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TGAC/KAT | e8870331de2b4bb0a1b3b91c6afb8fb9d59e9216 | deps/boost/tools/build/src/util/regex.py | python | replace_list | (items, match, replacement) | return [replace(item, match, replacement) for item in items] | Replaces occurrences of a match string in a given list of strings and returns
a list of new strings. The match string can be a regex expression.
Args:
items (list): the list of strings to modify.
match (str): the search expression.
replacement (str): the string to replace with. | Replaces occurrences of a match string in a given list of strings and returns
a list of new strings. The match string can be a regex expression. | [
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"""Replaces occurrences of a match string in a given list of strings and returns
a list of new strings. The match string can be a regex expression.
Args:
items (list): the list of strings to modify.
match (str): the search expression.
replacement (str): the string to replace with.
"""
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py | python | Button.__init__ | (self, master=None, cnf={}, **kw) | Construct a button widget with the parent MASTER.
STANDARD OPTIONS
activebackground, activeforeground, anchor,
background, bitmap, borderwidth, cursor,
disabledforeground, font, foreground
highlightbackground, highlightcolor,
highlightthickness, image, justify,
padx, pady, relief, repeatdelay,
repeatinterval, takefocus, text,
textvariable, underline, wraplength
WIDGET-SPECIFIC OPTIONS
command, compound, default, height,
overrelief, state, width | Construct a button widget with the parent MASTER. | [
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"""Construct a button widget with the parent MASTER.
STANDARD OPTIONS
activebackground, activeforeground, anchor,
background, bitmap, borderwidth, cursor,
disabledforeground, font, foreground
highlightbackground, highlightcolor,
highlightthickness, image, justify,
padx, pady, relief, repeatdelay,
repeatinterval, takefocus, text,
textvariable, underline, wraplength
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command, compound, default, height,
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"""
Widget.__init__(self, master, 'button', cnf, kw) | [
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Yelp/MOE | 5b5a6a2c6c3cf47320126f7f5894e2a83e347f5c | moe/views/rest/gp_hyper_opt.py | python | GpHyperOptView.pretty_view | (self) | return self.pretty_response() | A pretty, browser interactive view for the interface. Includes form request and response.
.. http:get:: /gp/hyper_opt/pretty | A pretty, browser interactive view for the interface. Includes form request and response. | [
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"""A pretty, browser interactive view for the interface. Includes form request and response.
.. http:get:: /gp/hyper_opt/pretty
"""
return self.pretty_response() | [
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taichi-dev/taichi | 973c04d6ba40f34e9e3bd5a28ae0ee0802f136a6 | python/taichi/lang/matrix.py | python | Matrix.norm | (self, eps=0) | return ops_mod.sqrt(self.norm_sqr() + eps) | Return the square root of the sum of the absolute squares of its elements.
Args:
eps (Number): a safe-guard value for sqrt, usually 0.
Examples::
a = ti.Vector([3, 4])
a.norm() # sqrt(3*3 + 4*4 + 0) = 5
# `a.norm(eps)` is equivalent to `ti.sqrt(a.dot(a) + eps).`
Return:
The square root of the sum of the absolute squares of its elements. | Return the square root of the sum of the absolute squares of its elements. | [
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] | def norm(self, eps=0):
"""Return the square root of the sum of the absolute squares of its elements.
Args:
eps (Number): a safe-guard value for sqrt, usually 0.
Examples::
a = ti.Vector([3, 4])
a.norm() # sqrt(3*3 + 4*4 + 0) = 5
# `a.norm(eps)` is equivalent to `ti.sqrt(a.dot(a) + eps).`
Return:
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"""
return ops_mod.sqrt(self.norm_sqr() + eps) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/arrays/string_arrow.py | python | ArrowStringArray.isna | (self) | return self._data.is_null().to_pandas().values | Boolean NumPy array indicating if each value is missing.
This should return a 1-D array the same length as 'self'. | Boolean NumPy array indicating if each value is missing. | [
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] | def isna(self) -> np.ndarray:
"""
Boolean NumPy array indicating if each value is missing.
This should return a 1-D array the same length as 'self'.
"""
# TODO: Implement .to_numpy for ChunkedArray
return self._data.is_null().to_pandas().values | [
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rdkit/rdkit | ede860ae316d12d8568daf5ee800921c3389c84e | rdkit/Chem/FeatMaps/FeatMapPoint.py | python | FeatMapPoint.initFromFeat | (self, feat) | >>> from rdkit import Geometry
>>> sfeat = ChemicalFeatures.FreeChemicalFeature('Aromatic','Foo',Geometry.Point3D(0,0,0))
>>> fmp = FeatMapPoint()
>>> fmp.initFromFeat(sfeat)
>>> fmp.GetFamily()==sfeat.GetFamily()
True
>>> fmp.GetType()==sfeat.GetType()
True
>>> list(fmp.GetPos())
[0.0, 0.0, 0.0]
>>> fmp.featDirs == []
True
>>> sfeat.featDirs = [Geometry.Point3D(1.0,0,0)]
>>> fmp.initFromFeat(sfeat)
>>> len(fmp.featDirs)
1 | >>> from rdkit import Geometry
>>> sfeat = ChemicalFeatures.FreeChemicalFeature('Aromatic','Foo',Geometry.Point3D(0,0,0))
>>> fmp = FeatMapPoint()
>>> fmp.initFromFeat(sfeat)
>>> fmp.GetFamily()==sfeat.GetFamily()
True
>>> fmp.GetType()==sfeat.GetType()
True
>>> list(fmp.GetPos())
[0.0, 0.0, 0.0]
>>> fmp.featDirs == []
True | [
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"""
>>> from rdkit import Geometry
>>> sfeat = ChemicalFeatures.FreeChemicalFeature('Aromatic','Foo',Geometry.Point3D(0,0,0))
>>> fmp = FeatMapPoint()
>>> fmp.initFromFeat(sfeat)
>>> fmp.GetFamily()==sfeat.GetFamily()
True
>>> fmp.GetType()==sfeat.GetType()
True
>>> list(fmp.GetPos())
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>>> fmp.featDirs == []
True
>>> sfeat.featDirs = [Geometry.Point3D(1.0,0,0)]
>>> fmp.initFromFeat(sfeat)
>>> len(fmp.featDirs)
1
"""
self.SetFamily(feat.GetFamily())
self.SetType(feat.GetType())
self.SetPos(feat.GetPos())
if hasattr(feat, 'featDirs'):
self.featDirs = feat.featDirs[:] | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/AWSPythonSDK/1.5.8/dateutil/tz/tz.py | python | tzfile.is_ambiguous | (self, dt, idx=None) | return timestamp < tt + od | Whether or not the "wall time" of a given datetime is ambiguous in this
zone.
:param dt:
A :py:class:`datetime.datetime`, naive or time zone aware.
:return:
Returns ``True`` if ambiguous, ``False`` otherwise.
.. versionadded:: 2.6.0 | Whether or not the "wall time" of a given datetime is ambiguous in this
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"""
Whether or not the "wall time" of a given datetime is ambiguous in this
zone.
:param dt:
A :py:class:`datetime.datetime`, naive or time zone aware.
:return:
Returns ``True`` if ambiguous, ``False`` otherwise.
.. versionadded:: 2.6.0
"""
if idx is None:
idx = self._find_last_transition(dt)
# Calculate the difference in offsets from current to previous
timestamp = _datetime_to_timestamp(dt)
tti = self._get_ttinfo(idx)
if idx is None or idx <= 0:
return False
od = self._get_ttinfo(idx - 1).offset - tti.offset
tt = self._trans_list[idx] # Transition time
return timestamp < tt + od | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/pymock/mock.py | python | _patch_dict.__exit__ | (self, *args) | return False | Unpatch the dict. | Unpatch the dict. | [
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"""Unpatch the dict."""
self._unpatch_dict()
return False | [
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google/earthenterprise | 0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9 | earth_enterprise/src/fusion/portableglobe/servers/portable_server.py | python | CompositeDbRootHandler.get | (self, layer_id) | Handle GET request for the dbroot. | Handle GET request for the dbroot. | [
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if not tornado.web.globe_.Is3d():
print "Bad request: dbRoot from non-3D globe."
elif not tornado.web.globe_.IsComposite():
print "Bad request: composite request for glb."
else:
tornado.web.local_server_.LocalDbRootHandler(self, int(layer_id))
self.finish() | [
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D-X-Y/caffe-faster-rcnn | eb50c97ff48f3df115d0e85fe0a32b0c7e2aa4cb | python/caffe/pycaffe.py | python | _Net_backward | (self, diffs=None, start=None, end=None, **kwargs) | return {out: self.blobs[out].diff for out in outputs} | Backward pass: prepare diffs and run the net backward.
Parameters
----------
diffs : list of diffs to return in addition to bottom diffs.
kwargs : Keys are output blob names and values are diff ndarrays.
If None, top diffs are taken from forward loss.
start : optional name of layer at which to begin the backward pass
end : optional name of layer at which to finish the backward pass
(inclusive)
Returns
-------
outs: {blob name: diff ndarray} dict. | Backward pass: prepare diffs and run the net backward. | [
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"""
Backward pass: prepare diffs and run the net backward.
Parameters
----------
diffs : list of diffs to return in addition to bottom diffs.
kwargs : Keys are output blob names and values are diff ndarrays.
If None, top diffs are taken from forward loss.
start : optional name of layer at which to begin the backward pass
end : optional name of layer at which to finish the backward pass
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Returns
-------
outs: {blob name: diff ndarray} dict.
"""
if diffs is None:
diffs = []
if start is not None:
start_ind = list(self._layer_names).index(start)
else:
start_ind = len(self.layers) - 1
if end is not None:
end_ind = list(self._layer_names).index(end)
outputs = set(self.bottom_names[end] + diffs)
else:
end_ind = 0
outputs = set(self.inputs + diffs)
if kwargs:
if set(kwargs.keys()) != set(self.outputs):
raise Exception('Top diff arguments do not match net outputs.')
# Set top diffs according to defined shapes and make arrays single and
# C-contiguous as Caffe expects.
for top, diff in six.iteritems(kwargs):
if diff.shape[0] != self.blobs[top].shape[0]:
raise Exception('Diff is not batch sized')
self.blobs[top].diff[...] = diff
self._backward(start_ind, end_ind)
# Unpack diffs to extract
return {out: self.blobs[out].diff for out in outputs} | [
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bilibili/biliobs | 573613dc3b2b63fe7c1506cc94717609a2c52c0c | base/android/jni_generator/jni_generator.py | python | InlHeaderFileGenerator.SubstituteNativeMethods | (self, template) | return '\n' + '\n'.join(ret) | Substitutes JAVA_CLASS and KMETHODS in the provided template. | Substitutes JAVA_CLASS and KMETHODS in the provided template. | [
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"""Substitutes JAVA_CLASS and KMETHODS in the provided template."""
ret = []
all_classes = self.GetUniqueClasses(self.natives)
all_classes[self.class_name] = self.fully_qualified_class
for clazz in all_classes:
kmethods = self.GetKMethodsString(clazz)
if kmethods:
values = {'JAVA_CLASS': clazz,
'KMETHODS': kmethods}
ret += [template.substitute(values)]
if not ret: return ''
return '\n' + '\n'.join(ret) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/plat-mac/lib-scriptpackages/StdSuites/AppleScript_Suite.py | python | AppleScript_Suite_Events._2d_ | (self, _object, _attributes={}, **_arguments) | -: Subtraction
Required argument: an AE object reference
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: anything | -: Subtraction
Required argument: an AE object reference
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: anything | [
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"""-: Subtraction
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if _arguments.get('errn', 0):
raise aetools.Error, aetools.decodeerror(_arguments)
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/ops/control_flow_ops.py | python | IsLoopExit | (op) | return op.type == "Exit" or op.type == "RefExit" | Return true if `op` is an Exit. | Return true if `op` is an Exit. | [
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"""Return true if `op` is an Exit."""
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqtinterfaces/mantidqtinterfaces/PyChop/PyChop2.py | python | PyChop2.getChopper | (self) | return self.object.getChopper() | ! Returns the currently set chopper rotor or instrument configuration | ! Returns the currently set chopper rotor or instrument configuration | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | contrib/gizmos/osx_carbon/gizmos.py | python | TreeListCtrl.GetImageList | (*args, **kwargs) | return _gizmos.TreeListCtrl_GetImageList(*args, **kwargs) | GetImageList(self) -> ImageList | GetImageList(self) -> ImageList | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py3/sklearn/datasets/_twenty_newsgroups.py | python | fetch_20newsgroups_vectorized | (subset="train", remove=(), data_home=None,
download_if_missing=True, return_X_y=False,
normalize=True) | return Bunch(data=data,
target=target,
target_names=target_names,
DESCR=fdescr) | Load the 20 newsgroups dataset and vectorize it into token counts \
(classification).
Download it if necessary.
This is a convenience function; the transformation is done using the
default settings for
:class:`sklearn.feature_extraction.text.CountVectorizer`. For more
advanced usage (stopword filtering, n-gram extraction, etc.), combine
fetch_20newsgroups with a custom
:class:`sklearn.feature_extraction.text.CountVectorizer`,
:class:`sklearn.feature_extraction.text.HashingVectorizer`,
:class:`sklearn.feature_extraction.text.TfidfTransformer` or
:class:`sklearn.feature_extraction.text.TfidfVectorizer`.
The resulting counts are normalized using
:func:`sklearn.preprocessing.normalize` unless normalize is set to False.
================= ==========
Classes 20
Samples total 18846
Dimensionality 130107
Features real
================= ==========
Read more in the :ref:`User Guide <20newsgroups_dataset>`.
Parameters
----------
subset : 'train' or 'test', 'all', optional
Select the dataset to load: 'train' for the training set, 'test'
for the test set, 'all' for both, with shuffled ordering.
remove : tuple
May contain any subset of ('headers', 'footers', 'quotes'). Each of
these are kinds of text that will be detected and removed from the
newsgroup posts, preventing classifiers from overfitting on
metadata.
'headers' removes newsgroup headers, 'footers' removes blocks at the
ends of posts that look like signatures, and 'quotes' removes lines
that appear to be quoting another post.
data_home : optional, default: None
Specify an download and cache folder for the datasets. If None,
all scikit-learn data is stored in '~/scikit_learn_data' subfolders.
download_if_missing : optional, True by default
If False, raise an IOError if the data is not locally available
instead of trying to download the data from the source site.
return_X_y : bool, default=False
If True, returns ``(data.data, data.target)`` instead of a Bunch
object.
.. versionadded:: 0.20
normalize : bool, default=True
If True, normalizes each document's feature vector to unit norm using
:func:`sklearn.preprocessing.normalize`.
.. versionadded:: 0.22
Returns
-------
bunch : Bunch object with the following attribute:
- bunch.data: sparse matrix, shape [n_samples, n_features]
- bunch.target: array, shape [n_samples]
- bunch.target_names: a list of categories of the returned data,
length [n_classes].
- bunch.DESCR: a description of the dataset.
(data, target) : tuple if ``return_X_y`` is True
.. versionadded:: 0.20 | Load the 20 newsgroups dataset and vectorize it into token counts \
(classification). | [
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download_if_missing=True, return_X_y=False,
normalize=True):
"""Load the 20 newsgroups dataset and vectorize it into token counts \
(classification).
Download it if necessary.
This is a convenience function; the transformation is done using the
default settings for
:class:`sklearn.feature_extraction.text.CountVectorizer`. For more
advanced usage (stopword filtering, n-gram extraction, etc.), combine
fetch_20newsgroups with a custom
:class:`sklearn.feature_extraction.text.CountVectorizer`,
:class:`sklearn.feature_extraction.text.HashingVectorizer`,
:class:`sklearn.feature_extraction.text.TfidfTransformer` or
:class:`sklearn.feature_extraction.text.TfidfVectorizer`.
The resulting counts are normalized using
:func:`sklearn.preprocessing.normalize` unless normalize is set to False.
================= ==========
Classes 20
Samples total 18846
Dimensionality 130107
Features real
================= ==========
Read more in the :ref:`User Guide <20newsgroups_dataset>`.
Parameters
----------
subset : 'train' or 'test', 'all', optional
Select the dataset to load: 'train' for the training set, 'test'
for the test set, 'all' for both, with shuffled ordering.
remove : tuple
May contain any subset of ('headers', 'footers', 'quotes'). Each of
these are kinds of text that will be detected and removed from the
newsgroup posts, preventing classifiers from overfitting on
metadata.
'headers' removes newsgroup headers, 'footers' removes blocks at the
ends of posts that look like signatures, and 'quotes' removes lines
that appear to be quoting another post.
data_home : optional, default: None
Specify an download and cache folder for the datasets. If None,
all scikit-learn data is stored in '~/scikit_learn_data' subfolders.
download_if_missing : optional, True by default
If False, raise an IOError if the data is not locally available
instead of trying to download the data from the source site.
return_X_y : bool, default=False
If True, returns ``(data.data, data.target)`` instead of a Bunch
object.
.. versionadded:: 0.20
normalize : bool, default=True
If True, normalizes each document's feature vector to unit norm using
:func:`sklearn.preprocessing.normalize`.
.. versionadded:: 0.22
Returns
-------
bunch : Bunch object with the following attribute:
- bunch.data: sparse matrix, shape [n_samples, n_features]
- bunch.target: array, shape [n_samples]
- bunch.target_names: a list of categories of the returned data,
length [n_classes].
- bunch.DESCR: a description of the dataset.
(data, target) : tuple if ``return_X_y`` is True
.. versionadded:: 0.20
"""
data_home = get_data_home(data_home=data_home)
filebase = '20newsgroup_vectorized'
if remove:
filebase += 'remove-' + ('-'.join(remove))
target_file = _pkl_filepath(data_home, filebase + ".pkl")
# we shuffle but use a fixed seed for the memoization
data_train = fetch_20newsgroups(data_home=data_home,
subset='train',
categories=None,
shuffle=True,
random_state=12,
remove=remove,
download_if_missing=download_if_missing)
data_test = fetch_20newsgroups(data_home=data_home,
subset='test',
categories=None,
shuffle=True,
random_state=12,
remove=remove,
download_if_missing=download_if_missing)
if os.path.exists(target_file):
X_train, X_test = joblib.load(target_file)
else:
vectorizer = CountVectorizer(dtype=np.int16)
X_train = vectorizer.fit_transform(data_train.data).tocsr()
X_test = vectorizer.transform(data_test.data).tocsr()
joblib.dump((X_train, X_test), target_file, compress=9)
# the data is stored as int16 for compactness
# but normalize needs floats
if normalize:
X_train = X_train.astype(np.float64)
X_test = X_test.astype(np.float64)
preprocessing.normalize(X_train, copy=False)
preprocessing.normalize(X_test, copy=False)
target_names = data_train.target_names
if subset == "train":
data = X_train
target = data_train.target
elif subset == "test":
data = X_test
target = data_test.target
elif subset == "all":
data = sp.vstack((X_train, X_test)).tocsr()
target = np.concatenate((data_train.target, data_test.target))
else:
raise ValueError("%r is not a valid subset: should be one of "
"['train', 'test', 'all']" % subset)
module_path = dirname(__file__)
with open(join(module_path, 'descr', 'twenty_newsgroups.rst')) as rst_file:
fdescr = rst_file.read()
if return_X_y:
return data, target
return Bunch(data=data,
target=target,
target_names=target_names,
DESCR=fdescr) | [
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gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | src/python/gem5/components/processors/random_generator.py | python | RandomGenerator.start_traffic | (self) | This function will start the assigned traffic to this generator. | This function will start the assigned traffic to this generator. | [
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] | def start_traffic(self) -> None:
"""
This function will start the assigned traffic to this generator.
"""
for core in self.cores:
core.start_traffic() | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/pdb.py | python | Pdb.user_call | (self, frame, argument_list) | This method is called when there is the remote possibility
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] | def user_call(self, frame, argument_list):
"""This method is called when there is the remote possibility
that we ever need to stop in this function."""
if self._wait_for_mainpyfile:
return
if self.stop_here(frame):
print >>self.stdout, '--Call--'
self.interaction(frame, None) | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/coverage/coverage/parser.py | python | ByteParser.child_parsers | (self) | return (ByteParser(self.text, code=c) for c in children) | Iterate over all the code objects nested within this one.
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"""Iterate over all the code objects nested within this one.
The iteration includes `self` as its first value.
"""
children = CodeObjects(self.code)
return (ByteParser(self.text, code=c) for c in children) | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/telemetry/telemetry/core/util.py | python | GetUnreservedAvailableLocalPort | () | return port | Returns an available port on the system.
WARNING: This method does not reserve the port it returns, so it may be used
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"""Returns an available port on the system.
WARNING: This method does not reserve the port it returns, so it may be used
by something else before you get to use it. This can lead to flake.
"""
tmp = socket.socket()
tmp.bind(('', 0))
port = tmp.getsockname()[1]
tmp.close()
return port | [
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facebook/redex | fac189a289bca2647061f9e364016afc1096500d | tools/python/dex.py | python | File.demangle_class_name | (self, cls_mangled) | return None | Given a mangled type name as it would appear in a DEX file like
"LX/JxK;", return the demangled version if we have a proguard file,
otherwise return the original class typename | Given a mangled type name as it would appear in a DEX file like
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otherwise return the original class typename | [
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"""Given a mangled type name as it would appear in a DEX file like
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otherwise return the original class typename"""
if self.proguard:
cls_demangled = demangle_classname(cls_mangled)
if cls_demangled:
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return None | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/stc.py | python | StyledTextCtrl.SetTabWidth | (*args, **kwargs) | return _stc.StyledTextCtrl_SetTabWidth(*args, **kwargs) | SetTabWidth(self, int tabWidth)
Change the visible size of a tab to be a multiple of the width of a space character. | SetTabWidth(self, int tabWidth) | [
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"""
SetTabWidth(self, int tabWidth)
Change the visible size of a tab to be a multiple of the width of a space character.
"""
return _stc.StyledTextCtrl_SetTabWidth(*args, **kwargs) | [
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weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | third_party/WebKit/Source/build/scripts/make_element_lookup_trie.py | python | _trie | (tags, index) | return (trie_node(char, subtags) for char, subtags in char_subtags) | Make a trie from list of tags, starting at index.
Resulting trie is partly space-optimized (semi-radix tree): once have only
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However, does not compact branch nodes with a single child. (FIXME)
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code generation differs between branch nodes and leaf nodes,
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Arguments:
tags: sorted list
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index: index at which to branch
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"""Make a trie from list of tags, starting at index.
Resulting trie is partly space-optimized (semi-radix tree): once have only
one string left, compact the entire branch to one leaf node.
However, does not compact branch nodes with a single child. (FIXME)
Returns:
(char, subtrie, tag, conditions): (char, trie, str, list)
code generation differs between branch nodes and leaf nodes,
hence need different data for each.
Arguments:
tags: sorted list
(sorted needed by groupby, list needed by len)
index: index at which to branch
(assumes prior to this index strings have a common prefix)
"""
def trie_node(char, subtags_iter):
# Pass in |char| so we can include in same tuple without unpacking
subtags = list(subtags_iter) # need list for len
if len(subtags) == 1: # terminal node, no subtrie
subtrie = None
tag = subtags[0]
conditions = _conditions(tag, index + 1)
else:
subtrie = _trie(subtags, index + 1)
tag = None
conditions = None
return char, subtrie, tag, conditions
# Group by char at index
def char_at_index(tag):
return tag[index].lower()
char_subtags = ((k, g) for k, g in groupby(tags, char_at_index))
# FIXME: if all subtags have a common prefix, merge with child
# and skip the switch in the generated code
return (trie_node(char, subtags) for char, subtags in char_subtags) | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/pexpect/pexpect.py | python | spawn.setecho | (self, state) | This sets the terminal echo mode on or off. Note that anything the
child sent before the echo will be lost, so you should be sure that
your input buffer is empty before you call setecho(). For example, the
following will work as expected::
p = pexpect.spawn('cat') # Echo is on by default.
p.sendline('1234') # We expect see this twice from the child...
p.expect(['1234']) # ... once from the tty echo...
p.expect(['1234']) # ... and again from cat itself.
p.setecho(False) # Turn off tty echo
p.sendline('abcd') # We will set this only once (echoed by cat).
p.sendline('wxyz') # We will set this only once (echoed by cat)
p.expect(['abcd'])
p.expect(['wxyz'])
The following WILL NOT WORK because the lines sent before the setecho
will be lost::
p = pexpect.spawn('cat')
p.sendline('1234')
p.setecho(False) # Turn off tty echo
p.sendline('abcd') # We will set this only once (echoed by cat).
p.sendline('wxyz') # We will set this only once (echoed by cat)
p.expect(['1234'])
p.expect(['1234'])
p.expect(['abcd'])
p.expect(['wxyz']) | This sets the terminal echo mode on or off. Note that anything the
child sent before the echo will be lost, so you should be sure that
your input buffer is empty before you call setecho(). For example, the
following will work as expected:: | [
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following will work as expected::
p = pexpect.spawn('cat') # Echo is on by default.
p.sendline('1234') # We expect see this twice from the child...
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p.expect(['1234']) # ... and again from cat itself.
p.setecho(False) # Turn off tty echo
p.sendline('abcd') # We will set this only once (echoed by cat).
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p.expect(['abcd'])
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p.sendline('1234')
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p.sendline('wxyz') # We will set this only once (echoed by cat)
p.expect(['1234'])
p.expect(['1234'])
p.expect(['abcd'])
p.expect(['wxyz'])
"""
self.child_fd
attr = termios.tcgetattr(self.child_fd)
if state:
attr[3] = attr[3] | termios.ECHO
else:
attr[3] = attr[3] & ~termios.ECHO
# I tried TCSADRAIN and TCSAFLUSH, but
# these were inconsistent and blocked on some platforms.
# TCSADRAIN would probably be ideal if it worked.
termios.tcsetattr(self.child_fd, termios.TCSANOW, attr) | [
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NASA-SW-VnV/ikos | 71325dfb94737332542caa708d7537752021522d | analyzer/python/ikos/view.py | python | Formatter._build_checks | (self, statement_reports) | return checks | Return the list of check for a source line | Return the list of check for a source line | [
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''' Return the list of check for a source line '''
checks = []
for statement_report in statement_reports:
statement = statement_report.statement()
checks.append({
'kind': statement_report.kind,
'status': statement_report.status,
'column': statement.column_or('?'),
'message': report.generate_message(statement_report, 4),
'function_id': statement.function_id,
'call_context_ids': statement_report.call_context_ids,
})
self._build_function(statement.function())
self._build_call_contexts(statement_report.call_contexts())
# Sort by status (error > warning > ok)
checks.sort(key=operator.itemgetter('status'), reverse=True)
return checks | [
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AojunZhou/Incremental-Network-Quantization | c7f6a609d5817d8424ce224209cf4c50f1e4de50 | python/caffe/io.py | python | Transformer.set_channel_swap | (self, in_, order) | Set the input channel order for e.g. RGB to BGR conversion
as needed for the reference ImageNet model.
N.B. this assumes the channels are the first dimension AFTER transpose.
Parameters
----------
in_ : which input to assign this channel order
order : the order to take the channels.
(2,1,0) maps RGB to BGR for example. | Set the input channel order for e.g. RGB to BGR conversion
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"""
Set the input channel order for e.g. RGB to BGR conversion
as needed for the reference ImageNet model.
N.B. this assumes the channels are the first dimension AFTER transpose.
Parameters
----------
in_ : which input to assign this channel order
order : the order to take the channels.
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"""
self.__check_input(in_)
if len(order) != self.inputs[in_][1]:
raise Exception('Channel swap needs to have the same number of '
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self.channel_swap[in_] = order | [
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greenheartgames/greenworks | 3ea4ab490b56676de3f0a237c74bcfdb17323e60 | deps/cpplint/cpplint.py | python | _IncludeState.ResetSection | (self, directive) | Reset section checking for preprocessor directive.
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"""Reset section checking for preprocessor directive.
Args:
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"""
# The name of the current section.
self._section = self._INITIAL_SECTION
# The path of last found header.
self._last_header = ''
# Update list of includes. Note that we never pop from the
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if directive in ('if', 'ifdef', 'ifndef'):
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elif directive in ('else', 'elif'):
self.include_list[-1] = [] | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_vendor/distro.py | python | LinuxDistribution.linux_distribution | (self, full_distribution_name=True) | return (
self.name() if full_distribution_name else self.id(),
self.version(),
self.codename()
) | Return information about the OS distribution that is compatible
with Python's :func:`platform.linux_distribution`, supporting a subset
of its parameters.
For details, see :func:`distro.linux_distribution`. | [] | def linux_distribution(self, full_distribution_name=True):
"""
Return information about the OS distribution that is compatible
with Python's :func:`platform.linux_distribution`, supporting a subset
of its parameters.
For details, see :func:`distro.linux_distribution`.
"""
return (
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self.version(),
self.codename()
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baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/ops/tensor_array_ops.py | python | TensorArray.scatter | (self, indices, value, name=None) | Scatter the values of a `Tensor` in specific indices of a `TensorArray`.
Args:
indices: A `1-D` `Tensor` taking values in `[0, max_value)`. If
the `TensorArray` is not dynamic, `max_value=size()`.
value: (N+1)-D. Tensor of type `dtype`. The Tensor to unpack.
name: A name for the operation (optional).
Returns:
A new TensorArray object with flow that ensures the scatter occurs.
Use this object all for subsequent operations.
Raises:
ValueError: if the shape inference fails. | Scatter the values of a `Tensor` in specific indices of a `TensorArray`. | [
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"""Scatter the values of a `Tensor` in specific indices of a `TensorArray`.
Args:
indices: A `1-D` `Tensor` taking values in `[0, max_value)`. If
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value: (N+1)-D. Tensor of type `dtype`. The Tensor to unpack.
name: A name for the operation (optional).
Returns:
A new TensorArray object with flow that ensures the scatter occurs.
Use this object all for subsequent operations.
Raises:
ValueError: if the shape inference fails.
"""
with ops.name_scope(name, "TensorArrayScatter",
[self._handle, value, indices]):
value = ops.convert_to_tensor(value, name="value")
with self._maybe_colocate_with(value):
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value=value,
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name=name)
ta = TensorArray(
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ta._infer_shape = self._infer_shape
ta._element_shape = self._element_shape
ta._colocate_with = self._colocate_with
if ta._infer_shape:
val_shape = flow_out.op.inputs[2].get_shape()
element_shape = tensor_shape.unknown_shape()
if val_shape.dims is not None:
element_shape = tensor_shape.TensorShape(val_shape.dims[1:])
ta._merge_element_shape(element_shape)
return ta | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py2/IPython/core/prefilter.py | python | PrefilterManager.get_handler_by_esc | (self, esc_str) | return self._esc_handlers.get(esc_str) | Get a handler by its escape string. | Get a handler by its escape string. | [
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] | def get_handler_by_esc(self, esc_str):
"""Get a handler by its escape string."""
return self._esc_handlers.get(esc_str) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/prompt-toolkit/py2/prompt_toolkit/buffer.py | python | CompletionState.go_to_index | (self, index) | return CompletionState(self.original_document, self.current_completions, complete_index=index) | Create a new :class:`.CompletionState` object with the new index. | Create a new :class:`.CompletionState` object with the new index. | [
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"""
Create a new :class:`.CompletionState` object with the new index.
"""
return CompletionState(self.original_document, self.current_completions, complete_index=index) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/distutils/msvccompiler.py | python | MSVCCompiler.get_msvc_paths | (self, path, platform='x86') | return [] | Get a list of devstudio directories (include, lib or path).
Return a list of strings. The list will be empty if unable to
access the registry or appropriate registry keys not found. | Get a list of devstudio directories (include, lib or path). | [
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"""Get a list of devstudio directories (include, lib or path).
Return a list of strings. The list will be empty if unable to
access the registry or appropriate registry keys not found.
"""
if not _can_read_reg:
return []
path = path + " dirs"
if self.__version >= 7:
key = (r"%s\%0.1f\VC\VC_OBJECTS_PLATFORM_INFO\Win32\Directories"
% (self.__root, self.__version))
else:
key = (r"%s\6.0\Build System\Components\Platforms"
r"\Win32 (%s)\Directories" % (self.__root, platform))
for base in HKEYS:
d = read_values(base, key)
if d:
if self.__version >= 7:
return string.split(self.__macros.sub(d[path]), ";")
else:
return string.split(d[path], ";")
# MSVC 6 seems to create the registry entries we need only when
# the GUI is run.
if self.__version == 6:
for base in HKEYS:
if read_values(base, r"%s\6.0" % self.__root) is not None:
self.warn("It seems you have Visual Studio 6 installed, "
"but the expected registry settings are not present.\n"
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"so that these entries are created.")
break
return [] | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/optimize/_trustregion_exact.py | python | gershgorin_bounds | (H) | return lb, ub | Given a square matrix ``H`` compute upper
and lower bounds for its eigenvalues (Gregoshgorin Bounds).
Defined ref. [1].
References
----------
.. [1] Conn, A. R., Gould, N. I., & Toint, P. L.
Trust region methods. 2000. Siam. pp. 19. | Given a square matrix ``H`` compute upper
and lower bounds for its eigenvalues (Gregoshgorin Bounds).
Defined ref. [1]. | [
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"""
Given a square matrix ``H`` compute upper
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Defined ref. [1].
References
----------
.. [1] Conn, A. R., Gould, N. I., & Toint, P. L.
Trust region methods. 2000. Siam. pp. 19.
"""
H_diag = np.diag(H)
H_diag_abs = np.abs(H_diag)
H_row_sums = np.sum(np.abs(H), axis=1)
lb = np.min(H_diag + H_diag_abs - H_row_sums)
ub = np.max(H_diag - H_diag_abs + H_row_sums)
return lb, ub | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_gdi.py | python | DC.DeviceToLogicalX | (*args, **kwargs) | return _gdi_.DC_DeviceToLogicalX(*args, **kwargs) | DeviceToLogicalX(self, int x) -> int
Convert device X coordinate to logical coordinate, using the current
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"""
DeviceToLogicalX(self, int x) -> int
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"""
return _gdi_.DC_DeviceToLogicalX(*args, **kwargs) | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/framework/ops.py | python | Operation._set_device | (self, device) | Set the device of this operation.
Args:
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/core/arrays/datetimelike.py | python | DatetimeLikeArrayMixin._time_shift | (self, periods, freq=None) | return self._generate_range(start=start, end=end, periods=None,
freq=self.freq) | Shift each value by `periods`.
Note this is different from ExtensionArray.shift, which
shifts the *position* of each element, padding the end with
missing values.
Parameters
----------
periods : int
Number of periods to shift by.
freq : pandas.DateOffset, pandas.Timedelta, or string
Frequency increment to shift by. | Shift each value by `periods`. | [
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"""
Shift each value by `periods`.
Note this is different from ExtensionArray.shift, which
shifts the *position* of each element, padding the end with
missing values.
Parameters
----------
periods : int
Number of periods to shift by.
freq : pandas.DateOffset, pandas.Timedelta, or string
Frequency increment to shift by.
"""
if freq is not None and freq != self.freq:
if isinstance(freq, compat.string_types):
freq = frequencies.to_offset(freq)
offset = periods * freq
result = self + offset
return result
if periods == 0:
# immutable so OK
return self.copy()
if self.freq is None:
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start = self[0] + periods * self.freq
end = self[-1] + periods * self.freq
# Note: in the DatetimeTZ case, _generate_range will infer the
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/autograph/utils/type_check.py | python | is_tensor | (*args) | return any(tensor_util.is_tensor(a) for a in args) | Check if any arguments are tensors.
Args:
*args: Python objects that may or may not be tensors.
Returns:
True if any *args are TensorFlow types, False if none are. | Check if any arguments are tensors. | [
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alexgkendall/caffe-posenet | 62aafbd7c45df91acdba14f5d1406d8295c2bc6f | scripts/cpp_lint.py | python | _DropCommonSuffixes | (filename) | return os.path.splitext(filename)[0] | Drops common suffixes like _test.cc or -inl.h from filename.
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okex/V3-Open-API-SDK | c5abb0db7e2287718e0055e17e57672ce0ec7fd9 | okex-python-sdk-api/venv/Lib/site-packages/pip-19.0.3-py3.8.egg/pip/_internal/vcs/__init__.py | python | RevOptions.make_new | (self, rev) | return self.vcs.make_rev_options(rev, extra_args=self.extra_args) | Make a copy of the current instance, but with a new rev.
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/ao/quantization/_learnable_fake_quantize.py | python | _LearnableFakeQuantize.enable_static_estimate | (self) | r"""Enables static observer estimates and disbales learning of
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swift/swift | 12d031cf8177fdec0137f9aa7e2912fa23c4416b | 3rdParty/SCons/scons-3.0.1/engine/SCons/CacheDir.py | python | CacheDir.retrieve | (self, node) | return False | This method is called from multiple threads in a parallel build,
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adobe/chromium | cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7 | third_party/tlslite/tlslite/X509.py | python | X509.parse | (self, s) | return self | Parse a PEM-encoded X.509 certificate.
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/ops/_op_impl/tbe/layer_norm_beta_gamma_backprop_ds.py | python | _layer_norm_beta_gamma_backprop_ds_tbe | () | return | LayerNormBetaGammaBackprop TBE register | LayerNormBetaGammaBackprop TBE register | [
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adobe/chromium | cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7 | third_party/protobuf/python/mox.py | python | MockAnything.__getattr__ | (self, method_name) | return self._CreateMockMethod(method_name) | Intercept method calls on this object.
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_x86_64/python2.7/dist-packages/numpy/core/numeric.py | python | geterrcall | () | return umath.geterrobj()[2] | Return the current callback function used on floating-point errors.
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Floating point error (divide by zero), with flag 1
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/tornado/tornado-6/tornado/options.py | python | OptionParser.mockable | (self) | return _Mockable(self) | Returns a wrapper around self that is compatible with
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/llbuild/bindings/python/llbuild.py | python | BuildEngine.task_discovered_dependency | (self, task, key) | \
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/contrib/session_bundle/exporter.py | python | Exporter._file_path_value | (self, path_tensor) | return str_value[0] | Returns the filepath value stored in constant `path_tensor`. | Returns the filepath value stored in constant `path_tensor`. | [
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] | def _file_path_value(self, path_tensor):
"""Returns the filepath value stored in constant `path_tensor`."""
if not isinstance(path_tensor, ops.Tensor):
raise TypeError("tensor is not a Tensor")
if path_tensor.op.type != "Const":
raise TypeError("Only constants tensor are supported")
if path_tensor.dtype != dtypes.string:
raise TypeError("File paths should be string")
str_value = path_tensor.op.get_attr("value").string_val
if len(str_value) != 1:
raise TypeError("Only scalar tensors are supported")
return str_value[0] | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_core.py | python | MouseEvent.GetWheelDelta | (*args, **kwargs) | return _core_.MouseEvent_GetWheelDelta(*args, **kwargs) | GetWheelDelta(self) -> int
Get wheel delta, normally 120. This is the threshold for action to be
taken, and one such action (for example, scrolling one increment)
should occur for each delta. | GetWheelDelta(self) -> int | [
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"""
GetWheelDelta(self) -> int
Get wheel delta, normally 120. This is the threshold for action to be
taken, and one such action (for example, scrolling one increment)
should occur for each delta.
"""
return _core_.MouseEvent_GetWheelDelta(*args, **kwargs) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/syntax/_latex.py | python | SyntaxData.GetCommentPattern | (self) | return [u'%'] | Returns a list of characters used to comment a block of code | Returns a list of characters used to comment a block of code | [
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/draftguitools/gui_splines.py | python | BSpline.GetResources | (self) | return {'Pixmap': 'Draft_BSpline',
'Accel': "B, S",
'MenuText': QT_TRANSLATE_NOOP("Draft_BSpline", "B-spline"),
'ToolTip': QT_TRANSLATE_NOOP("Draft_BSpline", "Creates a multiple-point B-spline. CTRL to snap, SHIFT to constrain.")} | Set icon, menu and tooltip. | Set icon, menu and tooltip. | [
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] | def GetResources(self):
"""Set icon, menu and tooltip."""
return {'Pixmap': 'Draft_BSpline',
'Accel': "B, S",
'MenuText': QT_TRANSLATE_NOOP("Draft_BSpline", "B-spline"),
'ToolTip': QT_TRANSLATE_NOOP("Draft_BSpline", "Creates a multiple-point B-spline. CTRL to snap, SHIFT to constrain.")} | [
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kevin-ssy/Optical-Flow-Guided-Feature | 07d4501a29002ee7821c38c1820e4a64c1acf6e8 | lib/caffe-action/scripts/cpp_lint.py | python | CheckIncludeLine | (filename, clean_lines, linenum, include_state, error) | Check rules that are applicable to #include lines.
Strings on #include lines are NOT removed from elided line, to make
certain tasks easier. However, to prevent false positives, checks
applicable to #include lines in CheckLanguage must be put here.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
include_state: An _IncludeState instance in which the headers are inserted.
error: The function to call with any errors found. | Check rules that are applicable to #include lines. | [
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] | def CheckIncludeLine(filename, clean_lines, linenum, include_state, error):
"""Check rules that are applicable to #include lines.
Strings on #include lines are NOT removed from elided line, to make
certain tasks easier. However, to prevent false positives, checks
applicable to #include lines in CheckLanguage must be put here.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
include_state: An _IncludeState instance in which the headers are inserted.
error: The function to call with any errors found.
"""
fileinfo = FileInfo(filename)
line = clean_lines.lines[linenum]
# "include" should use the new style "foo/bar.h" instead of just "bar.h"
if _RE_PATTERN_INCLUDE_NEW_STYLE.search(line):
error(filename, linenum, 'build/include_dir', 4,
'Include the directory when naming .h files')
# we shouldn't include a file more than once. actually, there are a
# handful of instances where doing so is okay, but in general it's
# not.
match = _RE_PATTERN_INCLUDE.search(line)
if match:
include = match.group(2)
is_system = (match.group(1) == '<')
if include in include_state:
error(filename, linenum, 'build/include', 4,
'"%s" already included at %s:%s' %
(include, filename, include_state[include]))
else:
include_state[include] = linenum
# We want to ensure that headers appear in the right order:
# 1) for foo.cc, foo.h (preferred location)
# 2) c system files
# 3) cpp system files
# 4) for foo.cc, foo.h (deprecated location)
# 5) other google headers
#
# We classify each include statement as one of those 5 types
# using a number of techniques. The include_state object keeps
# track of the highest type seen, and complains if we see a
# lower type after that.
error_message = include_state.CheckNextIncludeOrder(
_ClassifyInclude(fileinfo, include, is_system))
if error_message:
error(filename, linenum, 'build/include_order', 4,
'%s. Should be: %s.h, c system, c++ system, other.' %
(error_message, fileinfo.BaseName()))
canonical_include = include_state.CanonicalizeAlphabeticalOrder(include)
if not include_state.IsInAlphabeticalOrder(
clean_lines, linenum, canonical_include):
error(filename, linenum, 'build/include_alpha', 4,
'Include "%s" not in alphabetical order' % include)
include_state.SetLastHeader(canonical_include)
# Look for any of the stream classes that are part of standard C++.
match = _RE_PATTERN_INCLUDE.match(line)
if match:
include = match.group(2)
if Match(r'(f|ind|io|i|o|parse|pf|stdio|str|)?stream$', include):
# Many unit tests use cout, so we exempt them.
if not _IsTestFilename(filename):
error(filename, linenum, 'readability/streams', 3,
'Streams are highly discouraged.') | [
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thalium/icebox | 99d147d5b9269222225443ce171b4fd46d8985d4 | third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2.py | python | uCSIsCatLm | (code) | return ret | Check whether the character is part of Lm UCS Category | Check whether the character is part of Lm UCS Category | [
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] | def uCSIsCatLm(code):
"""Check whether the character is part of Lm UCS Category """
ret = libxml2mod.xmlUCSIsCatLm(code)
return ret | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py2/IPython/utils/_signatures.py | python | Signature.bind | (self, *args, **kwargs) | return self._bind(args, kwargs) | Get a :class:`BoundArguments` object, that maps the passed `args`
and `kwargs` to the function's signature. Raises :exc:`TypeError`
if the passed arguments can not be bound. | Get a :class:`BoundArguments` object, that maps the passed `args`
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] | def bind(self, *args, **kwargs):
'''Get a :class:`BoundArguments` object, that maps the passed `args`
and `kwargs` to the function's signature. Raises :exc:`TypeError`
if the passed arguments can not be bound.
'''
return self._bind(args, kwargs) | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/estimator/training.py | python | _TrainingExecutor.run_chief | (self) | return self._start_distributed_training() | Runs task chief. | Runs task chief. | [
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] | def run_chief(self):
"""Runs task chief."""
# TODO(xiejw): To allow execution framework to add train hooks.
return self._start_distributed_training() | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/toml/toml/encoder.py | python | dumps | (o, encoder=None) | return retval | Stringifies input dict as toml
Args:
o: Object to dump into toml
encoder: The ``TomlEncoder`` to use for constructing the output string
Returns:
String containing the toml corresponding to dict
Examples:
```python
>>> import toml
>>> output = {
... 'a': "I'm a string",
... 'b': ["I'm", "a", "list"],
... 'c': 2400
... }
>>> toml.dumps(output)
'a = "I\'m a string"\nb = [ "I\'m", "a", "list",]\nc = 2400\n'
``` | Stringifies input dict as toml | [
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] | def dumps(o, encoder=None):
"""Stringifies input dict as toml
Args:
o: Object to dump into toml
encoder: The ``TomlEncoder`` to use for constructing the output string
Returns:
String containing the toml corresponding to dict
Examples:
```python
>>> import toml
>>> output = {
... 'a': "I'm a string",
... 'b': ["I'm", "a", "list"],
... 'c': 2400
... }
>>> toml.dumps(output)
'a = "I\'m a string"\nb = [ "I\'m", "a", "list",]\nc = 2400\n'
```
"""
retval = ""
if encoder is None:
encoder = TomlEncoder(o.__class__)
addtoretval, sections = encoder.dump_sections(o, "")
retval += addtoretval
outer_objs = [id(o)]
while sections:
section_ids = [id(section) for section in sections.values()]
for outer_obj in outer_objs:
if outer_obj in section_ids:
raise ValueError("Circular reference detected")
outer_objs += section_ids
newsections = encoder.get_empty_table()
for section in sections:
addtoretval, addtosections = encoder.dump_sections(
sections[section], section)
if addtoretval or (not addtoretval and not addtosections):
if retval and retval[-2:] != "\n\n":
retval += "\n"
retval += "[" + section + "]\n"
if addtoretval:
retval += addtoretval
for s in addtosections:
newsections[section + "." + s] = addtosections[s]
sections = newsections
return retval | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/ctypeslib.py | python | _concrete_ndptr.contents | (self) | return frombuffer(buffer, dtype=full_dtype).squeeze(axis=0) | Get an ndarray viewing the data pointed to by this pointer.
This mirrors the `contents` attribute of a normal ctypes pointer | Get an ndarray viewing the data pointed to by this pointer. | [
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"""
Get an ndarray viewing the data pointed to by this pointer.
This mirrors the `contents` attribute of a normal ctypes pointer
"""
full_dtype = _dtype((self._dtype_, self._shape_))
full_ctype = ctypes.c_char * full_dtype.itemsize
buffer = ctypes.cast(self, ctypes.POINTER(full_ctype)).contents
return frombuffer(buffer, dtype=full_dtype).squeeze(axis=0) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/lib2to3/pgen2/grammar.py | python | Grammar.copy | (self) | return new | Copy the grammar. | Copy the grammar. | [
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Copy the grammar.
"""
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setattr(new, dict_attr, getattr(self, dict_attr).copy())
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new.states = self.states[:]
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_core.py | python | App_CleanUp | (*args) | return _core_.App_CleanUp(*args) | App_CleanUp()
For internal use only, it is used to cleanup after wxWidgets when
Python shuts down. | App_CleanUp() | [
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] | def App_CleanUp(*args):
"""
App_CleanUp()
For internal use only, it is used to cleanup after wxWidgets when
Python shuts down.
"""
return _core_.App_CleanUp(*args) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/polynomial/polynomial.py | python | polymulx | (c) | return prd | Multiply a polynomial by x.
Multiply the polynomial `c` by x, where x is the independent
variable.
Parameters
----------
c : array_like
1-D array of polynomial coefficients ordered from low to
high.
Returns
-------
out : ndarray
Array representing the result of the multiplication.
See Also
--------
polyadd, polysub, polymul, polydiv, polypow
Notes
-----
.. versionadded:: 1.5.0 | Multiply a polynomial by x. | [
"Multiply",
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"polynomial",
"by",
"x",
"."
] | def polymulx(c):
"""Multiply a polynomial by x.
Multiply the polynomial `c` by x, where x is the independent
variable.
Parameters
----------
c : array_like
1-D array of polynomial coefficients ordered from low to
high.
Returns
-------
out : ndarray
Array representing the result of the multiplication.
See Also
--------
polyadd, polysub, polymul, polydiv, polypow
Notes
-----
.. versionadded:: 1.5.0
"""
# c is a trimmed copy
[c] = pu.as_series([c])
# The zero series needs special treatment
if len(c) == 1 and c[0] == 0:
return c
prd = np.empty(len(c) + 1, dtype=c.dtype)
prd[0] = c[0]*0
prd[1:] = c
return prd | [
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NVIDIA/TensorRT | 42805f078052daad1a98bc5965974fcffaad0960 | samples/python/efficientnet/build_engine.py | python | EngineCalibrator.set_image_batcher | (self, image_batcher: ImageBatcher) | Define the image batcher to use, if any. If using only the cache file, an image batcher doesn't need
to be defined.
:param image_batcher: The ImageBatcher object | Define the image batcher to use, if any. If using only the cache file, an image batcher doesn't need
to be defined.
:param image_batcher: The ImageBatcher object | [
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"""
Define the image batcher to use, if any. If using only the cache file, an image batcher doesn't need
to be defined.
:param image_batcher: The ImageBatcher object
"""
self.image_batcher = image_batcher
size = int(np.dtype(self.image_batcher.dtype).itemsize * np.prod(self.image_batcher.shape))
self.batch_allocation = cuda.mem_alloc(size)
self.batch_generator = self.image_batcher.get_batch() | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/training/basic_session_run_hooks.py | python | NanTensorHook.__init__ | (self, loss_tensor, fail_on_nan_loss=True) | Initializes NanLoss monitor.
Args:
loss_tensor: `Tensor`, the loss tensor.
fail_on_nan_loss: `bool`, whether to raise exception when loss is NaN. | Initializes NanLoss monitor. | [
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] | def __init__(self, loss_tensor, fail_on_nan_loss=True):
"""Initializes NanLoss monitor.
Args:
loss_tensor: `Tensor`, the loss tensor.
fail_on_nan_loss: `bool`, whether to raise exception when loss is NaN.
"""
self._loss_tensor = loss_tensor
self._fail_on_nan_loss = fail_on_nan_loss | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/nntplib.py | python | _NNTPBase.xhdr | (self, hdr, str, *, file=None) | return resp, [remove_number(line) for line in lines] | Process an XHDR command (optional server extension). Arguments:
- hdr: the header type (e.g. 'subject')
- str: an article nr, a message id, or a range nr1-nr2
- file: Filename string or file object to store the result in
Returns:
- resp: server response if successful
- list: list of (nr, value) strings | Process an XHDR command (optional server extension). Arguments:
- hdr: the header type (e.g. 'subject')
- str: an article nr, a message id, or a range nr1-nr2
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Returns:
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- str: an article nr, a message id, or a range nr1-nr2
- file: Filename string or file object to store the result in
Returns:
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"""
pat = re.compile('^([0-9]+) ?(.*)\n?')
resp, lines = self._longcmdstring('XHDR {0} {1}'.format(hdr, str), file)
def remove_number(line):
m = pat.match(line)
return m.group(1, 2) if m else line
return resp, [remove_number(line) for line in lines] | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/inspect.py | python | _signature_strip_non_python_syntax | (signature) | return clean_signature, self_parameter, last_positional_only | Private helper function. Takes a signature in Argument Clinic's
extended signature format.
Returns a tuple of three things:
* that signature re-rendered in standard Python syntax,
* the index of the "self" parameter (generally 0), or None if
the function does not have a "self" parameter, and
* the index of the last "positional only" parameter,
or None if the signature has no positional-only parameters. | Private helper function. Takes a signature in Argument Clinic's
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"""
Private helper function. Takes a signature in Argument Clinic's
extended signature format.
Returns a tuple of three things:
* that signature re-rendered in standard Python syntax,
* the index of the "self" parameter (generally 0), or None if
the function does not have a "self" parameter, and
* the index of the last "positional only" parameter,
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"""
if not signature:
return signature, None, None
self_parameter = None
last_positional_only = None
lines = [l.encode('ascii') for l in signature.split('\n')]
generator = iter(lines).__next__
token_stream = tokenize.tokenize(generator)
delayed_comma = False
skip_next_comma = False
text = []
add = text.append
current_parameter = 0
OP = token.OP
ERRORTOKEN = token.ERRORTOKEN
# token stream always starts with ENCODING token, skip it
t = next(token_stream)
assert t.type == tokenize.ENCODING
for t in token_stream:
type, string = t.type, t.string
if type == OP:
if string == ',':
if skip_next_comma:
skip_next_comma = False
else:
assert not delayed_comma
delayed_comma = True
current_parameter += 1
continue
if string == '/':
assert not skip_next_comma
assert last_positional_only is None
skip_next_comma = True
last_positional_only = current_parameter - 1
continue
if (type == ERRORTOKEN) and (string == '$'):
assert self_parameter is None
self_parameter = current_parameter
continue
if delayed_comma:
delayed_comma = False
if not ((type == OP) and (string == ')')):
add(', ')
add(string)
if (string == ','):
add(' ')
clean_signature = ''.join(text)
return clean_signature, self_parameter, last_positional_only | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/xlsgrid.py | python | XLSRichText.__init__ | (self, book, cell, xf_index, display_text=None, hyperlink=None, rich_text=None, default_width=10) | Default class constructor.
:param `book`: an instance of the `xlrd.Book` class;
:param `cell`: an instance of `xlrd.sheet.Cell` class;
:param `xf_index`: an index into `xlrd.Book.xf_list`, which holds a
reference to the `xlrd.sheet.Cell` class (the actual cell for `xlrd`);
:param `display_text`: if Mark Hammonds' `pywin32` package is available,
this is the WYSIWYG cell content;
:param `hyperlink`: if this cell contains a hyperlink, it will be displayed
accordingly;
:param `rich_text`: if this cell contains text in rich text format, :class:`XLSGrid`
will do its best to render the text as rich text;
:param `default_width`: this is the default width of the text in 1/256
of the width of the zero character, using default Excel font (first FONT
record in the Excel file).
:note: If you are using version 0.7.1 or lower for `xlrd`, the *hyperlink*
parameter will always be ``None`` as this feature is available only in
`xlrd` 0.7.2 (SVN).
:note: If you are using version 0.7.1 or lower for `xlrd`, this class will
note be used by :class:`XLSGrid`.
.. warning::
This class currently supports only single-line non-rotated text,
and it discards properties like `shrink-to-fit` and `wrapping`. | Default class constructor. | [
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"""
Default class constructor.
:param `book`: an instance of the `xlrd.Book` class;
:param `cell`: an instance of `xlrd.sheet.Cell` class;
:param `xf_index`: an index into `xlrd.Book.xf_list`, which holds a
reference to the `xlrd.sheet.Cell` class (the actual cell for `xlrd`);
:param `display_text`: if Mark Hammonds' `pywin32` package is available,
this is the WYSIWYG cell content;
:param `hyperlink`: if this cell contains a hyperlink, it will be displayed
accordingly;
:param `rich_text`: if this cell contains text in rich text format, :class:`XLSGrid`
will do its best to render the text as rich text;
:param `default_width`: this is the default width of the text in 1/256
of the width of the zero character, using default Excel font (first FONT
record in the Excel file).
:note: If you are using version 0.7.1 or lower for `xlrd`, the *hyperlink*
parameter will always be ``None`` as this feature is available only in
`xlrd` 0.7.2 (SVN).
:note: If you are using version 0.7.1 or lower for `xlrd`, this class will
note be used by :class:`XLSGrid`.
.. warning::
This class currently supports only single-line non-rotated text,
and it discards properties like `shrink-to-fit` and `wrapping`.
"""
XLSText.__init__(self, book, cell, xf_index, display_text, hyperlink, default_width)
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/node-10.15.3/deps/v8/third_party/jinja2/compiler.py | python | CodeGenerator.push_parameter_definitions | (self, frame) | Pushes all parameter targets from the given frame into a local
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/stc.py | python | StyledTextCtrl.SetEdgeMode | (*args, **kwargs) | return _stc.StyledTextCtrl_SetEdgeMode(*args, **kwargs) | SetEdgeMode(self, int mode)
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artyom-beilis/cppcms | 463a9a68e0bc15e2d01e8b8d72cc4fcc7f2b3264 | contrib/integration/session/python/cppcms.py | python | Session.session_cookie_name | (self) | return r | Get the name of the cookie that is used to store CppCMS session
Note: the value of this cookie should be passed to load method
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"""
Get the name of the cookie that is used to store CppCMS session
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/examples/skflow/text_classification_cnn.py | python | cnn_model | (x, y) | return {'class': tf.argmax(prediction, 1), 'prob': prediction}, loss, train_op | 2 layer Convolutional network to predict from sequence of words
to a class. | 2 layer Convolutional network to predict from sequence of words
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"""2 layer Convolutional network to predict from sequence of words
to a class."""
# Convert indexes of words into embeddings.
# This creates embeddings matrix of [n_words, EMBEDDING_SIZE] and then
# maps word indexes of the sequence into [batch_size, sequence_length,
# EMBEDDING_SIZE].
y = tf.one_hot(y, 15, 1, 0)
word_vectors = learn.ops.categorical_variable(x, n_classes=n_words,
embedding_size=EMBEDDING_SIZE, name='words')
word_vectors = tf.expand_dims(word_vectors, 3)
with tf.variable_scope('CNN_Layer1'):
# Apply Convolution filtering on input sequence.
conv1 = tf.contrib.layers.convolution2d(word_vectors, N_FILTERS,
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# Add a RELU for non linearity.
conv1 = tf.nn.relu(conv1)
# Max pooling across output of Convolution+Relu.
pool1 = tf.nn.max_pool(conv1, ksize=[1, POOLING_WINDOW, 1, 1],
strides=[1, POOLING_STRIDE, 1, 1], padding='SAME')
# Transpose matrix so that n_filters from convolution becomes width.
pool1 = tf.transpose(pool1, [0, 1, 3, 2])
with tf.variable_scope('CNN_Layer2'):
# Second level of convolution filtering.
conv2 = tf.contrib.layers.convolution2d(pool1, N_FILTERS,
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# Max across each filter to get useful features for classification.
pool2 = tf.squeeze(tf.reduce_max(conv2, 1), squeeze_dims=[1])
# Apply regular WX + B and classification.
prediction, loss = learn.models.logistic_regression(pool2, y)
train_op = tf.contrib.layers.optimize_loss(
loss, tf.contrib.framework.get_global_step(),
optimizer='Adam', learning_rate=0.01)
return {'class': tf.argmax(prediction, 1), 'prob': prediction}, loss, train_op | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/stc.py | python | StyledTextCtrl.GetPasteConvertEndings | (*args, **kwargs) | return _stc.StyledTextCtrl_GetPasteConvertEndings(*args, **kwargs) | GetPasteConvertEndings(self) -> bool
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gnuradio/gnuradio | 09c3c4fa4bfb1a02caac74cb5334dfe065391e3b | gr-utils/modtool/core/base.py | python | ModTool._validate | (self) | Validates the arguments | Validates the arguments | [
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oracle/graaljs | 36a56e8e993d45fc40939a3a4d9c0c24990720f1 | graal-nodejs/tools/inspector_protocol/jinja2/lexer.py | python | Token.test | (self, expr) | return False | Test a token against a token expression. This can either be a
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/clang/bindings/python/clang/cindex.py | python | Type.translation_unit | (self) | return self._tu | The TranslationUnit to which this Type is associated. | The TranslationUnit to which this Type is associated. | [
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PixarAnimationStudios/USD | faed18ce62c8736b02413635b584a2f637156bad | pxr/usdImaging/usdviewq/appController.py | python | AppController._updateForStageChanges | (self, hasPrimResync=True) | Assuming there have been authoring changes to the already-loaded
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pyne/pyne | 0c2714d7c0d1b5e20be6ae6527da2c660dd6b1b3 | pyne/partisn.py | python | _get_xs_names | (mat_xs_names) | return list(xs_names) | Create list of names (strings) of the nuclides that appear in the cross
section library from the list of nuc_names. | Create list of names (strings) of the nuclides that appear in the cross
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xs_names = set()
list(map(xs_names.update, mat_xs_names.values()))
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/_pydecimal.py | python | Context.clear_flags | (self) | Reset all flags to zero | Reset all flags to zero | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/route53/connection.py | python | Route53Connection._make_qualified | (self, value) | Ensure passed domain names end in a period (.) character.
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Ensure passed domain names end in a period (.) character.
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if type(value) in [list, tuple, set]:
new_list = []
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/hfctables.py | python | UBMatrixPeakTable.__init__ | (self, parent) | return | Initialization
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"""
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self._cachedSpiceHKL = dict()
# class variables for column indexes
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self._colIndexWavelength = None
self._colIndexError = None
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xenia-project/xenia | 9b1fdac98665ac091b9660a5d0fbb259ed79e578 | third_party/google-styleguide/cpplint/cpplint.py | python | CheckMakePairUsesDeduction | (filename, clean_lines, linenum, error) | Check that make_pair's template arguments are deduced.
G++ 4.6 in C++11 mode fails badly if make_pair's template arguments are
specified explicitly, and such use isn't intended in any case.
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. | Check that make_pair's template arguments are deduced. | [
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"""Check that make_pair's template arguments are deduced.
G++ 4.6 in C++11 mode fails badly if make_pair's template arguments are
specified explicitly, and such use isn't intended in any case.
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.
"""
line = clean_lines.elided[linenum]
match = _RE_PATTERN_EXPLICIT_MAKEPAIR.search(line)
if match:
error(filename, linenum, 'build/explicit_make_pair',
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/distributed/elastic/rendezvous/etcd_server.py | python | EtcdServer.get_client | (self) | return etcd.Client(
host=self._host, port=self._port, version_prefix="/v2", read_timeout=10
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"""
Returns:
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"""
return etcd.Client(
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SFTtech/openage | d6a08c53c48dc1e157807471df92197f6ca9e04d | openage/util/observer.py | python | Observable.get_observer_count | (self) | return len(self.observers) | Return the number of registered observers. | Return the number of registered observers. | [
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CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Editor/Python/windows/Lib/site-packages/pip/_vendor/distlib/_backport/tarfile.py | python | TarIter.__init__ | (self, tarfile) | Construct a TarIter object. | Construct a TarIter object. | [
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macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/tools/gyp/pylib/gyp/xcodeproj_file.py | python | XCBuildPhase._AddPathToDict | (self, pbxbuildfile, path) | Adds path to the dict tracking paths belonging to this build phase.
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"""
if path in self._files_by_path:
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self._files_by_path[path] = pbxbuildfile | [
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PrincetonUniversity/athena-public-version | 9c266692b9423743d8e23509b3ab266a232a92d2 | tst/style/cpplint.py | python | _Quiet | () | return _cpplint_state.quiet | Return's the module's quiet setting. | Return's the module's quiet setting. | [
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gnuradio/gnuradio | 09c3c4fa4bfb1a02caac74cb5334dfe065391e3b | grc/core/blocks/block.py | python | Block.type_controller_modify | (self, direction) | return changed | Change the type controller.
Args:
direction: +1 or -1
Returns:
true for change | Change the type controller. | [
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"""
Change the type controller.
Args:
direction: +1 or -1
Returns:
true for change
"""
changed = False
type_param = None
for param in filter(lambda p: p.is_enum(), self.get_params()):
children = self.get_ports() + self.get_params()
# Priority to the type controller
if param.get_key() in ' '.join(map(lambda p: p._type, children)): type_param = param
# Use param if type param is unset
if not type_param:
type_param = param
if type_param:
# Try to increment the enum by direction
try:
keys = type_param.get_option_keys()
old_index = keys.index(type_param.get_value())
new_index = (old_index + direction + len(keys)) % len(keys)
type_param.set_value(keys[new_index])
changed = True
except:
pass
return changed | [
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | src/python/turicreate/data_structures/sarray.py | python | SArray.shape | (self) | return (len(self),) | The shape of the SArray, in a tuple. The first entry is the number of
rows.
Examples
--------
>>> sa = turicreate.SArray([1,2,3])
>>> sa.shape
(3,) | The shape of the SArray, in a tuple. The first entry is the number of
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"""
The shape of the SArray, in a tuple. The first entry is the number of
rows.
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>>> sa = turicreate.SArray([1,2,3])
>>> sa.shape
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return (len(self),) | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/vis/glprogram.py | python | GLProgram.run | (self) | Starts a new event loop with this object as the main program.
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visualization.setWindowTitle(self.name)
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/multiprocessing/pool.py | python | Pool.apply | (self, func, args=(), kwds={}) | return self.apply_async(func, args, kwds).get() | Equivalent of `func(*args, **kwds)`.
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'''
Equivalent of `func(*args, **kwds)`.
Pool must be running.
'''
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py3/numpy/polynomial/chebyshev.py | python | _zseries_int | (zs) | return zs | Integrate a z-series.
The integral is with respect to x, not z. This is achieved by a change
of variable using dx/dz given in the module notes.
Parameters
----------
zs : z-series
The z-series to integrate
Returns
-------
integral : z-series
The indefinite integral
Notes
-----
The zseries for x (ns) has been multiplied by two in order to avoid
using floats that are incompatible with Decimal and likely other
specialized scalar types. This scaling has been compensated by
dividing the resulting zs by two. | Integrate a z-series. | [
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] | def _zseries_int(zs):
"""Integrate a z-series.
The integral is with respect to x, not z. This is achieved by a change
of variable using dx/dz given in the module notes.
Parameters
----------
zs : z-series
The z-series to integrate
Returns
-------
integral : z-series
The indefinite integral
Notes
-----
The zseries for x (ns) has been multiplied by two in order to avoid
using floats that are incompatible with Decimal and likely other
specialized scalar types. This scaling has been compensated by
dividing the resulting zs by two.
"""
n = 1 + len(zs)//2
ns = np.array([-1, 0, 1], dtype=zs.dtype)
zs = _zseries_mul(zs, ns)
div = np.arange(-n, n+1)*2
zs[:n] /= div[:n]
zs[n+1:] /= div[n+1:]
zs[n] = 0
return zs | [
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | site_scons/libdeps.py | python | LibdepLinter._make_linter_decorator | () | return linter_rule_func | This is used for gathering the functions
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"""
This is used for gathering the functions
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funcs = {}
def linter_rule_func(func):
funcs[func.__name__] = func
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linter_rule_func.all = funcs
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_core.py | python | PyApp_SetMacPreferencesMenuItemId | (*args, **kwargs) | return _core_.PyApp_SetMacPreferencesMenuItemId(*args, **kwargs) | PyApp_SetMacPreferencesMenuItemId(long val) | PyApp_SetMacPreferencesMenuItemId(long val) | [
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Path/PathScripts/PathWaterline.py | python | ObjectWaterline._extractWaterlines | (self, obj, oclScan, lyr, layDep) | return loopList | _extractWaterlines(obj, oclScan, lyr, layDep) ... Extract water lines from OCL scan data. | _extractWaterlines(obj, oclScan, lyr, layDep) ... Extract water lines from OCL scan data. | [
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"""_extractWaterlines(obj, oclScan, lyr, layDep) ... Extract water lines from OCL scan data."""
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lastLn = len(self.topoMap) - 1
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while srch is True:
srch = False
if srchCnt > maxSrchs:
PathLog.debug(
"Max search scans, "
+ str(maxSrchs)
+ " reached\nPossible incomplete waterline result!"
)
break
for L in range(1, lastLn):
for P in range(1, lastPnt):
if self.topoMap[L][P] == 1:
# start loop follow
srch = True
loopNum += 1
loop = self._trackLoop(oclScan, lC, pC, L, P, loopNum)
self.topoMap[L][P] = 0 # Mute the starting point
loopList.append(loop)
srchCnt += 1
PathLog.debug(
"Search count for layer "
+ str(lyr)
+ " is "
+ str(srchCnt)
+ ", with "
+ str(loopNum)
+ " loops."
)
return loopList | [
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facebookresearch/mvfst-rl | 778bc4259ae7277e67c2ead593a493845c93db83 | scripts/plotting/plot_sweep.py | python | flags_to_set | (flags: Dict) | return {(k, tuple(v) if isinstance(v, list) else v)
for k, v in flags.items()} | Turn a dictionary of settings into a set of unique (key, value) pairs | Turn a dictionary of settings into a set of unique (key, value) pairs | [
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"""Turn a dictionary of settings into a set of unique (key, value) pairs"""
# The tricky part is that some flags may be lists, that are not hashable.
# We convert them to tuples here.
return {(k, tuple(v) if isinstance(v, list) else v)
for k, v in flags.items()} | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/ros_comm/roslaunch/src/roslaunch/parent.py | python | ROSLaunchParent.start | (self, auto_terminate=True) | Run the parent roslaunch.
@param auto_terminate: stop process monitor once there are no
more processes to monitor (default True). This defaults to
True, which is the command-line behavior of roslaunch. Scripts
may wish to set this to False if they wish to keep the
roslauch infrastructure up regardless of processes being
monitored. | Run the parent roslaunch. | [
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] | def start(self, auto_terminate=True):
"""
Run the parent roslaunch.
@param auto_terminate: stop process monitor once there are no
more processes to monitor (default True). This defaults to
True, which is the command-line behavior of roslaunch. Scripts
may wish to set this to False if they wish to keep the
roslauch infrastructure up regardless of processes being
monitored.
"""
self.logger.info("starting roslaunch parent run")
# load config, start XMLRPC servers and process monitor
try:
self._start_infrastructure()
except:
# infrastructure did not initialize, do teardown on whatever did come up
self._stop_infrastructure()
raise
# Initialize the actual runner.
# Requires config, pm, server and remote_runner
self._init_runner()
# Start the launch
self.runner.launch()
# inform process monitor that we are done with process registration
if auto_terminate:
self.pm.registrations_complete()
self.logger.info("... roslaunch parent running, waiting for process exit")
if self.process_listeners:
for l in self.process_listeners:
self.runner.pm.add_process_listener(l) | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/parallel_for/pfor.py | python | WhileOp.pfor_converter | (self) | return self | Return a converter for the while loop. | Return a converter for the while loop. | [
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"""Return a converter for the while loop."""
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stitchEm/stitchEm | 0f399501d41ab77933677f2907f41f80ceb704d7 | lib/bindings/samples/server/glfw.py | python | get_version_string | () | return _glfw.glfwGetVersionString() | Returns a string describing the compile-time configuration.
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const char* glfwGetVersionString(void); | Returns a string describing the compile-time configuration. | [
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"""
Returns a string describing the compile-time configuration.
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const char* glfwGetVersionString(void);
"""
return _glfw.glfwGetVersionString() | [
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baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/contrib/keras/python/keras/engine/topology.py | python | Container.save_weights | (self, filepath, overwrite=True) | Dumps all layer weights to a HDF5 file.
The weight file has:
- `layer_names` (attribute), a list of strings
(ordered names of model layers).
- For every layer, a `group` named `layer.name`
- For every such layer group, a group attribute `weight_names`,
a list of strings
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- For every weight in the layer, a dataset
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Arguments:
filepath: String, path to the file to save the weights to.
overwrite: Whether to silently overwrite any existing file at the
target location, or provide the user with a manual prompt.
Raises:
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"""Dumps all layer weights to a HDF5 file.
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(ordered names of model layers).
- For every layer, a `group` named `layer.name`
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target location, or provide the user with a manual prompt.
Raises:
ImportError: If h5py is not available.
"""
if h5py is None:
raise ImportError('`save_weights` requires h5py.')
# If file exists and should not be overwritten:
if not overwrite and os.path.isfile(filepath):
proceed = ask_to_proceed_with_overwrite(filepath)
if not proceed:
return
f = h5py.File(filepath, 'w')
save_weights_to_hdf5_group(f, self.layers)
f.flush()
f.close() | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/Jinja2/py2/jinja2/filters.py | python | do_unique | (environment, value, case_sensitive=False, attribute=None) | Returns a list of unique items from the given iterable.
.. sourcecode:: jinja
{{ ['foo', 'bar', 'foobar', 'FooBar']|unique|list }}
-> ['foo', 'bar', 'foobar']
The unique items are yielded in the same order as their first occurrence in
the iterable passed to the filter.
:param case_sensitive: Treat upper and lower case strings as distinct.
:param attribute: Filter objects with unique values for this attribute. | Returns a list of unique items from the given iterable. | [
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] | def do_unique(environment, value, case_sensitive=False, attribute=None):
"""Returns a list of unique items from the given iterable.
.. sourcecode:: jinja
{{ ['foo', 'bar', 'foobar', 'FooBar']|unique|list }}
-> ['foo', 'bar', 'foobar']
The unique items are yielded in the same order as their first occurrence in
the iterable passed to the filter.
:param case_sensitive: Treat upper and lower case strings as distinct.
:param attribute: Filter objects with unique values for this attribute.
"""
getter = make_attrgetter(
environment, attribute, postprocess=ignore_case if not case_sensitive else None
)
seen = set()
for item in value:
key = getter(item)
if key not in seen:
seen.add(key)
yield item | [
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jackaudio/jack2 | 21b293dbc37d42446141a08922cdec0d2550c6a0 | waflib/Task.py | python | deep_inputs | (cls) | return cls | Task class decorator to enable rebuilds on input files task signatures | Task class decorator to enable rebuilds on input files task signatures | [
"Task",
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] | def deep_inputs(cls):
"""
Task class decorator to enable rebuilds on input files task signatures
"""
def sig_explicit_deps(self):
Task.sig_explicit_deps(self)
Task.sig_deep_inputs(self)
cls.sig_explicit_deps = sig_explicit_deps
return cls | [
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papyrussolution/OpenPapyrus | bbfb5ec2ea2109b8e2f125edd838e12eaf7b8b91 | Src/OSF/protobuf-3.19.1/python/google/protobuf/internal/enum_type_wrapper.py | python | EnumTypeWrapper.__getattr__ | (self, name) | Returns the value corresponding to the given enum name. | Returns the value corresponding to the given enum name. | [
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] | def __getattr__(self, name):
"""Returns the value corresponding to the given enum name."""
try:
return super(
EnumTypeWrapper,
self).__getattribute__('_enum_type').values_by_name[name].number
except KeyError:
pass # fall out to break exception chaining
raise AttributeError('Enum {} has no value defined for name {!r}'.format(
self._enum_type.name, name)) | [
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