Bar.h
5. jsfooinlines.h
6. foo/Bar-inl.h
7. non-.h, e.g. *.tbl, *.msg
|
Identify which section inclname belongs to.
|
[
"Identify",
"which",
"section",
"inclname",
"belongs",
"to",
"."
] |
def section(self, enclosing_inclname):
'''Identify which section inclname belongs to.
The section numbers are as follows.
0. Module header (e.g. jsfoo.h or jsfooinlines.h within jsfoo.cpp)
1. mozilla/Foo.h
2. <foo.h> or <foo>
3. jsfoo.h, prmjtime.h, etc
4. foo/Bar.h
5. jsfooinlines.h
6. foo/Bar-inl.h
7. non-.h, e.g. *.tbl, *.msg
'''
if self.is_system:
return 2
if not self.inclname.endswith('.h'):
return 7
# A couple of modules have the .h file in js/ and the .cpp file elsewhere and so need
# special handling.
if is_module_header(enclosing_inclname, self.inclname):
return 0
if '/' in self.inclname:
if self.inclname.startswith('mozilla/'):
return 1
if self.inclname.endswith('-inl.h'):
return 6
return 4
if self.inclname.endswith('inlines.h'):
return 5
return 3
|
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"self",
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"enclosing_inclname",
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https://github.com/ricardoquesada/Spidermonkey/blob/4a75ea2543408bd1b2c515aa95901523eeef7858/config/check_spidermonkey_style.py#L335-L372
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/plotting/_matplotlib/converter.py
|
python
|
TimeSeries_TimedeltaFormatter.format_timedelta_ticks
|
(x, pos, n_decimals)
|
return s
|
Convert seconds to 'D days HH:MM:SS.F'
|
Convert seconds to 'D days HH:MM:SS.F'
|
[
"Convert",
"seconds",
"to",
"D",
"days",
"HH",
":",
"MM",
":",
"SS",
".",
"F"
] |
def format_timedelta_ticks(x, pos, n_decimals):
"""
Convert seconds to 'D days HH:MM:SS.F'
"""
s, ns = divmod(x, 1e9)
m, s = divmod(s, 60)
h, m = divmod(m, 60)
d, h = divmod(h, 24)
decimals = int(ns * 10 ** (n_decimals - 9))
s = f"{int(h):02d}:{int(m):02d}:{int(s):02d}"
if n_decimals > 0:
s += f".{decimals:0{n_decimals}d}"
if d != 0:
s = f"{int(d):d} days {s}"
return s
|
[
"def",
"format_timedelta_ticks",
"(",
"x",
",",
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",",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/plotting/_matplotlib/converter.py#L1111-L1125
|
|
mindspore-ai/mindspore
|
fb8fd3338605bb34fa5cea054e535a8b1d753fab
|
mindspore/python/mindspore/ops/operations/sponge_update_ops.py
|
python
|
PMEReciprocalForceUpdate.__init__
|
(self, atom_numbers, beta, fftx, ffty, fftz,
box_length_0, box_length_1, box_length_2, need_update=0)
|
Initialize PMEReciprocalForce
|
Initialize PMEReciprocalForce
|
[
"Initialize",
"PMEReciprocalForce"
] |
def __init__(self, atom_numbers, beta, fftx, ffty, fftz,
box_length_0, box_length_1, box_length_2, need_update=0):
"""Initialize PMEReciprocalForce"""
validator.check_value_type('atom_numbers', atom_numbers, int, self.name)
validator.check_value_type('beta', beta, float, self.name)
validator.check_value_type('fftx', fftx, int, self.name)
validator.check_value_type('ffty', ffty, int, self.name)
validator.check_value_type('fftz', fftz, int, self.name)
validator.check_value_type('box_length_0', box_length_0, float, self.name)
validator.check_value_type('box_length_1', box_length_1, float, self.name)
validator.check_value_type('box_length_2', box_length_2, float, self.name)
validator.check_value_type('need_update', need_update, int, self.name)
self.atom_numbers = atom_numbers
self.beta = beta
self.fftx = fftx
self.ffty = ffty
self.fftz = fftz
self.box_length_0 = box_length_0
self.box_length_1 = box_length_1
self.box_length_2 = box_length_2
self.need_update = need_update
self.init_prim_io_names(inputs=['uint_crd', 'charge', 'beta'],
outputs=['force'])
self.add_prim_attr('atom_numbers', self.atom_numbers)
self.add_prim_attr('beta', self.beta)
self.add_prim_attr('fftx', self.fftx)
self.add_prim_attr('ffty', self.ffty)
self.add_prim_attr('fftz', self.fftz)
self.add_prim_attr('box_length_0', self.box_length_0)
self.add_prim_attr('box_length_1', self.box_length_1)
self.add_prim_attr('box_length_2', self.box_length_2)
self.add_prim_attr('need_update', self.need_update)
|
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"add_prim_attr",
"(",
"'ffty'",
",",
"self",
".",
"ffty",
")",
"self",
".",
"add_prim_attr",
"(",
"'fftz'",
",",
"self",
".",
"fftz",
")",
"self",
".",
"add_prim_attr",
"(",
"'box_length_0'",
",",
"self",
".",
"box_length_0",
")",
"self",
".",
"add_prim_attr",
"(",
"'box_length_1'",
",",
"self",
".",
"box_length_1",
")",
"self",
".",
"add_prim_attr",
"(",
"'box_length_2'",
",",
"self",
".",
"box_length_2",
")",
"self",
".",
"add_prim_attr",
"(",
"'need_update'",
",",
"self",
".",
"need_update",
")"
] |
https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/ops/operations/sponge_update_ops.py#L1601-L1633
|
||
DLR-SC/tigl
|
d1c5901e948e33d10b1f9659ff3e22c4717b455f
|
thirdparty/nsiqcppstyle/nsiqcppstyle_checker.py
|
python
|
CppLexerNavigator.GetCurToken
|
(self)
|
return self.tokenlist[self.tokenindex]
|
Get Current Token
|
Get Current Token
|
[
"Get",
"Current",
"Token"
] |
def GetCurToken(self):
"""
Get Current Token
"""
return self.tokenlist[self.tokenindex]
|
[
"def",
"GetCurToken",
"(",
"self",
")",
":",
"return",
"self",
".",
"tokenlist",
"[",
"self",
".",
"tokenindex",
"]"
] |
https://github.com/DLR-SC/tigl/blob/d1c5901e948e33d10b1f9659ff3e22c4717b455f/thirdparty/nsiqcppstyle/nsiqcppstyle_checker.py#L417-L421
|
|
rrwick/Unicycler
|
96ffea71e3a78d63ade19d6124946773e65cf129
|
unicycler/misc.py
|
python
|
flip_number_order
|
(num_1, num_2)
|
Given two segment numbers, this function possibly flips them around. It returns the new numbers
(either unchanged or flipped) and whether or not a flip took place. The decision is somewhat
arbitrary, but it needs to be consistent so when we collect bridging read sequences they are
always in the same direction.
|
Given two segment numbers, this function possibly flips them around. It returns the new numbers
(either unchanged or flipped) and whether or not a flip took place. The decision is somewhat
arbitrary, but it needs to be consistent so when we collect bridging read sequences they are
always in the same direction.
|
[
"Given",
"two",
"segment",
"numbers",
"this",
"function",
"possibly",
"flips",
"them",
"around",
".",
"It",
"returns",
"the",
"new",
"numbers",
"(",
"either",
"unchanged",
"or",
"flipped",
")",
"and",
"whether",
"or",
"not",
"a",
"flip",
"took",
"place",
".",
"The",
"decision",
"is",
"somewhat",
"arbitrary",
"but",
"it",
"needs",
"to",
"be",
"consistent",
"so",
"when",
"we",
"collect",
"bridging",
"read",
"sequences",
"they",
"are",
"always",
"in",
"the",
"same",
"direction",
"."
] |
def flip_number_order(num_1, num_2):
"""
Given two segment numbers, this function possibly flips them around. It returns the new numbers
(either unchanged or flipped) and whether or not a flip took place. The decision is somewhat
arbitrary, but it needs to be consistent so when we collect bridging read sequences they are
always in the same direction.
"""
if num_1 > 0 and num_2 > 0:
flip = False
elif num_1 < 0 and num_2 < 0:
flip = True
elif num_1 < 0: # only num_1 is negative
flip = abs(num_1) > abs(num_2)
else: # only num_2 is negative
flip = abs(num_2) > abs(num_1)
if flip:
return (-num_2, -num_1), True
else:
return (num_1, num_2), False
|
[
"def",
"flip_number_order",
"(",
"num_1",
",",
"num_2",
")",
":",
"if",
"num_1",
">",
"0",
"and",
"num_2",
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"0",
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"flip",
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"# only num_1 is negative",
"flip",
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"abs",
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",",
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"else",
":",
"return",
"(",
"num_1",
",",
"num_2",
")",
",",
"False"
] |
https://github.com/rrwick/Unicycler/blob/96ffea71e3a78d63ade19d6124946773e65cf129/unicycler/misc.py#L299-L317
|
||
windystrife/UnrealEngine_NVIDIAGameWorks
|
b50e6338a7c5b26374d66306ebc7807541ff815e
|
Engine/Source/ThirdParty/CEF3/pristine/cef_source/tools/make_distrib.py
|
python
|
normalize_headers
|
(file, new_path = '')
|
Normalize headers post-processing. Remove the path component from any
project include directives.
|
Normalize headers post-processing. Remove the path component from any
project include directives.
|
[
"Normalize",
"headers",
"post",
"-",
"processing",
".",
"Remove",
"the",
"path",
"component",
"from",
"any",
"project",
"include",
"directives",
"."
] |
def normalize_headers(file, new_path = ''):
""" Normalize headers post-processing. Remove the path component from any
project include directives. """
data = read_file(file)
data = re.sub(r'''#include \"(?!include\/)[a-zA-Z0-9_\/]+\/+([a-zA-Z0-9_\.]+)\"''', \
"// Include path modified for CEF Binary Distribution.\n#include \""+new_path+"\\1\"", data)
write_file(file, data)
|
[
"def",
"normalize_headers",
"(",
"file",
",",
"new_path",
"=",
"''",
")",
":",
"data",
"=",
"read_file",
"(",
"file",
")",
"data",
"=",
"re",
".",
"sub",
"(",
"r'''#include \\\"(?!include\\/)[a-zA-Z0-9_\\/]+\\/+([a-zA-Z0-9_\\.]+)\\\"'''",
",",
"\"// Include path modified for CEF Binary Distribution.\\n#include \\\"\"",
"+",
"new_path",
"+",
"\"\\\\1\\\"\"",
",",
"data",
")",
"write_file",
"(",
"file",
",",
"data",
")"
] |
https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Source/ThirdParty/CEF3/pristine/cef_source/tools/make_distrib.py#L195-L201
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/AWSPythonSDK/1.5.8/docutils/utils/math/math2html.py
|
python
|
ContainerSize.setparameter
|
(self, container, name)
|
Read a size parameter off a container, and set it if present.
|
Read a size parameter off a container, and set it if present.
|
[
"Read",
"a",
"size",
"parameter",
"off",
"a",
"container",
"and",
"set",
"it",
"if",
"present",
"."
] |
def setparameter(self, container, name):
"Read a size parameter off a container, and set it if present."
value = container.getparameter(name)
self.setvalue(name, value)
|
[
"def",
"setparameter",
"(",
"self",
",",
"container",
",",
"name",
")",
":",
"value",
"=",
"container",
".",
"getparameter",
"(",
"name",
")",
"self",
".",
"setvalue",
"(",
"name",
",",
"value",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/AWSPythonSDK/1.5.8/docutils/utils/math/math2html.py#L3443-L3446
|
||
krishauser/Klampt
|
972cc83ea5befac3f653c1ba20f80155768ad519
|
Python/python2_version/klampt/src/robotsim.py
|
python
|
IKSolver.add
|
(self, objective)
|
return _robotsim.IKSolver_add(self, objective)
|
add(IKSolver self, IKObjective objective)
Adds a new simultaneous objective.
|
add(IKSolver self, IKObjective objective)
|
[
"add",
"(",
"IKSolver",
"self",
"IKObjective",
"objective",
")"
] |
def add(self, objective):
"""
add(IKSolver self, IKObjective objective)
Adds a new simultaneous objective.
"""
return _robotsim.IKSolver_add(self, objective)
|
[
"def",
"add",
"(",
"self",
",",
"objective",
")",
":",
"return",
"_robotsim",
".",
"IKSolver_add",
"(",
"self",
",",
"objective",
")"
] |
https://github.com/krishauser/Klampt/blob/972cc83ea5befac3f653c1ba20f80155768ad519/Python/python2_version/klampt/src/robotsim.py#L6595-L6604
|
|
zerotier/libzt
|
41eb9aebc80a5f1c816fa26a06cefde9de906676
|
src/bindings/python/sockets.py
|
python
|
socket.getpeername
|
(self)
|
libzt does not support this (yet)
|
libzt does not support this (yet)
|
[
"libzt",
"does",
"not",
"support",
"this",
"(",
"yet",
")"
] |
def getpeername(self):
"""libzt does not support this (yet)"""
raise NotImplementedError("libzt does not support this (yet?)")
|
[
"def",
"getpeername",
"(",
"self",
")",
":",
"raise",
"NotImplementedError",
"(",
"\"libzt does not support this (yet?)\"",
")"
] |
https://github.com/zerotier/libzt/blob/41eb9aebc80a5f1c816fa26a06cefde9de906676/src/bindings/python/sockets.py#L291-L293
|
||
rdkit/rdkit
|
ede860ae316d12d8568daf5ee800921c3389c84e
|
rdkit/ML/DecTree/PruneTree.py
|
python
|
_Pruner
|
(node, level=0)
|
return bestTree
|
Recursively finds and removes the nodes whose removals improve classification
**Arguments**
- node: the tree to be pruned. The pruning data should already be contained
within node (i.e. node.GetExamples() should return the pruning data)
- level: (optional) the level of recursion, used only in _verbose printing
**Returns**
the pruned version of node
**Notes**
- This uses a greedy algorithm which basically does a DFS traversal of the tree,
removing nodes whenever possible.
- If removing a node does not affect the accuracy, it *will be* removed. We
favor smaller trees.
|
Recursively finds and removes the nodes whose removals improve classification
|
[
"Recursively",
"finds",
"and",
"removes",
"the",
"nodes",
"whose",
"removals",
"improve",
"classification"
] |
def _Pruner(node, level=0):
"""Recursively finds and removes the nodes whose removals improve classification
**Arguments**
- node: the tree to be pruned. The pruning data should already be contained
within node (i.e. node.GetExamples() should return the pruning data)
- level: (optional) the level of recursion, used only in _verbose printing
**Returns**
the pruned version of node
**Notes**
- This uses a greedy algorithm which basically does a DFS traversal of the tree,
removing nodes whenever possible.
- If removing a node does not affect the accuracy, it *will be* removed. We
favor smaller trees.
"""
if _verbose:
print(' ' * level, '<%d> ' % level, '>>> Pruner')
children = node.GetChildren()[:]
bestTree = copy.deepcopy(node)
bestErr = 1e6
#
# Loop over the children of this node, removing them when doing so
# either improves the local error or leaves it unchanged (we're
# introducing a bias for simpler trees).
#
for i in range(len(children)):
child = children[i]
examples = child.GetExamples()
if _verbose:
print(' ' * level, '<%d> ' % level, ' Child:', i, child.GetLabel())
bestTree.Print()
print()
if len(examples):
if _verbose:
print(' ' * level, '<%d> ' % level, ' Examples', len(examples))
if child.GetTerminal():
if _verbose:
print(' ' * level, '<%d> ' % level, ' Terminal')
continue
if _verbose:
print(' ' * level, '<%d> ' % level, ' Nonterminal')
workTree = copy.deepcopy(bestTree)
#
# First recurse on the child (try removing things below it)
#
newNode = _Pruner(child, level=level + 1)
workTree.ReplaceChildIndex(i, newNode)
tempErr = _GetLocalError(workTree)
if tempErr <= bestErr:
bestErr = tempErr
bestTree = copy.deepcopy(workTree)
if _verbose:
print(' ' * level, '<%d> ' % level, '>->->->->->')
print(' ' * level, '<%d> ' % level, 'replacing:', i, child.GetLabel())
child.Print()
print(' ' * level, '<%d> ' % level, 'with:')
newNode.Print()
print(' ' * level, '<%d> ' % level, '<-<-<-<-<-<')
else:
workTree.ReplaceChildIndex(i, child)
#
# Now try replacing the child entirely
#
bestGuess = MaxCount(child.GetExamples())
newNode = DecTree.DecTreeNode(workTree, 'L:%d' % (
bestGuess), label=bestGuess, isTerminal=1)
newNode.SetExamples(child.GetExamples())
workTree.ReplaceChildIndex(i, newNode)
if _verbose:
print(' ' * level, '<%d> ' % level, 'ATTEMPT:')
workTree.Print()
newErr = _GetLocalError(workTree)
if _verbose:
print(' ' * level, '<%d> ' % level, '---> ', newErr, bestErr)
if newErr <= bestErr:
bestErr = newErr
bestTree = copy.deepcopy(workTree)
if _verbose:
print(' ' * level, '<%d> ' % level, 'PRUNING:')
workTree.Print()
else:
if _verbose:
print(' ' * level, '<%d> ' % level, 'FAIL')
# whoops... put the child back in:
workTree.ReplaceChildIndex(i, child)
else:
if _verbose:
print(' ' * level, '<%d> ' % level, ' No Examples', len(examples))
#
# FIX: we need to figure out what to do here (nodes that contain
# no examples in the testing set). I can concoct arguments for
# leaving them in and for removing them. At the moment they are
# left intact.
#
pass
if _verbose:
print(' ' * level, '<%d> ' % level, '<<< out')
return bestTree
|
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":",
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"(",
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",",
"'<%d> '",
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",",
"'<<< out'",
")",
"return",
"bestTree"
] |
https://github.com/rdkit/rdkit/blob/ede860ae316d12d8568daf5ee800921c3389c84e/rdkit/ML/DecTree/PruneTree.py#L49-L160
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/turtle.py
|
python
|
_Screen.exitonclick
|
(self)
|
Go into mainloop until the mouse is clicked.
No arguments.
Bind bye() method to mouseclick on TurtleScreen.
If "using_IDLE" - value in configuration dictionary is False
(default value), enter mainloop.
If IDLE with -n switch (no subprocess) is used, this value should be
set to True in turtle.cfg. In this case IDLE's mainloop
is active also for the client script.
This is a method of the Screen-class and not available for
TurtleScreen instances.
Example (for a Screen instance named screen):
>>> screen.exitonclick()
|
Go into mainloop until the mouse is clicked.
|
[
"Go",
"into",
"mainloop",
"until",
"the",
"mouse",
"is",
"clicked",
"."
] |
def exitonclick(self):
"""Go into mainloop until the mouse is clicked.
No arguments.
Bind bye() method to mouseclick on TurtleScreen.
If "using_IDLE" - value in configuration dictionary is False
(default value), enter mainloop.
If IDLE with -n switch (no subprocess) is used, this value should be
set to True in turtle.cfg. In this case IDLE's mainloop
is active also for the client script.
This is a method of the Screen-class and not available for
TurtleScreen instances.
Example (for a Screen instance named screen):
>>> screen.exitonclick()
"""
def exitGracefully(x, y):
"""Screen.bye() with two dummy-parameters"""
self.bye()
self.onclick(exitGracefully)
if _CFG["using_IDLE"]:
return
try:
mainloop()
except AttributeError:
exit(0)
|
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"def",
"exitonclick",
"(",
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")",
":",
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":",
"mainloop",
"(",
")",
"except",
"AttributeError",
":",
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"(",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/turtle.py#L3768-L3796
|
||
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
tools/idl_parser/idl_lexer.py
|
python
|
IDLLexer.t_ELLIPSIS
|
(self, t)
|
return t
|
r'\.\.\.
|
r'\.\.\.
|
[
"r",
"\\",
".",
"\\",
".",
"\\",
"."
] |
def t_ELLIPSIS(self, t):
r'\.\.\.'
return t
|
[
"def",
"t_ELLIPSIS",
"(",
"self",
",",
"t",
")",
":",
"return",
"t"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/idl_parser/idl_lexer.py#L128-L130
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unicode.py
|
python
|
_rfinder
|
(data, substr, start, end)
|
return -1
|
Right finder.
|
Right finder.
|
[
"Right",
"finder",
"."
] |
def _rfinder(data, substr, start, end):
"""Right finder."""
if len(substr) == 0:
return end
for i in range(min(len(data), end) - len(substr), start - 1, -1):
if _cmp_region(data, i, substr, 0, len(substr)) == 0:
return i
return -1
|
[
"def",
"_rfinder",
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"substr",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unicode.py#L590-L597
|
|
miyosuda/TensorFlowAndroidDemo
|
35903e0221aa5f109ea2dbef27f20b52e317f42d
|
jni-build/jni/include/tensorflow/examples/tutorials/mnist/mnist.py
|
python
|
inference
|
(images, hidden1_units, hidden2_units)
|
return logits
|
Build the MNIST model up to where it may be used for inference.
Args:
images: Images placeholder, from inputs().
hidden1_units: Size of the first hidden layer.
hidden2_units: Size of the second hidden layer.
Returns:
softmax_linear: Output tensor with the computed logits.
|
Build the MNIST model up to where it may be used for inference.
|
[
"Build",
"the",
"MNIST",
"model",
"up",
"to",
"where",
"it",
"may",
"be",
"used",
"for",
"inference",
"."
] |
def inference(images, hidden1_units, hidden2_units):
"""Build the MNIST model up to where it may be used for inference.
Args:
images: Images placeholder, from inputs().
hidden1_units: Size of the first hidden layer.
hidden2_units: Size of the second hidden layer.
Returns:
softmax_linear: Output tensor with the computed logits.
"""
# Hidden 1
with tf.name_scope('hidden1'):
weights = tf.Variable(
tf.truncated_normal([IMAGE_PIXELS, hidden1_units],
stddev=1.0 / math.sqrt(float(IMAGE_PIXELS))),
name='weights')
biases = tf.Variable(tf.zeros([hidden1_units]),
name='biases')
hidden1 = tf.nn.relu(tf.matmul(images, weights) + biases)
# Hidden 2
with tf.name_scope('hidden2'):
weights = tf.Variable(
tf.truncated_normal([hidden1_units, hidden2_units],
stddev=1.0 / math.sqrt(float(hidden1_units))),
name='weights')
biases = tf.Variable(tf.zeros([hidden2_units]),
name='biases')
hidden2 = tf.nn.relu(tf.matmul(hidden1, weights) + biases)
# Linear
with tf.name_scope('softmax_linear'):
weights = tf.Variable(
tf.truncated_normal([hidden2_units, NUM_CLASSES],
stddev=1.0 / math.sqrt(float(hidden2_units))),
name='weights')
biases = tf.Variable(tf.zeros([NUM_CLASSES]),
name='biases')
logits = tf.matmul(hidden2, weights) + biases
return logits
|
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"(",
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",",
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https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/tensorflow/examples/tutorials/mnist/mnist.py#L45-L83
|
|
savoirfairelinux/jami-daemon
|
7634487e9f568ae727f2d4cffbb735d23fa0324c
|
tools/jamictrl/controller.py
|
python
|
DRingCtrl.onCallInactive
|
(self, callid, state)
|
Update state for this call to current
|
Update state for this call to current
|
[
"Update",
"state",
"for",
"this",
"call",
"to",
"current"
] |
def onCallInactive(self, callid, state):
""" Update state for this call to current """
self.activeCalls[callid]['State'] = state
self.onCallInactive_cb()
|
[
"def",
"onCallInactive",
"(",
"self",
",",
"callid",
",",
"state",
")",
":",
"self",
".",
"activeCalls",
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"callid",
"]",
"[",
"'State'",
"]",
"=",
"state",
"self",
".",
"onCallInactive_cb",
"(",
")"
] |
https://github.com/savoirfairelinux/jami-daemon/blob/7634487e9f568ae727f2d4cffbb735d23fa0324c/tools/jamictrl/controller.py#L231-L235
|
||
apple/swift-lldb
|
d74be846ef3e62de946df343e8c234bde93a8912
|
scripts/Python/static-binding/lldb.py
|
python
|
SBProcess.GetSelectedThread
|
(self)
|
return _lldb.SBProcess_GetSelectedThread(self)
|
Returns the currently selected thread.
|
[] |
def GetSelectedThread(self):
"""
Returns the currently selected thread.
"""
return _lldb.SBProcess_GetSelectedThread(self)
|
[
"def",
"GetSelectedThread",
"(",
"self",
")",
":",
"return",
"_lldb",
".",
"SBProcess_GetSelectedThread",
"(",
"self",
")"
] |
https://github.com/apple/swift-lldb/blob/d74be846ef3e62de946df343e8c234bde93a8912/scripts/Python/static-binding/lldb.py#L8425-L8430
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/distutils/system_info.py
|
python
|
_c_string_literal
|
(s)
|
return '"{}"'.format(s)
|
Convert a python string into a literal suitable for inclusion into C code
|
Convert a python string into a literal suitable for inclusion into C code
|
[
"Convert",
"a",
"python",
"string",
"into",
"a",
"literal",
"suitable",
"for",
"inclusion",
"into",
"C",
"code"
] |
def _c_string_literal(s):
"""
Convert a python string into a literal suitable for inclusion into C code
"""
# only these three characters are forbidden in C strings
s = s.replace('\\', r'\\')
s = s.replace('"', r'\"')
s = s.replace('\n', r'\n')
return '"{}"'.format(s)
|
[
"def",
"_c_string_literal",
"(",
"s",
")",
":",
"# only these three characters are forbidden in C strings",
"s",
"=",
"s",
".",
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"(",
"'\\\\'",
",",
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",",
"r'\\n'",
")",
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"'\"{}\"'",
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"(",
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] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/distutils/system_info.py#L189-L197
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/lib/agw/speedmeter.py
|
python
|
SpeedMeter.GetIntervalColours
|
(self)
|
Returns the colours for the intervals.
|
Returns the colours for the intervals.
|
[
"Returns",
"the",
"colours",
"for",
"the",
"intervals",
"."
] |
def GetIntervalColours(self):
""" Returns the colours for the intervals."""
if hasattr(self, "_intervalcolours"):
return self._intervalcolours
else:
raise Exception("\nERROR: No Interval Colours Have Been Defined")
|
[
"def",
"GetIntervalColours",
"(",
"self",
")",
":",
"if",
"hasattr",
"(",
"self",
",",
"\"_intervalcolours\"",
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".",
"_intervalcolours",
"else",
":",
"raise",
"Exception",
"(",
"\"\\nERROR: No Interval Colours Have Been Defined\"",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/speedmeter.py#L1232-L1238
|
||
apache/incubator-mxnet
|
f03fb23f1d103fec9541b5ae59ee06b1734a51d9
|
python/mxnet/operator.py
|
python
|
PythonOp.forward
|
(self, in_data, out_data)
|
Forward interface. Override to create new operators.
Parameters
----------
in_data, out_data: list
input and output for forward. See document for
corresponding arguments of Operator::Forward
|
Forward interface. Override to create new operators.
|
[
"Forward",
"interface",
".",
"Override",
"to",
"create",
"new",
"operators",
"."
] |
def forward(self, in_data, out_data):
"""Forward interface. Override to create new operators.
Parameters
----------
in_data, out_data: list
input and output for forward. See document for
corresponding arguments of Operator::Forward
"""
out_data[0][:] = in_data[0]
|
[
"def",
"forward",
"(",
"self",
",",
"in_data",
",",
"out_data",
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":",
"out_data",
"[",
"0",
"]",
"[",
":",
"]",
"=",
"in_data",
"[",
"0",
"]"
] |
https://github.com/apache/incubator-mxnet/blob/f03fb23f1d103fec9541b5ae59ee06b1734a51d9/python/mxnet/operator.py#L80-L89
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/pandas/py2/pandas/core/generic.py
|
python
|
NDFrame._set_axis_name
|
(self, name, axis=0, inplace=False)
|
Set the name(s) of the axis.
Parameters
----------
name : str or list of str
Name(s) to set.
axis : {0 or 'index', 1 or 'columns'}, default 0
The axis to set the label. The value 0 or 'index' specifies index,
and the value 1 or 'columns' specifies columns.
inplace : bool, default False
If `True`, do operation inplace and return None.
.. versionadded:: 0.21.0
Returns
-------
Series, DataFrame, or None
The same type as the caller or `None` if `inplace` is `True`.
See Also
--------
DataFrame.rename : Alter the axis labels of :class:`DataFrame`.
Series.rename : Alter the index labels or set the index name
of :class:`Series`.
Index.rename : Set the name of :class:`Index` or :class:`MultiIndex`.
Examples
--------
>>> df = pd.DataFrame({"num_legs": [4, 4, 2]},
... ["dog", "cat", "monkey"])
>>> df
num_legs
dog 4
cat 4
monkey 2
>>> df._set_axis_name("animal")
num_legs
animal
dog 4
cat 4
monkey 2
>>> df.index = pd.MultiIndex.from_product(
... [["mammal"], ['dog', 'cat', 'monkey']])
>>> df._set_axis_name(["type", "name"])
legs
type name
mammal dog 4
cat 4
monkey 2
|
Set the name(s) of the axis.
|
[
"Set",
"the",
"name",
"(",
"s",
")",
"of",
"the",
"axis",
"."
] |
def _set_axis_name(self, name, axis=0, inplace=False):
"""
Set the name(s) of the axis.
Parameters
----------
name : str or list of str
Name(s) to set.
axis : {0 or 'index', 1 or 'columns'}, default 0
The axis to set the label. The value 0 or 'index' specifies index,
and the value 1 or 'columns' specifies columns.
inplace : bool, default False
If `True`, do operation inplace and return None.
.. versionadded:: 0.21.0
Returns
-------
Series, DataFrame, or None
The same type as the caller or `None` if `inplace` is `True`.
See Also
--------
DataFrame.rename : Alter the axis labels of :class:`DataFrame`.
Series.rename : Alter the index labels or set the index name
of :class:`Series`.
Index.rename : Set the name of :class:`Index` or :class:`MultiIndex`.
Examples
--------
>>> df = pd.DataFrame({"num_legs": [4, 4, 2]},
... ["dog", "cat", "monkey"])
>>> df
num_legs
dog 4
cat 4
monkey 2
>>> df._set_axis_name("animal")
num_legs
animal
dog 4
cat 4
monkey 2
>>> df.index = pd.MultiIndex.from_product(
... [["mammal"], ['dog', 'cat', 'monkey']])
>>> df._set_axis_name(["type", "name"])
legs
type name
mammal dog 4
cat 4
monkey 2
"""
axis = self._get_axis_number(axis)
idx = self._get_axis(axis).set_names(name)
inplace = validate_bool_kwarg(inplace, 'inplace')
renamed = self if inplace else self.copy()
renamed.set_axis(idx, axis=axis, inplace=True)
if not inplace:
return renamed
|
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] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py2/pandas/core/generic.py#L1282-L1341
|
||
gimli-org/gimli
|
17aa2160de9b15ababd9ef99e89b1bc3277bbb23
|
pygimli/physics/em/fdem.py
|
python
|
FDEM.deactivate
|
(self, fr)
|
Deactivate a single frequency.
|
Deactivate a single frequency.
|
[
"Deactivate",
"a",
"single",
"frequency",
"."
] |
def deactivate(self, fr):
"""Deactivate a single frequency."""
fi = np.nonzero(np.absolute(self.frequencies / fr - 1.) < 0.1)
self.isActiveFreq[fi] = False
self.activeFreq = np.nonzero(self.isActiveFreq)[0]
|
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"np",
".",
"nonzero",
"(",
"self",
".",
"isActiveFreq",
")",
"[",
"0",
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] |
https://github.com/gimli-org/gimli/blob/17aa2160de9b15ababd9ef99e89b1bc3277bbb23/pygimli/physics/em/fdem.py#L351-L355
|
||
miyosuda/TensorFlowAndroidMNIST
|
7b5a4603d2780a8a2834575706e9001977524007
|
jni-build/jni/include/tensorflow/contrib/layers/python/layers/target_column.py
|
python
|
_TargetColumn.get_eval_ops
|
(self, features, logits, targets, metrics=None)
|
Returns eval op.
|
Returns eval op.
|
[
"Returns",
"eval",
"op",
"."
] |
def get_eval_ops(self, features, logits, targets, metrics=None):
"""Returns eval op."""
raise NotImplementedError
|
[
"def",
"get_eval_ops",
"(",
"self",
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"features",
",",
"logits",
",",
"targets",
",",
"metrics",
"=",
"None",
")",
":",
"raise",
"NotImplementedError"
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https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/tensorflow/contrib/layers/python/layers/target_column.py#L142-L144
|
||
physercoe/starquant
|
c00cad64d1de2da05081b3dc320ef264c6295e08
|
source/gui/ui_strategy_window.py
|
python
|
CtaManager.load_strategy_class_from_folder
|
(self, path: Path, module_name: str = "", reload: bool = False)
|
Load strategy class from certain folder.
|
Load strategy class from certain folder.
|
[
"Load",
"strategy",
"class",
"from",
"certain",
"folder",
"."
] |
def load_strategy_class_from_folder(self, path: Path, module_name: str = "", reload: bool = False):
"""
Load strategy class from certain folder.
"""
for dirpath, dirnames, filenames in os.walk(path):
for filename in filenames:
if filename.endswith(".py"):
strategy_module_name = "mystrategy.".join(
[module_name, filename.replace(".py", "")])
self.load_strategy_class_from_module(
strategy_module_name, reload)
|
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https://github.com/physercoe/starquant/blob/c00cad64d1de2da05081b3dc320ef264c6295e08/source/gui/ui_strategy_window.py#L59-L69
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/pathlib2/pathlib2/__init__.py
|
python
|
Path.is_block_device
|
(self)
|
Whether this path is a block device.
|
Whether this path is a block device.
|
[
"Whether",
"this",
"path",
"is",
"a",
"block",
"device",
"."
] |
def is_block_device(self):
"""
Whether this path is a block device.
"""
try:
return S_ISBLK(self.stat().st_mode)
except OSError as e:
if not _ignore_error(e):
raise
# Path doesn't exist or is a broken symlink
# (see https://bitbucket.org/pitrou/pathlib/issue/12/)
return False
except ValueError:
# Non-encodable path
return False
|
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pathlib2/pathlib2/__init__.py#L1721-L1735
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/tools/Editra/src/extern/aui/auibar.py
|
python
|
AuiToolBar.SetToolTextOrientation
|
(self, orientation)
|
Sets the label orientation for the toolbar items.
:param integer `orientation`: the :class:`AuiToolBarItem` label orientation.
|
Sets the label orientation for the toolbar items.
|
[
"Sets",
"the",
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"for",
"the",
"toolbar",
"items",
"."
] |
def SetToolTextOrientation(self, orientation):
"""
Sets the label orientation for the toolbar items.
:param integer `orientation`: the :class:`AuiToolBarItem` label orientation.
"""
self._tool_text_orientation = orientation
if self._art:
self._art.SetTextOrientation(orientation)
|
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"_art",
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"SetTextOrientation",
"(",
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/tools/Editra/src/extern/aui/auibar.py#L2367-L2377
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/propgrid.py
|
python
|
PropertyGridPopulator.SetState
|
(*args, **kwargs)
|
return _propgrid.PropertyGridPopulator_SetState(*args, **kwargs)
|
SetState(self, state)
|
SetState(self, state)
|
[
"SetState",
"(",
"self",
"state",
")"
] |
def SetState(*args, **kwargs):
"""SetState(self, state)"""
return _propgrid.PropertyGridPopulator_SetState(*args, **kwargs)
|
[
"def",
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"PropertyGridPopulator_SetState",
"(",
"*",
"args",
",",
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"*",
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")"
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/propgrid.py#L2577-L2579
|
|
miyosuda/TensorFlowAndroidMNIST
|
7b5a4603d2780a8a2834575706e9001977524007
|
jni-build/jni/include/tensorflow/contrib/learn/python/learn/learn_io/data_feeder.py
|
python
|
setup_processor_data_feeder
|
(x)
|
return x
|
Sets up processor iterable.
Args:
x: numpy, pandas or iterable.
Returns:
Iterable of data to process.
|
Sets up processor iterable.
|
[
"Sets",
"up",
"processor",
"iterable",
"."
] |
def setup_processor_data_feeder(x):
"""Sets up processor iterable.
Args:
x: numpy, pandas or iterable.
Returns:
Iterable of data to process.
"""
if HAS_PANDAS:
x = extract_pandas_matrix(x)
return x
|
[
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"(",
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https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/tensorflow/contrib/learn/python/learn/learn_io/data_feeder.py#L162-L173
|
|
arangodb/arangodb
|
0d658689c7d1b721b314fa3ca27d38303e1570c8
|
3rdParty/V8/gyp/generator/cmake.py
|
python
|
RemovePrefix
|
(a, prefix)
|
return a[len(prefix):] if a.startswith(prefix) else a
|
Returns 'a' without 'prefix' if it starts with 'prefix'.
|
Returns 'a' without 'prefix' if it starts with 'prefix'.
|
[
"Returns",
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"without",
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"if",
"it",
"starts",
"with",
"prefix",
"."
] |
def RemovePrefix(a, prefix):
"""Returns 'a' without 'prefix' if it starts with 'prefix'."""
return a[len(prefix):] if a.startswith(prefix) else a
|
[
"def",
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"]",
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"(",
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https://github.com/arangodb/arangodb/blob/0d658689c7d1b721b314fa3ca27d38303e1570c8/3rdParty/V8/gyp/generator/cmake.py#L80-L82
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/tools/python3/src/Lib/pydoc.py
|
python
|
TextDoc.docmodule
|
(self, object, name=None, mod=None)
|
return result
|
Produce text documentation for a given module object.
|
Produce text documentation for a given module object.
|
[
"Produce",
"text",
"documentation",
"for",
"a",
"given",
"module",
"object",
"."
] |
def docmodule(self, object, name=None, mod=None):
"""Produce text documentation for a given module object."""
name = object.__name__ # ignore the passed-in name
synop, desc = splitdoc(getdoc(object))
result = self.section('NAME', name + (synop and ' - ' + synop))
all = getattr(object, '__all__', None)
docloc = self.getdocloc(object)
if docloc is not None:
result = result + self.section('MODULE REFERENCE', docloc + """
The following documentation is automatically generated from the Python
source files. It may be incomplete, incorrect or include features that
are considered implementation detail and may vary between Python
implementations. When in doubt, consult the module reference at the
location listed above.
""")
if desc:
result = result + self.section('DESCRIPTION', desc)
classes = []
for key, value in inspect.getmembers(object, inspect.isclass):
# if __all__ exists, believe it. Otherwise use old heuristic.
if (all is not None
or (inspect.getmodule(value) or object) is object):
if visiblename(key, all, object):
classes.append((key, value))
funcs = []
for key, value in inspect.getmembers(object, inspect.isroutine):
# if __all__ exists, believe it. Otherwise use old heuristic.
if (all is not None or
inspect.isbuiltin(value) or inspect.getmodule(value) is object):
if visiblename(key, all, object):
funcs.append((key, value))
data = []
for key, value in inspect.getmembers(object, isdata):
if visiblename(key, all, object):
data.append((key, value))
modpkgs = []
modpkgs_names = set()
if hasattr(object, '__path__'):
for importer, modname, ispkg in pkgutil.iter_modules(object.__path__):
modpkgs_names.add(modname)
if ispkg:
modpkgs.append(modname + ' (package)')
else:
modpkgs.append(modname)
modpkgs.sort()
result = result + self.section(
'PACKAGE CONTENTS', '\n'.join(modpkgs))
# Detect submodules as sometimes created by C extensions
submodules = []
for key, value in inspect.getmembers(object, inspect.ismodule):
if value.__name__.startswith(name + '.') and key not in modpkgs_names:
submodules.append(key)
if submodules:
submodules.sort()
result = result + self.section(
'SUBMODULES', '\n'.join(submodules))
if classes:
classlist = [value for key, value in classes]
contents = [self.formattree(
inspect.getclasstree(classlist, 1), name)]
for key, value in classes:
contents.append(self.document(value, key, name))
result = result + self.section('CLASSES', '\n'.join(contents))
if funcs:
contents = []
for key, value in funcs:
contents.append(self.document(value, key, name))
result = result + self.section('FUNCTIONS', '\n'.join(contents))
if data:
contents = []
for key, value in data:
contents.append(self.docother(value, key, name, maxlen=70))
result = result + self.section('DATA', '\n'.join(contents))
if hasattr(object, '__version__'):
version = str(object.__version__)
if version[:11] == '$' + 'Revision: ' and version[-1:] == '$':
version = version[11:-1].strip()
result = result + self.section('VERSION', version)
if hasattr(object, '__date__'):
result = result + self.section('DATE', str(object.__date__))
if hasattr(object, '__author__'):
result = result + self.section('AUTHOR', str(object.__author__))
if hasattr(object, '__credits__'):
result = result + self.section('CREDITS', str(object.__credits__))
try:
file = inspect.getabsfile(object)
except TypeError:
file = '(built-in)'
result = result + self.section('FILE', file)
return result
|
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")",
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"try",
":",
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"getabsfile",
"(",
"object",
")",
"except",
"TypeError",
":",
"file",
"=",
"'(built-in)'",
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"+",
"self",
".",
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"(",
"'FILE'",
",",
"file",
")",
"return",
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] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/pydoc.py#L1199-L1298
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/_misc.py
|
python
|
TimeSpan.Second
|
(*args, **kwargs)
|
return _misc_.TimeSpan_Second(*args, **kwargs)
|
Second() -> TimeSpan
|
Second() -> TimeSpan
|
[
"Second",
"()",
"-",
">",
"TimeSpan"
] |
def Second(*args, **kwargs):
"""Second() -> TimeSpan"""
return _misc_.TimeSpan_Second(*args, **kwargs)
|
[
"def",
"Second",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_misc_",
".",
"TimeSpan_Second",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_misc.py#L4364-L4366
|
|
apple/turicreate
|
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
|
src/python/turicreate/data_structures/sarray.py
|
python
|
SArray.head
|
(self, n=10)
|
return SArray(_proxy=self.__proxy__.head(n))
|
Returns an SArray which contains the first n rows of this SArray.
Parameters
----------
n : int
The number of rows to fetch.
Returns
-------
out : SArray
A new SArray which contains the first n rows of the current SArray.
Examples
--------
>>> tc.SArray(range(10)).head(5)
dtype: int
Rows: 5
[0, 1, 2, 3, 4]
|
Returns an SArray which contains the first n rows of this SArray.
|
[
"Returns",
"an",
"SArray",
"which",
"contains",
"the",
"first",
"n",
"rows",
"of",
"this",
"SArray",
"."
] |
def head(self, n=10):
"""
Returns an SArray which contains the first n rows of this SArray.
Parameters
----------
n : int
The number of rows to fetch.
Returns
-------
out : SArray
A new SArray which contains the first n rows of the current SArray.
Examples
--------
>>> tc.SArray(range(10)).head(5)
dtype: int
Rows: 5
[0, 1, 2, 3, 4]
"""
return SArray(_proxy=self.__proxy__.head(n))
|
[
"def",
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"__proxy__",
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"head",
"(",
"n",
")",
")"
] |
https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/src/python/turicreate/data_structures/sarray.py#L1471-L1492
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/msw/combo.py
|
python
|
ComboPopup.OnComboCharEvent
|
(*args, **kwargs)
|
return _combo.ComboPopup_OnComboCharEvent(*args, **kwargs)
|
OnComboCharEvent(self, KeyEvent event)
|
OnComboCharEvent(self, KeyEvent event)
|
[
"OnComboCharEvent",
"(",
"self",
"KeyEvent",
"event",
")"
] |
def OnComboCharEvent(*args, **kwargs):
"""OnComboCharEvent(self, KeyEvent event)"""
return _combo.ComboPopup_OnComboCharEvent(*args, **kwargs)
|
[
"def",
"OnComboCharEvent",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
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".",
"ComboPopup_OnComboCharEvent",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/combo.py#L708-L710
|
|
google/syzygy
|
8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5
|
third_party/numpy/files/numpy/polynomial/polynomial.py
|
python
|
polyval
|
(x, cs)
|
return c0
|
Evaluate a polynomial.
If `cs` is of length `n`, this function returns :
``p(x) = cs[0] + cs[1]*x + ... + cs[n-1]*x**(n-1)``
If x is a sequence or array then p(x) will have the same shape as x.
If r is a ring_like object that supports multiplication and addition
by the values in `cs`, then an object of the same type is returned.
Parameters
----------
x : array_like, ring_like
If x is a list or tuple, it is converted to an ndarray. Otherwise
it must support addition and multiplication with itself and the
elements of `cs`.
cs : array_like
1-d array of Chebyshev coefficients ordered from low to high.
Returns
-------
values : ndarray
The return array has the same shape as `x`.
See Also
--------
polyfit
Notes
-----
The evaluation uses Horner's method.
|
Evaluate a polynomial.
|
[
"Evaluate",
"a",
"polynomial",
"."
] |
def polyval(x, cs):
"""
Evaluate a polynomial.
If `cs` is of length `n`, this function returns :
``p(x) = cs[0] + cs[1]*x + ... + cs[n-1]*x**(n-1)``
If x is a sequence or array then p(x) will have the same shape as x.
If r is a ring_like object that supports multiplication and addition
by the values in `cs`, then an object of the same type is returned.
Parameters
----------
x : array_like, ring_like
If x is a list or tuple, it is converted to an ndarray. Otherwise
it must support addition and multiplication with itself and the
elements of `cs`.
cs : array_like
1-d array of Chebyshev coefficients ordered from low to high.
Returns
-------
values : ndarray
The return array has the same shape as `x`.
See Also
--------
polyfit
Notes
-----
The evaluation uses Horner's method.
"""
# cs is a trimmed copy
[cs] = pu.as_series([cs])
if isinstance(x, tuple) or isinstance(x, list) :
x = np.asarray(x)
c0 = cs[-1] + x*0
for i in range(2, len(cs) + 1) :
c0 = cs[-i] + c0*x
return c0
|
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"def",
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"# cs is a trimmed copy",
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"[",
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] |
https://github.com/google/syzygy/blob/8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5/third_party/numpy/files/numpy/polynomial/polynomial.py#L612-L655
|
|
hughperkins/tf-coriander
|
970d3df6c11400ad68405f22b0c42a52374e94ca
|
tensorflow/python/ops/data_flow_ops.py
|
python
|
SparseConditionalAccumulator.take_grad
|
(self, num_required, name=None)
|
return gen_data_flow_ops.sparse_accumulator_take_gradient(
self._accumulator_ref, num_required, dtype=self._dtype, name=name)
|
Attempts to extract the average gradient from the accumulator.
The operation blocks until sufficient number of gradients have been
successfully applied to the accumulator.
Once successful, the following actions are also triggered:
- Counter of accumulated gradients is reset to 0.
- Aggregated gradient is reset to 0 tensor.
- Accumulator's internal time step is incremented by 1.
Args:
num_required: Number of gradients that needs to have been aggregated
name: Optional name for the operation
Returns:
A tuple of indices, values, and shape representing the average gradient.
Raises:
InvalidArgumentError: If num_required < 1
|
Attempts to extract the average gradient from the accumulator.
|
[
"Attempts",
"to",
"extract",
"the",
"average",
"gradient",
"from",
"the",
"accumulator",
"."
] |
def take_grad(self, num_required, name=None):
"""Attempts to extract the average gradient from the accumulator.
The operation blocks until sufficient number of gradients have been
successfully applied to the accumulator.
Once successful, the following actions are also triggered:
- Counter of accumulated gradients is reset to 0.
- Aggregated gradient is reset to 0 tensor.
- Accumulator's internal time step is incremented by 1.
Args:
num_required: Number of gradients that needs to have been aggregated
name: Optional name for the operation
Returns:
A tuple of indices, values, and shape representing the average gradient.
Raises:
InvalidArgumentError: If num_required < 1
"""
return gen_data_flow_ops.sparse_accumulator_take_gradient(
self._accumulator_ref, num_required, dtype=self._dtype, name=name)
|
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",",
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https://github.com/hughperkins/tf-coriander/blob/970d3df6c11400ad68405f22b0c42a52374e94ca/tensorflow/python/ops/data_flow_ops.py#L1402-L1424
|
|
cksystemsgroup/scal
|
fa2208a97a77d65f4e90f85fef3404c27c1f2ac2
|
tools/cpplint.py
|
python
|
Search
|
(pattern, s)
|
return _regexp_compile_cache[pattern].search(s)
|
Searches the string for the pattern, caching the compiled regexp.
|
Searches the string for the pattern, caching the compiled regexp.
|
[
"Searches",
"the",
"string",
"for",
"the",
"pattern",
"caching",
"the",
"compiled",
"regexp",
"."
] |
def Search(pattern, s):
"""Searches the string for the pattern, caching the compiled regexp."""
if pattern not in _regexp_compile_cache:
_regexp_compile_cache[pattern] = sre_compile.compile(pattern)
return _regexp_compile_cache[pattern].search(s)
|
[
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")",
"return",
"_regexp_compile_cache",
"[",
"pattern",
"]",
".",
"search",
"(",
"s",
")"
] |
https://github.com/cksystemsgroup/scal/blob/fa2208a97a77d65f4e90f85fef3404c27c1f2ac2/tools/cpplint.py#L585-L589
|
|
openweave/openweave-core
|
11ceb6b7efd39fe05de7f79229247a5774d56766
|
src/device-manager/python/openweave/WeaveCoreBluetoothMgr.py
|
python
|
CoreBluetoothManager.peripheral_didDiscoverServices_
|
(self, peripheral, services)
|
Called by CoreBluetooth via runloop when peripheral services are discovered.
|
Called by CoreBluetooth via runloop when peripheral services are discovered.
|
[
"Called",
"by",
"CoreBluetooth",
"via",
"runloop",
"when",
"peripheral",
"services",
"are",
"discovered",
"."
] |
def peripheral_didDiscoverServices_(self, peripheral, services):
"""Called by CoreBluetooth via runloop when peripheral services are discovered."""
if len(self.peripheral.services()) == 0:
self.logger.error("Weave service not found")
self.connect_state = False
else:
# in debugging, we found connect being called twice. This
# would trigger discovering the services twice, and
# consequently, discovering characteristics twice. We use the
# self.service as a flag to indicate whether the
# characteristics need to be invalidated immediately.
if (self.service == self.peripheral.services()[0]):
self.logger.debug("didDiscoverServices already happened")
else:
self.service = self.peripheral.services()[0]
self.characteristics[self.service.UUID()] = []
# NOTE: currently limiting discovery to only the pair of Weave characteristics.
self.peripheral.discoverCharacteristics_forService_([weave_rx, weave_tx], self.service)
|
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https://github.com/openweave/openweave-core/blob/11ceb6b7efd39fe05de7f79229247a5774d56766/src/device-manager/python/openweave/WeaveCoreBluetoothMgr.py#L271-L288
|
||
PaddlePaddle/Paddle
|
1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c
|
python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/sharding_optimizer_stage2.py
|
python
|
ShardingOptimizerStage2.step
|
(self)
|
A wrapper for Optimizer's step function to finish the update operation of the optimizer.
|
A wrapper for Optimizer's step function to finish the update operation of the optimizer.
|
[
"A",
"wrapper",
"for",
"Optimizer",
"s",
"step",
"function",
"to",
"finish",
"the",
"update",
"operation",
"of",
"the",
"optimizer",
"."
] |
def step(self):
"""
A wrapper for Optimizer's step function to finish the update operation of the optimizer.
"""
if self.offload:
params_list = [self.offload_params.buffer]
#TODO(Baibaifan): Offload will support param_groups later
if not isinstance(self._optim._param_groups[0], dict):
self._optim._parameter_list = params_list
self._optim._param_groups = params_list
# Run the optimizer of the current rank step
if self.offload:
with device_guard(device=self.offload_device):
self._optim.step()
dev_id = int(paddle.get_device().split(":")[1])
for param in self._local_params:
if param.name in self._master_params.keys():
param.set_value(self._master_params[param.name].cuda(dev_id)
.cast(dtype=param.dtype))
else:
self._optim.step()
# Synchronize all the updated shards in between the ranks
self._broadcast_params()
|
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] |
https://github.com/PaddlePaddle/Paddle/blob/1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c/python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/sharding_optimizer_stage2.py#L337-L364
|
||
ycm-core/ycmd
|
fc0fb7e5e15176cc5a2a30c80956335988c6b59a
|
ycmd/completers/language_server/language_server_protocol.py
|
python
|
ServerFileState.GetDirtyFileAction
|
( self, contents )
|
return self._SendNewVersion( new_checksum, action, contents )
|
Progress the state for a file to be updated due to being supplied in the
dirty buffers list. Returns any one of the Actions to perform.
|
Progress the state for a file to be updated due to being supplied in the
dirty buffers list. Returns any one of the Actions to perform.
|
[
"Progress",
"the",
"state",
"for",
"a",
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"to",
"be",
"updated",
"due",
"to",
"being",
"supplied",
"in",
"the",
"dirty",
"buffers",
"list",
".",
"Returns",
"any",
"one",
"of",
"the",
"Actions",
"to",
"perform",
"."
] |
def GetDirtyFileAction( self, contents ):
"""Progress the state for a file to be updated due to being supplied in the
dirty buffers list. Returns any one of the Actions to perform."""
new_checksum = self._CalculateCheckSum( contents )
if ( self.state == ServerFileState.OPEN and
self.checksum.digest() == new_checksum.digest() ):
return ServerFileState.NO_ACTION
elif self.state == ServerFileState.CLOSED:
self.version = 0
action = ServerFileState.OPEN_FILE
else:
action = ServerFileState.CHANGE_FILE
return self._SendNewVersion( new_checksum, action, contents )
|
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"=",
"ServerFileState",
".",
"CHANGE_FILE",
"return",
"self",
".",
"_SendNewVersion",
"(",
"new_checksum",
",",
"action",
",",
"contents",
")"
] |
https://github.com/ycm-core/ycmd/blob/fc0fb7e5e15176cc5a2a30c80956335988c6b59a/ycmd/completers/language_server/language_server_protocol.py#L178-L192
|
|
pmq20/node-packer
|
12c46c6e44fbc14d9ee645ebd17d5296b324f7e0
|
lts/tools/gyp/pylib/gyp/xcode_emulation.py
|
python
|
XcodeSettings.GetWrapperExtension
|
(self)
|
Returns the bundle extension (.app, .framework, .plugin, etc). Only
valid for bundles.
|
Returns the bundle extension (.app, .framework, .plugin, etc). Only
valid for bundles.
|
[
"Returns",
"the",
"bundle",
"extension",
"(",
".",
"app",
".",
"framework",
".",
"plugin",
"etc",
")",
".",
"Only",
"valid",
"for",
"bundles",
"."
] |
def GetWrapperExtension(self):
"""Returns the bundle extension (.app, .framework, .plugin, etc). Only
valid for bundles."""
assert self._IsBundle()
if self.spec['type'] in ('loadable_module', 'shared_library'):
default_wrapper_extension = {
'loadable_module': 'bundle',
'shared_library': 'framework',
}[self.spec['type']]
wrapper_extension = self.GetPerTargetSetting(
'WRAPPER_EXTENSION', default=default_wrapper_extension)
return '.' + self.spec.get('product_extension', wrapper_extension)
elif self.spec['type'] == 'executable':
if self._IsIosAppExtension() or self._IsIosWatchKitExtension():
return '.' + self.spec.get('product_extension', 'appex')
else:
return '.' + self.spec.get('product_extension', 'app')
else:
assert False, "Don't know extension for '%s', target '%s'" % (
self.spec['type'], self.spec['target_name'])
|
[
"def",
"GetWrapperExtension",
"(",
"self",
")",
":",
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"_IsBundle",
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"'loadable_module'",
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"'product_extension'",
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"'appex'",
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"'product_extension'",
",",
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"assert",
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",",
"\"Don't know extension for '%s', target '%s'\"",
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"(",
"self",
".",
"spec",
"[",
"'type'",
"]",
",",
"self",
".",
"spec",
"[",
"'target_name'",
"]",
")"
] |
https://github.com/pmq20/node-packer/blob/12c46c6e44fbc14d9ee645ebd17d5296b324f7e0/lts/tools/gyp/pylib/gyp/xcode_emulation.py#L260-L279
|
||
crosslife/OpenBird
|
9e0198a1a2295f03fa1e8676e216e22c9c7d380b
|
cocos2d/tools/bindings-generator/backup/clang-llvm-3.3-pybinding/cindex.py
|
python
|
Type.get_size
|
(self)
|
return conf.lib.clang_Type_getSizeOf(self)
|
Retrieve the size of the record.
|
Retrieve the size of the record.
|
[
"Retrieve",
"the",
"size",
"of",
"the",
"record",
"."
] |
def get_size(self):
"""
Retrieve the size of the record.
"""
return conf.lib.clang_Type_getSizeOf(self)
|
[
"def",
"get_size",
"(",
"self",
")",
":",
"return",
"conf",
".",
"lib",
".",
"clang_Type_getSizeOf",
"(",
"self",
")"
] |
https://github.com/crosslife/OpenBird/blob/9e0198a1a2295f03fa1e8676e216e22c9c7d380b/cocos2d/tools/bindings-generator/backup/clang-llvm-3.3-pybinding/cindex.py#L1634-L1638
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/_core.py
|
python
|
PyApp.ProcessPendingEvents
|
(*args, **kwargs)
|
return _core_.PyApp_ProcessPendingEvents(*args, **kwargs)
|
ProcessPendingEvents(self)
Process all events in the Pending Events list -- it is necessary to
call this function to process posted events. This normally happens
during each event loop iteration.
|
ProcessPendingEvents(self)
|
[
"ProcessPendingEvents",
"(",
"self",
")"
] |
def ProcessPendingEvents(*args, **kwargs):
"""
ProcessPendingEvents(self)
Process all events in the Pending Events list -- it is necessary to
call this function to process posted events. This normally happens
during each event loop iteration.
"""
return _core_.PyApp_ProcessPendingEvents(*args, **kwargs)
|
[
"def",
"ProcessPendingEvents",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_core_",
".",
"PyApp_ProcessPendingEvents",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_core.py#L7858-L7866
|
|
avast/retdec
|
b9879088a5f0278508185ec645494e6c5c57a455
|
scripts/type_extractor/type_extractor/io.py
|
python
|
print_types_info_lti
|
(f_out, functions, types, structs, unions, enums, indent=0)
|
Lti output for types and functions.
|
Lti output for types and functions.
|
[
"Lti",
"output",
"for",
"types",
"and",
"functions",
"."
] |
def print_types_info_lti(f_out, functions, types, structs, unions, enums, indent=0):
"""Lti output for types and functions."""
for sname, sinfo in sorted(structs.items()):
lti = '%struct.' + sname + ' = type { '
lti = lti + ', '.join([str_types_sub(members.type_text, members.name_text)
for members in sinfo.members_list])
lti = lti + ' }\n'
f_out.write(lti)
for fname, f_info in sorted(functions.items()):
lti_1 = f_info.name_text+' '+str_types_sub(f_info.ret_type_text, '')
lti_2 = ' ' + str(len(f_info.params_list)) + ' '
lti_3 = ', '.join([str_types_sub(param.type_text, param.name_text)
for param in f_info.params_list])
lti_4 = ' # ' + f_info.decl
lti = lti_1 + lti_2 + lti_3 + lti_4
f_out.write(lti + '\n')
|
[
"def",
"print_types_info_lti",
"(",
"f_out",
",",
"functions",
",",
"types",
",",
"structs",
",",
"unions",
",",
"enums",
",",
"indent",
"=",
"0",
")",
":",
"for",
"sname",
",",
"sinfo",
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"(",
"structs",
".",
"items",
"(",
")",
")",
":",
"lti",
"=",
"'%struct.'",
"+",
"sname",
"+",
"' = type { '",
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"lti",
"+",
"', '",
".",
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"[",
"str_types_sub",
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"type_text",
",",
"members",
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"name_text",
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"members_list",
"]",
")",
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"=",
"lti",
"+",
"' }\\n'",
"f_out",
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"write",
"(",
"lti",
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",",
"f_info",
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"functions",
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"(",
")",
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":",
"lti_1",
"=",
"f_info",
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"+",
"' '",
"+",
"str_types_sub",
"(",
"f_info",
".",
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",",
"''",
")",
"lti_2",
"=",
"' '",
"+",
"str",
"(",
"len",
"(",
"f_info",
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"' '",
"lti_3",
"=",
"', '",
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"(",
"[",
"str_types_sub",
"(",
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"type_text",
",",
"param",
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"for",
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"params_list",
"]",
")",
"lti_4",
"=",
"' # '",
"+",
"f_info",
".",
"decl",
"lti",
"=",
"lti_1",
"+",
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"+",
"lti_3",
"+",
"lti_4",
"f_out",
".",
"write",
"(",
"lti",
"+",
"'\\n'",
")"
] |
https://github.com/avast/retdec/blob/b9879088a5f0278508185ec645494e6c5c57a455/scripts/type_extractor/type_extractor/io.py#L95-L111
|
||
plumonito/dtslam
|
5994bb9cf7a11981b830370db206bceb654c085d
|
3rdparty/opencv-git/3rdparty/jinja2/parser.py
|
python
|
Parser.fail_unknown_tag
|
(self, name, lineno=None)
|
return self._fail_ut_eof(name, self._end_token_stack, lineno)
|
Called if the parser encounters an unknown tag. Tries to fail
with a human readable error message that could help to identify
the problem.
|
Called if the parser encounters an unknown tag. Tries to fail
with a human readable error message that could help to identify
the problem.
|
[
"Called",
"if",
"the",
"parser",
"encounters",
"an",
"unknown",
"tag",
".",
"Tries",
"to",
"fail",
"with",
"a",
"human",
"readable",
"error",
"message",
"that",
"could",
"help",
"to",
"identify",
"the",
"problem",
"."
] |
def fail_unknown_tag(self, name, lineno=None):
"""Called if the parser encounters an unknown tag. Tries to fail
with a human readable error message that could help to identify
the problem.
"""
return self._fail_ut_eof(name, self._end_token_stack, lineno)
|
[
"def",
"fail_unknown_tag",
"(",
"self",
",",
"name",
",",
"lineno",
"=",
"None",
")",
":",
"return",
"self",
".",
"_fail_ut_eof",
"(",
"name",
",",
"self",
".",
"_end_token_stack",
",",
"lineno",
")"
] |
https://github.com/plumonito/dtslam/blob/5994bb9cf7a11981b830370db206bceb654c085d/3rdparty/opencv-git/3rdparty/jinja2/parser.py#L84-L89
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/urllib3/util/wait.py
|
python
|
_wait_for_io_events
|
(socks, events, timeout=None)
|
Waits for IO events to be available from a list of sockets
or optionally a single socket if passed in. Returns a list of
sockets that can be interacted with immediately.
|
Waits for IO events to be available from a list of sockets
or optionally a single socket if passed in. Returns a list of
sockets that can be interacted with immediately.
|
[
"Waits",
"for",
"IO",
"events",
"to",
"be",
"available",
"from",
"a",
"list",
"of",
"sockets",
"or",
"optionally",
"a",
"single",
"socket",
"if",
"passed",
"in",
".",
"Returns",
"a",
"list",
"of",
"sockets",
"that",
"can",
"be",
"interacted",
"with",
"immediately",
"."
] |
def _wait_for_io_events(socks, events, timeout=None):
""" Waits for IO events to be available from a list of sockets
or optionally a single socket if passed in. Returns a list of
sockets that can be interacted with immediately. """
if not HAS_SELECT:
raise ValueError('Platform does not have a selector')
if not isinstance(socks, list):
# Probably just a single socket.
if hasattr(socks, "fileno"):
socks = [socks]
# Otherwise it might be a non-list iterable.
else:
socks = list(socks)
with DefaultSelector() as selector:
for sock in socks:
selector.register(sock, events)
return [key[0].fileobj for key in
selector.select(timeout) if key[1] & events]
|
[
"def",
"_wait_for_io_events",
"(",
"socks",
",",
"events",
",",
"timeout",
"=",
"None",
")",
":",
"if",
"not",
"HAS_SELECT",
":",
"raise",
"ValueError",
"(",
"'Platform does not have a selector'",
")",
"if",
"not",
"isinstance",
"(",
"socks",
",",
"list",
")",
":",
"# Probably just a single socket.",
"if",
"hasattr",
"(",
"socks",
",",
"\"fileno\"",
")",
":",
"socks",
"=",
"[",
"socks",
"]",
"# Otherwise it might be a non-list iterable.",
"else",
":",
"socks",
"=",
"list",
"(",
"socks",
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"with",
"DefaultSelector",
"(",
")",
"as",
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"sock",
",",
"events",
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"return",
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"key",
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"0",
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".",
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"selector",
".",
"select",
"(",
"timeout",
")",
"if",
"key",
"[",
"1",
"]",
"&",
"events",
"]"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/urllib3/util/wait.py#L9-L26
|
||
Samsung/veles
|
95ed733c2e49bc011ad98ccf2416ecec23fbf352
|
veles/result_provider.py
|
python
|
IResultProvider.get_metric_values
|
()
|
:return The measurable results of model's execution, e.g., accuracy,
number of errors, RMSE, etc. Technically, they are a dictionary of
metric names (as returned by get_metric_names()) and achieved values.
|
:return The measurable results of model's execution, e.g., accuracy,
number of errors, RMSE, etc. Technically, they are a dictionary of
metric names (as returned by get_metric_names()) and achieved values.
|
[
":",
"return",
"The",
"measurable",
"results",
"of",
"model",
"s",
"execution",
"e",
".",
"g",
".",
"accuracy",
"number",
"of",
"errors",
"RMSE",
"etc",
".",
"Technically",
"they",
"are",
"a",
"dictionary",
"of",
"metric",
"names",
"(",
"as",
"returned",
"by",
"get_metric_names",
"()",
")",
"and",
"achieved",
"values",
"."
] |
def get_metric_values():
"""
:return The measurable results of model's execution, e.g., accuracy,
number of errors, RMSE, etc. Technically, they are a dictionary of
metric names (as returned by get_metric_names()) and achieved values.
"""
|
[
"def",
"get_metric_values",
"(",
")",
":"
] |
https://github.com/Samsung/veles/blob/95ed733c2e49bc011ad98ccf2416ecec23fbf352/veles/result_provider.py#L48-L53
|
||
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/framework/func_graph.py
|
python
|
FuncGraph.reset_captures
|
(self, capture_list)
|
Set the captures with the provided list of captures & placeholder.
|
Set the captures with the provided list of captures & placeholder.
|
[
"Set",
"the",
"captures",
"with",
"the",
"provided",
"list",
"of",
"captures",
"&",
"placeholder",
"."
] |
def reset_captures(self, capture_list):
"""Set the captures with the provided list of captures & placeholder."""
self._captures = py_collections.OrderedDict()
for tensor, placeholder in capture_list:
self._captures[ops.tensor_id(tensor)] = (tensor, placeholder)
|
[
"def",
"reset_captures",
"(",
"self",
",",
"capture_list",
")",
":",
"self",
".",
"_captures",
"=",
"py_collections",
".",
"OrderedDict",
"(",
")",
"for",
"tensor",
",",
"placeholder",
"in",
"capture_list",
":",
"self",
".",
"_captures",
"[",
"ops",
".",
"tensor_id",
"(",
"tensor",
")",
"]",
"=",
"(",
"tensor",
",",
"placeholder",
")"
] |
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/framework/func_graph.py#L635-L639
|
||
openweave/openweave-core
|
11ceb6b7efd39fe05de7f79229247a5774d56766
|
src/device-manager/python/openweave/WeaveBleBase.py
|
python
|
WeaveBleBase.GetBleEvent
|
(self)
|
return
|
Called by WeaveDeviceMgr.py on behalf of Weave to retrieve a queued message.
|
Called by WeaveDeviceMgr.py on behalf of Weave to retrieve a queued message.
|
[
"Called",
"by",
"WeaveDeviceMgr",
".",
"py",
"on",
"behalf",
"of",
"Weave",
"to",
"retrieve",
"a",
"queued",
"message",
"."
] |
def GetBleEvent(self):
""" Called by WeaveDeviceMgr.py on behalf of Weave to retrieve a queued message."""
return
|
[
"def",
"GetBleEvent",
"(",
"self",
")",
":",
"return"
] |
https://github.com/openweave/openweave-core/blob/11ceb6b7efd39fe05de7f79229247a5774d56766/src/device-manager/python/openweave/WeaveBleBase.py#L67-L69
|
|
msitt/blpapi-python
|
bebcf43668c9e5f5467b1f685f9baebbfc45bc87
|
src/blpapi/name.py
|
python
|
Name.__str__
|
(self)
|
return internals.blpapi_Name_string(self.__handle)
|
x.__str__() <==> str(x)
Return a string that this Name represents.
|
x.__str__() <==> str(x)
|
[
"x",
".",
"__str__",
"()",
"<",
"==",
">",
"str",
"(",
"x",
")"
] |
def __str__(self):
"""x.__str__() <==> str(x)
Return a string that this Name represents.
"""
return internals.blpapi_Name_string(self.__handle)
|
[
"def",
"__str__",
"(",
"self",
")",
":",
"return",
"internals",
".",
"blpapi_Name_string",
"(",
"self",
".",
"__handle",
")"
] |
https://github.com/msitt/blpapi-python/blob/bebcf43668c9e5f5467b1f685f9baebbfc45bc87/src/blpapi/name.py#L94-L101
|
|
google/llvm-propeller
|
45c226984fe8377ebfb2ad7713c680d652ba678d
|
openmp/runtime/tools/summarizeStats.py
|
python
|
setRadarFigure
|
(titles)
|
return {'ax':ax, 'theta':theta}
|
Set the attributes for the radar plots
|
Set the attributes for the radar plots
|
[
"Set",
"the",
"attributes",
"for",
"the",
"radar",
"plots"
] |
def setRadarFigure(titles):
"""Set the attributes for the radar plots"""
fig = plt.figure(figsize=(9,9))
rect = [0.1, 0.1, 0.8, 0.8]
labels = [0.2, 0.4, 0.6, 0.8, 1, 2, 3, 4, 5, 10]
matplotlib.rcParams.update({'font.size':13})
theta = radar_factory(len(titles))
ax = fig.add_axes(rect, projection='radar')
ax.set_rgrids(labels)
ax.set_varlabels(titles)
ax.text(theta[2], 1, "Linear->Log", horizontalalignment='center', color='green', fontsize=18)
return {'ax':ax, 'theta':theta}
|
[
"def",
"setRadarFigure",
"(",
"titles",
")",
":",
"fig",
"=",
"plt",
".",
"figure",
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"figsize",
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",",
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"rect",
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"[",
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] |
https://github.com/google/llvm-propeller/blob/45c226984fe8377ebfb2ad7713c680d652ba678d/openmp/runtime/tools/summarizeStats.py#L177-L188
|
|
arkenthera/electron-vibrancy
|
383153ef9ccb23a6c7517150d6bb0794dff3115e
|
scripts/cpplint.py
|
python
|
_BlockInfo.CheckBegin
|
(self, filename, clean_lines, linenum, error)
|
Run checks that applies to text up to the opening brace.
This is mostly for checking the text after the class identifier
and the "{", usually where the base class is specified. For other
blocks, there isn't much to check, so we always pass.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
|
Run checks that applies to text up to the opening brace.
|
[
"Run",
"checks",
"that",
"applies",
"to",
"text",
"up",
"to",
"the",
"opening",
"brace",
"."
] |
def CheckBegin(self, filename, clean_lines, linenum, error):
"""Run checks that applies to text up to the opening brace.
This is mostly for checking the text after the class identifier
and the "{", usually where the base class is specified. For other
blocks, there isn't much to check, so we always pass.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
"""
pass
|
[
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",",
"filename",
",",
"clean_lines",
",",
"linenum",
",",
"error",
")",
":",
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] |
https://github.com/arkenthera/electron-vibrancy/blob/383153ef9ccb23a6c7517150d6bb0794dff3115e/scripts/cpplint.py#L1778-L1791
|
||
google/syzygy
|
8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5
|
third_party/numpy/files/numpy/oldnumeric/ma.py
|
python
|
MaskedArray.__add__
|
(self, other)
|
return add(self, other)
|
Return add(self, other)
|
Return add(self, other)
|
[
"Return",
"add",
"(",
"self",
"other",
")"
] |
def __add__(self, other):
"Return add(self, other)"
return add(self, other)
|
[
"def",
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"(",
"self",
",",
"other",
")",
":",
"return",
"add",
"(",
"self",
",",
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")"
] |
https://github.com/google/syzygy/blob/8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5/third_party/numpy/files/numpy/oldnumeric/ma.py#L899-L901
|
|
FreeCAD/FreeCAD
|
ba42231b9c6889b89e064d6d563448ed81e376ec
|
src/Mod/Draft/draftguitools/gui_polygons.py
|
python
|
Polygon.action
|
(self, arg)
|
Handle the 3D scene events.
This is installed as an EventCallback in the Inventor view.
Parameters
----------
arg: dict
Dictionary with strings that indicates the type of event received
from the 3D view.
|
Handle the 3D scene events.
|
[
"Handle",
"the",
"3D",
"scene",
"events",
"."
] |
def action(self, arg):
"""Handle the 3D scene events.
This is installed as an EventCallback in the Inventor view.
Parameters
----------
arg: dict
Dictionary with strings that indicates the type of event received
from the 3D view.
"""
import DraftGeomUtils
if arg["Type"] == "SoKeyboardEvent":
if arg["Key"] == "ESCAPE":
self.finish()
elif arg["Type"] == "SoLocation2Event": # mouse movement detection
self.point, ctrlPoint, info = gui_tool_utils.getPoint(self, arg)
# this is to make sure radius is what you see on screen
if self.center and DraftVecUtils.dist(self.point, self.center) > 0:
viewdelta = DraftVecUtils.project(self.point.sub(self.center),
App.DraftWorkingPlane.axis)
if not DraftVecUtils.isNull(viewdelta):
self.point = self.point.add(viewdelta.negative())
if self.step == 0: # choose center
if gui_tool_utils.hasMod(arg, gui_tool_utils.MODALT):
if not self.altdown:
self.altdown = True
self.ui.switchUi(True)
else:
if self.altdown:
self.altdown = False
self.ui.switchUi(False)
else: # choose radius
if len(self.tangents) == 2:
cir = DraftGeomUtils.circleFrom2tan1pt(self.tangents[0],
self.tangents[1],
self.point)
_c = DraftGeomUtils.findClosestCircle(self.point, cir)
self.center = _c.Center
self.arctrack.setCenter(self.center)
elif self.tangents and self.tanpoints:
cir = DraftGeomUtils.circleFrom1tan2pt(self.tangents[0],
self.tanpoints[0],
self.point)
_c = DraftGeomUtils.findClosestCircle(self.point, cir)
self.center = _c.Center
self.arctrack.setCenter(self.center)
if gui_tool_utils.hasMod(arg, gui_tool_utils.MODALT):
if not self.altdown:
self.altdown = True
snapped = self.view.getObjectInfo((arg["Position"][0],
arg["Position"][1]))
if snapped:
ob = self.doc.getObject(snapped['Object'])
num = int(snapped['Component'].lstrip('Edge')) - 1
ed = ob.Shape.Edges[num]
if len(self.tangents) == 2:
cir = DraftGeomUtils.circleFrom3tan(self.tangents[0],
self.tangents[1],
ed)
cl = DraftGeomUtils.findClosestCircle(self.point, cir)
self.center = cl.Center
self.rad = cl.Radius
self.arctrack.setCenter(self.center)
else:
self.rad = self.center.add(DraftGeomUtils.findDistance(self.center,ed).sub(self.center)).Length
else:
self.rad = DraftVecUtils.dist(self.point, self.center)
else:
if self.altdown:
self.altdown = False
self.rad = DraftVecUtils.dist(self.point, self.center)
self.ui.setRadiusValue(self.rad, 'Length')
self.arctrack.setRadius(self.rad)
gui_tool_utils.redraw3DView()
elif (arg["Type"] == "SoMouseButtonEvent"
and arg["State"] == "DOWN"
and arg["Button"] == "BUTTON1"): # mouse click
if self.point:
if self.step == 0: # choose center
if (not self.node) and (not self.support):
gui_tool_utils.getSupport(arg)
(self.point,
ctrlPoint, info) = gui_tool_utils.getPoint(self, arg)
if gui_tool_utils.hasMod(arg, gui_tool_utils.MODALT):
snapped = self.view.getObjectInfo((arg["Position"][0],
arg["Position"][1]))
if snapped:
ob = self.doc.getObject(snapped['Object'])
num = int(snapped['Component'].lstrip('Edge')) - 1
ed = ob.Shape.Edges[num]
self.tangents.append(ed)
if len(self.tangents) == 2:
self.arctrack.on()
self.ui.radiusUi()
self.step = 1
_msg(translate("draft", "Pick radius"))
else:
if len(self.tangents) == 1:
self.tanpoints.append(self.point)
else:
self.center = self.point
self.node = [self.point]
self.arctrack.setCenter(self.center)
self.arctrack.on()
self.ui.radiusUi()
self.step = 1
_msg(translate("draft", "Pick radius"))
if self.planetrack:
self.planetrack.set(self.point)
elif self.step == 1: # choose radius
self.drawPolygon()
|
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] |
https://github.com/FreeCAD/FreeCAD/blob/ba42231b9c6889b89e064d6d563448ed81e376ec/src/Mod/Draft/draftguitools/gui_polygons.py#L89-L204
|
||
google/nucleus
|
68d3947fafba1337f294c0668a6e1c7f3f1273e3
|
nucleus/io/genomics_reader.py
|
python
|
TFRecordReader.c_reader
|
(self)
|
return self.reader
|
Returns the underlying C++ reader.
|
Returns the underlying C++ reader.
|
[
"Returns",
"the",
"underlying",
"C",
"++",
"reader",
"."
] |
def c_reader(self):
"""Returns the underlying C++ reader."""
return self.reader
|
[
"def",
"c_reader",
"(",
"self",
")",
":",
"return",
"self",
".",
"reader"
] |
https://github.com/google/nucleus/blob/68d3947fafba1337f294c0668a6e1c7f3f1273e3/nucleus/io/genomics_reader.py#L179-L181
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/functools.py
|
python
|
_compose_mro
|
(cls, types)
|
return _c3_mro(cls, abcs=mro)
|
Calculates the method resolution order for a given class *cls*.
Includes relevant abstract base classes (with their respective bases) from
the *types* iterable. Uses a modified C3 linearization algorithm.
|
Calculates the method resolution order for a given class *cls*.
|
[
"Calculates",
"the",
"method",
"resolution",
"order",
"for",
"a",
"given",
"class",
"*",
"cls",
"*",
"."
] |
def _compose_mro(cls, types):
"""Calculates the method resolution order for a given class *cls*.
Includes relevant abstract base classes (with their respective bases) from
the *types* iterable. Uses a modified C3 linearization algorithm.
"""
bases = set(cls.__mro__)
# Remove entries which are already present in the __mro__ or unrelated.
def is_related(typ):
return (typ not in bases and hasattr(typ, '__mro__')
and issubclass(cls, typ))
types = [n for n in types if is_related(n)]
# Remove entries which are strict bases of other entries (they will end up
# in the MRO anyway.
def is_strict_base(typ):
for other in types:
if typ != other and typ in other.__mro__:
return True
return False
types = [n for n in types if not is_strict_base(n)]
# Subclasses of the ABCs in *types* which are also implemented by
# *cls* can be used to stabilize ABC ordering.
type_set = set(types)
mro = []
for typ in types:
found = []
for sub in typ.__subclasses__():
if sub not in bases and issubclass(cls, sub):
found.append([s for s in sub.__mro__ if s in type_set])
if not found:
mro.append(typ)
continue
# Favor subclasses with the biggest number of useful bases
found.sort(key=len, reverse=True)
for sub in found:
for subcls in sub:
if subcls not in mro:
mro.append(subcls)
return _c3_mro(cls, abcs=mro)
|
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] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/functools.py#L696-L735
|
|
evpo/EncryptPad
|
156904860aaba8e7e8729b44e269b2992f9fe9f4
|
deps/botan/configure.py
|
python
|
process_command_line
|
(args)
|
return options
|
Handle command line options
Do not use logging in this method as command line options need to be
available before logging is setup.
|
Handle command line options
Do not use logging in this method as command line options need to be
available before logging is setup.
|
[
"Handle",
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"method",
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"command",
"line",
"options",
"need",
"to",
"be",
"available",
"before",
"logging",
"is",
"setup",
"."
] |
def process_command_line(args): # pylint: disable=too-many-locals,too-many-statements
"""
Handle command line options
Do not use logging in this method as command line options need to be
available before logging is setup.
"""
parser = optparse.OptionParser(
formatter=optparse.IndentedHelpFormatter(max_help_position=50),
version=Version.as_string())
parser.add_option('--verbose', action='store_true', default=False,
help='Show debug messages')
parser.add_option('--quiet', action='store_true', default=False,
help='Show only warnings and errors')
target_group = optparse.OptionGroup(parser, 'Target options')
target_group.add_option('--cpu', help='set the target CPU architecture')
target_group.add_option('--os', help='set the target operating system')
target_group.add_option('--cc', dest='compiler', help='set the desired build compiler')
target_group.add_option('--cc-min-version', dest='cc_min_version', default=None,
metavar='MAJOR.MINOR',
help='Set the minimal version of the target compiler. ' \
'Use --cc-min-version=0.0 to support all compiler versions. ' \
'Default is auto detection.')
target_group.add_option('--cc-bin', dest='compiler_binary', metavar='BINARY',
help='set path to compiler binary')
target_group.add_option('--cc-abi-flags', metavar='FLAGS', default='',
help='set compiler ABI flags')
target_group.add_option('--cxxflags', metavar='FLAGS', default=None,
help='override all compiler flags')
target_group.add_option('--extra-cxxflags', metavar='FLAGS', default=[], action='append',
help='set extra compiler flags')
target_group.add_option('--ldflags', metavar='FLAGS',
help='set linker flags', default=None)
target_group.add_option('--extra-libs', metavar='LIBS',
help='specify extra libraries to link against', default='')
target_group.add_option('--ar-command', dest='ar_command', metavar='AR', default=None,
help='set path to static archive creator')
target_group.add_option('--ar-options', dest='ar_options', metavar='AR_OPTIONS', default=None,
help='set options for ar')
target_group.add_option('--msvc-runtime', metavar='RT', default=None,
help='specify MSVC runtime (MT, MD, MTd, MDd)')
target_group.add_option('--compiler-cache',
help='specify a compiler cache to use')
target_group.add_option('--with-endian', metavar='ORDER', default=None,
help='override byte order guess')
target_group.add_option('--with-os-features', action='append', metavar='FEAT',
help='specify OS features to use')
target_group.add_option('--without-os-features', action='append', metavar='FEAT',
help='specify OS features to disable')
isa_extensions = [
'SSE2', 'SSSE3', 'SSE4.1', 'SSE4.2', 'AVX2', 'BMI2', 'RDRAND', 'RDSEED',
'AES-NI', 'SHA-NI',
'AltiVec', 'NEON', 'ARMv8 Crypto', 'POWER Crypto']
for isa_extn_name in isa_extensions:
isa_extn = isa_extn_name.lower().replace(' ', '')
target_group.add_option('--disable-%s' % (isa_extn),
help='disable %s intrinsics' % (isa_extn_name),
action='append_const',
const=isa_extn.replace('-', '').replace('.', '').replace(' ', ''),
dest='disable_intrinsics')
build_group = optparse.OptionGroup(parser, 'Build options')
build_group.add_option('--system-cert-bundle', metavar='PATH', default=None,
help='set path to trusted CA bundle')
build_group.add_option('--with-debug-info', action='store_true', default=False, dest='with_debug_info',
help='include debug symbols')
build_group.add_option('--with-sanitizers', action='store_true', default=False, dest='with_sanitizers',
help='enable ASan/UBSan checks')
build_group.add_option('--enable-sanitizers', metavar='SAN', default='',
help='enable specific sanitizers')
build_group.add_option('--with-stack-protector', dest='with_stack_protector',
action='store_false', default=None, help=optparse.SUPPRESS_HELP)
build_group.add_option('--without-stack-protector', dest='with_stack_protector',
action='store_false', help='disable stack smashing protections')
build_group.add_option('--with-coverage', action='store_true', default=False, dest='with_coverage',
help='add coverage info and disable opts')
build_group.add_option('--with-coverage-info', action='store_true', default=False, dest='with_coverage_info',
help='add coverage info')
build_group.add_option('--enable-shared-library', dest='build_shared_lib',
action='store_true', default=None,
help=optparse.SUPPRESS_HELP)
build_group.add_option('--disable-shared-library', dest='build_shared_lib',
action='store_false',
help='disable building shared library')
build_group.add_option('--enable-static-library', dest='build_static_lib',
action='store_true', default=None,
help=optparse.SUPPRESS_HELP)
build_group.add_option('--disable-static-library', dest='build_static_lib',
action='store_false',
help='disable building static library')
build_group.add_option('--optimize-for-size', dest='optimize_for_size',
action='store_true', default=False,
help='optimize for code size')
build_group.add_option('--no-optimizations', dest='no_optimizations',
action='store_true', default=False,
help='disable all optimizations (for debugging)')
build_group.add_option('--debug-mode', action='store_true', default=False, dest='debug_mode',
help='enable debug info, disable optimizations')
build_group.add_option('--amalgamation', dest='amalgamation',
default=False, action='store_true',
help='use amalgamation to build')
build_group.add_option('--name-amalgamation', metavar='NAME', default='botan_all',
help='specify alternate name for amalgamation files')
build_group.add_option('--with-build-dir', metavar='DIR', default='',
help='setup the build in DIR')
build_group.add_option('--with-external-includedir', metavar='DIR', default=[],
help='use DIR for external includes', action='append')
build_group.add_option('--with-external-libdir', metavar='DIR', default=[],
help='use DIR for external libs', action='append')
build_group.add_option('--define-build-macro', metavar='DEFINE', default=[],
help='set compile-time pre-processor definition like KEY[=VALUE]', action='append')
build_group.add_option('--with-sysroot-dir', metavar='DIR', default='',
help='use DIR for system root while cross-compiling')
build_group.add_option('--with-openmp', default=False, action='store_true',
help='enable use of OpenMP')
link_methods = ['symlink', 'hardlink', 'copy']
build_group.add_option('--link-method', default=None, metavar='METHOD',
choices=link_methods,
help='choose how links to include headers are created (%s)' % ', '.join(link_methods))
build_group.add_option('--with-local-config',
dest='local_config', metavar='FILE',
help='include the contents of FILE into build.h')
build_group.add_option('--distribution-info', metavar='STRING',
help='distribution specific version',
default='unspecified')
build_group.add_option('--maintainer-mode', dest='maintainer_mode',
action='store_true', default=False,
help=optparse.SUPPRESS_HELP)
build_group.add_option('--werror-mode', dest='werror_mode',
action='store_true', default=False,
help="Prohibit compiler warnings")
build_group.add_option('--no-store-vc-rev', action='store_true', default=False,
help=optparse.SUPPRESS_HELP)
build_group.add_option('--no-install-python-module', action='store_true', default=False,
help='skip installing Python module')
build_group.add_option('--with-python-versions', dest='python_version',
metavar='N.M',
default='%d.%d' % (sys.version_info[0], sys.version_info[1]),
help='where to install botan2.py (def %default)')
build_group.add_option('--disable-cc-tests', dest='enable_cc_tests',
default=True, action='store_false',
help=optparse.SUPPRESS_HELP)
build_group.add_option('--with-valgrind', help='use valgrind API',
dest='with_valgrind', action='store_true', default=False)
# Cmake and bakefile options are hidden as they should not be used by end users
build_group.add_option('--with-cmake', action='store_true',
default=False, help=optparse.SUPPRESS_HELP)
build_group.add_option('--with-bakefile', action='store_true',
default=False, help=optparse.SUPPRESS_HELP)
build_group.add_option('--unsafe-fuzzer-mode', action='store_true', default=False,
help='Disable essential checks for testing')
build_group.add_option('--build-fuzzers', dest='build_fuzzers',
metavar='TYPE', default=None,
help='Build fuzzers (afl, libfuzzer, klee, test)')
build_group.add_option('--with-fuzzer-lib', metavar='LIB', default=None, dest='fuzzer_lib',
help='additionally link in LIB')
build_group.add_option('--test-mode', action='store_true', default=False,
help=optparse.SUPPRESS_HELP)
build_group.add_option('--with-debug-asserts', action='store_true', default=False,
help=optparse.SUPPRESS_HELP)
build_group.add_option('--build-targets', default=None, dest="build_targets", action='append',
help="build specific targets and tools (%s)" % ', '.join(ACCEPTABLE_BUILD_TARGETS))
build_group.add_option('--with-pkg-config', action='store_true', default=None,
help=optparse.SUPPRESS_HELP)
build_group.add_option('--without-pkg-config', dest='with_pkg_config', action='store_false',
help=optparse.SUPPRESS_HELP)
build_group.add_option('--boost-library-name', dest='boost_libnames', default=[],
help="file name of some boost library to link", action='append')
docs_group = optparse.OptionGroup(parser, 'Documentation Options')
docs_group.add_option('--with-documentation', action='store_true',
help=optparse.SUPPRESS_HELP)
docs_group.add_option('--without-documentation', action='store_false',
default=True, dest='with_documentation',
help='Skip building/installing documentation')
docs_group.add_option('--with-sphinx', action='store_true',
default=None, help='Use Sphinx')
docs_group.add_option('--without-sphinx', action='store_false',
dest='with_sphinx', help=optparse.SUPPRESS_HELP)
docs_group.add_option('--with-pdf', action='store_true',
default=False, help='Use Sphinx to generate PDF doc')
docs_group.add_option('--without-pdf', action='store_false',
dest='with_pdf', help=optparse.SUPPRESS_HELP)
docs_group.add_option('--with-rst2man', action='store_true',
default=None, help='Use rst2man to generate man page')
docs_group.add_option('--without-rst2man', action='store_false',
dest='with_rst2man', help=optparse.SUPPRESS_HELP)
docs_group.add_option('--with-doxygen', action='store_true',
default=False, help='Use Doxygen')
docs_group.add_option('--without-doxygen', action='store_false',
dest='with_doxygen', help=optparse.SUPPRESS_HELP)
mods_group = optparse.OptionGroup(parser, 'Module selection')
mods_group.add_option('--module-policy', dest='module_policy',
help="module policy file (see src/build-data/policy)",
metavar='POL', default=None)
mods_group.add_option('--enable-modules', dest='enabled_modules',
metavar='MODS', action='append',
help='enable specific modules')
mods_group.add_option('--disable-modules', dest='disabled_modules',
metavar='MODS', action='append',
help='disable specific modules')
mods_group.add_option('--no-autoload', action='store_true', default=False,
help=optparse.SUPPRESS_HELP)
mods_group.add_option('--minimized-build', action='store_true', dest='no_autoload',
help='minimize build')
# Should be derived from info.txt but this runs too early
third_party = ['boost', 'bzip2', 'lzma', 'openssl', 'commoncrypto', 'sqlite3', 'zlib', 'tpm']
for mod in third_party:
mods_group.add_option('--with-%s' % (mod),
help=('use %s' % (mod)) if mod in third_party else optparse.SUPPRESS_HELP,
action='append_const',
const=mod,
dest='enabled_modules')
mods_group.add_option('--without-%s' % (mod),
help=optparse.SUPPRESS_HELP,
action='append_const',
const=mod,
dest='disabled_modules')
mods_group.add_option('--with-everything', help=optparse.SUPPRESS_HELP,
action='store_true', default=False)
install_group = optparse.OptionGroup(parser, 'Installation options')
install_group.add_option('--program-suffix', metavar='SUFFIX',
help='append string to program names')
install_group.add_option('--library-suffix', metavar='SUFFIX', default='',
help='append string to library names')
install_group.add_option('--prefix', metavar='DIR',
help='set the install prefix')
install_group.add_option('--docdir', metavar='DIR',
help='set the doc install dir')
install_group.add_option('--bindir', metavar='DIR',
help='set the binary install dir')
install_group.add_option('--libdir', metavar='DIR',
help='set the library install dir')
install_group.add_option('--mandir', metavar='DIR',
help='set the install dir for man pages')
install_group.add_option('--includedir', metavar='DIR',
help='set the include file install dir')
info_group = optparse.OptionGroup(parser, 'Informational')
info_group.add_option('--list-modules', dest='list_modules',
action='store_true',
help='list available modules and exit')
info_group.add_option('--list-os-features', dest='list_os_features',
action='store_true',
help='list available OS features and exit')
parser.add_option_group(target_group)
parser.add_option_group(build_group)
parser.add_option_group(docs_group)
parser.add_option_group(mods_group)
parser.add_option_group(install_group)
parser.add_option_group(info_group)
# These exist only for autoconf compatibility (requested by zw for mtn)
compat_with_autoconf_options = [
'datadir',
'datarootdir',
'dvidir',
'exec-prefix',
'htmldir',
'infodir',
'libexecdir',
'localedir',
'localstatedir',
'oldincludedir',
'pdfdir',
'psdir',
'sbindir',
'sharedstatedir',
'sysconfdir'
]
for opt in compat_with_autoconf_options:
parser.add_option('--' + opt, help=optparse.SUPPRESS_HELP)
(options, args) = parser.parse_args(args)
if args != []:
raise UserError('Unhandled option(s): ' + ' '.join(args))
if options.with_endian not in [None, 'little', 'big']:
raise UserError('Bad value to --with-endian "%s"' % (options.with_endian))
if options.debug_mode:
options.no_optimizations = True
options.with_debug_info = True
if options.with_coverage:
options.with_coverage_info = True
options.no_optimizations = True
def parse_multiple_enable(modules):
if modules is None:
return []
return sorted({m for m in flatten([s.split(',') for s in modules]) if m != ''})
options.enabled_modules = parse_multiple_enable(options.enabled_modules)
options.disabled_modules = parse_multiple_enable(options.disabled_modules)
options.with_os_features = parse_multiple_enable(options.with_os_features)
options.without_os_features = parse_multiple_enable(options.without_os_features)
options.disable_intrinsics = parse_multiple_enable(options.disable_intrinsics)
return options
|
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",",
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",",
"'exec-prefix'",
",",
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",",
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",",
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",",
"'oldincludedir'",
",",
"'pdfdir'",
",",
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"!=",
"[",
"]",
":",
"raise",
"UserError",
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"'Unhandled option(s): '",
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"' '",
".",
"join",
"(",
"args",
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")",
"if",
"options",
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"with_endian",
"not",
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"[",
"None",
",",
"'little'",
",",
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"]",
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"(",
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"(",
"[",
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"split",
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"disable_intrinsics",
"=",
"parse_multiple_enable",
"(",
"options",
".",
"disable_intrinsics",
")",
"return",
"options"
] |
https://github.com/evpo/EncryptPad/blob/156904860aaba8e7e8729b44e269b2992f9fe9f4/deps/botan/configure.py#L291-L679
|
|
llvm/llvm-project
|
ffa6262cb4e2a335d26416fad39a581b4f98c5f4
|
mlir/utils/jupyter/mlir_opt_kernel/kernel.py
|
python
|
MlirOptKernel.process_output
|
(self, output)
|
Reports regular command output.
|
Reports regular command output.
|
[
"Reports",
"regular",
"command",
"output",
"."
] |
def process_output(self, output):
"""Reports regular command output."""
if not self.silent:
# Send standard output
stream_content = {'name': 'stdout', 'text': output}
self.send_response(self.iopub_socket, 'stream', stream_content)
|
[
"def",
"process_output",
"(",
"self",
",",
"output",
")",
":",
"if",
"not",
"self",
".",
"silent",
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"# Send standard output",
"stream_content",
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"{",
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"'stdout'",
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".",
"send_response",
"(",
"self",
".",
"iopub_socket",
",",
"'stream'",
",",
"stream_content",
")"
] |
https://github.com/llvm/llvm-project/blob/ffa6262cb4e2a335d26416fad39a581b4f98c5f4/mlir/utils/jupyter/mlir_opt_kernel/kernel.py#L87-L92
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/windows/Lib/distutils/dir_util.py
|
python
|
remove_tree
|
(directory, verbose=1, dry_run=0)
|
Recursively remove an entire directory tree.
Any errors are ignored (apart from being reported to stdout if 'verbose'
is true).
|
Recursively remove an entire directory tree.
|
[
"Recursively",
"remove",
"an",
"entire",
"directory",
"tree",
"."
] |
def remove_tree(directory, verbose=1, dry_run=0):
"""Recursively remove an entire directory tree.
Any errors are ignored (apart from being reported to stdout if 'verbose'
is true).
"""
global _path_created
if verbose >= 1:
log.info("removing '%s' (and everything under it)", directory)
if dry_run:
return
cmdtuples = []
_build_cmdtuple(directory, cmdtuples)
for cmd in cmdtuples:
try:
cmd[0](cmd[1])
# remove dir from cache if it's already there
abspath = os.path.abspath(cmd[1])
if abspath in _path_created:
del _path_created[abspath]
except OSError as exc:
log.warn("error removing %s: %s", directory, exc)
|
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] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/distutils/dir_util.py#L178-L200
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/timeit.py
|
python
|
reindent
|
(src, indent)
|
return src.replace("\n", "\n" + " "*indent)
|
Helper to reindent a multi-line statement.
|
Helper to reindent a multi-line statement.
|
[
"Helper",
"to",
"reindent",
"a",
"multi",
"-",
"line",
"statement",
"."
] |
def reindent(src, indent):
"""Helper to reindent a multi-line statement."""
return src.replace("\n", "\n" + " "*indent)
|
[
"def",
"reindent",
"(",
"src",
",",
"indent",
")",
":",
"return",
"src",
".",
"replace",
"(",
"\"\\n\"",
",",
"\"\\n\"",
"+",
"\" \"",
"*",
"indent",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/timeit.py#L79-L81
|
|
MegEngine/MegEngine
|
ce9ad07a27ec909fb8db4dd67943d24ba98fb93a
|
imperative/python/megengine/module/quantized/module.py
|
python
|
QuantizedModule.from_qat_module
|
(cls, qat_module: QATModule)
|
r"""
Return a :class:`~.QATModule` instance converted from
a float :class:`~.Module` instance.
|
r"""
Return a :class:`~.QATModule` instance converted from
a float :class:`~.Module` instance.
|
[
"r",
"Return",
"a",
":",
"class",
":",
"~",
".",
"QATModule",
"instance",
"converted",
"from",
"a",
"float",
":",
"class",
":",
"~",
".",
"Module",
"instance",
"."
] |
def from_qat_module(cls, qat_module: QATModule):
r"""
Return a :class:`~.QATModule` instance converted from
a float :class:`~.Module` instance.
"""
|
[
"def",
"from_qat_module",
"(",
"cls",
",",
"qat_module",
":",
"QATModule",
")",
":"
] |
https://github.com/MegEngine/MegEngine/blob/ce9ad07a27ec909fb8db4dd67943d24ba98fb93a/imperative/python/megengine/module/quantized/module.py#L29-L33
|
||
Illumina/strelka
|
d7377443b62319f7c7bd70c241c4b2df3459e29a
|
src/python/deNovoQualityScore/denovo.py
|
python
|
is_in_regions
|
(variant, regions=None, chrom=None)
|
return False
|
Check if the variant is located within the annotated regions
|
Check if the variant is located within the annotated regions
|
[
"Check",
"if",
"the",
"variant",
"is",
"located",
"within",
"the",
"annotated",
"regions"
] |
def is_in_regions(variant, regions=None, chrom=None):
"""Check if the variant is located within the annotated regions"""
if chrom is None:
chrom = variant.CHROM.lstrip('chr')
if regions and chrom in regions:
for coords in regions[chrom]:
if variant.POS >= coords[0] and variant.POS <= coords[1]:
return True
return False
|
[
"def",
"is_in_regions",
"(",
"variant",
",",
"regions",
"=",
"None",
",",
"chrom",
"=",
"None",
")",
":",
"if",
"chrom",
"is",
"None",
":",
"chrom",
"=",
"variant",
".",
"CHROM",
".",
"lstrip",
"(",
"'chr'",
")",
"if",
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"and",
"chrom",
"in",
"regions",
":",
"for",
"coords",
"in",
"regions",
"[",
"chrom",
"]",
":",
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".",
"POS",
">=",
"coords",
"[",
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".",
"POS",
"<=",
"coords",
"[",
"1",
"]",
":",
"return",
"True",
"return",
"False"
] |
https://github.com/Illumina/strelka/blob/d7377443b62319f7c7bd70c241c4b2df3459e29a/src/python/deNovoQualityScore/denovo.py#L1021-L1032
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/parso/py3/parso/python/diff.py
|
python
|
DiffParser._parse
|
(self, until_line)
|
Parses at least until the given line, but might just parse more until a
valid state is reached.
|
Parses at least until the given line, but might just parse more until a
valid state is reached.
|
[
"Parses",
"at",
"least",
"until",
"the",
"given",
"line",
"but",
"might",
"just",
"parse",
"more",
"until",
"a",
"valid",
"state",
"is",
"reached",
"."
] |
def _parse(self, until_line):
"""
Parses at least until the given line, but might just parse more until a
valid state is reached.
"""
last_until_line = 0
while until_line > self._nodes_tree.parsed_until_line:
node = self._try_parse_part(until_line)
nodes = node.children
self._nodes_tree.add_parsed_nodes(nodes, self._keyword_token_indents)
if self._replace_tos_indent is not None:
self._nodes_tree.indents[-1] = self._replace_tos_indent
LOG.debug(
'parse_part from %s to %s (to %s in part parser)',
nodes[0].get_start_pos_of_prefix()[0],
self._nodes_tree.parsed_until_line,
node.end_pos[0] - 1
)
# Since the tokenizer sometimes has bugs, we cannot be sure that
# this loop terminates. Therefore assert that there's always a
# change.
assert last_until_line != self._nodes_tree.parsed_until_line, last_until_line
last_until_line = self._nodes_tree.parsed_until_line
|
[
"def",
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":",
"last_until_line",
"=",
"0",
"while",
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">",
"self",
".",
"_nodes_tree",
".",
"parsed_until_line",
":",
"node",
"=",
"self",
".",
"_try_parse_part",
"(",
"until_line",
")",
"nodes",
"=",
"node",
".",
"children",
"self",
".",
"_nodes_tree",
".",
"add_parsed_nodes",
"(",
"nodes",
",",
"self",
".",
"_keyword_token_indents",
")",
"if",
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".",
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":",
"self",
".",
"_nodes_tree",
".",
"indents",
"[",
"-",
"1",
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"debug",
"(",
"'parse_part from %s to %s (to %s in part parser)'",
",",
"nodes",
"[",
"0",
"]",
".",
"get_start_pos_of_prefix",
"(",
")",
"[",
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"]",
",",
"self",
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"_nodes_tree",
".",
"parsed_until_line",
",",
"node",
".",
"end_pos",
"[",
"0",
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"-",
"1",
")",
"# Since the tokenizer sometimes has bugs, we cannot be sure that",
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"# change.",
"assert",
"last_until_line",
"!=",
"self",
".",
"_nodes_tree",
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"parsed_until_line",
",",
"last_until_line",
"last_until_line",
"=",
"self",
".",
"_nodes_tree",
".",
"parsed_until_line"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/parso/py3/parso/python/diff.py#L407-L431
|
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