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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/setuptools/sandbox.py | python | ExceptionSaver.resume | (self) | restore and re-raise any exception | restore and re-raise any exception | [
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"-",
"raise",
"any",
"exception"
] | def resume(self):
"restore and re-raise any exception"
if '_saved' not in vars(self):
return
type, exc = map(pickle.loads, self._saved)
six.reraise(type, exc, self._tb) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/indexes/base.py | python | Index.drop_duplicates | (self, keep="first") | return super().drop_duplicates(keep=keep) | Return Index with duplicate values removed.
Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
- 'first' : Drop duplicates except for the first occurrence.
- 'last' : Drop duplicates except for the last occurrence.
- ``False`` : Drop all duplicates.
Returns
-------
deduplicated : Index
See Also
--------
Series.drop_duplicates : Equivalent method on Series.
DataFrame.drop_duplicates : Equivalent method on DataFrame.
Index.duplicated : Related method on Index, indicating duplicate
Index values.
Examples
--------
Generate an pandas.Index with duplicate values.
>>> idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'])
The `keep` parameter controls which duplicate values are removed.
The value 'first' keeps the first occurrence for each
set of duplicated entries. The default value of keep is 'first'.
>>> idx.drop_duplicates(keep='first')
Index(['lama', 'cow', 'beetle', 'hippo'], dtype='object')
The value 'last' keeps the last occurrence for each set of duplicated
entries.
>>> idx.drop_duplicates(keep='last')
Index(['cow', 'beetle', 'lama', 'hippo'], dtype='object')
The value ``False`` discards all sets of duplicated entries.
>>> idx.drop_duplicates(keep=False)
Index(['cow', 'beetle', 'hippo'], dtype='object') | Return Index with duplicate values removed. | [
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"""
Return Index with duplicate values removed.
Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
- 'first' : Drop duplicates except for the first occurrence.
- 'last' : Drop duplicates except for the last occurrence.
- ``False`` : Drop all duplicates.
Returns
-------
deduplicated : Index
See Also
--------
Series.drop_duplicates : Equivalent method on Series.
DataFrame.drop_duplicates : Equivalent method on DataFrame.
Index.duplicated : Related method on Index, indicating duplicate
Index values.
Examples
--------
Generate an pandas.Index with duplicate values.
>>> idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'])
The `keep` parameter controls which duplicate values are removed.
The value 'first' keeps the first occurrence for each
set of duplicated entries. The default value of keep is 'first'.
>>> idx.drop_duplicates(keep='first')
Index(['lama', 'cow', 'beetle', 'hippo'], dtype='object')
The value 'last' keeps the last occurrence for each set of duplicated
entries.
>>> idx.drop_duplicates(keep='last')
Index(['cow', 'beetle', 'lama', 'hippo'], dtype='object')
The value ``False`` discards all sets of duplicated entries.
>>> idx.drop_duplicates(keep=False)
Index(['cow', 'beetle', 'hippo'], dtype='object')
"""
return super().drop_duplicates(keep=keep) | [
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/random.py | python | WichmannHill.setstate | (self, state) | Restore internal state from object returned by getstate(). | Restore internal state from object returned by getstate(). | [
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"""Restore internal state from object returned by getstate()."""
version = state[0]
if version == 1:
version, self._seed, self.gauss_next = state
else:
raise ValueError("state with version %s passed to "
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(version, self.VERSION)) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/scipy/stats/kde.py | python | gaussian_kde.integrate_box | (self, low_bounds, high_bounds, maxpts=None) | return value | Computes the integral of a pdf over a rectangular interval.
Parameters
----------
low_bounds : array_like
A 1-D array containing the lower bounds of integration.
high_bounds : array_like
A 1-D array containing the upper bounds of integration.
maxpts : int, optional
The maximum number of points to use for integration.
Returns
-------
value : scalar
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"""Computes the integral of a pdf over a rectangular interval.
Parameters
----------
low_bounds : array_like
A 1-D array containing the lower bounds of integration.
high_bounds : array_like
A 1-D array containing the upper bounds of integration.
maxpts : int, optional
The maximum number of points to use for integration.
Returns
-------
value : scalar
The result of the integral.
"""
from . import mvn
if maxpts is not None:
extra_kwds = {'maxpts': maxpts}
else:
extra_kwds = {}
value, inform = mvn.mvnun(low_bounds, high_bounds, self.dataset,
self.covariance, **extra_kwds)
if inform:
msg = ('An integral in mvn.mvnun requires more points than %s' %
(self.d * 1000))
warnings.warn(msg)
return value | [
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trilinos/Trilinos | 6168be6dd51e35e1cd681e9c4b24433e709df140 | packages/framework/pr_tools/trilinosprhelpers/TrilinosPRConfigurationBase.py | python | TrilinosPRConfigurationBase.arg_pr_genconfig_job_name | (self) | return self.args.genconfig_build_name | The Jenkins job name that is executing this Pull Request test.
Default is to use the value in args.pullrequest_build_name. | The Jenkins job name that is executing this Pull Request test.
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"""
The Jenkins job name that is executing this Pull Request test.
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"""
return self.args.genconfig_build_name | [
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fredakilla/GPlayEngine | ae6b45f4c68f696fcd171ce6996a5a4e80aee09e | thirdparty/freetype/src/tools/docmaker/content.py | python | ContentProcessor.__init__ | ( self ) | Initialize a block content processor. | Initialize a block content processor. | [
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] | def __init__( self ):
"""Initialize a block content processor."""
self.reset()
self.sections = {} # dictionary of documentation sections
self.section = None # current documentation section
self.chapters = [] # list of chapters
self.headers = {} | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/plot.py | python | PlotGraphics.getSymExtent | (self, printerScale) | return symExt | Get max width and height of lines and markers symbols for legend | Get max width and height of lines and markers symbols for legend | [
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"""Get max width and height of lines and markers symbols for legend"""
self.objects[0]._pointSize = self._pointSize
symExt = self.objects[0].getSymExtent(printerScale)
for o in self.objects[1:]:
o._pointSize = self._pointSize
oSymExt = o.getSymExtent(printerScale)
symExt = np.maximum(symExt, oSymExt)
return symExt | [
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SFTtech/openage | d6a08c53c48dc1e157807471df92197f6ca9e04d | buildsystem/codecompliance/legal.py | python | find_issues | (check_files, paths, git_change_years=False) | Tests all source files for the required legal headers. | Tests all source files for the required legal headers. | [
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"""
Tests all source files for the required legal headers.
"""
third_party_files = set()
yield from test_headers(
check_files, paths, git_change_years, third_party_files)
# test whether all third-party files are listed in copying.md
listed_files = set()
for line in readfile('copying.md').split('\n'):
match = re.match("^ - `([^`]+)`.*$", line)
if not match:
continue
filename = match.group(1)
listed_files.add(filename)
# file listed, but has no 3rd-party header?
for filename in sorted(listed_files - third_party_files):
if has_ext(filename, EXTENSIONS_REQUIRING_LEGAL_HEADERS):
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yield (
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py3/IPython/core/extensions.py | python | ExtensionManager.unload_extension | (self, module_str) | Unload an IPython extension by its module name.
This function looks up the extension's name in ``sys.modules`` and
simply calls ``mod.unload_ipython_extension(self)``.
Returns the string "no unload function" if the extension doesn't define
a function to unload itself, "not loaded" if the extension isn't loaded,
otherwise None. | Unload an IPython extension by its module name. | [
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] | def unload_extension(self, module_str):
"""Unload an IPython extension by its module name.
This function looks up the extension's name in ``sys.modules`` and
simply calls ``mod.unload_ipython_extension(self)``.
Returns the string "no unload function" if the extension doesn't define
a function to unload itself, "not loaded" if the extension isn't loaded,
otherwise None.
"""
if module_str not in self.loaded:
return "not loaded"
if module_str in sys.modules:
mod = sys.modules[module_str]
if self._call_unload_ipython_extension(mod):
self.loaded.discard(module_str)
else:
return "no unload function" | [
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swift/swift | 12d031cf8177fdec0137f9aa7e2912fa23c4416b | 3rdParty/SCons/scons-3.0.1/engine/SCons/Tool/docbook/__init__.py | python | _detect | (env) | Detect all the command line tools that we might need for creating
the requested output formats. | Detect all the command line tools that we might need for creating
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] | def _detect(env):
"""
Detect all the command line tools that we might need for creating
the requested output formats.
"""
global prefer_xsltproc
if env.get('DOCBOOK_PREFER_XSLTPROC',''):
prefer_xsltproc = True
if ((not has_libxml2 and not has_lxml) or (prefer_xsltproc)):
# Try to find the XSLT processors
__detect_cl_tool(env, 'DOCBOOK_XSLTPROC', xsltproc_com, xsltproc_com_priority)
__detect_cl_tool(env, 'DOCBOOK_XMLLINT', xmllint_com)
__detect_cl_tool(env, 'DOCBOOK_FOP', fop_com, ['fop','xep','jw']) | [
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/ops/composite/multitype_ops/add_impl.py | python | _TupleAdd.__init__ | (self, name) | Initialize _TupleAdd. | Initialize _TupleAdd. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_windows.py | python | PyPreviewFrame.__init__ | (self, *args, **kwargs) | __init__(self, PrintPreview preview, Frame parent, String title, Point pos=DefaultPosition,
Size size=DefaultSize,
long style=DEFAULT_FRAME_STYLE, String name=FrameNameStr) -> PyPreviewFrame | __init__(self, PrintPreview preview, Frame parent, String title, Point pos=DefaultPosition,
Size size=DefaultSize,
long style=DEFAULT_FRAME_STYLE, String name=FrameNameStr) -> PyPreviewFrame | [
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_windows_.PyPreviewFrame_swiginit(self,_windows_.new_PyPreviewFrame(*args, **kwargs))
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_internal/utils/misc.py | python | strtobool | (val) | Convert a string representation of truth to true (1) or false (0).
True values are 'y', 'yes', 't', 'true', 'on', and '1'; false values
are 'n', 'no', 'f', 'false', 'off', and '0'. Raises ValueError if
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# type: (str) -> int
"""Convert a string representation of truth to true (1) or false (0).
True values are 'y', 'yes', 't', 'true', 'on', and '1'; false values
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"""
val = val.lower()
if val in ('y', 'yes', 't', 'true', 'on', '1'):
return 1
elif val in ('n', 'no', 'f', 'false', 'off', '0'):
return 0
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raise ValueError("invalid truth value %r" % (val,)) | [
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msftguy/ssh-rd | a5f3a79daeac5844edebf01916c9613563f1c390 | _3rd/boost_1_48_0/tools/build/v2/build/feature.py | python | free_features | () | return __free_features | Returns all free features. | Returns all free features. | [
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MegEngine/MegEngine | ce9ad07a27ec909fb8db4dd67943d24ba98fb93a | imperative/python/megengine/tensor.py | python | Tensor.device | (self) | return super().device | r"""Returns a string represents the device a :class:`~.Tensor` storaged on. | r"""Returns a string represents the device a :class:`~.Tensor` storaged on. | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/framework/meta_graph.py | python | _read_file | (filename) | return graph_def | Reads a file containing `GraphDef` and returns the protocol buffer.
Args:
filename: `graph_def` filename including the path.
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Raises:
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graph_def = graph_pb2.GraphDef()
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raise IOError(f"File {filename} does not exist.")
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with file_io.FileIO(filename, "rb") as f:
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try:
graph_def.ParseFromString(file_content)
return graph_def
except Exception: # pylint: disable=broad-except
pass
# Next try to read it as a text file.
try:
text_format.Merge(file_content, graph_def)
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | NavigationKeyEvent.IsFromTab | (*args, **kwargs) | return _core_.NavigationKeyEvent_IsFromTab(*args, **kwargs) | IsFromTab(self) -> bool
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CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Editor/Python/windows/Lib/site-packages/pip/_vendor/ipaddress.py | python | _BaseV4._is_valid_netmask | (self, netmask) | return 0 <= netmask <= self._max_prefixlen | Verify that the netmask is valid.
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mask = netmask.split('.')
if len(mask) == 4:
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Arch/importJSON.py | python | export | (exportList, filename) | exports the given objects to a .json file | exports the given objects to a .json file | [
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'objects': [getObjectData(obj) for obj in exportList]
}
# Write file
if six.PY2:
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json.dump(data, outfile, separators = (',', ':'))
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FreeCAD.Console.PrintMessage(
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eventql/eventql | 7ca0dbb2e683b525620ea30dc40540a22d5eb227 | deps/3rdparty/spidermonkey/mozjs/media/webrtc/trunk/tools/gyp/pylib/gyp/xcode_emulation.py | python | _GetXcodeEnv | (xcode_settings, built_products_dir, srcroot, configuration,
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configuration: The build configuration name.
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'CONFIGURATION' : configuration,
'PRODUCT_NAME' : xcode_settings.GetProductName(),
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'SRCROOT' : srcroot,
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env['SDKROOT'] = ''
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env['EXECUTABLE_NAME'] = xcode_settings.GetExecutableName()
env['EXECUTABLE_PATH'] = xcode_settings.GetExecutablePath()
env['FULL_PRODUCT_NAME'] = xcode_settings.GetFullProductName()
mach_o_type = xcode_settings.GetMachOType()
if mach_o_type:
env['MACH_O_TYPE'] = mach_o_type
env['PRODUCT_TYPE'] = xcode_settings.GetProductType()
if xcode_settings._IsBundle():
env['CONTENTS_FOLDER_PATH'] = \
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env['UNLOCALIZED_RESOURCES_FOLDER_PATH'] = \
xcode_settings.GetBundleResourceFolder()
env['INFOPLIST_PATH'] = xcode_settings.GetBundlePlistPath()
env['WRAPPER_NAME'] = xcode_settings.GetWrapperName()
install_name = xcode_settings.GetInstallName()
if install_name:
env['LD_DYLIB_INSTALL_NAME'] = install_name
install_name_base = xcode_settings.GetInstallNameBase()
if install_name_base:
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adobe/chromium | cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7 | third_party/python_gflags/gflags.py | python | FlagValues.AddValidator | (self, validator) | Register new flags validator to be checked.
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/nntplib.py | python | NNTP.set_debuglevel | (self, level) | Set the debugging level. Argument 'level' means:
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqt/mantidqt/widgets/sliceviewer/peaksviewer/view.py | python | PeaksViewerView.__init__ | (self,
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Qihoo360/mongosync | 55b647e81c072ebe91daaa3b9dc1a953c3c22e19 | dep/mongo-cxx-driver/site_scons/buildscripts/cpplint.py | python | _CppLintState.SetOutputFormat | (self, output_format) | Sets the output format for errors. | Sets the output format for errors. | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/sessions.py | python | Session.post | (self, url, data=None, json=None, **kwargs) | return self.request('POST', url, data=data, json=json, **kwargs) | r"""Sends a POST request. Returns :class:`Response` object.
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_vendor/urllib3/poolmanager.py | python | PoolManager.urlopen | (self, method, url, redirect=True, **kw) | return self.urlopen(method, redirect_location, **kw) | Same as :meth:`urllib3.HTTPConnectionPool.urlopen`
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response = conn.urlopen(method, url, **kw)
else:
response = conn.urlopen(method, u.request_uri, **kw)
redirect_location = redirect and response.get_redirect_location()
if not redirect_location:
return response
# Support relative URLs for redirecting.
redirect_location = urljoin(url, redirect_location)
# RFC 7231, Section 6.4.4
if response.status == 303:
method = "GET"
retries = kw.get("retries")
if not isinstance(retries, Retry):
retries = Retry.from_int(retries, redirect=redirect)
# Strip headers marked as unsafe to forward to the redirected location.
# Check remove_headers_on_redirect to avoid a potential network call within
# conn.is_same_host() which may use socket.gethostbyname() in the future.
if retries.remove_headers_on_redirect and not conn.is_same_host(
redirect_location
):
headers = list(six.iterkeys(kw["headers"]))
for header in headers:
if header.lower() in retries.remove_headers_on_redirect:
kw["headers"].pop(header, None)
try:
retries = retries.increment(method, url, response=response, _pool=conn)
except MaxRetryError:
if retries.raise_on_redirect:
response.drain_conn()
raise
return response
kw["retries"] = retries
kw["redirect"] = redirect
log.info("Redirecting %s -> %s", url, redirect_location)
response.drain_conn()
return self.urlopen(method, redirect_location, **kw) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/_pyio.py | python | FileIO.closefd | (self) | return self._closefd | True if the file descriptor will be closed by close(). | True if the file descriptor will be closed by close(). | [
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"""True if the file descriptor will be closed by close()."""
return self._closefd | [
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/draftviewproviders/view_draft_annotation.py | python | ViewProviderDraftAnnotation.onChanged | (self, vobj, prop) | Execute when a view property is changed. | Execute when a view property is changed. | [
"Execute",
"when",
"a",
"view",
"property",
"is",
"changed",
"."
] | def onChanged(self, vobj, prop):
"""Execute when a view property is changed."""
properties = vobj.PropertiesList
meta = vobj.Object.Document.Meta
if prop == "AnnotationStyle" and "AnnotationStyle" in properties:
if not vobj.AnnotationStyle or vobj.AnnotationStyle == " ":
# unset style
_msg(16 * "-")
_msg("Unset style")
for visprop in utils.ANNOTATION_STYLE.keys():
if visprop in properties:
# make property writable
vobj.setPropertyStatus(visprop, '-ReadOnly')
else:
# set style
styles = {}
for key, value in meta.items():
if key.startswith("Draft_Style_"):
styles[key[12:]] = json.loads(value)
if vobj.AnnotationStyle in styles:
_msg(16 * "-")
_msg("Style: {}".format(vobj.AnnotationStyle))
style = styles[vobj.AnnotationStyle]
for visprop in style.keys():
if visprop in properties:
try:
getattr(vobj, visprop).setValue(style[visprop])
_msg("setValue: "
"'{}', '{}'".format(visprop,
style[visprop]))
except AttributeError:
setattr(vobj, visprop, style[visprop])
_msg("setattr: "
"'{}', '{}'".format(visprop,
style[visprop]))
# make property read-only
vobj.setPropertyStatus(visprop, 'ReadOnly') | [
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baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/debug/cli/analyzer_cli.py | python | DebugAnalyzer._render_node_traceback | (self, node_name) | return debugger_cli_common.rich_text_lines_from_rich_line_list(lines) | Render traceback of a node's creation in Python, if available.
Args:
node_name: (str) name of the node.
Returns:
A RichTextLines object containing the stack trace of the node's
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] | def _render_node_traceback(self, node_name):
"""Render traceback of a node's creation in Python, if available.
Args:
node_name: (str) name of the node.
Returns:
A RichTextLines object containing the stack trace of the node's
construction.
"""
lines = [RL(""), RL(""), RL("Traceback of node construction:", "bold")]
try:
node_stack = self._debug_dump.node_traceback(node_name)
for depth, (file_path, line, function_name, text) in enumerate(
node_stack):
lines.append("%d: %s" % (depth, file_path))
attribute = debugger_cli_common.MenuItem(
"", "ps %s -b %d" % (file_path, line)) if text else None
line_number_line = RL(" ")
line_number_line += RL("Line: %d" % line, attribute)
lines.append(line_number_line)
lines.append(" Function: %s" % function_name)
lines.append(" Text: " + (("\"%s\"" % text) if text else "None"))
lines.append("")
except KeyError:
lines.append("(Node unavailable in the loaded Python graph)")
except LookupError:
lines.append("(Unavailable because no Python graph has been loaded)")
return debugger_cli_common.rich_text_lines_from_rich_line_list(lines) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_core.py | python | BoxSizer.__init__ | (self, *args, **kwargs) | __init__(self, int orient=HORIZONTAL) -> BoxSizer
Constructor for a wx.BoxSizer. *orient* may be one of ``wx.VERTICAL``
or ``wx.HORIZONTAL`` for creating either a column sizer or a row
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"""
__init__(self, int orient=HORIZONTAL) -> BoxSizer
Constructor for a wx.BoxSizer. *orient* may be one of ``wx.VERTICAL``
or ``wx.HORIZONTAL`` for creating either a column sizer or a row
sizer.
"""
_core_.BoxSizer_swiginit(self,_core_.new_BoxSizer(*args, **kwargs))
self._setOORInfo(self) | [
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francinexue/xuefu | b6ff79747a42e020588c0c0a921048e08fe4680c | api/ctpx/ctptd.py | python | CtpTd.onRspOrderAction | (self, InputOrderActionField, RspInfoField, requestId, final) | 报单操作请求响应 | 报单操作请求响应 | [
"报单操作请求响应"
] | def onRspOrderAction(self, InputOrderActionField, RspInfoField, requestId, final):
"""报单操作请求响应"""
# print u"onRspOrderAction --- sessionId: {0}, frontID: {1}, orderRef: {2}".format(InputOrderActionField.sessionID,
# InputOrderActionField.frontID, InputOrderActionField.orderRef)
# print(u"onRspOrderAction --- errorCode:{0}, errorMsg:{1}.".format(
# RspInfoField.errorID, RspInfoField.errorMsg.decode('gbk')))
for listener in self._barEventListeners:
listener.onRspOrderInsert(InputOrderActionField, RspInfoField) | [
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PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/fluid/framework.py | python | name_scope | (prefix=None) | :api_attr: Static Graph
Generate hierarchical name prefix for the operators in Static Graph.
Note:
This should only used for debugging and visualization purpose.
Don't use it for serious analysis such as graph/program transformations.
Don't use it in dygraph, since it will cause memory leak.
Args:
prefix(str, optional): prefix. Default is none.
Examples:
.. code-block:: python
import paddle
paddle.enable_static()
with paddle.static.name_scope("s1"):
a = paddle.static.data(name='data', shape=[None, 1], dtype='int32')
b = a + 1
with paddle.static.name_scope("s2"):
c = b * 1
with paddle.static.name_scope("s3"):
d = c / 1
with paddle.static.name_scope("s1"):
f = paddle.tensor.pow(d, 2.0)
with paddle.static.name_scope("s4"):
g = f - 1
# Op are created in the default main program.
for op in paddle.static.default_main_program().block(0).ops:
# elementwise_add is created in /s1/
if op.type == 'elementwise_add':
assert op.desc.attr("op_namescope") == '/s1/'
# elementwise_mul is created in '/s1/s2'
elif op.type == 'elementwise_mul':
assert op.desc.attr("op_namescope") == '/s1/s2/'
# elementwise_div is created in '/s1/s3'
elif op.type == 'elementwise_div':
assert op.desc.attr("op_namescope") == '/s1/s3/'
# elementwise_sum is created in '/s4'
elif op.type == 'elementwise_sub':
assert op.desc.attr("op_namescope") == '/s4/'
# pow is created in /s1_1/
elif op.type == 'pow':
assert op.desc.attr("op_namescope") == '/s1_1/' | :api_attr: Static Graph | [
":",
"api_attr",
":",
"Static",
"Graph"
] | def name_scope(prefix=None):
"""
:api_attr: Static Graph
Generate hierarchical name prefix for the operators in Static Graph.
Note:
This should only used for debugging and visualization purpose.
Don't use it for serious analysis such as graph/program transformations.
Don't use it in dygraph, since it will cause memory leak.
Args:
prefix(str, optional): prefix. Default is none.
Examples:
.. code-block:: python
import paddle
paddle.enable_static()
with paddle.static.name_scope("s1"):
a = paddle.static.data(name='data', shape=[None, 1], dtype='int32')
b = a + 1
with paddle.static.name_scope("s2"):
c = b * 1
with paddle.static.name_scope("s3"):
d = c / 1
with paddle.static.name_scope("s1"):
f = paddle.tensor.pow(d, 2.0)
with paddle.static.name_scope("s4"):
g = f - 1
# Op are created in the default main program.
for op in paddle.static.default_main_program().block(0).ops:
# elementwise_add is created in /s1/
if op.type == 'elementwise_add':
assert op.desc.attr("op_namescope") == '/s1/'
# elementwise_mul is created in '/s1/s2'
elif op.type == 'elementwise_mul':
assert op.desc.attr("op_namescope") == '/s1/s2/'
# elementwise_div is created in '/s1/s3'
elif op.type == 'elementwise_div':
assert op.desc.attr("op_namescope") == '/s1/s3/'
# elementwise_sum is created in '/s4'
elif op.type == 'elementwise_sub':
assert op.desc.attr("op_namescope") == '/s4/'
# pow is created in /s1_1/
elif op.type == 'pow':
assert op.desc.attr("op_namescope") == '/s1_1/'
"""
# TODO(panyx0718): Only [0-9a-z].
# in dygraph we don't need namescope since it will cause mem leak
if in_dygraph_mode():
yield
else:
assert prefix, "namescope prefix can not be empty."
global _name_scope
_name_scope = _name_scope.child(prefix)
try:
yield
finally:
_name_scope = _name_scope.parent() | [
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hpi-xnor/BMXNet-v2 | af2b1859eafc5c721b1397cef02f946aaf2ce20d | python/mxnet/torch.py | python | _init_torch_module | () | List and add all the torch backed ndarray functions to current module. | List and add all the torch backed ndarray functions to current module. | [
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] | def _init_torch_module():
"""List and add all the torch backed ndarray functions to current module."""
plist = ctypes.POINTER(FunctionHandle)()
size = ctypes.c_uint()
check_call(_LIB.MXListFunctions(ctypes.byref(size),
ctypes.byref(plist)))
module_obj = sys.modules[__name__]
for i in range(size.value):
hdl = FunctionHandle(plist[i])
function = _make_torch_function(hdl)
# if function name starts with underscore, register as static method of NDArray
if function is not None:
setattr(module_obj, function.__name__, function) | [
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weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | third_party/jinja2/environment.py | python | Environment.call_filter | (self, name, value, args=None, kwargs=None,
context=None, eval_ctx=None) | return func(*args, **(kwargs or {})) | Invokes a filter on a value the same way the compiler does it.
.. versionadded:: 2.7 | Invokes a filter on a value the same way the compiler does it. | [
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] | def call_filter(self, name, value, args=None, kwargs=None,
context=None, eval_ctx=None):
"""Invokes a filter on a value the same way the compiler does it.
.. versionadded:: 2.7
"""
func = self.filters.get(name)
if func is None:
raise TemplateRuntimeError('no filter named %r' % name)
args = [value] + list(args or ())
if getattr(func, 'contextfilter', False):
if context is None:
raise TemplateRuntimeError('Attempted to invoke context '
'filter without context')
args.insert(0, context)
elif getattr(func, 'evalcontextfilter', False):
if eval_ctx is None:
if context is not None:
eval_ctx = context.eval_ctx
else:
eval_ctx = EvalContext(self)
args.insert(0, eval_ctx)
elif getattr(func, 'environmentfilter', False):
args.insert(0, self)
return func(*args, **(kwargs or {})) | [
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priyankchheda/algorithms | c361aa9071573fa9966d5b02d05e524815abcf2b | graph/library/graph.py | python | Graph.add_vertex | (self, node) | Adds new vertex to graph. If vertex is already present in graph,
no action will take place.
:param node: new node to be added to graph | Adds new vertex to graph. If vertex is already present in graph,
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""" Adds new vertex to graph. If vertex is already present in graph,
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"""
if node not in self._graph_dict:
self._graph_dict[node] = [] | [
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pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | lts/deps/v8/third_party/jinja2/runtime.py | python | Context.get | (self, key, default=None) | Returns an item from the template context, if it doesn't exist
`default` is returned. | Returns an item from the template context, if it doesn't exist
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"""Returns an item from the template context, if it doesn't exist
`default` is returned.
"""
try:
return self[key]
except KeyError:
return default | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/cmd.py | python | Cmd.do_help | (self, arg) | List available commands with "help" or detailed help with "help cmd". | List available commands with "help" or detailed help with "help cmd". | [
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] | def do_help(self, arg):
'List available commands with "help" or detailed help with "help cmd".'
if arg:
# XXX check arg syntax
try:
func = getattr(self, 'help_' + arg)
except AttributeError:
try:
doc=getattr(self, 'do_' + arg).__doc__
if doc:
self.stdout.write("%s\n"%str(doc))
return
except AttributeError:
pass
self.stdout.write("%s\n"%str(self.nohelp % (arg,)))
return
func()
else:
names = self.get_names()
cmds_doc = []
cmds_undoc = []
help = {}
for name in names:
if name[:5] == 'help_':
help[name[5:]]=1
names.sort()
# There can be duplicates if routines overridden
prevname = ''
for name in names:
if name[:3] == 'do_':
if name == prevname:
continue
prevname = name
cmd=name[3:]
if cmd in help:
cmds_doc.append(cmd)
del help[cmd]
elif getattr(self, name).__doc__:
cmds_doc.append(cmd)
else:
cmds_undoc.append(cmd)
self.stdout.write("%s\n"%str(self.doc_leader))
self.print_topics(self.doc_header, cmds_doc, 15,80)
self.print_topics(self.misc_header, list(help.keys()),15,80)
self.print_topics(self.undoc_header, cmds_undoc, 15,80) | [
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macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/v8/third_party/jinja2/parser.py | python | Parser.parse_statement | (self) | Parse a single statement. | Parse a single statement. | [
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] | def parse_statement(self):
"""Parse a single statement."""
token = self.stream.current
if token.type != 'name':
self.fail('tag name expected', token.lineno)
self._tag_stack.append(token.value)
pop_tag = True
try:
if token.value in _statement_keywords:
return getattr(self, 'parse_' + self.stream.current.value)()
if token.value == 'call':
return self.parse_call_block()
if token.value == 'filter':
return self.parse_filter_block()
ext = self.extensions.get(token.value)
if ext is not None:
return ext(self)
# did not work out, remove the token we pushed by accident
# from the stack so that the unknown tag fail function can
# produce a proper error message.
self._tag_stack.pop()
pop_tag = False
self.fail_unknown_tag(token.value, token.lineno)
finally:
if pop_tag:
self._tag_stack.pop() | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/ir.py | python | FunctionIR.infer_constant | (self, name) | return self._consts.infer_constant(name) | Try to infer the constant value of a given variable. | Try to infer the constant value of a given variable. | [
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] | def infer_constant(self, name):
"""
Try to infer the constant value of a given variable.
"""
if isinstance(name, Var):
name = name.name
return self._consts.infer_constant(name) | [
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zhaoweicai/mscnn | 534bcac5710a579d60827f192035f7eef6d8c585 | scripts/cpp_lint.py | python | _Filters | () | return _cpplint_state.filters | Returns the module's list of output filters, as a list. | Returns the module's list of output filters, as a list. | [
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | python/configobj/validate.py | python | is_float | (value, min=None, max=None) | return value | A check that tests that a given value is a float
(an integer will be accepted), and optionally - that it is between bounds.
If the value is a string, then the conversion is done - if possible.
Otherwise a VdtError is raised.
This can accept negative values.
>>> vtor.check('float', '2')
2.0
From now on we multiply the value to avoid comparing decimals
>>> vtor.check('float', '-6.8') * 10
-68.0
>>> vtor.check('float', '12.2') * 10
122.0
>>> vtor.check('float', 8.4) * 10
84.0
>>> vtor.check('float', 'a')
Traceback (most recent call last):
VdtTypeError: the value "a" is of the wrong type.
>>> vtor.check('float(10.1)', '10.2') * 10
102.0
>>> vtor.check('float(max=20.2)', '15.1') * 10
151.0
>>> vtor.check('float(10.0)', '9.0')
Traceback (most recent call last):
VdtValueTooSmallError: the value "9.0" is too small.
>>> vtor.check('float(max=20.0)', '35.0')
Traceback (most recent call last):
VdtValueTooBigError: the value "35.0" is too big. | A check that tests that a given value is a float
(an integer will be accepted), and optionally - that it is between bounds.
If the value is a string, then the conversion is done - if possible.
Otherwise a VdtError is raised.
This can accept negative values.
>>> vtor.check('float', '2')
2.0
From now on we multiply the value to avoid comparing decimals
>>> vtor.check('float', '-6.8') * 10
-68.0
>>> vtor.check('float', '12.2') * 10
122.0
>>> vtor.check('float', 8.4) * 10
84.0
>>> vtor.check('float', 'a')
Traceback (most recent call last):
VdtTypeError: the value "a" is of the wrong type.
>>> vtor.check('float(10.1)', '10.2') * 10
102.0
>>> vtor.check('float(max=20.2)', '15.1') * 10
151.0
>>> vtor.check('float(10.0)', '9.0')
Traceback (most recent call last):
VdtValueTooSmallError: the value "9.0" is too small.
>>> vtor.check('float(max=20.0)', '35.0')
Traceback (most recent call last):
VdtValueTooBigError: the value "35.0" is too big. | [
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"""
A check that tests that a given value is a float
(an integer will be accepted), and optionally - that it is between bounds.
If the value is a string, then the conversion is done - if possible.
Otherwise a VdtError is raised.
This can accept negative values.
>>> vtor.check('float', '2')
2.0
From now on we multiply the value to avoid comparing decimals
>>> vtor.check('float', '-6.8') * 10
-68.0
>>> vtor.check('float', '12.2') * 10
122.0
>>> vtor.check('float', 8.4) * 10
84.0
>>> vtor.check('float', 'a')
Traceback (most recent call last):
VdtTypeError: the value "a" is of the wrong type.
>>> vtor.check('float(10.1)', '10.2') * 10
102.0
>>> vtor.check('float(max=20.2)', '15.1') * 10
151.0
>>> vtor.check('float(10.0)', '9.0')
Traceback (most recent call last):
VdtValueTooSmallError: the value "9.0" is too small.
>>> vtor.check('float(max=20.0)', '35.0')
Traceback (most recent call last):
VdtValueTooBigError: the value "35.0" is too big.
"""
(min_val, max_val) = _is_num_param(
('min', 'max'), (min, max), to_float=True)
if not isinstance(value, (int, long, float, basestring)):
raise VdtTypeError(value)
if not isinstance(value, float):
# if it's a string - does it represent a float ?
try:
value = float(value)
except ValueError:
raise VdtTypeError(value)
if (min_val is not None) and (value < min_val):
raise VdtValueTooSmallError(value)
if (max_val is not None) and (value > max_val):
raise VdtValueTooBigError(value)
return value | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py2/numpy/distutils/misc_util.py | python | get_path_from_frame | (frame, parent_path=None) | return d or '.' | Return path of the module given a frame object from the call stack.
Returned path is relative to parent_path when given,
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Returned path is relative to parent_path when given,
otherwise it is absolute path.
"""
# First, try to find if the file name is in the frame.
try:
caller_file = eval('__file__', frame.f_globals, frame.f_locals)
d = os.path.dirname(os.path.abspath(caller_file))
except NameError:
# __file__ is not defined, so let's try __name__. We try this second
# because setuptools spoofs __name__ to be '__main__' even though
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if hasattr(mod, '__file__'):
d = os.path.dirname(os.path.abspath(mod.__file__))
else:
# we're probably running setup.py as execfile("setup.py")
# (likely we're building an egg)
d = os.path.abspath('.')
# hmm, should we use sys.argv[0] like in __builtin__ case?
if parent_path is not None:
d = rel_path(d, parent_path)
return d or '.' | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/python-gflags/gflags.py | python | MarkFlagAsRequired | (flag_name, flag_values=FLAGS) | Ensure that flag is not None during program execution.
Registers a flag validator, which will follow usual validator
rules.
Args:
flag_name: string, name of the flag
flag_values: FlagValues
Raises:
AttributeError: if flag_name is not registered as a valid flag name. | Ensure that flag is not None during program execution. | [
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] | def MarkFlagAsRequired(flag_name, flag_values=FLAGS):
"""Ensure that flag is not None during program execution.
Registers a flag validator, which will follow usual validator
rules.
Args:
flag_name: string, name of the flag
flag_values: FlagValues
Raises:
AttributeError: if flag_name is not registered as a valid flag name.
"""
RegisterValidator(flag_name,
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message='Flag --%s must be specified.' % flag_name,
flag_values=flag_values) | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/compiler/xla/experimental/xla_sharding/xla_sharding.py | python | Sharding.assign_device | (cls, core) | return Sharding(
proto=xla_data_pb2.OpSharding(
type=xla_data_pb2.OpSharding.MAXIMAL,
tile_assignment_dimensions=[1],
tile_assignment_devices=[core])) | Returns an AssignDevice sharding attribute.
This causes an op to be computed in its entirety only on one core in
the XLA device.
Args:
core: The core to assign this Op to. | Returns an AssignDevice sharding attribute. | [
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] | def assign_device(cls, core):
"""Returns an AssignDevice sharding attribute.
This causes an op to be computed in its entirety only on one core in
the XLA device.
Args:
core: The core to assign this Op to.
"""
return Sharding(
proto=xla_data_pb2.OpSharding(
type=xla_data_pb2.OpSharding.MAXIMAL,
tile_assignment_dimensions=[1],
tile_assignment_devices=[core])) | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/protobuf/python/google/protobuf/internal/well_known_types.py | python | FieldMask.FromJsonString | (self, value) | Converts string to FieldMask according to proto3 JSON spec. | Converts string to FieldMask according to proto3 JSON spec. | [
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self.Clear()
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mapequation/infomap | 5f56b94fe0f956483f61a03ef07e94d8def2205e | interfaces/python/infomap.py | python | Infomap.module_codelength | (self) | return super().getModuleCodelength() | Get the total codelength of the modules.
The module codelength is defined such that
``codelength = index_codelength + module_codelength``
For a hierarchical solution, the module codelength
is the sum of codelengths for each top module.
See Also
--------
codelength
index_codelength
Returns
-------
float
The module codelength | Get the total codelength of the modules. | [
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] | def module_codelength(self):
"""Get the total codelength of the modules.
The module codelength is defined such that
``codelength = index_codelength + module_codelength``
For a hierarchical solution, the module codelength
is the sum of codelengths for each top module.
See Also
--------
codelength
index_codelength
Returns
-------
float
The module codelength
"""
return super().getModuleCodelength() | [
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JoseExposito/touchegg | 1f3fda214358d071c05da4bf17c070c33d67b5eb | cmake/cpplint.py | python | _IncludeState.ResetSection | (self, directive) | Reset section checking for preprocessor directive.
Args:
directive: preprocessor directive (e.g. "if", "else"). | Reset section checking for preprocessor directive. | [
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] | def ResetSection(self, directive):
"""Reset section checking for preprocessor directive.
Args:
directive: preprocessor directive (e.g. "if", "else").
"""
# 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
# include list.
if directive in ('if', 'ifdef', 'ifndef'):
self.include_list.append([])
elif directive in ('else', 'elif'):
self.include_list[-1] = [] | [
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materialx/MaterialX | 77ff72f352470b5c76dddde765951a8e3bcf79fc | python/MaterialX/main.py | python | _getActiveParameters | (self) | return list() | (Deprecated) Return a vector of all parameters belonging to this interface, taking inheritance into account. | (Deprecated) Return a vector of all parameters belonging to this interface, taking inheritance into account. | [
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esa/pykep | b410363653623730b577de257c04b0e0289f2014 | pykep/phasing/__init__.py | python | three_impulses_approx | (pl1, pl2, ep1=None, ep2=None) | return _three_impulses_approx(pl1, pl2, ep1, ep2) | DV = pykep.phasing.three_impulses_approx(pl1, pl2, ep1=None, ep2=None)
- pl1: departure planet
- pl2: arrival planet
- ep1: departure epoch (optional and only useful for non keplerian planets)
- ep1: arrival epoch (default value is ep1).
- [out] DV: estimated DV cost for the orbital trab=nsfer
Returns the DV in m/s necessary for an orbit transfer between pl1 and pl2 assuming a perfect phasing.
The transfer will be made of three impulses. One to match apogees, one to match inclination and RAAN and
one to match perigees. Two of the three impulses will be merged together at either departure or arrival.
The argument of perigee is not matched, so that this approximation is only good for near-circular orbits.
Examples::
DV = three_impulses_approx(pl1, pl2)
DV = three_impulses_approx(pl1, pl2, ep1 = epoch(5500))
DV = three_impulses_approx(pl1, pl2, ep1 = epoch(5500), ep2 = epoch(5700)) | DV = pykep.phasing.three_impulses_approx(pl1, pl2, ep1=None, ep2=None) | [
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"""
DV = pykep.phasing.three_impulses_approx(pl1, pl2, ep1=None, ep2=None)
- pl1: departure planet
- pl2: arrival planet
- ep1: departure epoch (optional and only useful for non keplerian planets)
- ep1: arrival epoch (default value is ep1).
- [out] DV: estimated DV cost for the orbital trab=nsfer
Returns the DV in m/s necessary for an orbit transfer between pl1 and pl2 assuming a perfect phasing.
The transfer will be made of three impulses. One to match apogees, one to match inclination and RAAN and
one to match perigees. Two of the three impulses will be merged together at either departure or arrival.
The argument of perigee is not matched, so that this approximation is only good for near-circular orbits.
Examples::
DV = three_impulses_approx(pl1, pl2)
DV = three_impulses_approx(pl1, pl2, ep1 = epoch(5500))
DV = three_impulses_approx(pl1, pl2, ep1 = epoch(5500), ep2 = epoch(5700))
"""
from pykep.core import _three_impulses_approx
if ep2 is None:
ep2 = ep1
if ep1 is None:
return _three_impulses_approx(pl1, pl2)
return _three_impulses_approx(pl1, pl2, ep1, ep2) | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/mock/mock.py | python | _patch.start | (self) | return result | Activate a patch, returning any created mock. | Activate a patch, returning any created mock. | [
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"""Activate a patch, returning any created mock."""
result = self.__enter__()
self._active_patches.add(self)
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/decimal.py | python | Context.remainder_near | (self, a, b) | return a.remainder_near(b, context=self) | Returns to be "a - b * n", where n is the integer nearest the exact
value of "x / b" (if two integers are equally near then the even one
is chosen). If the result is equal to 0 then its sign will be the
sign of a.
This operation will fail under the same conditions as integer division
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remainder cannot be calculated).
>>> ExtendedContext.remainder_near(Decimal('2.1'), Decimal('3'))
Decimal('-0.9')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('6'))
Decimal('-2')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('3'))
Decimal('1')
>>> ExtendedContext.remainder_near(Decimal('-10'), Decimal('3'))
Decimal('-1')
>>> ExtendedContext.remainder_near(Decimal('10.2'), Decimal('1'))
Decimal('0.2')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('0.3'))
Decimal('0.1')
>>> ExtendedContext.remainder_near(Decimal('3.6'), Decimal('1.3'))
Decimal('-0.3')
>>> ExtendedContext.remainder_near(3, 11)
Decimal('3')
>>> ExtendedContext.remainder_near(Decimal(3), 11)
Decimal('3')
>>> ExtendedContext.remainder_near(3, Decimal(11))
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value of "x / b" (if two integers are equally near then the even one
is chosen). If the result is equal to 0 then its sign will be the
sign of a. | [
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is chosen). If the result is equal to 0 then its sign will be the
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Decimal('-2')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('3'))
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>>> ExtendedContext.remainder_near(Decimal('10.2'), Decimal('1'))
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>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('0.3'))
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>>> ExtendedContext.remainder_near(Decimal('3.6'), Decimal('1.3'))
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>>> ExtendedContext.remainder_near(Decimal(3), 11)
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>>> ExtendedContext.remainder_near(3, Decimal(11))
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a = _convert_other(a, raiseit=True)
return a.remainder_near(b, context=self) | [
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freesurfer/freesurfer | 6dbe527d43ffa611acb2cd112e9469f9bfec8e36 | cnn_sphere_register/ext/neuron/neuron/utils.py | python | volshape_to_meshgrid | (volshape, **kwargs) | return tf.meshgrid(*linvec, **kwargs) | compute Tensor meshgrid from a volume size
Parameters:
volshape: the volume size
**args: "name" (optional)
Returns:
A list of Tensors
See Also:
tf.meshgrid, ndgrid, volshape_to_ndgrid | compute Tensor meshgrid from a volume size | [
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"""
compute Tensor meshgrid from a volume size
Parameters:
volshape: the volume size
**args: "name" (optional)
Returns:
A list of Tensors
See Also:
tf.meshgrid, ndgrid, volshape_to_ndgrid
"""
isint = [float(d).is_integer() for d in volshape]
if not all(isint):
raise ValueError("volshape needs to be a list of integers")
linvec = [tf.range(0, d) for d in volshape]
return tf.meshgrid(*linvec, **kwargs) | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/ops/array_ops.py | python | _BitcastShape | (op) | Shape function for Bitcast op. | Shape function for Bitcast op. | [
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"""Shape function for Bitcast op."""
input_shape = op.inputs[0].get_shape()
if input_shape == tensor_shape.unknown_shape():
return [tensor_shape.unknown_shape()]
input_type = op.inputs[0].dtype
size_of_input = input_type.size
output = dtypes.as_dtype(op.get_attr("type"))
size_of_output = output.size
if size_of_input == size_of_output:
return [input_shape]
else:
if size_of_output > size_of_input:
new_shape = input_shape.with_rank_at_least(1).as_list()
last_val = new_shape[-1]
if last_val is None or last_val == (size_of_output // size_of_input):
new_shape = new_shape[:-1]
else:
raise ValueError(
"Cannot bitcast due to shape. %d is not evenly divisible by %d." %
(new_shape[-1], size_of_input // size_of_output))
else:
new_shape = input_shape
new_shape = new_shape.concatenate([size_of_input // size_of_output])
return [tensor_shape.TensorShape(new_shape)] | [
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gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | util/minorview/view.py | python | BlobView.set_da_size | (self) | Set the DrawingArea size after scaling | Set the DrawingArea size after scaling | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tkinter/__init__.py | python | Grid.grid_remove | (self) | Unmap this widget but remember the grid options. | Unmap this widget but remember the grid options. | [
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zhaoweicai/cascade-rcnn | 2252f46158ea6555868ca6fa5c221ea71d9b5e6c | scripts/cpp_lint.py | python | _NamespaceInfo.CheckEnd | (self, filename, clean_lines, linenum, error) | Check end of namespace comments. | Check end of namespace comments. | [
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line = clean_lines.raw_lines[linenum]
# Check how many lines is enclosed in this namespace. Don't issue
# warning for missing namespace comments if there aren't enough
# lines. However, do apply checks if there is already an end of
# namespace comment and it's incorrect.
#
# TODO(unknown): We always want to check end of namespace comments
# if a namespace is large, but sometimes we also want to apply the
# check if a short namespace contained nontrivial things (something
# other than forward declarations). There is currently no logic on
# deciding what these nontrivial things are, so this check is
# triggered by namespace size only, which works most of the time.
if (linenum - self.starting_linenum < 10
and not Match(r'};*\s*(//|/\*).*\bnamespace\b', line)):
return
# Look for matching comment at end of namespace.
#
# Note that we accept C style "/* */" comments for terminating
# namespaces, so that code that terminate namespaces inside
# preprocessor macros can be cpplint clean.
#
# We also accept stuff like "// end of namespace <name>." with the
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#
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line):
error(filename, linenum, 'readability/namespace', 5,
'Namespace should be terminated with "// namespace %s"' %
self.name)
else:
# Anonymous namespace
if not Match(r'};*\s*(//|/\*).*\bnamespace[\*/\.\\\s]*$', line):
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adobe/chromium | cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7 | tools/isolate/merge_isolate.py | python | invert_map | (variables) | return out, set(variables) | Converts a dict(OS, dict(deptype, list(dependencies)) to a flattened view.
Returns a tuple of:
1. dict(deptype, dict(dependency, set(OSes)) for easier processing.
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"""Converts a dict(OS, dict(deptype, list(dependencies)) to a flattened view.
Returns a tuple of:
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2. All the OSes found as a set.
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out = dict((key, {}) for key in KEYS)
for os_name, values in variables.iteritems():
for key in (KEY_TRACKED, KEY_UNTRACKED):
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out['command'].setdefault(command, set()).add(os_name)
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out['read_only'].setdefault(values.get('read_only'), set()).add(os_name)
return out, set(variables) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/_pydecimal.py | python | _decimal_lshift_exact | (n, e) | Given integers n and e, return n * 10**e if it's an integer, else None.
The computation is designed to avoid computing large powers of 10
unnecessarily.
>>> _decimal_lshift_exact(3, 4)
30000
>>> _decimal_lshift_exact(300, -999999999) # returns None | Given integers n and e, return n * 10**e if it's an integer, else None. | [
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""" Given integers n and e, return n * 10**e if it's an integer, else None.
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>>> _decimal_lshift_exact(3, 4)
30000
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"""
if n == 0:
return 0
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str_n = str(abs(n))
val_n = len(str_n) - len(str_n.rstrip('0'))
return None if val_n < -e else n // 10**-e | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_aarch64/python2.7/dist-packages/geographic_msgs/msg/_GeoPose.py | python | GeoPose._get_types | (self) | return self._slot_types | internal API method | internal API method | [
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"""
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oracle/graaljs | 36a56e8e993d45fc40939a3a4d9c0c24990720f1 | graal-nodejs/deps/v8/third_party/jinja2/sandbox.py | python | unsafe | (f) | return f | Marks a function or method as unsafe.
::
@unsafe
def delete(self):
pass | Marks a function or method as unsafe. | [
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"""Marks a function or method as unsafe.
::
@unsafe
def delete(self):
pass
"""
f.unsafe_callable = True
return f | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/optimize/optimize.py | python | check_grad | (func, grad, x0, *args, **kwargs) | return sqrt(sum((grad(x0, *args) -
approx_fprime(x0, func, step, *args))**2)) | Check the correctness of a gradient function by comparing it against a
(forward) finite-difference approximation of the gradient.
Parameters
----------
func : callable ``func(x0, *args)``
Function whose derivative is to be checked.
grad : callable ``grad(x0, *args)``
Gradient of `func`.
x0 : ndarray
Points to check `grad` against forward difference approximation of grad
using `func`.
args : \\*args, optional
Extra arguments passed to `func` and `grad`.
epsilon : float, optional
Step size used for the finite difference approximation. It defaults to
``sqrt(numpy.finfo(float).eps)``, which is approximately 1.49e-08.
Returns
-------
err : float
The square root of the sum of squares (i.e. the 2-norm) of the
difference between ``grad(x0, *args)`` and the finite difference
approximation of `grad` using func at the points `x0`.
See Also
--------
approx_fprime
Examples
--------
>>> def func(x):
... return x[0]**2 - 0.5 * x[1]**3
>>> def grad(x):
... return [2 * x[0], -1.5 * x[1]**2]
>>> from scipy.optimize import check_grad
>>> check_grad(func, grad, [1.5, -1.5])
2.9802322387695312e-08 | Check the correctness of a gradient function by comparing it against a
(forward) finite-difference approximation of the gradient. | [
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Parameters
----------
func : callable ``func(x0, *args)``
Function whose derivative is to be checked.
grad : callable ``grad(x0, *args)``
Gradient of `func`.
x0 : ndarray
Points to check `grad` against forward difference approximation of grad
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args : \\*args, optional
Extra arguments passed to `func` and `grad`.
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Step size used for the finite difference approximation. It defaults to
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See Also
--------
approx_fprime
Examples
--------
>>> def func(x):
... return x[0]**2 - 0.5 * x[1]**3
>>> def grad(x):
... return [2 * x[0], -1.5 * x[1]**2]
>>> from scipy.optimize import check_grad
>>> check_grad(func, grad, [1.5, -1.5])
2.9802322387695312e-08
"""
step = kwargs.pop('epsilon', _epsilon)
if kwargs:
raise ValueError("Unknown keyword arguments: %r" %
(list(kwargs.keys()),))
return sqrt(sum((grad(x0, *args) -
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GoldenCheetah/GoldenCheetah | 919a418895040144be5579884446ed6cd701bf0d | travis/macdeployqtfix.py | python | fix_main_binaries | () | return True | list the main binaries of the app bundle and fix them | list the main binaries of the app bundle and fix them | [
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"app",
"bundle",
"and",
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] | def fix_main_binaries():
"""
list the main binaries of the app bundle and fix them
"""
# deduce bundle path
bundlepath = os.path.sep.join(GlobalConfig.exepath.split(os.path.sep)[0:-3])
# fix main binary
GlobalConfig.logger.info('fixing executable \'{0}\''.format(GlobalConfig.exepath))
if fix_binary(GlobalConfig.exepath):
GlobalConfig.logger.info('fixing plugins')
for root, dummy, files in os.walk(bundlepath):
for name in [f for f in files if os.path.splitext(f)[1] == '.dylib']:
GlobalConfig.logger.info('fixing plugin {0}'.format(name))
if not fix_binary(os.path.join(root, name)):
return False
return True | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/sim/batch.py | python | saveStateCSV | (state,f) | Given a state dictionary, saves it to CSV format to the given
output stream f | Given a state dictionary, saves it to CSV format to the given
output stream f | [
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] | def saveStateCSV(state,f):
"""Given a state dictionary, saves it to CSV format to the given
output stream f"""
saveStateHeaderCSV(state,f)
f.write(','.join(str(v) for v in access.flatten(state)))
f.write('\n') | [
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/contrib/framework/python/ops/sampling_ops.py | python | _calculate_acceptance_probabilities | (init_probs, target_probs) | return ratio_l / max_ratio | Calculate the per-class acceptance rates.
Args:
init_probs: The class probabilities of the data.
target_probs: The desired class proportion in minibatches.
Returns:
A list of the per-class acceptance probabilities.
This method is based on solving the following analysis:
Let F be the probability of a rejection (on any example).
Let p_i be the proportion of examples in the data in class i (init_probs)
Let a_i is the rate the rejection sampler should *accept* class i
Let t_i is the target proportion in the minibatches for class i (target_probs)
```
F = sum_i(p_i * (1-a_i))
= 1 - sum_i(p_i * a_i) using sum_i(p_i) = 1
```
An example with class `i` will be accepted if `k` rejections occur, then an
example with class `i` is seen by the rejector, and it is accepted. This can
be written as follows:
```
t_i = sum_k=0^inf(F^k * p_i * a_i)
= p_i * a_j / (1 - F) using geometric series identity, since 0 <= F < 1
= p_i * a_i / sum_j(p_j * a_j) using F from above
```
Note that the following constraints hold:
```
0 <= p_i <= 1, sum_i(p_i) = 1
0 <= a_i <= 1
0 <= t_i <= 1, sum_i(t_i) = 1
```
A solution for a_i in terms of the other variabes is the following:
```a_i = (t_i / p_i) / max_i[t_i / p_i]``` | Calculate the per-class acceptance rates. | [
"Calculate",
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] | def _calculate_acceptance_probabilities(init_probs, target_probs):
"""Calculate the per-class acceptance rates.
Args:
init_probs: The class probabilities of the data.
target_probs: The desired class proportion in minibatches.
Returns:
A list of the per-class acceptance probabilities.
This method is based on solving the following analysis:
Let F be the probability of a rejection (on any example).
Let p_i be the proportion of examples in the data in class i (init_probs)
Let a_i is the rate the rejection sampler should *accept* class i
Let t_i is the target proportion in the minibatches for class i (target_probs)
```
F = sum_i(p_i * (1-a_i))
= 1 - sum_i(p_i * a_i) using sum_i(p_i) = 1
```
An example with class `i` will be accepted if `k` rejections occur, then an
example with class `i` is seen by the rejector, and it is accepted. This can
be written as follows:
```
t_i = sum_k=0^inf(F^k * p_i * a_i)
= p_i * a_j / (1 - F) using geometric series identity, since 0 <= F < 1
= p_i * a_i / sum_j(p_j * a_j) using F from above
```
Note that the following constraints hold:
```
0 <= p_i <= 1, sum_i(p_i) = 1
0 <= a_i <= 1
0 <= t_i <= 1, sum_i(t_i) = 1
```
A solution for a_i in terms of the other variabes is the following:
```a_i = (t_i / p_i) / max_i[t_i / p_i]```
"""
# Make list of t_i / p_i.
ratio_l = target_probs / init_probs
# Replace NaNs with 0s.
ratio_l = math_ops.select(math_ops.is_nan(ratio_l),
array_ops.zeros_like(ratio_l),
ratio_l)
# Calculate list of acceptance probabilities.
max_ratio = math_ops.reduce_max(ratio_l)
return ratio_l / max_ratio | [
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su2code/SU2 | 72b2fa977b64b9683a388920f05298a40d39e5c5 | SU2_PY/SU2/util/ordered_dict.py | python | OrderedDict.__setitem__ | (self, key, value, dict_setitem=dict.__setitem__) | od.__setitem__(i, y) <==> od[i]=y | od.__setitem__(i, y) <==> od[i]=y | [
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# Setting a new item creates a new link which goes at the end of the linked
# list, and the inherited dictionary is updated with the new key/value pair.
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root = self.__root
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last[1] = root[0] = self.__map[key] = [last, root, key]
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/predictor/predictor_factories.py | python | from_estimator | (estimator,
serving_input_receiver_fn,
output_key=None,
graph=None,
config=None) | return core_estimator_predictor.CoreEstimatorPredictor(
estimator,
serving_input_receiver_fn,
output_key=output_key,
graph=graph,
config=config) | Constructs a `Predictor` from a `tf.python.estimator.Estimator`.
Args:
estimator: an instance of `learn.python.estimator.Estimator`.
serving_input_receiver_fn: a function that takes no arguments and returns
an instance of `ServingInputReceiver` compatible with `estimator`.
output_key: Optional string specifying the export output to use. If
`None`, then `DEFAULT_SERVING_SIGNATURE_DEF_KEY` is used.
graph: Optional. The Tensorflow `graph` in which prediction should be
done.
config: `ConfigProto` proto used to configure the session.
Returns:
An initialized `Predictor`.
Raises:
TypeError: if `estimator` is a contrib `Estimator` instead of a core
`Estimator`. | Constructs a `Predictor` from a `tf.python.estimator.Estimator`. | [
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serving_input_receiver_fn,
output_key=None,
graph=None,
config=None):
"""Constructs a `Predictor` from a `tf.python.estimator.Estimator`.
Args:
estimator: an instance of `learn.python.estimator.Estimator`.
serving_input_receiver_fn: a function that takes no arguments and returns
an instance of `ServingInputReceiver` compatible with `estimator`.
output_key: Optional string specifying the export output to use. If
`None`, then `DEFAULT_SERVING_SIGNATURE_DEF_KEY` is used.
graph: Optional. The Tensorflow `graph` in which prediction should be
done.
config: `ConfigProto` proto used to configure the session.
Returns:
An initialized `Predictor`.
Raises:
TypeError: if `estimator` is a contrib `Estimator` instead of a core
`Estimator`.
"""
if isinstance(estimator, contrib_estimator.Estimator):
raise TypeError('Expected estimator to be of type '
'tf.python.estimator.Estimator, but got type '
'tf.contrib.learn.Estimator. You likely want to call '
'from_contrib_estimator.')
return core_estimator_predictor.CoreEstimatorPredictor(
estimator,
serving_input_receiver_fn,
output_key=output_key,
graph=graph,
config=config) | [
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psnonis/FinBERT | c0c555d833a14e2316a3701e59c0b5156f804b4e | bert-gpu/run_pretraining.py | python | get_next_sentence_output | (bert_config, input_tensor, labels) | Get loss and log probs for the next sentence prediction. | Get loss and log probs for the next sentence prediction. | [
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] | def get_next_sentence_output(bert_config, input_tensor, labels):
"""Get loss and log probs for the next sentence prediction."""
# Simple binary classification. Note that 0 is "next sentence" and 1 is
# "random sentence". This weight matrix is not used after pre-training.
with tf.variable_scope("cls/seq_relationship"):
output_weights = tf.get_variable(
"output_weights",
shape=[2, bert_config.hidden_size],
initializer=modeling.create_initializer(bert_config.initializer_range))
output_bias = tf.get_variable(
"output_bias", shape=[2], initializer=tf.zeros_initializer())
logits = tf.matmul(tf.cast(input_tensor, tf.float32), output_weights, transpose_b=True)
logits = tf.nn.bias_add(logits, output_bias)
log_probs = tf.nn.log_softmax(logits, axis=-1)
labels = tf.reshape(labels, [-1])
one_hot_labels = tf.one_hot(labels, depth=2, dtype=tf.float32)
per_example_loss = -tf.reduce_sum(one_hot_labels * log_probs, axis=-1)
loss = tf.reduce_mean(per_example_loss)
return (loss, per_example_loss, log_probs) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/grid.py | python | Grid.GetCellHighlightColour | (*args, **kwargs) | return _grid.Grid_GetCellHighlightColour(*args, **kwargs) | GetCellHighlightColour(self) -> Colour | GetCellHighlightColour(self) -> Colour | [
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"""GetCellHighlightColour(self) -> Colour"""
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/richtext.py | python | RichTextBuffer.BeginURL | (*args, **kwargs) | return _richtext.RichTextBuffer_BeginURL(*args, **kwargs) | BeginURL(self, String url, String characterStyle=wxEmptyString) -> bool | BeginURL(self, String url, String characterStyle=wxEmptyString) -> bool | [
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"""BeginURL(self, String url, String characterStyle=wxEmptyString) -> bool"""
return _richtext.RichTextBuffer_BeginURL(*args, **kwargs) | [
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protocolbuffers/protobuf | b5ab0b7a18b7336c60130f4ddb2d97c51792f896 | python/google/protobuf/message.py | python | Message.CopyFrom | (self, other_msg) | Copies the content of the specified message into the current message.
The method clears the current message and then merges the specified
message using MergeFrom.
Args:
other_msg (Message): A message to copy into the current one. | Copies the content of the specified message into the current message. | [
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] | def CopyFrom(self, other_msg):
"""Copies the content of the specified message into the current message.
The method clears the current message and then merges the specified
message using MergeFrom.
Args:
other_msg (Message): A message to copy into the current one.
"""
if self is other_msg:
return
self.Clear()
self.MergeFrom(other_msg) | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/distribute/cross_device_utils.py | python | stitch_values | (values_and_indices_list) | return result | Stitch values together according to their indices.
Args:
values_and_indices_list: a list of tuples of values and indices indicating
the values and postions in the returned list.
Returns:
a stitched list of values. | Stitch values together according to their indices. | [
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] | def stitch_values(values_and_indices_list):
"""Stitch values together according to their indices.
Args:
values_and_indices_list: a list of tuples of values and indices indicating
the values and postions in the returned list.
Returns:
a stitched list of values.
"""
length = 0
for values_and_indices in values_and_indices_list:
length += len(values_and_indices[0])
result = [None] * length
for values_and_indices in values_and_indices_list:
if values_and_indices and values_and_indices[0]:
for v, i in zip(*values_and_indices):
assert result[i] is None
result[i] = v
return result | [
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ducha-aiki/LSUVinit | a42ecdc0d44c217a29b65e98748d80b90d5c6279 | python/caffe/detector.py | python | Detector.configure_crop | (self, context_pad) | Configure crop dimensions and amount of context for cropping.
If context is included, make the special input mean for context padding.
Parameters
----------
context_pad : amount of context for cropping. | Configure crop dimensions and amount of context for cropping.
If context is included, make the special input mean for context padding. | [
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"""
Configure crop dimensions and amount of context for cropping.
If context is included, make the special input mean for context padding.
Parameters
----------
context_pad : amount of context for cropping.
"""
# crop dimensions
in_ = self.inputs[0]
tpose = self.transformer.transpose[in_]
inv_tpose = [tpose[t] for t in tpose]
self.crop_dims = np.array(self.blobs[in_].data.shape[1:])[inv_tpose]
#.transpose(inv_tpose)
# context padding
self.context_pad = context_pad
if self.context_pad:
in_ = self.inputs[0]
transpose = self.transformer.transpose.get(in_)
channel_order = self.transformer.channel_swap.get(in_)
raw_scale = self.transformer.raw_scale.get(in_)
# Padding context crops needs the mean in unprocessed input space.
mean = self.transformer.mean.get(in_)
if mean is not None:
inv_transpose = [transpose[t] for t in transpose]
crop_mean = mean.copy().transpose(inv_transpose)
if channel_order is not None:
channel_order_inverse = [channel_order.index(i)
for i in range(crop_mean.shape[2])]
crop_mean = crop_mean[:, :, channel_order_inverse]
if raw_scale is not None:
crop_mean /= raw_scale
self.crop_mean = crop_mean
else:
self.crop_mean = np.zeros(self.crop_dims, dtype=np.float32) | [
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forkineye/ESPixelStick | 22926f1c0d1131f1369fc7cad405689a095ae3cb | dist/bin/pyserial/serial/serialjava.py | python | Serial.cd | (self) | Read terminal status line: Carrier Detect | Read terminal status line: Carrier Detect | [
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"""Read terminal status line: Carrier Detect"""
if not self.sPort:
raise portNotOpenError
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/setuptools/command/easy_install.py | python | ScriptWriter.get_args | (cls, dist, header=None) | Yield write_script() argument tuples for a distribution's
console_scripts and gui_scripts entry points. | Yield write_script() argument tuples for a distribution's
console_scripts and gui_scripts entry points. | [
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"""
Yield write_script() argument tuples for a distribution's
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"""
if header is None:
header = cls.get_header()
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/urllib/request.py | python | FancyURLopener.http_error_301 | (self, url, fp, errcode, errmsg, headers, data=None) | return self.http_error_302(url, fp, errcode, errmsg, headers, data) | Error 301 -- also relocated (permanently). | Error 301 -- also relocated (permanently). | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py3/sklearn/feature_selection/_mutual_info.py | python | _estimate_mi | (X, y, discrete_features='auto', discrete_target=False,
n_neighbors=3, copy=True, random_state=None) | return np.array(mi) | Estimate mutual information between the features and the target.
Parameters
----------
X : array_like or sparse matrix, shape (n_samples, n_features)
Feature matrix.
y : array_like, shape (n_samples,)
Target vector.
discrete_features : {'auto', bool, array_like}, default 'auto'
If bool, then determines whether to consider all features discrete
or continuous. If array, then it should be either a boolean mask
with shape (n_features,) or array with indices of discrete features.
If 'auto', it is assigned to False for dense `X` and to True for
sparse `X`.
discrete_target : bool, default False
Whether to consider `y` as a discrete variable.
n_neighbors : int, default 3
Number of neighbors to use for MI estimation for continuous variables,
see [1]_ and [2]_. Higher values reduce variance of the estimation, but
could introduce a bias.
copy : bool, default True
Whether to make a copy of the given data. If set to False, the initial
data will be overwritten.
random_state : int, RandomState instance or None, optional, default None
The seed of the pseudo random number generator for adding small noise
to continuous variables in order to remove repeated values. If int,
random_state is the seed used by the random number generator; If
RandomState instance, random_state is the random number generator; If
None, the random number generator is the RandomState instance used by
`np.random`.
Returns
-------
mi : ndarray, shape (n_features,)
Estimated mutual information between each feature and the target.
A negative value will be replaced by 0.
References
----------
.. [1] A. Kraskov, H. Stogbauer and P. Grassberger, "Estimating mutual
information". Phys. Rev. E 69, 2004.
.. [2] B. C. Ross "Mutual Information between Discrete and Continuous
Data Sets". PLoS ONE 9(2), 2014. | Estimate mutual information between the features and the target. | [
"Estimate",
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] | def _estimate_mi(X, y, discrete_features='auto', discrete_target=False,
n_neighbors=3, copy=True, random_state=None):
"""Estimate mutual information between the features and the target.
Parameters
----------
X : array_like or sparse matrix, shape (n_samples, n_features)
Feature matrix.
y : array_like, shape (n_samples,)
Target vector.
discrete_features : {'auto', bool, array_like}, default 'auto'
If bool, then determines whether to consider all features discrete
or continuous. If array, then it should be either a boolean mask
with shape (n_features,) or array with indices of discrete features.
If 'auto', it is assigned to False for dense `X` and to True for
sparse `X`.
discrete_target : bool, default False
Whether to consider `y` as a discrete variable.
n_neighbors : int, default 3
Number of neighbors to use for MI estimation for continuous variables,
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copy : bool, default True
Whether to make a copy of the given data. If set to False, the initial
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random_state : int, RandomState instance or None, optional, default None
The seed of the pseudo random number generator for adding small noise
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random_state is the seed used by the random number generator; If
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None, the random number generator is the RandomState instance used by
`np.random`.
Returns
-------
mi : ndarray, shape (n_features,)
Estimated mutual information between each feature and the target.
A negative value will be replaced by 0.
References
----------
.. [1] A. Kraskov, H. Stogbauer and P. Grassberger, "Estimating mutual
information". Phys. Rev. E 69, 2004.
.. [2] B. C. Ross "Mutual Information between Discrete and Continuous
Data Sets". PLoS ONE 9(2), 2014.
"""
X, y = check_X_y(X, y, accept_sparse='csc', y_numeric=not discrete_target)
n_samples, n_features = X.shape
if isinstance(discrete_features, (str, bool)):
if isinstance(discrete_features, str):
if discrete_features == 'auto':
discrete_features = issparse(X)
else:
raise ValueError("Invalid string value for discrete_features.")
discrete_mask = np.empty(n_features, dtype=bool)
discrete_mask.fill(discrete_features)
else:
discrete_features = check_array(discrete_features, ensure_2d=False)
if discrete_features.dtype != 'bool':
discrete_mask = np.zeros(n_features, dtype=bool)
discrete_mask[discrete_features] = True
else:
discrete_mask = discrete_features
continuous_mask = ~discrete_mask
if np.any(continuous_mask) and issparse(X):
raise ValueError("Sparse matrix `X` can't have continuous features.")
rng = check_random_state(random_state)
if np.any(continuous_mask):
if copy:
X = X.copy()
if not discrete_target:
X[:, continuous_mask] = scale(X[:, continuous_mask],
with_mean=False, copy=False)
# Add small noise to continuous features as advised in Kraskov et. al.
X = X.astype(float, **_astype_copy_false(X))
means = np.maximum(1, np.mean(np.abs(X[:, continuous_mask]), axis=0))
X[:, continuous_mask] += 1e-10 * means * rng.randn(
n_samples, np.sum(continuous_mask))
if not discrete_target:
y = scale(y, with_mean=False)
y += 1e-10 * np.maximum(1, np.mean(np.abs(y))) * rng.randn(n_samples)
mi = [_compute_mi(x, y, discrete_feature, discrete_target, n_neighbors) for
x, discrete_feature in zip(_iterate_columns(X), discrete_mask)]
return np.array(mi) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/eclib/errdlg.py | python | ErrorDialog.OnButton | (self, evt) | Handles button events
@param evt: event that called this handler
@postcondition: Dialog is closed
@postcondition: If Report Event then email program is opened | Handles button events
@param evt: event that called this handler
@postcondition: Dialog is closed
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e_id = evt.GetId()
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/sipconfig.py | python | _expand_macro_value | (macros, rhs, properties) | return rhs | Expand the value of a macro based on ones seen so far. | Expand the value of a macro based on ones seen so far. | [
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value = ""
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value = macros.get(lhs, "")
rhs = rhs[:mstart] + value + rhs[mend:]
estart = rhs.find("$$(")
mstart = rhs.find("$$")
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TGAC/KAT | e8870331de2b4bb0a1b3b91c6afb8fb9d59e9216 | deps/boost/tools/build/src/util/path.py | python | reverse | (path) | return os.sep.join('..' for t in path.split(os.sep)) | Returns path2 such that `os.path.join(path, path2) == '.'`.
`path` may not contain '..' or be rooted.
Args:
path (str): the path to reverse
Returns:
the string of the reversed path
Example:
>>> p1 = 'path/to/somewhere'
>>> p2 = reverse('path/to/somewhere')
>>> p2
'../../..'
>>> os.path.normpath(os.path.join(p1, p2))
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"""Returns path2 such that `os.path.join(path, path2) == '.'`.
`path` may not contain '..' or be rooted.
Args:
path (str): the path to reverse
Returns:
the string of the reversed path
Example:
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>>> p2
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return os.sep.join('..' for t in path.split(os.sep)) | [
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NVIDIA/DALI | bf16cc86ba8f091b145f91962f21fe1b6aff243d | dali/python/nvidia/dali/backend.py | python | check_cuda_runtime | () | Checks the availability of CUDA runtime/GPU, and NPP, nvJEPG, and cuFFT libraries and prints an
appropriate warning. | Checks the availability of CUDA runtime/GPU, and NPP, nvJEPG, and cuFFT libraries and prints an
appropriate warning. | [
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"""
Checks the availability of CUDA runtime/GPU, and NPP, nvJEPG, and cuFFT libraries and prints an
appropriate warning.
"""
global cuda_checked
if not cuda_checked:
cuda_checked = True
if GetCudaVersion() == -1:
deprecation_warning("GPU is not available. Only CPU operators are available.")
if GetCufftVersion() == -1:
deprecation_warning("Cannot access cuFFT library. Please check cuda installation and/or "
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if GetNppVersion() == -1:
deprecation_warning("Cannot access NPP library. Please check cuda installation and/or "
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if GetNvjpegVersion() == -1:
deprecation_warning("Cannot access nvJPEG library. Please check cuda installation and/or "
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/node-10.15.3/deps/v8/third_party/jinja2/loaders.py | python | BaseLoader.list_templates | (self) | Iterates over all templates. If the loader does not support that
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/PIL/PngImagePlugin.py | python | iTXt.__new__ | (cls, text, lang=None, tkey=None) | return self | :param cls: the class to use when creating the instance
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/webkit.py | python | WebKitCtrl.IncreaseTextSize | (*args, **kwargs) | return _webkit.WebKitCtrl_IncreaseTextSize(*args, **kwargs) | IncreaseTextSize(self) | IncreaseTextSize(self) | [
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google/nucleus | 68d3947fafba1337f294c0668a6e1c7f3f1273e3 | nucleus/io/genomics_reader.py | python | DispatchingGenomicsReader._native_reader | (self, input_path, **kwargs) | Returns a GenomicsReader for reading the records `natively`.
Args:
input_path: The path to the native file to read.
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"""Returns a GenomicsReader for reading the records `natively`.
Args:
input_path: The path to the native file to read.
**kwargs: Zero or more keyword arguments.
Returns:
A GenomicsReader.
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moflow/moflow | 2dfb27c799c90c6caf1477508eca3eec616ef7d2 | bap/libtracewrap/libtrace/protobuf/python/mox.py | python | And.equals | (self, rhs) | return True | Checks whether all Comparators are equal to rhs.
Args:
# rhs: can be anything
Returns:
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bool
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/distutils/config.py | python | PyPIRCCommand._get_rc_file | (self) | return os.path.join(os.path.expanduser('~'), '.pypirc') | Returns rc file path. | Returns rc file path. | [
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OSGeo/gdal | 3748fc4ba4fba727492774b2b908a2130c864a83 | swig/python/osgeo/gdal.py | python | Band.GetDataCoverageStatus | (self, *args) | return _gdal.Band_GetDataCoverageStatus(self, *args) | r"""GetDataCoverageStatus(Band self, int nXOff, int nYOff, int nXSize, int nYSize, int nMaskFlagStop=0) -> int | r"""GetDataCoverageStatus(Band self, int nXOff, int nYOff, int nXSize, int nYSize, int nMaskFlagStop=0) -> int | [
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r"""GetDataCoverageStatus(Band self, int nXOff, int nYOff, int nXSize, int nYSize, int nMaskFlagStop=0) -> int"""
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netket/netket | 0d534e54ecbf25b677ea72af6b85947979420652 | netket/nn/masked_linear.py | python | wrap_kernel_init | (kernel_init, mask) | return wrapped_kernel_init | Correction to LeCun normal init. | Correction to LeCun normal init. | [
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"""Correction to LeCun normal init."""
corr = jnp.sqrt(mask.size / mask.sum())
def wrapped_kernel_init(*args):
return corr * mask * kernel_init(*args)
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scummvm/scummvm | 9c039d027e7ffb9d83ae2e274147e2daf8d57ce2 | devtools/dumper-companion.py | python | has_resource_fork | (dirpath: bytes, filename: bytes) | return os.path.exists(os.path.join(filepath, bytes("..namedfork/rsrc", "utf8"))) | Check if file has a resource fork
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filepath = os.path.join(dirpath, filename)
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/jinja2/environment.py | python | _environment_sanity_check | (environment) | return environment | Perform a sanity check on the environment. | Perform a sanity check on the environment. | [
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assert environment.block_start_string != \
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assert environment.newline_sequence in ('\r', '\r\n', '\n'), \
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Tencent/CMONGO | c40380caa14e05509f46993aa8b8da966b09b0b5 | src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Tool/wix.py | python | generate | (env) | Add Builders and construction variables for WiX to an Environment. | Add Builders and construction variables for WiX to an Environment. | [
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"""Add Builders and construction variables for WiX to an Environment."""
if not exists(env):
return
env['WIXCANDLEFLAGS'] = ['-nologo']
env['WIXCANDLEINCLUDE'] = []
env['WIXCANDLECOM'] = '$WIXCANDLE $WIXCANDLEFLAGS -I $WIXCANDLEINCLUDE -o ${TARGET} ${SOURCE}'
env['WIXLIGHTFLAGS'].append( '-nologo' )
env['WIXLIGHTCOM'] = "$WIXLIGHT $WIXLIGHTFLAGS -out ${TARGET} ${SOURCES}"
env['WIXSRCSUF'] = '.wxs'
env['WIXOBJSUF'] = '.wixobj'
object_builder = SCons.Builder.Builder(
action = '$WIXCANDLECOM',
suffix = '$WIXOBJSUF',
src_suffix = '$WIXSRCSUF')
linker_builder = SCons.Builder.Builder(
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src_suffix = '$WIXOBJSUF',
src_builder = object_builder)
env['BUILDERS']['WiX'] = linker_builder | [
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GoSSIP-SJTU/TripleDoggy | 03648d6b19c812504b14e8b98c8c7b3f443f4e54 | bindings/python/llvm/object.py | python | Relocation.offset | (self) | return lib.LLVMGetRelocationOffset(self) | The offset of this relocation, in long bytes. | The offset of this relocation, in long bytes. | [
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if self.expired:
raise Exception('Relocation instance has expired.')
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/nntplib.py | python | NNTP.body | (self, id, file=None) | return self.artcmd('BODY ' + id, file) | Process a BODY command. Argument:
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- file: Filename string or file object to store the article in
Returns:
- resp: server response if successful
- nr: article number
- id: message id
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- file: Filename string or file object to store the article in
Returns:
- resp: server response if successful
- nr: article number
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- resp: server response if successful
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/core/arrays/base.py | python | ExtensionArray.__iter__ | (self) | Iterate over elements of the array. | Iterate over elements of the array. | [
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"""
Iterate over elements of the array.
"""
# This needs to be implemented so that pandas recognizes extension
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# calls to ``__getitem__``, which may be slower than necessary.
for i in range(len(self)):
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/distutils/command/install.py | python | install.get_inputs | (self) | return inputs | Returns the inputs of all the sub-commands | Returns the inputs of all the sub-commands | [
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# XXX gee, this looks familiar ;-(
inputs = []
for cmd_name in self.get_sub_commands():
cmd = self.get_finalized_command(cmd_name)
inputs.extend(cmd.get_inputs())
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eventql/eventql | 7ca0dbb2e683b525620ea30dc40540a22d5eb227 | deps/3rdparty/spidermonkey/mozjs/python/bitstring/bitstring.py | python | ConstBitStream.bytealign | (self) | return skipped | Align to next byte and return number of skipped bits.
Raises ValueError if the end of the bitstring is reached before
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"""Align to next byte and return number of skipped bits.
Raises ValueError if the end of the bitstring is reached before
aligning to the next byte.
"""
skipped = (8 - (self._pos % 8)) % 8
self.pos += self._offset + skipped
assert self._assertsanity()
return skipped | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/hotshot/__init__.py | python | Profile.runctx | (self, cmd, globals, locals) | return self | Evaluate an exec-compatible string in a specific
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self._prof.runcode(code, globals, locals)
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2class.py | python | xmlDtd.dtdAttrDesc | (self, elem, name) | return __tmp | Search the DTD for the description of this attribute on
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/pkg_resources/extern/__init__.py | python | VendorImporter.search_path | (self) | Search first the vendor package then as a natural package. | Search first the vendor package then as a natural package. | [
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"""
Search first the vendor package then as a natural package.
"""
yield self.vendor_pkg + '.'
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CGRU/cgru | 1881a4128530e3d31ac6c25314c18314fc50c2c7 | afanasy/python/af.py | python | Block.setTaskProgressChangeTimeout | (self, value) | If running task will not change its progress (percentage)
for this time, it will be stopped with an error.
:param value: timeout in seconds | If running task will not change its progress (percentage)
for this time, it will be stopped with an error.
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"value",
")"
] | https://github.com/CGRU/cgru/blob/1881a4128530e3d31ac6c25314c18314fc50c2c7/afanasy/python/af.py#L425-L431 |
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