nwo stringlengths 5 86 | sha stringlengths 40 40 | path stringlengths 4 189 | language stringclasses 1 value | identifier stringlengths 1 94 | parameters stringlengths 2 4.03k | argument_list stringclasses 1 value | return_statement stringlengths 0 11.5k | docstring stringlengths 1 33.2k | docstring_summary stringlengths 0 5.15k | docstring_tokens list | function stringlengths 34 151k | function_tokens list | url stringlengths 90 278 |
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/dataview.py | python | DataViewItemAttr.GetItalic | (*args, **kwargs) | return _dataview.DataViewItemAttr_GetItalic(*args, **kwargs) | GetItalic(self) -> bool | GetItalic(self) -> bool | [
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"""GetItalic(self) -> bool"""
return _dataview.DataViewItemAttr_GetItalic(*args, **kwargs) | [
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CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Editor/Python/windows/Lib/site-packages/pip/_vendor/ipaddress.py | python | ip_network | (address, strict=True) | Take an IP string/int and return an object of the correct type.
Args:
address: A string or integer, the IP network. Either IPv4 or
IPv6 networks may be supplied; integers less than 2**32 will
be considered to be IPv4 by default.
Returns:
An IPv4Network or IPv6Network object.
Raises:
ValueError: if the string passed isn't either a v4 or a v6
address. Or if the network has host bits set. | Take an IP string/int and return an object of the correct type. | [
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"""Take an IP string/int and return an object of the correct type.
Args:
address: A string or integer, the IP network. Either IPv4 or
IPv6 networks may be supplied; integers less than 2**32 will
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Returns:
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Raises:
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"""
try:
return IPv4Network(address, strict)
except (AddressValueError, NetmaskValueError):
pass
try:
return IPv6Network(address, strict)
except (AddressValueError, NetmaskValueError):
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raise ValueError('%r does not appear to be an IPv4 or IPv6 network' %
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py3/scipy/linalg/special_matrices.py | python | invhilbert | (n, exact=False) | return invh | Compute the inverse of the Hilbert matrix of order `n`.
The entries in the inverse of a Hilbert matrix are integers. When `n`
is greater than 14, some entries in the inverse exceed the upper limit
of 64 bit integers. The `exact` argument provides two options for
dealing with these large integers.
Parameters
----------
n : int
The order of the Hilbert matrix.
exact : bool, optional
If False, the data type of the array that is returned is np.float64,
and the array is an approximation of the inverse.
If True, the array is the exact integer inverse array. To represent
the exact inverse when n > 14, the returned array is an object array
of long integers. For n <= 14, the exact inverse is returned as an
array with data type np.int64.
Returns
-------
invh : (n, n) ndarray
The data type of the array is np.float64 if `exact` is False.
If `exact` is True, the data type is either np.int64 (for n <= 14)
or object (for n > 14). In the latter case, the objects in the
array will be long integers.
See Also
--------
hilbert : Create a Hilbert matrix.
Notes
-----
.. versionadded:: 0.10.0
Examples
--------
>>> from scipy.linalg import invhilbert
>>> invhilbert(4)
array([[ 16., -120., 240., -140.],
[ -120., 1200., -2700., 1680.],
[ 240., -2700., 6480., -4200.],
[ -140., 1680., -4200., 2800.]])
>>> invhilbert(4, exact=True)
array([[ 16, -120, 240, -140],
[ -120, 1200, -2700, 1680],
[ 240, -2700, 6480, -4200],
[ -140, 1680, -4200, 2800]], dtype=int64)
>>> invhilbert(16)[7,7]
4.2475099528537506e+19
>>> invhilbert(16, exact=True)[7,7]
42475099528537378560L | Compute the inverse of the Hilbert matrix of order `n`. | [
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"""
Compute the inverse of the Hilbert matrix of order `n`.
The entries in the inverse of a Hilbert matrix are integers. When `n`
is greater than 14, some entries in the inverse exceed the upper limit
of 64 bit integers. The `exact` argument provides two options for
dealing with these large integers.
Parameters
----------
n : int
The order of the Hilbert matrix.
exact : bool, optional
If False, the data type of the array that is returned is np.float64,
and the array is an approximation of the inverse.
If True, the array is the exact integer inverse array. To represent
the exact inverse when n > 14, the returned array is an object array
of long integers. For n <= 14, the exact inverse is returned as an
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Returns
-------
invh : (n, n) ndarray
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or object (for n > 14). In the latter case, the objects in the
array will be long integers.
See Also
--------
hilbert : Create a Hilbert matrix.
Notes
-----
.. versionadded:: 0.10.0
Examples
--------
>>> from scipy.linalg import invhilbert
>>> invhilbert(4)
array([[ 16., -120., 240., -140.],
[ -120., 1200., -2700., 1680.],
[ 240., -2700., 6480., -4200.],
[ -140., 1680., -4200., 2800.]])
>>> invhilbert(4, exact=True)
array([[ 16, -120, 240, -140],
[ -120, 1200, -2700, 1680],
[ 240, -2700, 6480, -4200],
[ -140, 1680, -4200, 2800]], dtype=int64)
>>> invhilbert(16)[7,7]
4.2475099528537506e+19
>>> invhilbert(16, exact=True)[7,7]
42475099528537378560L
"""
from scipy.special import comb
if exact:
if n > 14:
dtype = object
else:
dtype = np.int64
else:
dtype = np.float64
invh = np.empty((n, n), dtype=dtype)
for i in xrange(n):
for j in xrange(0, i + 1):
s = i + j
invh[i, j] = ((-1) ** s * (s + 1) *
comb(n + i, n - j - 1, exact) *
comb(n + j, n - i - 1, exact) *
comb(s, i, exact) ** 2)
if i != j:
invh[j, i] = invh[i, j]
return invh | [
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kamyu104/LeetCode-Solutions | 77605708a927ea3b85aee5a479db733938c7c211 | Python/design-hashmap.py | python | MyHashMap.put | (self, key, value) | value will always be positive.
:type key: int
:type value: int
:rtype: void | value will always be positive.
:type key: int
:type value: int
:rtype: void | [
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"""
value will always be positive.
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:type value: int
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"""
l = self.__data[key % len(self.__data)]
node = l.find(key)
if node:
node.val = value
else:
l.insert(ListNode(key, value)) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/attr/filters.py | python | _split_what | (what) | return (
frozenset(cls for cls in what if isclass(cls)),
frozenset(cls for cls in what if isinstance(cls, Attribute)),
) | Returns a tuple of `frozenset`s of classes and attributes. | Returns a tuple of `frozenset`s of classes and attributes. | [
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Returns a tuple of `frozenset`s of classes and attributes.
"""
return (
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rodeofx/OpenWalter | 6116fbe3f04f1146c854afbfbdbe944feaee647e | walter/maya/scripts/walterPanel/walterMayaTraverser.py | python | WalterMayaImplementation.setOverride | (self, origin, layer, path, material, overrideType) | Save the material from the Maya nodes. It's looking for the connections
of the Walter Standin object and creates/replaces the connection to the
material.
Args:
origin: The Walter Standin object that contains the tree.
layer: Render layer to save the material.
path: The Alembic path to the node.
material: The material object
overrideType: The type of the override. Example: shader/displacement | Save the material from the Maya nodes. It's looking for the connections
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"""
Save the material from the Maya nodes. It's looking for the connections
of the Walter Standin object and creates/replaces the connection to the
material.
Args:
origin: The Walter Standin object that contains the tree.
layer: Render layer to save the material.
path: The Alembic path to the node.
material: The material object
overrideType: The type of the override. Example: shader/displacement
"""
# Material
materialNode = self.getDependNode(material)
if not materialNode:
om.MGlobal.displayError(
"%s: Material %s doesn't exist." % (self.NAME, material))
return
materialMessage = materialNode.findPlug("message", False)
# Get walterStandin.layersAssignation
layersAssignation = self.getLayersAssignationPlug(origin)
# Get walterStandin.layersAssignation[i].shaderConnections
shadersPlug = self.findShadersPlug(layersAssignation, layer)
# Create if not found
if not shadersPlug:
# Get walterStandin.layersAssignation[i]
layersAssignationPlug = self.addElementToPlug(layersAssignation)
# Get walterStandin.layersAssignation[i].layer
layerPlug = self.getChildMPlug(layersAssignationPlug, 'layer')
# Get walterStandin.layersAssignation[i].shaderConnections
shadersPlug = self.getChildMPlug(
layersAssignationPlug, 'shaderConnections')
# Connect the layer to the layerPlug
layerDepend = self.getDependNode(layer)
layerMessage = layerDepend.findPlug("message", False)
self.modifier.connect(layerMessage, layerPlug)
self.modifier.doIt()
firstAvailableCompound = None
# Find if there is already an assignment with this path
for j in range(shadersPlug.numElements()):
# Get walterStandin.layersAssignation[i].shaderConnections[j]
shadersCompound = shadersPlug.elementByPhysicalIndex(j)
# Get walterStandin.layersAssignation[].shaderConnections[j].abcnode
abcnodePlug = self.getChildMPlug(shadersCompound, 'abcnode')
abcnode = abcnodePlug.asString()
if not firstAvailableCompound and not abcnode:
# Save it to reuse in future and avoid creating new elements
firstAvailableCompound = shadersCompound
if abcnode != path:
continue
# We are here because we found requested assignment. We need to
# change the connection with the shader
# Get walterStandin.layersAssignation[i].shaderConnections[j].shader
shaderPlug = self.getChildMPlug(shadersCompound, overrideType)
self.disconnectPlug(shaderPlug)
self.modifier.connect(materialMessage, shaderPlug)
self.modifier.doIt()
return
# We are here because were unable to find the path.
# Add an element to walterStandin.layersAssignation[i].shaderConnections
# or use available if found
shadersCompound = \
firstAvailableCompound or self.addElementToPlug(shadersPlug)
# Get walterStandin.layersAssignation[i].shaderConnections[j].abcnode
abcnodePlug = self.getChildMPlug(shadersCompound, 'abcnode')
abcnodePlug.setString(path)
# Get walterStandin.layersAssignation[i].shaderConnections[j].shader
shaderPlug = self.getChildMPlug(shadersCompound, overrideType)
self.disconnectPlug(shaderPlug)
self.modifier.connect(materialMessage, shaderPlug)
self.modifier.doIt() | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/extern/aui/framemanager.py | python | FindPaneInDock | (dock, window) | return None | This method looks up a specified window pointer inside a dock.
If found, the corresponding :class:`AuiDockInfo` pointer is returned, otherwise ``None``.
:param `dock`: a :class:`AuiDockInfo` structure;
:param Window `window`: the window associated to the pane we are seeking. | This method looks up a specified window pointer inside a dock.
If found, the corresponding :class:`AuiDockInfo` pointer is returned, otherwise ``None``. | [
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If found, the corresponding :class:`AuiDockInfo` pointer is returned, otherwise ``None``.
:param `dock`: a :class:`AuiDockInfo` structure;
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for p in dock.panes:
if p.window == window:
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/io/pytables.py | python | _ensure_decoded | (s) | return s | if we have bytes, decode them to unicode | if we have bytes, decode them to unicode | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/src/robotsim.py | python | RobotModelDriver.getValue | (self) | return _robotsim.RobotModelDriver_getValue(self) | getValue(RobotModelDriver self) -> double
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"""
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"""
return _robotsim.RobotModelDriver_getValue(self) | [
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sailing-pmls/bosen | 06cb58902d011fbea5f9428f10ce30e621492204 | style_script/cpplint.py | python | ProcessConfigOverrides | (filename) | return True | Loads the configuration files and processes the config overrides.
Args:
filename: The name of the file being processed by the linter.
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False if the current |filename| should not be processed further. | Loads the configuration files and processes the config overrides. | [
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""" Loads the configuration files and processes the config overrides.
Args:
filename: The name of the file being processed by the linter.
Returns:
False if the current |filename| should not be processed further.
"""
abs_filename = os.path.abspath(filename)
cfg_filters = []
keep_looking = True
while keep_looking:
abs_path, base_name = os.path.split(abs_filename)
if not base_name:
break # Reached the root directory.
cfg_file = os.path.join(abs_path, "CPPLINT.cfg")
abs_filename = abs_path
if not os.path.isfile(cfg_file):
continue
try:
with open(cfg_file) as file_handle:
for line in file_handle:
line, _, _ = line.partition('#') # Remove comments.
if not line.strip():
continue
name, _, val = line.partition('=')
name = name.strip()
val = val.strip()
if name == 'set noparent':
keep_looking = False
elif name == 'filter':
cfg_filters.append(val)
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# and we found the .cfg file at /foo/CPPLINT.cfg, then the config
# file's "exclude_files" filter is meant to be checked against "bar"
# and not "baz" nor "bar/baz.cc".
if base_name:
pattern = re.compile(val)
if pattern.match(base_name):
sys.stderr.write('Ignoring "%s": file excluded by "%s". '
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'pattern "%s"\n' %
(filename, cfg_file, base_name, val))
return False
elif name == 'linelength':
global _line_length
try:
_line_length = int(val)
except ValueError:
sys.stderr.write('Line length must be numeric.')
else:
sys.stderr.write(
'Invalid configuration option (%s) in file %s\n' %
(name, cfg_file))
except IOError:
sys.stderr.write(
"Skipping config file '%s': Can't open for reading\n" % cfg_file)
keep_looking = False
# Apply all the accumulated filters in reverse order (top-level directory
# config options having the least priority).
for filter in reversed(cfg_filters):
_AddFilters(filter)
return True | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py | python | Text.image_create | (self, index, cnf={}, **kw) | return self.tk.call(
self._w, "image", "create", index,
*self._options(cnf, kw)) | Create an embedded image at INDEX. | Create an embedded image at INDEX. | [
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"""Create an embedded image at INDEX."""
return self.tk.call(
self._w, "image", "create", index,
*self._options(cnf, kw)) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/importlib/resources.py | python | is_resource | (package: Package, name: str) | return path.is_file() | True if 'name' is a resource inside 'package'.
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"""True if 'name' is a resource inside 'package'.
Directories are *not* resources.
"""
package = _get_package(package)
_normalize_path(name)
reader = _get_resource_reader(package)
if reader is not None:
return reader.is_resource(name)
try:
package_contents = set(contents(package))
except (NotADirectoryError, FileNotFoundError):
return False
if name not in package_contents:
return False
# Just because the given file_name lives as an entry in the package's
# contents doesn't necessarily mean it's a resource. Directories are not
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path = Path(package.__spec__.origin).parent / name
return path.is_file() | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/idlelib/tabbedpages.py | python | TabbedPageSet.remove_page | (self, page_name) | Destroy the page whose name is given in page_name. | Destroy the page whose name is given in page_name. | [
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] | def remove_page(self, page_name):
"""Destroy the page whose name is given in page_name."""
if not page_name in self.pages:
raise KeyError("No such TabPage: '%s" % page_name)
self._pages_order.remove(page_name)
# handle removing last remaining, default, or currently shown page
if len(self._pages_order) > 0:
if page_name == self._default_page:
# set a new default page
self._default_page = self._pages_order[0]
else:
self._default_page = None
if page_name == self._current_page:
self.change_page(self._default_page)
self._tab_set.remove_tab(page_name)
page = self.pages.pop(page_name)
page.frame.destroy() | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | Image.ResampleBicubic | (*args, **kwargs) | return _core_.Image_ResampleBicubic(*args, **kwargs) | ResampleBicubic(self, int width, int height) -> Image | ResampleBicubic(self, int width, int height) -> Image | [
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"""ResampleBicubic(self, int width, int height) -> Image"""
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Kitware/ParaView | f760af9124ff4634b23ebbeab95a4f56e0261955 | Wrapping/Python/paraview/coprocessing.py | python | CoProcessor.__AppendToCinemaDTable | (self, time, producer, filename) | This is called every time catalyst writes any data file or screenshot
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Note, we aggregate file operations later with __FinalizeCinemaDTable. | This is called every time catalyst writes any data file or screenshot
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"""
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Note, we aggregate file operations later with __FinalizeCinemaDTable.
"""
if self.__CinemaDHelper is None:
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comm = vtk.vtkMultiProcessController.GetGlobalController()
if comm.GetLocalProcessId() == 0:
self.__CinemaDHelper.AppendToCinemaDTable(time, producer, filename) | [
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francinexue/xuefu | b6ff79747a42e020588c0c0a921048e08fe4680c | ctpx/ctp3/ctptd.py | python | CtpTd.onFrontConnected | (self) | 当客户端与交易后台建立起通信连接时（还未登录前），该方法被调用。 | 当客户端与交易后台建立起通信连接时（还未登录前），该方法被调用。 | [
"当客户端与交易后台建立起通信连接时（还未登录前），该方法被调用。"
] | def onFrontConnected(self):
"""当客户端与交易后台建立起通信连接时（还未登录前），该方法被调用。"""
reqLoginField = td.ReqUserLoginField()
reqLoginField.userID = self._userID
reqLoginField.password = self._password
reqLoginField.brokerID = self._brokerID
self._requestId += 1
self.reqUserLogin(reqLoginField, self._requestId) | [
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PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/distributed/fleet/utils/http_server.py | python | KVHandler.do_PUT | (self) | put method for kv handler, set value according to key. | put method for kv handler, set value according to key. | [
"put",
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"handler",
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] | def do_PUT(self):
"""
put method for kv handler, set value according to key.
"""
log_str = "PUT " + self.address_string() + self.path
paths = self.path.split('/')
if len(paths) < 3:
print('len of request path must be 3: ' + self.path)
self.send_status_code(400)
return
_, scope, key = paths
content_length = int(self.headers['Content-Length'])
try:
value = self.rfile.read(content_length)
except:
print("receive error invalid request")
self.send_status_code(404)
return
with self.server.kv_lock:
if self.server.kv.get(scope) is None:
self.server.kv[scope] = {}
self.server.kv[scope][key] = value
self.send_status_code(200)
_http_server_logger.info(log_str) | [
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sdhash/sdhash | b9eff63e4e5867e910f41fd69032bbb1c94a2a5e | sdhash-ui/cherrypy/__init__.py | python | _TimeoutMonitor.run | (self) | Check timeout on all responses. (Internal) | Check timeout on all responses. (Internal) | [
"Check",
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"responses",
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] | def run(self):
"""Check timeout on all responses. (Internal)"""
for req, resp in self.servings:
resp.check_timeout() | [
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2class.py | python | xmlDoc.searchNsByHref | (self, node, href) | return __tmp | Search a Ns aliasing a given URI. Recurse on the parents
until it finds the defined namespace or return None
otherwise. | Search a Ns aliasing a given URI. Recurse on the parents
until it finds the defined namespace or return None
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] | def searchNsByHref(self, node, href):
"""Search a Ns aliasing a given URI. Recurse on the parents
until it finds the defined namespace or return None
otherwise. """
if node is None: node__o = None
else: node__o = node._o
ret = libxml2mod.xmlSearchNsByHref(self._o, node__o, href)
if ret is None:raise treeError('xmlSearchNsByHref() failed')
__tmp = xmlNs(_obj=ret)
return __tmp | [
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baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/framework/ops.py | python | Graph.collections | (self) | return list(self._collections) | Returns the names of the collections known to this graph. | Returns the names of the collections known to this graph. | [
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] | def collections(self):
"""Returns the names of the collections known to this graph."""
return list(self._collections) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/cuda/decorators.py | python | jit | (func_or_sig=None, argtypes=None, device=False, inline=False, bind=True,
link=[], debug=None, **kws) | JIT compile a python function conforming to the CUDA Python specification.
If a signature is supplied, then a function is returned that takes a
function to compile. If
:param func_or_sig: A function to JIT compile, or a signature of a function
to compile. If a function is supplied, then an :class:`AutoJitCUDAKernel`
is returned. If a signature is supplied, then a function which takes a
function to compile and returns an :class:`AutoJitCUDAKernel` is
returned.
.. note:: A kernel cannot have any return value.
:type func_or_sig: function or numba.typing.Signature
:param device: Indicates whether this is a device function.
:type device: bool
:param bind: Force binding to CUDA context immediately
:type bind: bool
:param link: A list of files containing PTX source to link with the function
:type link: list
:param debug: If True, check for exceptions thrown when executing the
kernel. Since this degrades performance, this should only be used for
debugging purposes. Defaults to False. (The default value can be
overridden by setting environment variable ``NUMBA_CUDA_DEBUGINFO=1``.)
:param fastmath: If true, enables flush-to-zero and fused-multiply-add,
disables precise division and square root. This parameter has no effect
on device function, whose fastmath setting depends on the kernel function
from which they are called.
:param max_registers: Limit the kernel to using at most this number of
registers per thread. Useful for increasing occupancy. | JIT compile a python function conforming to the CUDA Python specification.
If a signature is supplied, then a function is returned that takes a
function to compile. If | [
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link=[], debug=None, **kws):
"""
JIT compile a python function conforming to the CUDA Python specification.
If a signature is supplied, then a function is returned that takes a
function to compile. If
:param func_or_sig: A function to JIT compile, or a signature of a function
to compile. If a function is supplied, then an :class:`AutoJitCUDAKernel`
is returned. If a signature is supplied, then a function which takes a
function to compile and returns an :class:`AutoJitCUDAKernel` is
returned.
.. note:: A kernel cannot have any return value.
:type func_or_sig: function or numba.typing.Signature
:param device: Indicates whether this is a device function.
:type device: bool
:param bind: Force binding to CUDA context immediately
:type bind: bool
:param link: A list of files containing PTX source to link with the function
:type link: list
:param debug: If True, check for exceptions thrown when executing the
kernel. Since this degrades performance, this should only be used for
debugging purposes. Defaults to False. (The default value can be
overridden by setting environment variable ``NUMBA_CUDA_DEBUGINFO=1``.)
:param fastmath: If true, enables flush-to-zero and fused-multiply-add,
disables precise division and square root. This parameter has no effect
on device function, whose fastmath setting depends on the kernel function
from which they are called.
:param max_registers: Limit the kernel to using at most this number of
registers per thread. Useful for increasing occupancy.
"""
debug = config.CUDA_DEBUGINFO_DEFAULT if debug is None else debug
if link and config.ENABLE_CUDASIM:
raise NotImplementedError('Cannot link PTX in the simulator')
if 'boundscheck' in kws:
raise NotImplementedError("bounds checking is not supported for CUDA")
fastmath = kws.get('fastmath', False)
if argtypes is None and not sigutils.is_signature(func_or_sig):
if func_or_sig is None:
if config.ENABLE_CUDASIM:
def autojitwrapper(func):
return FakeCUDAKernel(func, device=device, fastmath=fastmath,
debug=debug)
else:
def autojitwrapper(func):
return jit(func, device=device, bind=bind, debug=debug,
**kws)
return autojitwrapper
# func_or_sig is a function
else:
if config.ENABLE_CUDASIM:
return FakeCUDAKernel(func_or_sig, device=device, fastmath=fastmath,
debug=debug)
elif device:
return jitdevice(func_or_sig, debug=debug, **kws)
else:
targetoptions = kws.copy()
targetoptions['debug'] = debug
return AutoJitCUDAKernel(func_or_sig, bind=bind, targetoptions=targetoptions)
else:
if config.ENABLE_CUDASIM:
def jitwrapper(func):
return FakeCUDAKernel(func, device=device, fastmath=fastmath,
debug=debug)
return jitwrapper
restype, argtypes = convert_types(func_or_sig, argtypes)
if restype and not device and restype != types.void:
raise TypeError("CUDA kernel must have void return type.")
def kernel_jit(func):
kernel = compile_kernel(func, argtypes, link=link, debug=debug,
inline=inline, fastmath=fastmath)
# Force compilation for the current context
if bind:
kernel.bind()
return kernel
def device_jit(func):
return compile_device(func, restype, argtypes, inline=inline,
debug=debug)
if device:
return device_jit
else:
return kernel_jit | [
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lmb-freiburg/ogn | 974f72ef4bf840d6f6693d22d1843a79223e77ce | python/caffe/io.py | python | load_image | (filename, color=True) | return img | Load an image converting from grayscale or alpha as needed.
Parameters
----------
filename : string
color : boolean
flag for color format. True (default) loads as RGB while False
loads as intensity (if image is already grayscale).
Returns
-------
image : an image with type np.float32 in range [0, 1]
of size (H x W x 3) in RGB or
of size (H x W x 1) in grayscale. | Load an image converting from grayscale or alpha as needed. | [
"Load",
"an",
"image",
"converting",
"from",
"grayscale",
"or",
"alpha",
"as",
"needed",
"."
] | def load_image(filename, color=True):
"""
Load an image converting from grayscale or alpha as needed.
Parameters
----------
filename : string
color : boolean
flag for color format. True (default) loads as RGB while False
loads as intensity (if image is already grayscale).
Returns
-------
image : an image with type np.float32 in range [0, 1]
of size (H x W x 3) in RGB or
of size (H x W x 1) in grayscale.
"""
img = skimage.img_as_float(skimage.io.imread(filename, as_grey=not color)).astype(np.float32)
if img.ndim == 2:
img = img[:, :, np.newaxis]
if color:
img = np.tile(img, (1, 1, 3))
elif img.shape[2] == 4:
img = img[:, :, :3]
return img | [
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Tencent/CMONGO | c40380caa14e05509f46993aa8b8da966b09b0b5 | buildscripts/moduleconfig.py | python | discover_modules | (module_root, allowed_modules) | return found_modules | Scans module_root for subdirectories that look like MongoDB modules.
Returns a list of imported build.py module objects. | Scans module_root for subdirectories that look like MongoDB modules. | [
"Scans",
"module_root",
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"that",
"look",
"like",
"MongoDB",
"modules",
"."
] | def discover_modules(module_root, allowed_modules):
"""Scans module_root for subdirectories that look like MongoDB modules.
Returns a list of imported build.py module objects.
"""
found_modules = []
if allowed_modules is not None:
allowed_modules = allowed_modules.split(',')
if not os.path.isdir(module_root):
return found_modules
for name in os.listdir(module_root):
root = os.path.join(module_root, name)
if name.startswith('.') or not os.path.isdir(root):
continue
build_py = os.path.join(root, 'build.py')
module = None
if allowed_modules is not None and name not in allowed_modules:
print "skipping module: %s" % name
continue
if os.path.isfile(build_py):
print "adding module: %s" % name
fp = open(build_py, "r")
try:
module = imp.load_module("module_" + name, fp, build_py,
(".py", "r", imp.PY_SOURCE))
if getattr(module, "name", None) is None:
module.name = name
found_modules.append(module)
finally:
fp.close()
return found_modules | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/idlelib/RemoteDebugger.py | python | start_debugger | (rpchandler, gui_adap_oid) | return idb_adap_oid | Start the debugger and its RPC link in the Python subprocess
Start the subprocess side of the split debugger and set up that side of the
RPC link by instantiating the GUIProxy, Idb debugger, and IdbAdapter
objects and linking them together. Register the IdbAdapter with the
RPCServer to handle RPC requests from the split debugger GUI via the
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"""Start the debugger and its RPC link in the Python subprocess
Start the subprocess side of the split debugger and set up that side of the
RPC link by instantiating the GUIProxy, Idb debugger, and IdbAdapter
objects and linking them together. Register the IdbAdapter with the
RPCServer to handle RPC requests from the split debugger GUI via the
IdbProxy.
"""
gui_proxy = GUIProxy(rpchandler, gui_adap_oid)
idb = Debugger.Idb(gui_proxy)
idb_adap = IdbAdapter(idb)
rpchandler.register(idb_adap_oid, idb_adap)
return idb_adap_oid | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/stc.py | python | StyledTextCtrl.DoDropText | (*args, **kwargs) | return _stc.StyledTextCtrl_DoDropText(*args, **kwargs) | DoDropText(self, long x, long y, String data) -> bool
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microsoft/checkedc-clang | a173fefde5d7877b7750e7ce96dd08cf18baebf2 | llvm/utils/lit/lit/util.py | python | to_unicode | (s) | return s | Return the parameter as type which supports unicode, possibly decoding
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"""
if isinstance(s, bytes):
# In Python2, this branch is taken for both 'str' and 'bytes'.
# In Python3, this branch is taken only for 'bytes'.
return s.decode('utf-8')
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/profiler/parser/framework_parser.py | python | FrameworkParser.save_path | (self) | return os.path.realpath(os.path.join(self._output_path, self.output_file_format.format(rank_id=self._rank_id))) | The property of save path.
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/core/defchararray.py | python | asarray | (obj, itemsize=None, unicode=None, order=None) | return array(obj, itemsize, copy=False,
unicode=unicode, order=order) | Convert the input to a `chararray`, copying the data only if
necessary.
Versus a regular NumPy array of type `str` or `unicode`, this
class adds the following functionality:
1) values automatically have whitespace removed from the end
when indexed
2) comparison operators automatically remove whitespace from the
end when comparing values
3) vectorized string operations are provided as methods
(e.g. `str.endswith`) and infix operators (e.g. ``+``, ``*``,``%``)
Parameters
----------
obj : array of str or unicode-like
itemsize : int, optional
`itemsize` is the number of characters per scalar in the
resulting array. If `itemsize` is None, and `obj` is an
object array or a Python list, the `itemsize` will be
automatically determined. If `itemsize` is provided and `obj`
is of type str or unicode, then the `obj` string will be
chunked into `itemsize` pieces.
unicode : bool, optional
When true, the resulting `chararray` can contain Unicode
characters, when false only 8-bit characters. If unicode is
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- a `chararray`,
- an ndarray of type `str` or 'unicode`
- a Python str or unicode object,
then the unicode setting of the output array will be
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order : {'C', 'F'}, optional
Specify the order of the array. If order is 'C' (default), then the
array will be in C-contiguous order (last-index varies the
fastest). If order is 'F', then the returned array
will be in Fortran-contiguous order (first-index varies the
fastest). | Convert the input to a `chararray`, copying the data only if
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"""
Convert the input to a `chararray`, copying the data only if
necessary.
Versus a regular NumPy array of type `str` or `unicode`, this
class adds the following functionality:
1) values automatically have whitespace removed from the end
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2) comparison operators automatically remove whitespace from the
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3) vectorized string operations are provided as methods
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itemsize : int, optional
`itemsize` is the number of characters per scalar in the
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"""
return array(obj, itemsize, copy=False,
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coinapi/coinapi-sdk | 854f21e7f69ea8599ae35c5403565cf299d8b795 | oeml-sdk/python/openapi_client/model/order_cancel_all_request.py | python | OrderCancelAllRequest.__init__ | (self, exchange_id, *args, **kwargs) | OrderCancelAllRequest - a model defined in OpenAPI
Args:
exchange_id (str): Identifier of the exchange from which active orders should be canceled.
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,) | OrderCancelAllRequest - a model defined in OpenAPI | [
"OrderCancelAllRequest",
"-",
"a",
"model",
"defined",
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"OpenAPI"
] | def __init__(self, exchange_id, *args, **kwargs): # noqa: E501
"""OrderCancelAllRequest - a model defined in OpenAPI
Args:
exchange_id (str): Identifier of the exchange from which active orders should be canceled.
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
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If passed, type conversion is attempted
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_visited_composed_classes = (Animal,)
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
self.exchange_id = exchange_id
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.") | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/weakref.py | python | finalize.alive | (self) | return self in self._registry | Whether finalizer is alive | Whether finalizer is alive | [
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] | def alive(self):
"""Whether finalizer is alive"""
return self in self._registry | [
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livecode/livecode | 4606a10ea10b16d5071d0f9f263ccdd7ede8b31d | gyp/pylib/gyp/xcode_emulation.py | python | XcodeSettings.GetWrapperExtension | (self) | Returns the bundle extension (.app, .framework, .plugin, etc). Only
valid for bundles. | Returns the bundle extension (.app, .framework, .plugin, etc). Only
valid for bundles. | [
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"""Returns the bundle extension (.app, .framework, .plugin, etc). Only
valid for bundles."""
assert self._IsBundle()
if self.spec['type'] in ('loadable_module', 'shared_library'):
default_wrapper_extension = {
'loadable_module': 'bundle',
'shared_library': 'framework',
}[self.spec['type']]
wrapper_extension = self.GetPerTargetSetting(
'WRAPPER_EXTENSION', default=default_wrapper_extension)
return '.' + self.spec.get('product_extension', wrapper_extension)
elif self.spec['type'] == 'executable':
if self._IsIosAppExtension() or self._IsIosWatchKitExtension():
return '.' + self.spec.get('product_extension', 'appex')
else:
return '.' + self.spec.get('product_extension', 'app')
else:
assert False, "Don't know extension for '%s', target '%s'" % (
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/mapreduce/mapreduce/input_readers.py | python | NamespaceInputReader.split_input | (cls, mapper_spec) | return [NamespaceInputReader(ns_range, batch_size)
for ns_range in namespace_ranges] | Returns a list of input readers for the input spec.
Args:
mapper_spec: The MapperSpec for this InputReader.
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Args:
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Returns:
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"""
batch_size = int(_get_params(mapper_spec).get(
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shard_count = mapper_spec.shard_count
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microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | NV_ReadPublicResponse.__init__ | (self, nvPublic = None, nvName = None) | This command is used to read the public area and Name of an NV
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authorization is required to read this data.
Attributes:
nvPublic (TPMS_NV_PUBLIC): The public area of the NV Index
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microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | TPMS_PCR_SELECTION.initFromTpm | (self, buf) | TpmMarshaller method | TpmMarshaller method | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/eclib/_filetree.py | python | FileTree.DoBeginEdit | (self, item) | return False | Overridable method that will be called when
a user has started to edit an item.
@param item: TreeItem
return: bool (True == Allow Edit) | Overridable method that will be called when
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seqan/seqan | f5f658343c366c9c3d44ba358ffc9317e78a09ed | util/py_lib/seqan/dox/proc_doc.py | python | RawTextToTextNodeConverter.handleCommand | (self, token) | Handle command for the given token. | Handle command for the given token. | [
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self.handleCommandClosing() # handle closing of command
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self.tokens_cmd.append(token)
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if not token.type in self.command_pairs.keys():
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raise dox_parser.ParserError(token, 'Unexpected token. Must be one of %s' % expected)
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microsoft/clang | 86d4513d3e0daa4d5a29b0b1de7c854ca15f9fe5 | utils/check_cfc/obj_diff.py | python | compare_exact | (objfilea, objfileb) | return filecmp.cmp(objfilea, objfileb) | Byte for byte comparison between object files.
Returns True if equal, False otherwise. | Byte for byte comparison between object files.
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choasup/caffe-yolo9000 | e8a476c4c23d756632f7a26c681a96e3ab672544 | scripts/cpp_lint.py | python | RemoveMultiLineComments | (filename, lines, error) | Removes multiline (c-style) comments from lines. | Removes multiline (c-style) comments from lines. | [
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lineix = 0
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lineix_begin = FindNextMultiLineCommentStart(lines, lineix)
if lineix_begin >= len(lines):
return
lineix_end = FindNextMultiLineCommentEnd(lines, lineix_begin)
if lineix_end >= len(lines):
error(filename, lineix_begin + 1, 'readability/multiline_comment', 5,
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return
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/idlelib/run.py | python | MyHandler.EOFhook | (self) | Override SocketIO method - terminate wait on callback and exit thread | Override SocketIO method - terminate wait on callback and exit thread | [
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"Override SocketIO method - terminate wait on callback and exit thread"
global quitting
quitting = True
thread.interrupt_main() | [
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jackaudio/jack2 | 21b293dbc37d42446141a08922cdec0d2550c6a0 | waflib/Tools/ccroot.py | python | add_objects_from_tgen | (self, tg) | Add the objects from the depending compiled tasks as link task inputs.
Some objects are filtered: for instance, .pdb files are added
to the compiled tasks but not to the link tasks (to avoid errors)
PRIVATE INTERNAL USE ONLY | Add the objects from the depending compiled tasks as link task inputs. | [
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link_task = self.link_task
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for x in tsk.outputs:
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GoSSIP-SJTU/Armariris | ad5d868482956b2194a77b39c8d543c7c2318200 | utils/llvm-build/llvmbuild/main.py | python | cmake_quote_string | (value) | return value | cmake_quote_string(value) -> str
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"""
cmake_quote_string(value) -> str
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"""
# Currently, we only handle escaping backslashes.
value = value.replace("\\", "\\\\")
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eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/contributed/sumopy/coremodules/demand/virtualpop.py | python | IndividualMotorcycles.get_ids_veh_pop | (self) | return self.parent.ids_imoto | To be overridden by other individual vehicle types. | To be overridden by other individual vehicle types. | [
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arangodb/arangodb | 0d658689c7d1b721b314fa3ca27d38303e1570c8 | 3rdParty/V8/gyp/input.py | python | DependencyGraphNode.DirectAndImportedDependencies | (self, targets, dependencies=None) | return self._AddImportedDependencies(targets, dependencies) | Returns a list of a target's direct dependencies and all indirect
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koying/SPMC | beca52667112f2661204ebb42406115825512491 | tools/EventClients/lib/python/xbmcclient.py | python | XBMCClient.send_log | (self, loglevel=0, logmessage="", autoprint=True) | return packet.send(self.sock, self.addr, self.uid) | Keyword arguments:
loglevel -- the loglevel, follows XBMC standard.
logmessage -- the message to log
autoprint -- if the logmessage should automaticly be printed to stdout | Keyword arguments:
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/Maya_AnimationRiggingTools/ArtToolsOSX/MayaTools/General/Scripts/P4.py | python | Map.is_empty | (self) | return self.count() == 0 | Returns True if this map has no entries yet, otherwise False | Returns True if this map has no entries yet, otherwise False | [
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"""Returns True if this map has no entries yet, otherwise False"""
return self.count() == 0 | [
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weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/pep8.py | python | Checker.build_tokens_line | (self) | return mapping | Build a logical line from tokens. | Build a logical line from tokens. | [
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] | def build_tokens_line(self):
"""Build a logical line from tokens."""
logical = []
comments = []
length = 0
prev_row = prev_col = mapping = None
for token_type, text, start, end, line in self.tokens:
if token_type in SKIP_TOKENS:
continue
if not mapping:
mapping = [(0, start)]
if token_type == tokenize.COMMENT:
comments.append(text)
continue
if token_type == tokenize.STRING:
text = mute_string(text)
if prev_row:
(start_row, start_col) = start
if prev_row != start_row: # different row
prev_text = self.lines[prev_row - 1][prev_col - 1]
if prev_text == ',' or (prev_text not in '{[('
and text not in '}])'):
text = ' ' + text
elif prev_col != start_col: # different column
text = line[prev_col:start_col] + text
logical.append(text)
length += len(text)
mapping.append((length, end))
(prev_row, prev_col) = end
self.logical_line = ''.join(logical)
self.noqa = comments and noqa(''.join(comments))
return mapping | [
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lynckia/licode | a892fbec56191ce21deb962fdd2a1f68c653dc23 | erizo/utils/conan-include-paths/conanfile.py | python | IncludePathsGenerator.content | (self) | return " ".join(flag for flag in flags if flag) | With compiler_args you can invoke your compiler:
$ gcc main.c @conanbuildinfo.args -o main
$ clang main.c @conanbuildinfo.args -o main
$ cl /EHsc main.c @conanbuildinfo.args | With compiler_args you can invoke your compiler:
$ gcc main.c | [
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"""With compiler_args you can invoke your compiler:
$ gcc main.c @conanbuildinfo.args -o main
$ clang main.c @conanbuildinfo.args -o main
$ cl /EHsc main.c @conanbuildinfo.args
"""
flags = []
#flags.extend(format_defines(self._deps_build_info.defines))
flags.extend(format_include_paths(self._deps_build_info.include_paths,
settings=self.conanfile.settings))
#flags.extend(self._deps_build_info.cxxflags)
#flags.extend(self._deps_build_info.cflags)
#arch_flag = architecture_flag(arch=self.conanfile.settings.get_safe("arch"),
# compiler=self.compiler)
#if arch_flag:
# flags.append(arch_flag)
#build_type = self.conanfile.settings.get_safe("build_type")
#btfs = build_type_flags(compiler=self.compiler, build_type=build_type,
# vs_toolset=self.conanfile.settings.get_safe("compiler.toolset"))
#if btfs:
# flags.extend(btfs)
#btd = build_type_define(build_type=build_type)
#if btd:
# flags.extend(format_defines([btd]))
#if self.compiler == "Visual Studio":
# runtime = visual_runtime(self.conanfile.settings.get_safe("compiler.runtime"))
# if runtime:
# flags.append(runtime)
# # Necessary in the "cl" invocation before specify the rest of linker flags
# flags.append(visual_linker_option_separator)
#the_os = (self.conanfile.settings.get_safe("os_build") or
# self.conanfile.settings.get_safe("os"))
#flags.extend(rpath_flags(the_os, self.compiler, self._deps_build_info.lib_paths))
#flags.extend(format_library_paths(self._deps_build_info.lib_paths, compiler=self.compiler))
#flags.extend(format_libraries(self._deps_build_info.libs, compiler=self.compiler))
#flags.extend(self._deps_build_info.sharedlinkflags)
#flags.extend(self._deps_build_info.exelinkflags)
#flags.extend(self._libcxx_flags())
#flags.append(cppstd_flag(self.conanfile.settings.get_safe("compiler"),
# self.conanfile.settings.get_safe("compiler.version"),
# self.conanfile.settings.get_safe("cppstd")))
#sysrf = sysroot_flag(self._deps_build_info.sysroot, compiler=self.compiler)
#if sysrf:
# flags.append(sysrf)
return " ".join(flag for flag in flags if flag) | [
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sccn/lsl_archived | 2ff44b7a5172b02fe845b1fc72b9ab5578a489ed | LSL/liblsl-Python/pylsl/pylsl.py | python | resolve_byprop | (prop, value, minimum=1, timeout=FOREVER) | return [StreamInfo(handle=buffer[k]) for k in range(num_found)] | Resolve all streams with a specific value for a given property.
If the goal is to resolve a specific stream, this method is preferred over
resolving all streams and then selecting the desired one.
Keyword arguments:
prop -- The StreamInfo property that should have a specific value (e.g.,
"name", "type", "source_id", or "desc/manufaturer").
value -- The string value that the property should have (e.g., "EEG" as
the type property).
minimum -- Return at least this many streams. (default 1)
timeout -- Optionally a timeout of the operation, in seconds. If the
timeout expires, less than the desired number of streams
(possibly none) will be returned. (default FOREVER)
Returns a list of matching StreamInfo objects (with empty desc field), any
of which can subsequently be used to open an inlet.
Example: results = resolve_Stream_byprop("type","EEG") | Resolve all streams with a specific value for a given property. | [
"Resolve",
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"streams",
"with",
"a",
"specific",
"value",
"for",
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"given",
"property",
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] | def resolve_byprop(prop, value, minimum=1, timeout=FOREVER):
"""Resolve all streams with a specific value for a given property.
If the goal is to resolve a specific stream, this method is preferred over
resolving all streams and then selecting the desired one.
Keyword arguments:
prop -- The StreamInfo property that should have a specific value (e.g.,
"name", "type", "source_id", or "desc/manufaturer").
value -- The string value that the property should have (e.g., "EEG" as
the type property).
minimum -- Return at least this many streams. (default 1)
timeout -- Optionally a timeout of the operation, in seconds. If the
timeout expires, less than the desired number of streams
(possibly none) will be returned. (default FOREVER)
Returns a list of matching StreamInfo objects (with empty desc field), any
of which can subsequently be used to open an inlet.
Example: results = resolve_Stream_byprop("type","EEG")
"""
# noinspection PyCallingNonCallable
buffer = (c_void_p*1024)()
num_found = lib.lsl_resolve_byprop(byref(buffer), 1024,
c_char_p(str.encode(prop)),
c_char_p(str.encode(value)),
minimum,
c_double(timeout))
return [StreamInfo(handle=buffer[k]) for k in range(num_found)] | [
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trilinos/Trilinos | 6168be6dd51e35e1cd681e9c4b24433e709df140 | packages/seacas/libraries/ioss/src/visualization/catalyst/phactori/phactori.py | python | FindMinMaxSumCntFromData | (inputcsData, inVariableInfo,
inSecondaryVariableInfo, DataMinMax, DataSumCnt,
DataForIds, inPlotIdLineList) | fairly complex high level mpi-operation routine. This takes a paraview
filter client side object, gets the client side data
(which is presumably a multiblock
dataset) and finds the min, max, sum, and count of items for a variable.
It uses MPI (if the item is not global) to share values and get them
across all processors. Used for plotting min/max/mean and for evaluating
boolean criteria (such as whether or not to produce images) for min/max
/mean/count. Data return is a bit messy and should be updated--it fills
in DataMinMax, DataSumCnt, and DataForIds if it is not None | fairly complex high level mpi-operation routine. This takes a paraview
filter client side object, gets the client side data
(which is presumably a multiblock
dataset) and finds the min, max, sum, and count of items for a variable.
It uses MPI (if the item is not global) to share values and get them
across all processors. Used for plotting min/max/mean and for evaluating
boolean criteria (such as whether or not to produce images) for min/max
/mean/count. Data return is a bit messy and should be updated--it fills
in DataMinMax, DataSumCnt, and DataForIds if it is not None | [
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inSecondaryVariableInfo, DataMinMax, DataSumCnt,
DataForIds, inPlotIdLineList):
"""fairly complex high level mpi-operation routine. This takes a paraview
filter client side object, gets the client side data
(which is presumably a multiblock
dataset) and finds the min, max, sum, and count of items for a variable.
It uses MPI (if the item is not global) to share values and get them
across all processors. Used for plotting min/max/mean and for evaluating
boolean criteria (such as whether or not to produce images) for min/max
/mean/count. Data return is a bit messy and should be updated--it fills
in DataMinMax, DataSumCnt, and DataForIds if it is not None"""
if PhactoriDbg():
myDebugPrint3("FindMinMaxSumCntFromData entered\n")
FindMinMaxSumCntFromDataRecurse1(inputcsData, inVariableInfo,
inSecondaryVariableInfo, DataMinMax, DataSumCnt,
DataForIds, inPlotIdLineList)
#if variable is global, it is same on all processors so we don't need to do
#any mpi communication
if inVariableInfo.mVariableType != 'global':
#do mpi to share values around
UseReduceToSumDoubleAndIntPair(DataSumCnt)
if DataSumCnt[1] == 0:
#no data; we shouldn't add anything to plot lines
if PhactoriDbg(100):
myDebugPrint3('no data for variable; returning\n', 100)
return
#bad situation; if we have no data on this processor we don't want
#it to mess up other processors min/max
if DataMinMax[2] == False:
DataMinMax[0] = sys.float_info.max
DataMinMax[1] = -sys.float_info.max
UseReduceToGetMinMaxPairs(DataMinMax)
if DataForIds != None:
UseReduceToSpreadValues(DataForIds)
if PhactoriDbg():
myDebugPrint3('min/max result: ' + str(DataMinMax) + '\n')
if PhactoriDbg():
myDebugPrint3(' sum result: ' + str(DataSumCnt[0]) + ' count result: ' + str(DataSumCnt[1]) + '\n')
#myDebugPrint3(' average result: ' + str(DataSumCnt[0]/DataSumCnt[1]) + '\n')
if PhactoriDbg():
myDebugPrint3(' average result: ' + \
str(DataSumCnt[0]/float(DataSumCnt[1])) + '\n')
if PhactoriDbg():
myDebugPrint3('DataForIds result: ' + str(DataForIds) + '\n')
inVariableInfo.mStats.mMin = DataMinMax[0]
inVariableInfo.mStats.mMax = DataMinMax[1]
inVariableInfo.mStats.mSum = DataSumCnt[0]
inVariableInfo.mStats.mCount = DataSumCnt[1]
inVariableInfo.mStats.mStatsTestCounter = \
gPipeAndViewsState.mFrameTagCounter
if PhactoriDbg():
myDebugPrint3("FindMinMaxSumCntFromData returning\n") | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/interpolate/_bsplines.py | python | _get_dtype | (dtype) | Return np.complex128 for complex dtypes, np.float64 otherwise. | Return np.complex128 for complex dtypes, np.float64 otherwise. | [
"Return",
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".",
"complex128",
"for",
"complex",
"dtypes",
"np",
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"float64",
"otherwise",
"."
] | def _get_dtype(dtype):
"""Return np.complex128 for complex dtypes, np.float64 otherwise."""
if np.issubdtype(dtype, np.complexfloating):
return np.complex_
else:
return np.float_ | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/framework/ops.py | python | Tensor.set_shape | (self, shape) | Updates the shape of this tensor.
This method can be called multiple times, and will merge the given
`shape` with the current shape of this tensor. It can be used to
provide additional information about the shape of this tensor that
cannot be inferred from the graph alone. For example, this can be used
to provide additional information about the shapes of images:
```python
_, image_data = tf.TFRecordReader(...).read(...)
image = tf.image.decode_png(image_data, channels=3)
# The height and width dimensions of `image` are data dependent, and
# cannot be computed without executing the op.
print(image.get_shape())
==> TensorShape([Dimension(None), Dimension(None), Dimension(3)])
# We know that each image in this dataset is 28 x 28 pixels.
image.set_shape([28, 28, 3])
print(image.get_shape())
==> TensorShape([Dimension(28), Dimension(28), Dimension(3)])
```
Args:
shape: A `TensorShape` representing the shape of this tensor.
Raises:
ValueError: If `shape` is not compatible with the current shape of
this tensor. | Updates the shape of this tensor. | [
"Updates",
"the",
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"of",
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"tensor",
"."
] | def set_shape(self, shape):
"""Updates the shape of this tensor.
This method can be called multiple times, and will merge the given
`shape` with the current shape of this tensor. It can be used to
provide additional information about the shape of this tensor that
cannot be inferred from the graph alone. For example, this can be used
to provide additional information about the shapes of images:
```python
_, image_data = tf.TFRecordReader(...).read(...)
image = tf.image.decode_png(image_data, channels=3)
# The height and width dimensions of `image` are data dependent, and
# cannot be computed without executing the op.
print(image.get_shape())
==> TensorShape([Dimension(None), Dimension(None), Dimension(3)])
# We know that each image in this dataset is 28 x 28 pixels.
image.set_shape([28, 28, 3])
print(image.get_shape())
==> TensorShape([Dimension(28), Dimension(28), Dimension(3)])
```
Args:
shape: A `TensorShape` representing the shape of this tensor.
Raises:
ValueError: If `shape` is not compatible with the current shape of
this tensor.
"""
self._shape = self._shape.merge_with(shape) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/sysconfig.py | python | _main | () | Display all information sysconfig detains. | Display all information sysconfig detains. | [
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] | def _main():
"""Display all information sysconfig detains."""
if '--generate-posix-vars' in sys.argv:
_generate_posix_vars()
return
print('Platform: "%s"' % get_platform())
print('Python version: "%s"' % get_python_version())
print('Current installation scheme: "%s"' % _get_default_scheme())
print()
_print_dict('Paths', get_paths())
print()
_print_dict('Variables', get_config_vars()) | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/labeled_tensor/python/ops/core.py | python | define_unary_op | (op_name, elementwise_function) | return op | Define a unary operation for labeled tensors.
Args:
op_name: string name of the TensorFlow op.
elementwise_function: function to call to evaluate the op on a single
tf.Tensor object. This function must accept two arguments: a tf.Tensor
object, and an optional `name`.
Returns:
Function defining the given op that acts on LabeledTensors. | Define a unary operation for labeled tensors. | [
"Define",
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"for",
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"."
] | def define_unary_op(op_name, elementwise_function):
"""Define a unary operation for labeled tensors.
Args:
op_name: string name of the TensorFlow op.
elementwise_function: function to call to evaluate the op on a single
tf.Tensor object. This function must accept two arguments: a tf.Tensor
object, and an optional `name`.
Returns:
Function defining the given op that acts on LabeledTensors.
"""
default_name = 'lt_%s' % op_name
@tc.returns(LabeledTensor)
@tc.accepts(LabeledTensorLike, tc.Optional(string_types))
def op(labeled_tensor, name=None):
"""LabeledTensor version of `tf.{op_name}`.
See `tf.{op_name}` for full details.
Args:
labeled_tensor: Input tensor.
name: Optional op name.
Returns:
A LabeledTensor with result of applying `tf.{op_name}` elementwise.
"""
with ops.name_scope(name, default_name, [labeled_tensor]) as scope:
labeled_tensor = convert_to_labeled_tensor(labeled_tensor)
result_tensor = elementwise_function(labeled_tensor.tensor, name=scope)
return LabeledTensor(result_tensor, labeled_tensor.axes)
op.__doc__ = op.__doc__.format(op_name=op_name)
op.__name__ = op_name
return op | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/training/coordinator.py | python | Coordinator.request_stop | (self, ex=None) | Request that the threads stop.
After this is called, calls to `should_stop()` will return `True`.
Note: If an exception is being passed in, in must be in the context of
handling the exception (i.e. `try: ... except Exception as ex: ...`) and not
a newly created one.
Args:
ex: Optional `Exception`, or Python `exc_info` tuple as returned by
`sys.exc_info()`. If this is the first call to `request_stop()` the
corresponding exception is recorded and re-raised from `join()`. | Request that the threads stop. | [
"Request",
"that",
"the",
"threads",
"stop",
"."
] | def request_stop(self, ex=None):
"""Request that the threads stop.
After this is called, calls to `should_stop()` will return `True`.
Note: If an exception is being passed in, in must be in the context of
handling the exception (i.e. `try: ... except Exception as ex: ...`) and not
a newly created one.
Args:
ex: Optional `Exception`, or Python `exc_info` tuple as returned by
`sys.exc_info()`. If this is the first call to `request_stop()` the
corresponding exception is recorded and re-raised from `join()`.
"""
with self._lock:
ex = self._filter_exception(ex)
# If we have already joined the coordinator the exception will not have a
# chance to be reported, so just raise it normally. This can happen if
# you continue to use a session have having stopped and joined the
# coordinator threads.
if self._joined:
if isinstance(ex, tuple):
six.reraise(*ex)
elif ex is not None:
# NOTE(touts): This is bogus if request_stop() is not called
# from the exception handler that raised ex.
six.reraise(*sys.exc_info())
if not self._stop_event.is_set():
if ex and self._exc_info_to_raise is None:
if isinstance(ex, tuple):
logging.info("Error reported to Coordinator: %s, %s",
type(ex[1]),
compat.as_str_any(ex[1]))
self._exc_info_to_raise = ex
else:
logging.info("Error reported to Coordinator: %s, %s",
type(ex),
compat.as_str_any(ex))
self._exc_info_to_raise = sys.exc_info()
# self._exc_info_to_raise should contain a tuple containing exception
# (type, value, traceback)
if (len(self._exc_info_to_raise) != 3 or
not self._exc_info_to_raise[0] or
not self._exc_info_to_raise[1]):
# Raise, catch and record the exception here so that error happens
# where expected.
try:
raise ValueError(
"ex must be a tuple or sys.exc_info must return the current "
"exception: %s"
% self._exc_info_to_raise)
except ValueError:
# Record this error so it kills the coordinator properly.
# NOTE(touts): As above, this is bogus if request_stop() is not
# called from the exception handler that raised ex.
self._exc_info_to_raise = sys.exc_info()
self._stop_event.set() | [
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gnuradio/gnuradio | 09c3c4fa4bfb1a02caac74cb5334dfe065391e3b | tools/clang_format.py | python | Repo.diff | (self, command) | return self._callgito(["diff"] + command) | git diff wrapper | git diff wrapper | [
"git",
"diff",
"wrapper"
] | def diff(self, command):
"""git diff wrapper
"""
return self._callgito(["diff"] + command) | [
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H-uru/Plasma | c2140ea046e82e9c199e257a7f2e7edb42602871 | Scripts/Python/plasma/Plasma.py | python | PtChangePassword | (password) | Changes the current account's password | Changes the current account's password | [
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"""Changes the current account's password"""
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intel/llvm | e6d0547e9d99b5a56430c4749f6c7e328bf221ab | libcxx/utils/gdb/libcxx/printers.py | python | AbstractRBTreePrinter._traverse | (self) | Traverses the binary search tree in order. | Traverses the binary search tree in order. | [
"Traverses",
"the",
"binary",
"search",
"tree",
"in",
"order",
"."
] | def _traverse(self):
"""Traverses the binary search tree in order."""
current = self.util.root
skip_left_child = False
while True:
if not skip_left_child and self.util.left_child(current):
current = self.util.left_child(current)
continue
skip_left_child = False
for key_value in self._get_key_value(current):
yield "", key_value
right_child = self.util.right_child(current)
if right_child:
current = right_child
continue
while self.util.is_right_child(current):
current = self.util.parent(current)
if self.util.is_left_child(current):
current = self.util.parent(current)
skip_left_child = True
continue
break | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py3/sklearn/naive_bayes.py | python | _BaseDiscreteNB.fit | (self, X, y, sample_weight=None) | return self | Fit Naive Bayes classifier according to X, y
Parameters
----------
X : {array-like, sparse matrix} of shape (n_samples, n_features)
Training vectors, where n_samples is the number of samples and
n_features is the number of features.
y : array-like of shape (n_samples,)
Target values.
sample_weight : array-like of shape (n_samples,), default=None
Weights applied to individual samples (1. for unweighted).
Returns
-------
self : object | Fit Naive Bayes classifier according to X, y | [
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"""Fit Naive Bayes classifier according to X, y
Parameters
----------
X : {array-like, sparse matrix} of shape (n_samples, n_features)
Training vectors, where n_samples is the number of samples and
n_features is the number of features.
y : array-like of shape (n_samples,)
Target values.
sample_weight : array-like of shape (n_samples,), default=None
Weights applied to individual samples (1. for unweighted).
Returns
-------
self : object
"""
X, y = self._check_X_y(X, y)
_, n_features = X.shape
self.n_features_ = n_features
labelbin = LabelBinarizer()
Y = labelbin.fit_transform(y)
self.classes_ = labelbin.classes_
if Y.shape[1] == 1:
Y = np.concatenate((1 - Y, Y), axis=1)
# LabelBinarizer().fit_transform() returns arrays with dtype=np.int64.
# We convert it to np.float64 to support sample_weight consistently;
# this means we also don't have to cast X to floating point
if sample_weight is not None:
Y = Y.astype(np.float64, copy=False)
sample_weight = np.asarray(sample_weight)
sample_weight = np.atleast_2d(sample_weight)
Y *= check_array(sample_weight).T
class_prior = self.class_prior
# Count raw events from data before updating the class log prior
# and feature log probas
n_effective_classes = Y.shape[1]
self._init_counters(n_effective_classes, n_features)
self._count(X, Y)
alpha = self._check_alpha()
self._update_feature_log_prob(alpha)
self._update_class_log_prior(class_prior=class_prior)
return self | [
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PixarAnimationStudios/USD | faed18ce62c8736b02413635b584a2f637156bad | pxr/usdImaging/usdAppUtils/rendererArgs.py | python | GetAllPluginArguments | () | return [ UsdImagingGL.Engine.GetRendererDisplayName(pluginId) for
pluginId in UsdImagingGL.Engine.GetRendererPlugins() ] | Returns argument strings for all the renderer plugins available. | Returns argument strings for all the renderer plugins available. | [
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"""
Returns argument strings for all the renderer plugins available.
"""
from pxr import UsdImagingGL
return [ UsdImagingGL.Engine.GetRendererDisplayName(pluginId) for
pluginId in UsdImagingGL.Engine.GetRendererPlugins() ] | [
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | dom/bindings/parser/WebIDL.py | python | Parser.p_CallbackRestOrInterface | (self, p) | CallbackRestOrInterface : CallbackRest
| Interface | CallbackRestOrInterface : CallbackRest
| Interface | [
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] | def p_CallbackRestOrInterface(self, p):
"""
CallbackRestOrInterface : CallbackRest
| Interface
"""
assert p[1]
p[0] = p[1] | [
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greenheartgames/greenworks | 3ea4ab490b56676de3f0a237c74bcfdb17323e60 | deps/cpplint/cpplint.py | python | _CppLintState.BackupFilters | (self) | Saves the current filter list to backup storage. | Saves the current filter list to backup storage. | [
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""" Saves the current filter list to backup storage."""
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/chardet/chardistribution.py | python | CharDistributionAnalysis.reset | (self) | reset analyser, clear any state | reset analyser, clear any state | [
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] | def reset(self):
"""reset analyser, clear any state"""
# If this flag is set to True, detection is done and conclusion has
# been made
self._done = False
self._total_chars = 0 # Total characters encountered
# The number of characters whose frequency order is less than 512
self._freq_chars = 0 | [
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giuspen/cherrytree | 84712f206478fcf9acf30174009ad28c648c6344 | pygtk2/modules/core.py | python | CherryTree.update_node_name_header_num_latest_visited | (self) | Update on the Node Name Header the Number of Latest Visited | Update on the Node Name Header the Number of Latest Visited | [
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"""Update on the Node Name Header the Number of Latest Visited"""
for button in self.header_node_name_hbuttonbox.get_children():
self.header_node_name_hbuttonbox.remove(button)
for i in range(self.nodes_on_node_name_header):
button = gtk.Button()
button.connect('clicked', self.on_button_node_name_header_clicked, i)
label = gtk.Label()
label.set_ellipsize(pango.ELLIPSIZE_END)
button.add(label)
self.header_node_name_hbuttonbox.add(button)
self.update_node_name_header_labels_latest_visited() | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/computation/expressions.py | python | _evaluate_standard | (op, op_str, a, b) | return op(a, b) | Standard evaluation. | Standard evaluation. | [
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] | def _evaluate_standard(op, op_str, a, b):
"""
Standard evaluation.
"""
if _TEST_MODE:
_store_test_result(False)
return op(a, b) | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/control/robotinterface.py | python | RobotInterfaceBase.clock | (self) | Returns the current time on the robot's clock, in seconds | Returns the current time on the robot's clock, in seconds | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_windows.py | python | SashWindow.SetExtraBorderSize | (*args, **kwargs) | return _windows_.SashWindow_SetExtraBorderSize(*args, **kwargs) | SetExtraBorderSize(self, int width) | SetExtraBorderSize(self, int width) | [
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"""SetExtraBorderSize(self, int width)"""
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Cantera/cantera | 0119484b261967ccb55a0066c020599cacc312e4 | interfaces/cython/cantera/ctml_writer.py | python | validate | (species='yes', reactions='yes') | Enable or disable validation of species and reactions.
:param species:
Set to ``'yes'`` (default) or ``'no'``.
:param reactions:
Set to ``'yes'`` (default) or ``'no'``. This controls duplicate reaction checks
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"""
Enable or disable validation of species and reactions.
:param species:
Set to ``'yes'`` (default) or ``'no'``.
:param reactions:
Set to ``'yes'`` (default) or ``'no'``. This controls duplicate reaction checks
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"""
global _valsp
global _valrxn
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svn2github/webrtc | 0e4615a75ed555ec866cd5543bfea586f3385ceb | webrtc/tools/barcode_tools/barcode_encoder.py | python | combine_yuv_frames_into_one_file | (output_file_name, input_directory='.') | return success | Combines several YUV frames into one YUV video file.
The function combines the YUV frames from input_directory into one YUV video
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output_file_name(string): The name of the file to produce.
input_directory(string): The directory from which the YUV frames are read.
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"""Combines several YUV frames into one YUV video file.
The function combines the YUV frames from input_directory into one YUV video
file. The frames should be named in the format frame_xxxx.yuv where xxxx
stands for the frame number. The numbers have to be consecutive and start from
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Args:
output_file_name(string): The name of the file to produce.
input_directory(string): The directory from which the YUV frames are read.
Return:
(bool): True if the frame stitching went OK.
"""
output_file = open(output_file_name, "wb")
success = helper_functions.perform_action_on_all_files(
input_directory, 'barcode_', 'yuv', 0, _add_to_file_and_delete,
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output_file.close()
return success | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqtinterfaces/mantidqtinterfaces/Muon/GUI/Common/plot_widget/plotting_canvas/plotting_canvas_presenter.py | python | PlottingCanvasPresenter.set_axis_limits | (self, ax_num, xlims, ylims) | Sets the x and y limits for a specified axis in the figure | Sets the x and y limits for a specified axis in the figure | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/requests/sessions.py | python | Session.head | (self, url, **kwargs) | return self.request('HEAD', url, **kwargs) | r"""Sends a HEAD request. Returns :class:`Response` object.
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:rtype: requests.Response | r"""Sends a HEAD request. Returns :class:`Response` object. | [
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:param url: URL for the new :class:`Request` object.
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kwargs.setdefault('allow_redirects', False)
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microsoft/DirectXShaderCompiler | 8348ff8d9e0287610ba05d3a828e10af981a1c05 | tools/clang/bindings/python/clang/cindex.py | python | CursorKind.is_attribute | (self) | return conf.lib.clang_isAttribute(self) | Test if this is an attribute kind. | Test if this is an attribute kind. | [
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snap-stanford/snap-python | d53c51b0a26aa7e3e7400b014cdf728948fde80a | setup/snap.py | python | TNEANetNodeI.IsInNId | (self, *args) | return _snap.TNEANetNodeI_IsInNId(self, *args) | IsInNId(TNEANetNodeI self, int const & NId) -> bool
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"""
IsInNId(TNEANetNodeI self, int const & NId) -> bool
Parameters:
NId: int const &
"""
return _snap.TNEANetNodeI_IsInNId(self, *args) | [
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hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/framework/function.py | python | _DefinedFunction.__init__ | (self,
func,
argnames,
input_types,
func_name=None,
grad_func=None,
python_grad_func=None,
**kwargs) | Creates _DefinedFunction.
Args:
func: A python callable which constructs a tf function body.
argnames: A list of strings for function argument names.
input_types: The function's argument types. Can be a tuple, list of
tf data types.
func_name: The function name. Defaults to None, in which derives from
'func'.
grad_func: This function's gradient function, if not None. Defaults
to None.
python_grad_func: A python callable implementing the gradient of
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**kwargs: The keyword arguments. **kwargs is passed to every call
site of this function.
Raises:
ValueError: The function definition is invalid. | Creates _DefinedFunction. | [
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] | def __init__(self,
func,
argnames,
input_types,
func_name=None,
grad_func=None,
python_grad_func=None,
**kwargs):
"""Creates _DefinedFunction.
Args:
func: A python callable which constructs a tf function body.
argnames: A list of strings for function argument names.
input_types: The function's argument types. Can be a tuple, list of
tf data types.
func_name: The function name. Defaults to None, in which derives from
'func'.
grad_func: This function's gradient function, if not None. Defaults
to None.
python_grad_func: A python callable implementing the gradient of
the function python-side.
**kwargs: The keyword arguments. **kwargs is passed to every call
site of this function.
Raises:
ValueError: The function definition is invalid.
"""
self._func = func
self._input_types = input_types
self._func_name = func_name
self._grad_func = grad_func
self._python_grad_func = python_grad_func
self._extra_kwargs = kwargs
self._definition = None # Constructed lazily.
self._args = []
assert isinstance(input_types, (list, tuple))
for i in range(len(input_types)):
argname = argnames[i] if i < len(argnames) else ("arg%d" % i)
argtype = input_types[i]
self._args.append((argname, argtype)) | [
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cms-sw/cmssw | fd9de012d503d3405420bcbeec0ec879baa57cf2 | EventFilter/L1TXRawToDigi/python/util/rrapi.py | python | RRApiError.__str__ | (self) | return self.message | Get message | Get message | [
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""" Get message """
return self.message | [
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jeog/TDAmeritradeAPI | 91c738afd7d57b54f6231170bd64c2550fafd34d | python/tdma_api/get.py | python | OrdersGetter.set_to_entered_time | (self, to_entered_time) | Sets/Changes date/time after which no orders will be returned.
iso8601 date/time ("yyyy-MM-dd" or "yyyy-MM-dd'T'HH::mm::ssz")
<= 60 days ago | Sets/Changes date/time after which no orders will be returned. | [
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"""Sets/Changes date/time after which no orders will be returned.
iso8601 date/time ("yyyy-MM-dd" or "yyyy-MM-dd'T'HH::mm::ssz")
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clib.set_str(self._abi('SetToEnteredTime'), to_entered_time,
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/distributed/rpc/backend_registry.py | python | register_backend | (
backend_name, construct_rpc_backend_options_handler, init_backend_handler
) | return BackendType[backend_name] | Registers a new RPC backend.
Args:
backend_name (str): backend string to identify the handler.
construct_rpc_backend_options_handler (function):
Handler that is invoked when
rpc_backend.construct_rpc_backend_options(**dict) is called.
init_backend_handler (function): Handler that is invoked when the
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This returns the agent. | Registers a new RPC backend. | [
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backend_name, construct_rpc_backend_options_handler, init_backend_handler
):
"""Registers a new RPC backend.
Args:
backend_name (str): backend string to identify the handler.
construct_rpc_backend_options_handler (function):
Handler that is invoked when
rpc_backend.construct_rpc_backend_options(**dict) is called.
init_backend_handler (function): Handler that is invoked when the
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This returns the agent.
"""
global BackendType
if backend_registered(backend_name):
raise RuntimeError("RPC backend {}: already registered".format(backend_name))
# Create a new enum type, `BackendType`, with extended members.
existing_enum_dict = {member.name: member.value for member in BackendType}
extended_enum_dict = dict(
{
backend_name: BackendValue(
construct_rpc_backend_options_handler=construct_rpc_backend_options_handler,
init_backend_handler=init_backend_handler,
)
},
**existing_enum_dict
)
# Can't handle Function Enum API (mypy bug #9079)
BackendType = enum.Enum(value="BackendType", names=extended_enum_dict) # type: ignore[misc]
# Unable to assign a function a method (mypy bug #2427)
BackendType.__repr__ = _backend_type_repr # type: ignore[assignment]
BackendType.__doc__ = _backend_type_doc
return BackendType[backend_name] | [
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diwu/Tiny-Wings-Remake-on-Android | a9fd714432a350b69615bf8dbb40448231a54524 | twxes10/libs/cocos2dx/platform/third_party/marmalade/freetype/src/tools/docmaker/tohtml.py | python | HtmlFormatter.make_html_words | ( self, words ) | return line | convert a series of simple words into some HTML text | convert a series of simple words into some HTML text | [
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""" convert a series of simple words into some HTML text """
line = ""
if words:
line = html_quote( words[0] )
for w in words[1:]:
line = line + " " + html_quote( w )
return line | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/smtplib.py | python | SMTP.rcpt | (self, recip, options=[]) | return self.getreply() | SMTP 'rcpt' command -- indicates 1 recipient for this mail. | SMTP 'rcpt' command -- indicates 1 recipient for this mail. | [
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"""SMTP 'rcpt' command -- indicates 1 recipient for this mail."""
optionlist = ''
if options and self.does_esmtp:
optionlist = ' ' + ' '.join(options)
self.putcmd("rcpt", "TO:%s%s" % (quoteaddr(recip), optionlist))
return self.getreply() | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/turtle.py | python | TurtleScreen.window_height | (self) | return self._window_size()[1] | Return the height of the turtle window.
Example (for a TurtleScreen instance named screen):
>>> screen.window_height()
480 | Return the height of the turtle window. | [
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""" Return the height of the turtle window.
Example (for a TurtleScreen instance named screen):
>>> screen.window_height()
480
"""
return self._window_size()[1] | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/parallel_for/gradients.py | python | batch_jacobian | (output, inp, use_pfor=True, parallel_iterations=None) | return array_ops.reshape(output, new_shape) | Computes and stacks jacobians of `output[i,...]` w.r.t. `input[i,...]`.
e.g.
x = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
y = x * x
jacobian = batch_jacobian(y, x)
# => [[[2, 0], [0, 4]], [[6, 0], [0, 8]]]
Args:
output: A tensor with shape [b, y1, ..., y_n]. `output[i,...]` should
only depend on `inp[i,...]`.
inp: A tensor with shape [b, x1, ..., x_m]
use_pfor: If true, uses pfor for computing the Jacobian. Else uses a
tf.while_loop.
parallel_iterations: A knob to control how many iterations are vectorized
and dispatched in parallel. The default value of None, when use_pfor is
true, corresponds to vectorizing all the iterations. When use_pfor is
false, the default value of None corresponds to parallel_iterations=10.
This knob can be used to control the total memory usage.
Returns:
A tensor `t` with shape [b, y_1, ..., y_n, x1, ..., x_m] where `t[i, ...]`
is the jacobian of `output[i, ...]` w.r.t. `inp[i, ...]`, i.e. stacked
per-example jacobians.
Raises:
ValueError: if first dimension of `output` and `inp` do not match. | Computes and stacks jacobians of `output[i,...]` w.r.t. `input[i,...]`. | [
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"""Computes and stacks jacobians of `output[i,...]` w.r.t. `input[i,...]`.
e.g.
x = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
y = x * x
jacobian = batch_jacobian(y, x)
# => [[[2, 0], [0, 4]], [[6, 0], [0, 8]]]
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"""
output_shape = output.shape
if not output_shape[0].is_compatible_with(inp.shape[0]):
raise ValueError(f"Need first dimension of `output` shape ({output.shape}) "
f"and `inp` shape ({inp.shape}) to match.")
if output_shape.is_fully_defined():
batch_size = int(output_shape[0])
output_row_size = output_shape.num_elements() // batch_size
else:
output_shape = array_ops.shape(output)
batch_size = output_shape[0]
output_row_size = array_ops.size(output) // batch_size
inp_shape = array_ops.shape(inp)
# Flatten output to 2-D.
with ops.control_dependencies(
[check_ops.assert_equal(batch_size, inp_shape[0])]):
output = array_ops.reshape(output, [batch_size, output_row_size])
def loop_fn(i):
y = array_ops.gather(output, i, axis=1)
return gradient_ops.gradients(y, inp)[0]
if use_pfor:
pfor_output = control_flow_ops.pfor(loop_fn, output_row_size,
parallel_iterations=parallel_iterations)
else:
pfor_output = control_flow_ops.for_loop(
loop_fn, output.dtype,
output_row_size,
parallel_iterations=parallel_iterations)
if pfor_output is None:
return None
pfor_output = array_ops.reshape(pfor_output,
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output = array_ops.transpose(pfor_output, [1, 0, 2])
new_shape = array_ops.concat([output_shape, inp_shape[1:]], axis=0)
return array_ops.reshape(output, new_shape) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_windows.py | python | PreMDIParentFrame | (*args, **kwargs) | return val | PreMDIParentFrame() -> MDIParentFrame | PreMDIParentFrame() -> MDIParentFrame | [
"PreMDIParentFrame",
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"-",
">",
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] | def PreMDIParentFrame(*args, **kwargs):
"""PreMDIParentFrame() -> MDIParentFrame"""
val = _windows_.new_PreMDIParentFrame(*args, **kwargs)
return val | [
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fifengine/fifengine | 4b62c42e85bec19893cef8e63e6855927cff2c47 | engine/python/fife/extensions/fifelog.py | python | LogManager.__init__ | (self, engine, promptlog=True, filelog=False) | Constructs new log manager
@param engine: Engine to hook into
@param promptlog: If true, logs to prompt
@param filelog: If true, logs to file (fife.log) | Constructs new log manager | [
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"""
Constructs new log manager
@param engine: Engine to hook into
@param promptlog: If true, logs to prompt
@param filelog: If true, logs to file (fife.log)
"""
self.engine = engine
self.lm = engine.getLogManager()
self.lm.setLogToPrompt(promptlog)
self.lm.setLogToFile(filelog)
self.mod2name = {}
for k, v in list(fife.__dict__.items()):
if k.startswith('LM_') and k not in ('LM_CORE', 'LM_MODULE_MAX'):
self.mod2name[v] = self.lm.getModuleName(v)
self.name2mod = dict([(v.lower(), k) for k, v in list(self.mod2name.items())]) | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/control-examples/OperationalSpaceController.py | python | Task.drawGL | (self,q) | Optionally can be overridden to visualize the task in OpenGL. | Optionally can be overridden to visualize the task in OpenGL. | [
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] | def drawGL(self,q):
"""Optionally can be overridden to visualize the task in OpenGL."""
pass | [
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panda3d/panda3d | 833ad89ebad58395d0af0b7ec08538e5e4308265 | direct/src/showbase/Audio3DManager.py | python | Audio3DManager.getSoundMinDistance | (self, sound) | return sound.get3dMinDistance() | Controls the distance (in units) that this sound begins to fall off.
Also affects the rate it falls off.
Default is 3.28 (in feet, this is 1 meter) | Controls the distance (in units) that this sound begins to fall off.
Also affects the rate it falls off.
Default is 3.28 (in feet, this is 1 meter) | [
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"""
Controls the distance (in units) that this sound begins to fall off.
Also affects the rate it falls off.
Default is 3.28 (in feet, this is 1 meter)
"""
return sound.get3dMinDistance() | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/debug/cli/profile_analyzer_cli.py | python | ProfileDataTableView.__init__ | (self, profile_datum_list, time_unit=cli_shared.TIME_UNIT_US) | Constructor.
Args:
profile_datum_list: List of `ProfileDatum` objects.
time_unit: must be in cli_shared.TIME_UNITS. | Constructor. | [
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] | def __init__(self, profile_datum_list, time_unit=cli_shared.TIME_UNIT_US):
"""Constructor.
Args:
profile_datum_list: List of `ProfileDatum` objects.
time_unit: must be in cli_shared.TIME_UNITS.
"""
self._profile_datum_list = profile_datum_list
self.formatted_start_time = [
datum.start_time for datum in profile_datum_list]
self.formatted_op_time = [
cli_shared.time_to_readable_str(datum.op_time,
force_time_unit=time_unit)
for datum in profile_datum_list]
self.formatted_exec_time = [
cli_shared.time_to_readable_str(
datum.node_exec_stats.all_end_rel_micros,
force_time_unit=time_unit)
for datum in profile_datum_list]
self._column_names = ["Node",
"Op Type",
"Start Time (us)",
"Op Time (%s)" % time_unit,
"Exec Time (%s)" % time_unit,
"Filename:Lineno(function)"]
self._column_sort_ids = [SORT_OPS_BY_OP_NAME, SORT_OPS_BY_OP_TYPE,
SORT_OPS_BY_START_TIME, SORT_OPS_BY_OP_TIME,
SORT_OPS_BY_EXEC_TIME, SORT_OPS_BY_LINE] | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/setuptools/msvc.py | python | RegistryInfo.vc_for_python | (self) | return r'DevDiv\VCForPython' | Microsoft Visual C++ for Python registry key.
Return
------
str
Registry key | Microsoft Visual C++ for Python registry key. | [
"Microsoft",
"Visual",
"C",
"++",
"for",
"Python",
"registry",
"key",
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] | def vc_for_python(self):
"""
Microsoft Visual C++ for Python registry key.
Return
------
str
Registry key
"""
return r'DevDiv\VCForPython' | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/SANS/ISISCommandInterface.py | python | get_q_resolution_w2 | () | return val | Get the second width for rectangular apertures
@returns the second width in mm | Get the second width for rectangular apertures | [
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"for",
"rectangular",
"apertures"
] | def get_q_resolution_w2():
'''
Get the second width for rectangular apertures
@returns the second width in mm
'''
val = get_q_resolution_float(ReductionSingleton().to_Q.get_q_resolution_w2, "W2")
print(str(val))
return val | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/contrib/factorization/python/ops/gmm_ops.py | python | GmmAlgorithm._define_partial_maximization_operation | (self, shard_id, shard) | Computes the partial statistics of the means and covariances.
Args:
shard_id: current shard id.
shard: current data shard, 1 X num_examples X dimensions. | Computes the partial statistics of the means and covariances. | [
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] | def _define_partial_maximization_operation(self, shard_id, shard):
"""Computes the partial statistics of the means and covariances.
Args:
shard_id: current shard id.
shard: current data shard, 1 X num_examples X dimensions.
"""
# Soft assignment of each data point to each of the two clusters.
self._points_in_k[shard_id] = tf.reduce_sum(self._w[shard_id], 0,
keep_dims=True)
# Partial means.
w_mul_x = tf.expand_dims(
tf.matmul(self._w[shard_id],
tf.squeeze(shard, [0]), transpose_a=True), 1)
self._w_mul_x.append(w_mul_x)
# Partial covariances.
x = tf.concat(0, [shard for _ in range(self._num_classes)])
x_trans = tf.transpose(x, perm=[0, 2, 1])
x_mul_w = tf.concat(0, [
tf.expand_dims(x_trans[k, :, :] * self._w[shard_id][:, k], 0)
for k in range(self._num_classes)])
self._w_mul_x2.append(tf.batch_matmul(x_mul_w, x)) | [
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mapsme/omim | 1892903b63f2c85b16ed4966d21fe76aba06b9ba | tools/python/maps_generator/generator/env.py | python | find_last_build_dir | (hint: Optional[AnyStr] = None) | return None if not pairs or pairs[0][1] == 0 else pairs[0][0].split(os.sep)[-1] | It tries to find a last generation directory. If it's found function
returns path of last generation directory. Otherwise returns None. | It tries to find a last generation directory. If it's found function
returns path of last generation directory. Otherwise returns None. | [
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"""
It tries to find a last generation directory. If it's found function
returns path of last generation directory. Otherwise returns None.
"""
if hint is not None:
p = os.path.join(settings.MAIN_OUT_PATH, hint)
return hint if os.path.exists(p) else None
try:
paths = [
os.path.join(settings.MAIN_OUT_PATH, f)
for f in os.listdir(settings.MAIN_OUT_PATH)
]
except FileNotFoundError:
logger.exception(f"{settings.MAIN_OUT_PATH} not found.")
return None
versions = []
for path in paths:
version_path = os.path.join(path, settings.VERSION_FILE_NAME)
if not os.path.isfile(version_path):
versions.append(0)
else:
versions.append(Version.read(version_path))
pairs = sorted(zip(paths, versions), key=lambda p: p[1], reverse=True)
return None if not pairs or pairs[0][1] == 0 else pairs[0][0].split(os.sep)[-1] | [
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/idl/idl/parser.py | python | _parse_initializer | (ctxt, node) | return init | Parse a global initializer. | Parse a global initializer. | [
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# type: (errors.ParserContext, Union[yaml.nodes.ScalarNode, yaml.nodes.MappingNode]) -> syntax.GlobalInitializer
"""Parse a global initializer."""
init = syntax.GlobalInitializer(ctxt.file_name, node.start_mark.line, node.start_mark.column)
if node.id == 'scalar':
init.name = node.value
return init
_generic_parser(ctxt, node, "initializer", init, {
"register": _RuleDesc('scalar', _RuleDesc.REQUIRED),
"store": _RuleDesc('scalar'),
})
return init | [
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KratosMultiphysics/Kratos | 0000833054ed0503424eb28205d6508d9ca6cbbc | applications/ShallowWaterApplication/python_scripts/postprocess/line_graph_output_process.py | python | LineGraphOutputProcess.Check | (self) | Check the file settings. | Check the file settings. | [
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] | def Check(self):
"""Check the file settings."""
# Generate a dummy file to validate the parameters
file = TimeBasedAsciiFileWriterUtility(self.model_part, self.file_settings, "").file
file.close()
DeleteFileIfExisting(file.name) | [
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microsoft/DirectXShaderCompiler | 8348ff8d9e0287610ba05d3a828e10af981a1c05 | utils/hct/CodeTags.py | python | StripIndent | (lines, indent) | return map(strip_indent, lines) | Remove indent from lines of text | Remove indent from lines of text | [
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"Remove indent from lines of text"
def strip_indent(line):
if line.startswith(indent):
return line[len(indent):]
return line
if isinstance(lines, basestring):
lines = lines.splitlines()
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBFrame.GetCFA | (self) | return _lldb.SBFrame_GetCFA(self) | GetCFA(self) -> addr_t
Get the Canonical Frame Address for this stack frame.
This is the DWARF standard's definition of a CFA, a stack address
that remains constant throughout the lifetime of the function.
Returns an lldb::addr_t stack address, or LLDB_INVALID_ADDRESS if
the CFA cannot be determined. | GetCFA(self) -> addr_t | [
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"""
GetCFA(self) -> addr_t
Get the Canonical Frame Address for this stack frame.
This is the DWARF standard's definition of a CFA, a stack address
that remains constant throughout the lifetime of the function.
Returns an lldb::addr_t stack address, or LLDB_INVALID_ADDRESS if
the CFA cannot be determined.
"""
return _lldb.SBFrame_GetCFA(self) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/richtext.py | python | RichTextCtrl.BeginLineSpacing | (*args, **kwargs) | return _richtext.RichTextCtrl_BeginLineSpacing(*args, **kwargs) | BeginLineSpacing(self, int lineSpacing) -> bool
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"""
BeginLineSpacing(self, int lineSpacing) -> bool
Begin line spacing
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manticoresoftware/manticoresearch | f675d16267543d934ce84074f087d13496ec462c | api/sphinxapi.py | python | SphinxClient.SetFilterStringList | ( self, attribute, value, exclude=0 ) | Set string list filter. | Set string list filter. | [
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Set string list filter.
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ElunaLuaEngine/Eluna | 4d862f0bf6b08de451fe215ee0645fbdf7a23a9b | docs/ElunaDoc/parser.py | python | ClassParser.to_class_doc | (self) | return MangosClassDoc(self.class_name, self.class_description, self.methods) | Create an instance of `MangosClassDoc` from the parser's data.
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"""
return MangosClassDoc(self.class_name, self.class_description, self.methods) | [
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opencv/opencv | 76aff8478883858f0e46746044348ebb16dc3c67 | doc/pattern_tools/svgfig.py | python | Ticks.compute_logminiticks | (self, base) | Return optimal logarithmic miniticks, given a set of ticks.
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"""
if self.low >= self.high:
raise ValueError("low must be less than high")
lowN = math.floor(math.log(self.low, base))
highN = math.ceil(math.log(self.high, base))
output = []
num_ticks = 0
for n in range(int(lowN), int(highN)+1):
x = base**n
if self.low <= x <= self.high:
num_ticks += 1
for m in range(2, int(math.ceil(base))):
minix = m * x
if self.low <= minix <= self.high:
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if num_ticks <= 2:
return []
else:
return output | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/internals/array_manager.py | python | ArrayManager.fast_xs | (self, loc: int) | return result | Return the array corresponding to `frame.iloc[loc]`.
Parameters
----------
loc : int
Returns
-------
np.ndarray or ExtensionArray | Return the array corresponding to `frame.iloc[loc]`. | [
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] | def fast_xs(self, loc: int) -> ArrayLike:
"""
Return the array corresponding to `frame.iloc[loc]`.
Parameters
----------
loc : int
Returns
-------
np.ndarray or ExtensionArray
"""
dtype = interleaved_dtype([arr.dtype for arr in self.arrays])
values = [arr[loc] for arr in self.arrays]
if isinstance(dtype, ExtensionDtype):
result = dtype.construct_array_type()._from_sequence(values, dtype=dtype)
# for datetime64/timedelta64, the np.ndarray constructor cannot handle pd.NaT
elif is_datetime64_ns_dtype(dtype):
result = DatetimeArray._from_sequence(values, dtype=dtype)._data
elif is_timedelta64_ns_dtype(dtype):
result = TimedeltaArray._from_sequence(values, dtype=dtype)._data
else:
result = np.array(values, dtype=dtype)
return result | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/signal/ltisys.py | python | StateSpace.__new__ | (cls, *system, **kwargs) | return super(StateSpace, cls).__new__(cls) | Create new StateSpace object and settle inheritance. | Create new StateSpace object and settle inheritance. | [
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] | def __new__(cls, *system, **kwargs):
"""Create new StateSpace object and settle inheritance."""
# Handle object conversion if input is an instance of `lti`
if len(system) == 1 and isinstance(system[0], LinearTimeInvariant):
return system[0].to_ss()
# Choose whether to inherit from `lti` or from `dlti`
if cls is StateSpace:
if kwargs.get('dt') is None:
return StateSpaceContinuous.__new__(StateSpaceContinuous,
*system, **kwargs)
else:
return StateSpaceDiscrete.__new__(StateSpaceDiscrete,
*system, **kwargs)
# No special conversion needed
return super(StateSpace, cls).__new__(cls) | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/ops/session_ops.py | python | TensorHandle.__init__ | (self, handle, dtype, session) | Constructs a new tensor handle.
A tensor handle for a persistent tensor is a python string
that has the form of "tensor_name;unique_id;device_name".
Args:
handle: A tensor handle.
dtype: The data type of the tensor represented by `handle`.
session: The session in which the tensor is produced. | Constructs a new tensor handle. | [
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] | def __init__(self, handle, dtype, session):
"""Constructs a new tensor handle.
A tensor handle for a persistent tensor is a python string
that has the form of "tensor_name;unique_id;device_name".
Args:
handle: A tensor handle.
dtype: The data type of the tensor represented by `handle`.
session: The session in which the tensor is produced.
"""
self._handle = compat.as_str_any(handle)
self._dtype = dtype
self._session = session
self._auto_gc_enabled = True | [
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