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windystrife/UnrealEngine_NVIDIAGameWorks
b50e6338a7c5b26374d66306ebc7807541ff815e
Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/pip/wheel.py
python
WheelBuilder.build
(self)
Build wheels.
Build wheels.
[ "Build", "wheels", "." ]
def build(self): """Build wheels.""" #unpack and constructs req set self.requirement_set.prepare_files(self.finder) reqset = self.requirement_set.requirements.values() #make the wheelhouse if not os.path.exists(self.wheel_dir): os.makedirs(self.wheel_dir) #build the wheels logger.notify('Building wheels for collected packages: %s' % ', '.join([req.name for req in reqset])) logger.indent += 2 build_success, build_failure = [], [] for req in reqset: if req.is_wheel: logger.notify("Skipping building wheel: %s", req.url) continue if self._build_one(req): build_success.append(req) else: build_failure.append(req) logger.indent -= 2 #notify sucess/failure if build_success: logger.notify('Successfully built %s' % ' '.join([req.name for req in build_success])) if build_failure: logger.notify('Failed to build %s' % ' '.join([req.name for req in build_failure]))
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https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/pip/wheel.py#L305-L335
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/pexpect/pexpect/popen_spawn.py
python
PopenSpawn.send
(self, s)
Send data to the subprocess' stdin. Returns the number of bytes written.
Send data to the subprocess' stdin.
[ "Send", "data", "to", "the", "subprocess", "stdin", "." ]
def send(self, s): '''Send data to the subprocess' stdin. Returns the number of bytes written. ''' s = self._coerce_send_string(s) self._log(s, 'send') b = self._encoder.encode(s, final=False) if PY3: return self.proc.stdin.write(b) else: # On Python 2, .write() returns None, so we return the length of # bytes written ourselves. This assumes they all got written. self.proc.stdin.write(b) return len(b)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pexpect/pexpect/popen_spawn.py#L132-L147
idaholab/moose
9eeebc65e098b4c30f8205fb41591fd5b61eb6ff
python/mooseutils/message.py
python
mooseMessage
(*args, **kwargs)
A generic message function. Args: args[tuple]: Comma separated items to be printed, non strings are converted with 'repr'. Kwargs: error[bool]: (Default: False) When True and 'dialog=True' the the "Critical" icon is included with the message. warning[bool]: (Default: False) When True and 'dialog=True' the the "Critical" icon is included with the message. traceback[bool]: (Default: False) When True the stack trace is printed with the message. dialog[bool]: (Default: False) When true a QDialog object is created, the error will still print to the console as well. color[str]: (Default: None) Add the bash color string to the message (see colorText). debug[bool]: (Default: False) Print the message only if tools.MOOSE_DEBUG_MODE = True. test[bool]: FOR TESTING ONLY! (Default: False) When True the QDialog is not executed, just returned. indent[int]: Number of levels to indent (2 spaces are applied to each level)
A generic message function.
[ "A", "generic", "message", "function", "." ]
def mooseMessage(*args, **kwargs): """ A generic message function. Args: args[tuple]: Comma separated items to be printed, non strings are converted with 'repr'. Kwargs: error[bool]: (Default: False) When True and 'dialog=True' the the "Critical" icon is included with the message. warning[bool]: (Default: False) When True and 'dialog=True' the the "Critical" icon is included with the message. traceback[bool]: (Default: False) When True the stack trace is printed with the message. dialog[bool]: (Default: False) When true a QDialog object is created, the error will still print to the console as well. color[str]: (Default: None) Add the bash color string to the message (see colorText). debug[bool]: (Default: False) Print the message only if tools.MOOSE_DEBUG_MODE = True. test[bool]: FOR TESTING ONLY! (Default: False) When True the QDialog is not executed, just returned. indent[int]: Number of levels to indent (2 spaces are applied to each level) """ # Grab the options error = kwargs.pop('error', False) warning = kwargs.pop('warning', False) trace = kwargs.pop('traceback', False) dialog = kwargs.pop('dialog', False) color = kwargs.pop('color', None) test = kwargs.pop('test', False) indent = kwargs.pop('indent', 0) # Build the message message = [] for arg in args: if not isinstance(arg, str): message.append(repr(arg)) else: message.append(arg) message = '{}{}'.format(' '*2*indent, ' '.join(message)) # Show a dialog box if MOOSE_USE_QT5 and dialog and not MOOSE_TESTING_MODE: box = QtWidgets.QMessageBox() box.setText(message) if warning: box.setIcon(QtWidgets.QMessageBox.Warning) elif error: box.setIcon(QtWidgets.QMessageBox.Critical) if test: return box box.exec_() # Emit the message to any listeners if MOOSE_USE_QT5: messageEmitter.write(message, color) # Print the message to screen if color: message = colorText(message, color) print(message) # Show the traceback if trace and MOOSE_USE_QT5: traceback.print_stack() stack = ''.join(traceback.format_stack()) messageEmitter.write(stack, color)
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https://github.com/idaholab/moose/blob/9eeebc65e098b4c30f8205fb41591fd5b61eb6ff/python/mooseutils/message.py#L39-L101
TheLegendAli/DeepLab-Context
fb04e9e2fc2682490ad9f60533b9d6c4c0e0479c
python/caffe/pycaffe.py
python
_Net_forward
(self, blobs=None, start=None, end=None, **kwargs)
return {out: self.blobs[out].data for out in outputs}
Forward pass: prepare inputs and run the net forward. Take blobs: list of blobs to return in addition to output blobs. kwargs: Keys are input blob names and values are blob ndarrays. For formatting inputs for Caffe, see Net.preprocess(). If None, input is taken from data layers. start: optional name of layer at which to begin the forward pass end: optional name of layer at which to finish the forward pass (inclusive) Give outs: {blob name: blob ndarray} dict.
Forward pass: prepare inputs and run the net forward.
[ "Forward", "pass", ":", "prepare", "inputs", "and", "run", "the", "net", "forward", "." ]
def _Net_forward(self, blobs=None, start=None, end=None, **kwargs): """ Forward pass: prepare inputs and run the net forward. Take blobs: list of blobs to return in addition to output blobs. kwargs: Keys are input blob names and values are blob ndarrays. For formatting inputs for Caffe, see Net.preprocess(). If None, input is taken from data layers. start: optional name of layer at which to begin the forward pass end: optional name of layer at which to finish the forward pass (inclusive) Give outs: {blob name: blob ndarray} dict. """ if blobs is None: blobs = [] if start is not None: start_ind = list(self._layer_names).index(start) else: start_ind = 0 if end is not None: end_ind = list(self._layer_names).index(end) outputs = set([end] + blobs) else: end_ind = len(self.layers) - 1 outputs = set(self.outputs + blobs) if kwargs: if set(kwargs.keys()) != set(self.inputs): raise Exception('Input blob arguments do not match net inputs.') # Set input according to defined shapes and make arrays single and # C-contiguous as Caffe expects. for in_, blob in kwargs.iteritems(): if blob.ndim != 4: raise Exception('{} blob is not 4-d'.format(in_)) if blob.shape[0] != self.blobs[in_].num: raise Exception('Input is not batch sized') self.blobs[in_].data[...] = blob self._forward(start_ind, end_ind) # Unpack blobs to extract return {out: self.blobs[out].data for out in outputs}
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https://github.com/TheLegendAli/DeepLab-Context/blob/fb04e9e2fc2682490ad9f60533b9d6c4c0e0479c/python/caffe/pycaffe.py#L38-L83
esa/pykep
b410363653623730b577de257c04b0e0289f2014
pykep/trajopt/_indirect.py
python
indirect_pt2or.__init__
(self, x0, elemf, mass, thrust, isp, atol, rtol, tof, freetime=True, alpha=1, bound=True, mu=pk.MU_SUN)
Initialises ``pykep.trajopt.indirect_pt2or`` problem. Args: - x0 (``list``, ``tuple``, ``numpy.ndarray``): Departure state [m, m, m, m/s, m/s, m/s, kg]. - elemf (``list``, ``tuple``, ``numpy.ndarray``): Arrival Keplerian elements SI units. (mean anomaly will be changed). - mass (``float``, ``int``): Spacecraft wet mass [kg]. - thrust (``float``, ``int``): Spacecraft maximum thrust [N]. - isp (``float``, ``int``): Spacecraft specific impulse [s]. - atol (``float``, ``int``): Absolute integration solution tolerance. - rtol (``float``, ``int``): Relative integration solution tolerance. - tof (``list``): Transfer time bounds [days]. - freetime (``bool``): Activates final time transversality condition. Allows final time to vary. - alpha (``float``, ``int``): Homotopy parameter, governing the degree to which the theoretical control law is intended to reduce propellant expenditure or energy. - bound (``bool``): Activates bounded control, in which the control throttle is bounded between 0 and 1, otherwise the control throttle is allowed to unbounded. - mu (``float``): Gravitational parameter of primary body [m^3/s^2].
Initialises ``pykep.trajopt.indirect_pt2or`` problem.
[ "Initialises", "pykep", ".", "trajopt", ".", "indirect_pt2or", "problem", "." ]
def __init__(self, x0, elemf, mass, thrust, isp, atol, rtol, tof, freetime=True, alpha=1, bound=True, mu=pk.MU_SUN): """Initialises ``pykep.trajopt.indirect_pt2or`` problem. Args: - x0 (``list``, ``tuple``, ``numpy.ndarray``): Departure state [m, m, m, m/s, m/s, m/s, kg]. - elemf (``list``, ``tuple``, ``numpy.ndarray``): Arrival Keplerian elements SI units. (mean anomaly will be changed). - mass (``float``, ``int``): Spacecraft wet mass [kg]. - thrust (``float``, ``int``): Spacecraft maximum thrust [N]. - isp (``float``, ``int``): Spacecraft specific impulse [s]. - atol (``float``, ``int``): Absolute integration solution tolerance. - rtol (``float``, ``int``): Relative integration solution tolerance. - tof (``list``): Transfer time bounds [days]. - freetime (``bool``): Activates final time transversality condition. Allows final time to vary. - alpha (``float``, ``int``): Homotopy parameter, governing the degree to which the theoretical control law is intended to reduce propellant expenditure or energy. - bound (``bool``): Activates bounded control, in which the control throttle is bounded between 0 and 1, otherwise the control throttle is allowed to unbounded. - mu (``float``): Gravitational parameter of primary body [m^3/s^2]. """ # initialise base _indirect_base.__init__( self, mass, thrust, isp, mu, True, freetime, alpha, bound, atol, rtol ) # departure state and arrival Keplerian elements self.x0 = np.asarray(x0, np.float64) self.elemf = np.asarray(elemf, np.float64) self.tof = tof
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https://github.com/esa/pykep/blob/b410363653623730b577de257c04b0e0289f2014/pykep/trajopt/_indirect.py#L460-L488
microsoft/DirectXShaderCompiler
8348ff8d9e0287610ba05d3a828e10af981a1c05
tools/clang/utils/check_cfc/obj_diff.py
python
first_diff
(a, b, fromfile, tofile)
return difference
Returns the first few lines of a difference, if there is one. Python diff can be very slow with large objects and the most interesting changes are the first ones. Truncate data before sending to difflib. Returns None is there is no difference.
Returns the first few lines of a difference, if there is one. Python diff can be very slow with large objects and the most interesting changes are the first ones. Truncate data before sending to difflib. Returns None is there is no difference.
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def first_diff(a, b, fromfile, tofile): """Returns the first few lines of a difference, if there is one. Python diff can be very slow with large objects and the most interesting changes are the first ones. Truncate data before sending to difflib. Returns None is there is no difference.""" # Find first diff first_diff_idx = None for idx, val in enumerate(a): if val != b[idx]: first_diff_idx = idx break if first_diff_idx == None: # No difference return None # Diff to first line of diff plus some lines context = 3 diff = difflib.unified_diff(a[:first_diff_idx+context], b[:first_diff_idx+context], fromfile, tofile) difference = "\n".join(diff) if first_diff_idx + context < len(a): difference += "\n*** Diff truncated ***" return difference
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https://github.com/microsoft/DirectXShaderCompiler/blob/8348ff8d9e0287610ba05d3a828e10af981a1c05/tools/clang/utils/check_cfc/obj_diff.py#L39-L65
emscripten-core/emscripten
0d413d3c5af8b28349682496edc14656f5700c2f
third_party/websockify/websockify/websocket.py
python
WebSocketServer.vmsg
(self, *args, **kwargs)
Same as msg() but as debug.
Same as msg() but as debug.
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def vmsg(self, *args, **kwargs): """ Same as msg() but as debug. """ self.logger.log(logging.DEBUG, *args, **kwargs)
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https://github.com/emscripten-core/emscripten/blob/0d413d3c5af8b28349682496edc14656f5700c2f/third_party/websockify/websockify/websocket.py#L873-L875
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/configure.py
python
set_tf_cuda_clang
(environ_cp)
set TF_CUDA_CLANG action_env. Args: environ_cp: copy of the os.environ.
set TF_CUDA_CLANG action_env.
[ "set", "TF_CUDA_CLANG", "action_env", "." ]
def set_tf_cuda_clang(environ_cp): """set TF_CUDA_CLANG action_env. Args: environ_cp: copy of the os.environ. """ question = 'Do you want to use clang as CUDA compiler?' yes_reply = 'Clang will be used as CUDA compiler.' no_reply = 'nvcc will be used as CUDA compiler.' set_action_env_var( environ_cp, 'TF_CUDA_CLANG', None, False, question=question, yes_reply=yes_reply, no_reply=no_reply, bazel_config_name='cuda_clang')
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/configure.py#L539-L556
thalium/icebox
99d147d5b9269222225443ce171b4fd46d8985d4
third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2class.py
python
xmlNode.hasNsProp
(self, name, nameSpace)
return __tmp
Search for an attribute associated to a node This attribute has to be anchored in the namespace specified. This does the entity substitution. This function looks in DTD attribute declaration for #FIXED or default declaration values unless DTD use has been turned off. Note that a namespace of None indicates to use the default namespace.
Search for an attribute associated to a node This attribute has to be anchored in the namespace specified. This does the entity substitution. This function looks in DTD attribute declaration for #FIXED or default declaration values unless DTD use has been turned off. Note that a namespace of None indicates to use the default namespace.
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def hasNsProp(self, name, nameSpace): """Search for an attribute associated to a node This attribute has to be anchored in the namespace specified. This does the entity substitution. This function looks in DTD attribute declaration for #FIXED or default declaration values unless DTD use has been turned off. Note that a namespace of None indicates to use the default namespace. """ ret = libxml2mod.xmlHasNsProp(self._o, name, nameSpace) if ret is None:return None __tmp = xmlAttr(_obj=ret) return __tmp
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https://github.com/thalium/icebox/blob/99d147d5b9269222225443ce171b4fd46d8985d4/third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2class.py#L2484-L2494
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/pdb.py
python
Pdb.do_retval
(self, arg)
retval Print the return value for the last return of a function.
retval Print the return value for the last return of a function.
[ "retval", "Print", "the", "return", "value", "for", "the", "last", "return", "of", "a", "function", "." ]
def do_retval(self, arg): """retval Print the return value for the last return of a function. """ if '__return__' in self.curframe_locals: self.message(repr(self.curframe_locals['__return__'])) else: self.error('Not yet returned!')
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/pdb.py#L1145-L1152
root-project/root
fcd3583bb14852bf2e8cd2415717cbaac0e75896
build/unix/makepchinput.py
python
getExtraIncludes
(headers)
return allHeadersPartContent
Add include files according to list
Add include files according to list
[ "Add", "include", "files", "according", "to", "list" ]
def getExtraIncludes(headers): """ Add include files according to list """ allHeadersPartContent="" for header in headers: allHeadersPartContent+='#include "%s"\n' %header return allHeadersPartContent
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https://github.com/root-project/root/blob/fcd3583bb14852bf2e8cd2415717cbaac0e75896/build/unix/makepchinput.py#L164-L171
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/prompt-toolkit/py2/prompt_toolkit/buffer.py
python
Buffer.copy_selection
(self, _cut=False)
return clipboard_data
Copy selected text and return :class:`.ClipboardData` instance.
Copy selected text and return :class:`.ClipboardData` instance.
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def copy_selection(self, _cut=False): """ Copy selected text and return :class:`.ClipboardData` instance. """ new_document, clipboard_data = self.document.cut_selection() if _cut: self.document = new_document self.selection_state = None return clipboard_data
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/prompt-toolkit/py2/prompt_toolkit/buffer.py#L972-L981
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/setuptools/msvc.py
python
_augment_exception
(exc, version, arch='')
Add details to the exception message to help guide the user as to what action will resolve it.
Add details to the exception message to help guide the user as to what action will resolve it.
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def _augment_exception(exc, version, arch=''): """ Add details to the exception message to help guide the user as to what action will resolve it. """ # Error if MSVC++ directory not found or environment not set message = exc.args[0] if "vcvarsall" in message.lower() or "visual c" in message.lower(): # Special error message if MSVC++ not installed tmpl = 'Microsoft Visual C++ {version:0.1f} is required.' message = tmpl.format(**locals()) msdownload = 'www.microsoft.com/download/details.aspx?id=%d' if version == 9.0: if arch.lower().find('ia64') > -1: # For VC++ 9.0, if IA64 support is needed, redirect user # to Windows SDK 7.0 message += ' Get it with "Microsoft Windows SDK 7.0": ' message += msdownload % 3138 else: # For VC++ 9.0 redirect user to Vc++ for Python 2.7 : # This redirection link is maintained by Microsoft. # Contact vspython@microsoft.com if it needs updating. message += ' Get it from http://aka.ms/vcpython27' elif version == 10.0: # For VC++ 10.0 Redirect user to Windows SDK 7.1 message += ' Get it with "Microsoft Windows SDK 7.1": ' message += msdownload % 8279 elif version >= 14.0: # For VC++ 14.0 Redirect user to Visual C++ Build Tools message += (' Get it with "Microsoft Visual C++ Build Tools": ' r'http://landinghub.visualstudio.com/' 'visual-cpp-build-tools') exc.args = (message, )
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/setuptools/msvc.py#L204-L238
turi-code/SFrame
796b9bdfb2fa1b881d82080754643c7e68629cd2
oss_src/unity/python/sframe/data_structures/sgraph.py
python
SGraph.get_vertex_fields
(self)
Return a list of vertex attribute fields in the SGraph. Returns ------- out : list Names of fields contained in the vertex data. See Also -------- get_fields, get_edge_fields Examples -------- >>> from graphlab import SGraph, Vertex, Edge >>> g = SGraph() >>> verts = [Vertex(0, attr={'name': 'alex'}), Vertex(1, attr={'name': 'barbara'})] >>> g = g.add_vertices(verts) >>> g = g.add_edges(Edge(0, 1, attr={'frequency': 6})) >>> fields = g.get_vertex_fields() ['__id', 'name']
Return a list of vertex attribute fields in the SGraph.
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def get_vertex_fields(self): """ Return a list of vertex attribute fields in the SGraph. Returns ------- out : list Names of fields contained in the vertex data. See Also -------- get_fields, get_edge_fields Examples -------- >>> from graphlab import SGraph, Vertex, Edge >>> g = SGraph() >>> verts = [Vertex(0, attr={'name': 'alex'}), Vertex(1, attr={'name': 'barbara'})] >>> g = g.add_vertices(verts) >>> g = g.add_edges(Edge(0, 1, attr={'frequency': 6})) >>> fields = g.get_vertex_fields() ['__id', 'name'] """ with cython_context(): return self.__proxy__.get_vertex_fields()
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https://github.com/turi-code/SFrame/blob/796b9bdfb2fa1b881d82080754643c7e68629cd2/oss_src/unity/python/sframe/data_structures/sgraph.py#L757-L783
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemFramework/v1/ResourceManager/resource_manager/resource_group.py
python
ResourceGroup.add_parameters
(self, parameter_definitions, force=False)
return changed
Adds resource and parameter definitions to a resource group's resource-template.json file. Args: parameter_definitions: dictionary containing parameter definitions. force (named): indicates if resource and parameter definitions replace existing definitions. Default is False. Returns: True if any definitions were added.
Adds resource and parameter definitions to a resource group's resource-template.json file.
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def add_parameters(self, parameter_definitions, force=False): """Adds resource and parameter definitions to a resource group's resource-template.json file. Args: parameter_definitions: dictionary containing parameter definitions. force (named): indicates if resource and parameter definitions replace existing definitions. Default is False. Returns: True if any definitions were added. """ changed = False parameters = util.dict_get_or_add(self.template, 'Parameters', {}) for parameter_name, parameter_definition in six.iteritems(parameter_definitions): if parameter_name in parameters and not force: self.__context.view.parameter_exists(self.template_path, parameter_name) else: self.__context.view.adding_parameter(self.template_path, parameter_name) parameters[parameter_name] = parameter_definition changed = True return changed
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemFramework/v1/ResourceManager/resource_manager/resource_group.py#L447-L472
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_core.py
python
Image.GetSubImage
(*args, **kwargs)
return _core_.Image_GetSubImage(*args, **kwargs)
GetSubImage(self, Rect rect) -> Image Returns a sub image of the current one as long as the rect belongs entirely to the image.
GetSubImage(self, Rect rect) -> Image
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def GetSubImage(*args, **kwargs): """ GetSubImage(self, Rect rect) -> Image Returns a sub image of the current one as long as the rect belongs entirely to the image. """ return _core_.Image_GetSubImage(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_core.py#L3309-L3316
cvxpy/cvxpy
5165b4fb750dfd237de8659383ef24b4b2e33aaf
cvxpy/transforms/scalarize.py
python
log_sum_exp
( objectives: List[Union[Minimize, Maximize]], weights, gamma: float = 1.0 )
return Minimize(expr)
Combines objectives as log_sum_exp of weighted terms. The objective takes the form log(sum_{i=1}^n exp(gamma*weights[i]*objectives[i]))/gamma As gamma goes to 0, log_sum_exp approaches weighted_sum. As gamma goes to infinity, log_sum_exp approaches max. Args: objectives: A list of Minimize/Maximize objectives. weights: A vector of weights. gamma: Parameter interpolating between weighted_sum and max. Returns: A Minimize objective.
Combines objectives as log_sum_exp of weighted terms.
[ "Combines", "objectives", "as", "log_sum_exp", "of", "weighted", "terms", "." ]
def log_sum_exp( objectives: List[Union[Minimize, Maximize]], weights, gamma: float = 1.0 ) -> Minimize: """Combines objectives as log_sum_exp of weighted terms. The objective takes the form log(sum_{i=1}^n exp(gamma*weights[i]*objectives[i]))/gamma As gamma goes to 0, log_sum_exp approaches weighted_sum. As gamma goes to infinity, log_sum_exp approaches max. Args: objectives: A list of Minimize/Maximize objectives. weights: A vector of weights. gamma: Parameter interpolating between weighted_sum and max. Returns: A Minimize objective. """ num_objs = len(objectives) terms = [(objectives[i]*weights[i]).args[0] for i in range(num_objs)] expr = atoms.log_sum_exp(gamma*atoms.vstack(terms))/gamma return Minimize(expr)
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https://github.com/cvxpy/cvxpy/blob/5165b4fb750dfd237de8659383ef24b4b2e33aaf/cvxpy/transforms/scalarize.py#L109-L131
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/io/sql.py
python
SQLTable._execute_insert
(self, conn, keys, data_iter)
Execute SQL statement inserting data Parameters ---------- conn : sqlalchemy.engine.Engine or sqlalchemy.engine.Connection keys : list of str Column names data_iter : generator of list Each item contains a list of values to be inserted
Execute SQL statement inserting data
[ "Execute", "SQL", "statement", "inserting", "data" ]
def _execute_insert(self, conn, keys, data_iter): """Execute SQL statement inserting data Parameters ---------- conn : sqlalchemy.engine.Engine or sqlalchemy.engine.Connection keys : list of str Column names data_iter : generator of list Each item contains a list of values to be inserted """ data = [dict(zip(keys, row)) for row in data_iter] conn.execute(self.table.insert(), data)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/io/sql.py#L657-L669
FreeCAD/FreeCAD
ba42231b9c6889b89e064d6d563448ed81e376ec
src/Mod/Path/PathScripts/PathWaterline.py
python
ObjectWaterline._findNextWlPoint
(self, lC, pC, cl, cp, pl, pp)
return [cl, cp, num]
_findNextWlPoint(lC, pC, cl, cp, pl, pp) ... Find the next waterline point in the point cloud layer provided.
_findNextWlPoint(lC, pC, cl, cp, pl, pp) ... Find the next waterline point in the point cloud layer provided.
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def _findNextWlPoint(self, lC, pC, cl, cp, pl, pp): """_findNextWlPoint(lC, pC, cl, cp, pl, pp) ... Find the next waterline point in the point cloud layer provided.""" dl = cl - pl dp = cp - pp num = 0 i = 3 s = 0 mtch = 0 found = False while mtch < 8: # check all 8 points around current point if lC[i] == dl: if pC[i] == dp: s = i - 3 found = True # Check for y branch where current point is connection between branches for y in range(1, mtch): if lC[i + y] == dl: if pC[i + y] == dp: num = 1 break break i += 1 mtch += 1 if found is False: # ("_findNext: No start point found.") return [cl, cp, num] for r in range(0, 8): l = cl + lC[s + r] p = cp + pC[s + r] if self.topoMap[l][p] == 1: return [l, p, num] # ("_findNext: No next pnt found") return [cl, cp, num]
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https://github.com/FreeCAD/FreeCAD/blob/ba42231b9c6889b89e064d6d563448ed81e376ec/src/Mod/Path/PathScripts/PathWaterline.py#L1651-L1686
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/io/sql.py
python
SQLTable._execute_insert
(self, conn, keys, data_iter)
Execute SQL statement inserting data Parameters ---------- conn : sqlalchemy.engine.Engine or sqlalchemy.engine.Connection keys : list of str Column names data_iter : generator of list Each item contains a list of values to be inserted
Execute SQL statement inserting data
[ "Execute", "SQL", "statement", "inserting", "data" ]
def _execute_insert(self, conn, keys, data_iter): """Execute SQL statement inserting data Parameters ---------- conn : sqlalchemy.engine.Engine or sqlalchemy.engine.Connection keys : list of str Column names data_iter : generator of list Each item contains a list of values to be inserted """ data = [dict(zip(keys, row)) for row in data_iter] conn.execute(self.table.insert(), data)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/pandas/io/sql.py#L657-L669
ChromiumWebApps/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
third_party/libevent/event_rpcgen.py
python
EntryArray.GetDeclaration
(self, funcname)
return code
Allows direct access to elements of the array.
Allows direct access to elements of the array.
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def GetDeclaration(self, funcname): """Allows direct access to elements of the array.""" translate = self.GetTranslation() translate["funcname"] = funcname code = [ 'int %(funcname)s(struct %(parent_name)s *, int, %(ctype)s *);' % translate ] return code
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/third_party/libevent/event_rpcgen.py#L865-L872
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/windows/Lib/logging/__init__.py
python
Logger.error
(self, msg, *args, **kwargs)
Log 'msg % args' with severity 'ERROR'. To pass exception information, use the keyword argument exc_info with a true value, e.g. logger.error("Houston, we have a %s", "major problem", exc_info=1)
Log 'msg % args' with severity 'ERROR'.
[ "Log", "msg", "%", "args", "with", "severity", "ERROR", "." ]
def error(self, msg, *args, **kwargs): """ Log 'msg % args' with severity 'ERROR'. To pass exception information, use the keyword argument exc_info with a true value, e.g. logger.error("Houston, we have a %s", "major problem", exc_info=1) """ if self.isEnabledFor(ERROR): self._log(ERROR, msg, args, **kwargs)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/logging/__init__.py#L1397-L1407
h0x91b/redis-v8
ac8b9d49701d75bcee3719892a2a6a50b437e47a
redis/deps/v8/tools/stats-viewer.py
python
ChromeCounterCollection.Counter
(self, i)
return ChromeCounter(self.data, name_offset, value_offset)
Return the i'th counter.
Return the i'th counter.
[ "Return", "the", "i", "th", "counter", "." ]
def Counter(self, i): """Return the i'th counter.""" name_offset = self.counter_names_offset + i * self._COUNTER_NAME_SIZE value_offset = self.counter_values_offset + i * self.max_threads * 4 return ChromeCounter(self.data, name_offset, value_offset)
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https://github.com/h0x91b/redis-v8/blob/ac8b9d49701d75bcee3719892a2a6a50b437e47a/redis/deps/v8/tools/stats-viewer.py#L444-L448
PaddlePaddle/Paddle
1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c
python/paddle/fluid/framework.py
python
IrNode.outputs
(self)
return [IrNode(n) for n in self.node.outputs]
Return the node outputs. Returns: list(IrNode): node outputs wrapped by IrNode.
Return the node outputs.
[ "Return", "the", "node", "outputs", "." ]
def outputs(self): """ Return the node outputs. Returns: list(IrNode): node outputs wrapped by IrNode. """ return [IrNode(n) for n in self.node.outputs]
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https://github.com/PaddlePaddle/Paddle/blob/1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c/python/paddle/fluid/framework.py#L3953-L3960
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemDefectReporter/v1/AWS/lambda-code/SanitizationLambda/sanitization_lambda.py
python
Sanitizer.__delete_object_from_source
(self,key)
Deletes object with key from source bucket.
Deletes object with key from source bucket.
[ "Deletes", "object", "with", "key", "from", "source", "bucket", "." ]
def __delete_object_from_source(self,key): ''' Deletes object with key from source bucket. ''' try: self.s3_client.delete_object(Bucket=self.source_bucket, Key=key) except Exception as error: self.rejected_files.append(FileStatus(key, True, "Could not delete object after moving object to target bucket.", error))
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemDefectReporter/v1/AWS/lambda-code/SanitizationLambda/sanitization_lambda.py#L153-L159
domino-team/openwrt-cc
8b181297c34d14d3ca521cc9f31430d561dbc688
package/gli-pub/openwrt-node-packages-master/node/node-v6.9.1/tools/gyp/pylib/gyp/mac_tool.py
python
MacTool.ExecMergeInfoPlist
(self, output, *inputs)
Merge multiple .plist files into a single .plist file.
Merge multiple .plist files into a single .plist file.
[ "Merge", "multiple", ".", "plist", "files", "into", "a", "single", ".", "plist", "file", "." ]
def ExecMergeInfoPlist(self, output, *inputs): """Merge multiple .plist files into a single .plist file.""" merged_plist = {} for path in inputs: plist = self._LoadPlistMaybeBinary(path) self._MergePlist(merged_plist, plist) plistlib.writePlist(merged_plist, output)
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https://github.com/domino-team/openwrt-cc/blob/8b181297c34d14d3ca521cc9f31430d561dbc688/package/gli-pub/openwrt-node-packages-master/node/node-v6.9.1/tools/gyp/pylib/gyp/mac_tool.py#L344-L350
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/scipy/stats/_multivariate.py
python
wishart_gen._mode
(self, dim, df, scale)
return out
Parameters ---------- dim : int Dimension of the scale matrix %(_doc_default_callparams)s Notes ----- As this function does no argument checking, it should not be called directly; use 'mode' instead.
Parameters ---------- dim : int Dimension of the scale matrix %(_doc_default_callparams)s
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def _mode(self, dim, df, scale): """ Parameters ---------- dim : int Dimension of the scale matrix %(_doc_default_callparams)s Notes ----- As this function does no argument checking, it should not be called directly; use 'mode' instead. """ if df >= dim + 1: out = (df-dim-1) * scale else: out = None return out
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/stats/_multivariate.py#L1748-L1766
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
contrib/gizmos/msw/gizmos.py
python
StaticPicture.SetScale
(*args, **kwargs)
return _gizmos.StaticPicture_SetScale(*args, **kwargs)
SetScale(self, int scale)
SetScale(self, int scale)
[ "SetScale", "(", "self", "int", "scale", ")" ]
def SetScale(*args, **kwargs): """SetScale(self, int scale)""" return _gizmos.StaticPicture_SetScale(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/contrib/gizmos/msw/gizmos.py#L1023-L1025
stan-dev/math
5fd79f89933269a4ca4d8dd1fde2a36d53d4768c
lib/eigen_3.3.9/debug/gdb/printers.py
python
EigenQuaternionPrinter.__init__
(self, val)
Extract all the necessary information
Extract all the necessary information
[ "Extract", "all", "the", "necessary", "information" ]
def __init__(self, val): "Extract all the necessary information" # The gdb extension does not support value template arguments - need to extract them by hand type = val.type if type.code == gdb.TYPE_CODE_REF: type = type.target() self.type = type.unqualified().strip_typedefs() self.innerType = self.type.template_argument(0) self.val = val # Quaternions have a struct as their storage, so we need to walk through this self.data = self.val['m_coeffs']['m_storage']['m_data']['array'] self.data = self.data.cast(self.innerType.pointer())
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https://github.com/stan-dev/math/blob/5fd79f89933269a4ca4d8dd1fde2a36d53d4768c/lib/eigen_3.3.9/debug/gdb/printers.py#L135-L147
google/mediapipe
e6c19885c6d3c6f410c730952aeed2852790d306
mediapipe/python/solutions/face_detection.py
python
FaceDetection.process
(self, image: np.ndarray)
return super().process(input_data={'image': image})
Processes an RGB image and returns a list of the detected face location data. Args: image: An RGB image represented as a numpy ndarray. Raises: RuntimeError: If the underlying graph throws any error. ValueError: If the input image is not three channel RGB. Returns: A NamedTuple object with a "detections" field that contains a list of the detected face location data.
Processes an RGB image and returns a list of the detected face location data.
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def process(self, image: np.ndarray) -> NamedTuple: """Processes an RGB image and returns a list of the detected face location data. Args: image: An RGB image represented as a numpy ndarray. Raises: RuntimeError: If the underlying graph throws any error. ValueError: If the input image is not three channel RGB. Returns: A NamedTuple object with a "detections" field that contains a list of the detected face location data. """ return super().process(input_data={'image': image})
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https://github.com/google/mediapipe/blob/e6c19885c6d3c6f410c730952aeed2852790d306/mediapipe/python/solutions/face_detection.py#L97-L112
snap-stanford/snap-python
d53c51b0a26aa7e3e7400b014cdf728948fde80a
setup/snap.py
python
TNEANet.BegEAStrI
(self, *args)
return _snap.TNEANet_BegEAStrI(self, *args)
BegEAStrI(TNEANet self, TStr attr) -> TNEANet::TAStrI Parameters: attr: TStr const & BegEAStrI(TNEANet self, TStr attr) -> TNEANetAStrI Parameters: attr: TStr const &
BegEAStrI(TNEANet self, TStr attr) -> TNEANet::TAStrI
[ "BegEAStrI", "(", "TNEANet", "self", "TStr", "attr", ")", "-", ">", "TNEANet", "::", "TAStrI" ]
def BegEAStrI(self, *args): """ BegEAStrI(TNEANet self, TStr attr) -> TNEANet::TAStrI Parameters: attr: TStr const & BegEAStrI(TNEANet self, TStr attr) -> TNEANetAStrI Parameters: attr: TStr const & """ return _snap.TNEANet_BegEAStrI(self, *args)
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https://github.com/snap-stanford/snap-python/blob/d53c51b0a26aa7e3e7400b014cdf728948fde80a/setup/snap.py#L22680-L22693
PaddlePaddle/Paddle
1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c
python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/dygraph_sharding_optimizer.py
python
DygraphShardingOptimizer._map_param_to_rank
(self)
return mapping
mapping parameters to the shard which holds it. Return: Dict[str, int]
mapping parameters to the shard which holds it.
[ "mapping", "parameters", "to", "the", "shard", "which", "holds", "it", "." ]
def _map_param_to_rank(self): """ mapping parameters to the shard which holds it. Return: Dict[str, int] """ mapping = {} for rank, params in self._rank2params.items(): for param in params: mapping[param.name] = rank return mapping
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https://github.com/PaddlePaddle/Paddle/blob/1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c/python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/dygraph_sharding_optimizer.py#L111-L122
ideawu/ssdb
f229ba277c7f7d0ca5a441c0c6fb3d1209af68e4
deps/cpy/antlr3/tree.py
python
BaseTreeAdaptor.createToken
(self, fromToken=None, tokenType=None, text=None)
Tell me how to create a token for use with imaginary token nodes. For example, there is probably no input symbol associated with imaginary token DECL, but you need to create it as a payload or whatever for the DECL node as in ^(DECL type ID). If you care what the token payload objects' type is, you should override this method and any other createToken variant.
Tell me how to create a token for use with imaginary token nodes. For example, there is probably no input symbol associated with imaginary token DECL, but you need to create it as a payload or whatever for the DECL node as in ^(DECL type ID).
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def createToken(self, fromToken=None, tokenType=None, text=None): """ Tell me how to create a token for use with imaginary token nodes. For example, there is probably no input symbol associated with imaginary token DECL, but you need to create it as a payload or whatever for the DECL node as in ^(DECL type ID). If you care what the token payload objects' type is, you should override this method and any other createToken variant. """ raise NotImplementedError
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https://github.com/ideawu/ssdb/blob/f229ba277c7f7d0ca5a441c0c6fb3d1209af68e4/deps/cpy/antlr3/tree.py#L1109-L1120
MythTV/mythtv
d282a209cb8be85d036f85a62a8ec971b67d45f4
mythtv/programs/scripts/metadata/Music/musicbrainzngs/musicbrainz.py
python
_check_filter_and_make_params
(entity, includes, release_status=[], release_type=[])
return params
Check that the status or type values are valid. Then, check that the filters can be used with the given includes. Return a params dict that can be passed to _do_mb_query.
Check that the status or type values are valid. Then, check that the filters can be used with the given includes. Return a params dict that can be passed to _do_mb_query.
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def _check_filter_and_make_params(entity, includes, release_status=[], release_type=[]): """Check that the status or type values are valid. Then, check that the filters can be used with the given includes. Return a params dict that can be passed to _do_mb_query. """ if isinstance(release_status, compat.basestring): release_status = [release_status] if isinstance(release_type, compat.basestring): release_type = [release_type] _check_filter(release_status, VALID_RELEASE_STATUSES) _check_filter(release_type, VALID_RELEASE_TYPES) if (release_status and "releases" not in includes and entity != "release"): raise InvalidFilterError("Can't have a status with no release include") if (release_type and "release-groups" not in includes and "releases" not in includes and entity not in ["release-group", "release"]): raise InvalidFilterError("Can't have a release type " "with no releases or release-groups involved") # Build parameters. params = {} if len(release_status): params["status"] = "|".join(release_status) if len(release_type): params["type"] = "|".join(release_type) return params
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https://github.com/MythTV/mythtv/blob/d282a209cb8be85d036f85a62a8ec971b67d45f4/mythtv/programs/scripts/metadata/Music/musicbrainzngs/musicbrainz.py#L236-L263
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/stc.py
python
StyledTextCtrl.AnnotationGetStyles
(*args, **kwargs)
return _stc.StyledTextCtrl_AnnotationGetStyles(*args, **kwargs)
AnnotationGetStyles(self, int line) -> String Get the annotation styles for a line
AnnotationGetStyles(self, int line) -> String
[ "AnnotationGetStyles", "(", "self", "int", "line", ")", "-", ">", "String" ]
def AnnotationGetStyles(*args, **kwargs): """ AnnotationGetStyles(self, int line) -> String Get the annotation styles for a line """ return _stc.StyledTextCtrl_AnnotationGetStyles(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/stc.py#L5959-L5965
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python3/src/Lib/distutils/dist.py
python
Distribution.parse_command_line
(self)
return True
Parse the setup script's command line, taken from the 'script_args' instance attribute (which defaults to 'sys.argv[1:]' -- see 'setup()' in core.py). This list is first processed for "global options" -- options that set attributes of the Distribution instance. Then, it is alternately scanned for Distutils commands and options for that command. Each new command terminates the options for the previous command. The allowed options for a command are determined by the 'user_options' attribute of the command class -- thus, we have to be able to load command classes in order to parse the command line. Any error in that 'options' attribute raises DistutilsGetoptError; any error on the command-line raises DistutilsArgError. If no Distutils commands were found on the command line, raises DistutilsArgError. Return true if command-line was successfully parsed and we should carry on with executing commands; false if no errors but we shouldn't execute commands (currently, this only happens if user asks for help).
Parse the setup script's command line, taken from the 'script_args' instance attribute (which defaults to 'sys.argv[1:]' -- see 'setup()' in core.py). This list is first processed for "global options" -- options that set attributes of the Distribution instance. Then, it is alternately scanned for Distutils commands and options for that command. Each new command terminates the options for the previous command. The allowed options for a command are determined by the 'user_options' attribute of the command class -- thus, we have to be able to load command classes in order to parse the command line. Any error in that 'options' attribute raises DistutilsGetoptError; any error on the command-line raises DistutilsArgError. If no Distutils commands were found on the command line, raises DistutilsArgError. Return true if command-line was successfully parsed and we should carry on with executing commands; false if no errors but we shouldn't execute commands (currently, this only happens if user asks for help).
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def parse_command_line(self): """Parse the setup script's command line, taken from the 'script_args' instance attribute (which defaults to 'sys.argv[1:]' -- see 'setup()' in core.py). This list is first processed for "global options" -- options that set attributes of the Distribution instance. Then, it is alternately scanned for Distutils commands and options for that command. Each new command terminates the options for the previous command. The allowed options for a command are determined by the 'user_options' attribute of the command class -- thus, we have to be able to load command classes in order to parse the command line. Any error in that 'options' attribute raises DistutilsGetoptError; any error on the command-line raises DistutilsArgError. If no Distutils commands were found on the command line, raises DistutilsArgError. Return true if command-line was successfully parsed and we should carry on with executing commands; false if no errors but we shouldn't execute commands (currently, this only happens if user asks for help). """ # # We now have enough information to show the Macintosh dialog # that allows the user to interactively specify the "command line". # toplevel_options = self._get_toplevel_options() # We have to parse the command line a bit at a time -- global # options, then the first command, then its options, and so on -- # because each command will be handled by a different class, and # the options that are valid for a particular class aren't known # until we have loaded the command class, which doesn't happen # until we know what the command is. self.commands = [] parser = FancyGetopt(toplevel_options + self.display_options) parser.set_negative_aliases(self.negative_opt) parser.set_aliases({'licence': 'license'}) args = parser.getopt(args=self.script_args, object=self) option_order = parser.get_option_order() log.set_verbosity(self.verbose) # for display options we return immediately if self.handle_display_options(option_order): return while args: args = self._parse_command_opts(parser, args) if args is None: # user asked for help (and got it) return # Handle the cases of --help as a "global" option, ie. # "setup.py --help" and "setup.py --help command ...". For the # former, we show global options (--verbose, --dry-run, etc.) # and display-only options (--name, --version, etc.); for the # latter, we omit the display-only options and show help for # each command listed on the command line. if self.help: self._show_help(parser, display_options=len(self.commands) == 0, commands=self.commands) return # Oops, no commands found -- an end-user error if not self.commands: raise DistutilsArgError("no commands supplied") # All is well: return true return True
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/distutils/dist.py#L439-L504
benoitsteiner/tensorflow-opencl
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
tensorflow/examples/learn/resnet.py
python
res_net_model
(features, labels, mode)
return tf.estimator.EstimatorSpec( mode, loss=loss, eval_metric_ops=eval_metric_ops)
Builds a residual network.
Builds a residual network.
[ "Builds", "a", "residual", "network", "." ]
def res_net_model(features, labels, mode): """Builds a residual network.""" # Configurations for each bottleneck group. BottleneckGroup = namedtuple('BottleneckGroup', ['num_blocks', 'num_filters', 'bottleneck_size']) groups = [ BottleneckGroup(3, 128, 32), BottleneckGroup(3, 256, 64), BottleneckGroup(3, 512, 128), BottleneckGroup(3, 1024, 256) ] x = features[X_FEATURE] input_shape = x.get_shape().as_list() # Reshape the input into the right shape if it's 2D tensor if len(input_shape) == 2: ndim = int(sqrt(input_shape[1])) x = tf.reshape(x, [-1, ndim, ndim, 1]) # First convolution expands to 64 channels with tf.variable_scope('conv_layer1'): net = tf.layers.conv2d( x, filters=64, kernel_size=7, activation=tf.nn.relu) net = tf.layers.batch_normalization(net) # Max pool net = tf.layers.max_pooling2d( net, pool_size=3, strides=2, padding='same') # First chain of resnets with tf.variable_scope('conv_layer2'): net = tf.layers.conv2d( net, filters=groups[0].num_filters, kernel_size=1, padding='valid') # Create the bottleneck groups, each of which contains `num_blocks` # bottleneck groups. for group_i, group in enumerate(groups): for block_i in range(group.num_blocks): name = 'group_%d/block_%d' % (group_i, block_i) # 1x1 convolution responsible for reducing dimension with tf.variable_scope(name + '/conv_in'): conv = tf.layers.conv2d( net, filters=group.num_filters, kernel_size=1, padding='valid', activation=tf.nn.relu) conv = tf.layers.batch_normalization(conv) with tf.variable_scope(name + '/conv_bottleneck'): conv = tf.layers.conv2d( conv, filters=group.bottleneck_size, kernel_size=3, padding='same', activation=tf.nn.relu) conv = tf.layers.batch_normalization(conv) # 1x1 convolution responsible for restoring dimension with tf.variable_scope(name + '/conv_out'): input_dim = net.get_shape()[-1].value conv = tf.layers.conv2d( conv, filters=input_dim, kernel_size=1, padding='valid', activation=tf.nn.relu) conv = tf.layers.batch_normalization(conv) # shortcut connections that turn the network into its counterpart # residual function (identity shortcut) net = conv + net try: # upscale to the next group size next_group = groups[group_i + 1] with tf.variable_scope('block_%d/conv_upscale' % group_i): net = tf.layers.conv2d( net, filters=next_group.num_filters, kernel_size=1, padding='same', activation=None, bias_initializer=None) except IndexError: pass net_shape = net.get_shape().as_list() net = tf.nn.avg_pool( net, ksize=[1, net_shape[1], net_shape[2], 1], strides=[1, 1, 1, 1], padding='VALID') net_shape = net.get_shape().as_list() net = tf.reshape(net, [-1, net_shape[1] * net_shape[2] * net_shape[3]]) # Compute logits (1 per class) and compute loss. logits = tf.layers.dense(net, N_DIGITS, activation=None) # Compute predictions. predicted_classes = tf.argmax(logits, 1) if mode == tf.estimator.ModeKeys.PREDICT: predictions = { 'class': predicted_classes, 'prob': tf.nn.softmax(logits) } return tf.estimator.EstimatorSpec(mode, predictions=predictions) # Compute loss. onehot_labels = tf.one_hot(tf.cast(labels, tf.int32), N_DIGITS, 1, 0) loss = tf.losses.softmax_cross_entropy( onehot_labels=onehot_labels, logits=logits) # Create training op. if mode == tf.estimator.ModeKeys.TRAIN: optimizer = tf.train.AdagradOptimizer(learning_rate=0.01) train_op = optimizer.minimize(loss, global_step=tf.train.get_global_step()) return tf.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op) # Compute evaluation metrics. eval_metric_ops = { 'accuracy': tf.metrics.accuracy( labels=labels, predictions=predicted_classes) } return tf.estimator.EstimatorSpec( mode, loss=loss, eval_metric_ops=eval_metric_ops)
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expands to 64 channels", "with", "tf", ".", "variable_scope", "(", "'conv_layer1'", ")", ":", "net", "=", "tf", ".", "layers", ".", "conv2d", "(", "x", ",", "filters", "=", "64", ",", "kernel_size", "=", "7", ",", "activation", "=", "tf", ".", "nn", ".", "relu", ")", "net", "=", "tf", ".", "layers", ".", "batch_normalization", "(", "net", ")", "# Max pool", "net", "=", "tf", ".", "layers", ".", "max_pooling2d", "(", "net", ",", "pool_size", "=", "3", ",", "strides", "=", "2", ",", "padding", "=", "'same'", ")", "# First chain of resnets", "with", "tf", ".", "variable_scope", "(", "'conv_layer2'", ")", ":", "net", "=", "tf", ".", "layers", ".", "conv2d", "(", "net", ",", "filters", "=", "groups", "[", "0", "]", ".", "num_filters", ",", "kernel_size", "=", "1", ",", "padding", "=", "'valid'", ")", "# Create the bottleneck groups, each of which contains `num_blocks`", "# bottleneck groups.", "for", "group_i", ",", "group", "in", "enumerate", "(", "groups", ")", ":", "for", "block_i", "in", "range", "(", "group", ".", "num_blocks", ")", ":", "name", "=", "'group_%d/block_%d'", "%", "(", "group_i", ",", "block_i", ")", "# 1x1 convolution responsible for reducing dimension", "with", "tf", ".", "variable_scope", "(", "name", "+", "'/conv_in'", ")", ":", "conv", "=", "tf", ".", "layers", ".", "conv2d", "(", "net", ",", "filters", "=", "group", ".", "num_filters", ",", "kernel_size", "=", "1", ",", "padding", "=", "'valid'", ",", "activation", "=", "tf", ".", "nn", ".", "relu", ")", "conv", "=", "tf", ".", "layers", ".", "batch_normalization", "(", "conv", ")", "with", "tf", ".", "variable_scope", "(", "name", "+", "'/conv_bottleneck'", ")", ":", "conv", "=", "tf", ".", "layers", ".", "conv2d", "(", "conv", ",", "filters", "=", "group", ".", "bottleneck_size", ",", "kernel_size", "=", "3", ",", "padding", "=", "'same'", ",", "activation", "=", "tf", ".", "nn", ".", "relu", ")", "conv", "=", "tf", ".", "layers", ".", "batch_normalization", "(", "conv", ")", "# 1x1 convolution responsible for restoring dimension", "with", "tf", ".", "variable_scope", "(", "name", "+", "'/conv_out'", ")", ":", "input_dim", "=", "net", ".", "get_shape", "(", ")", "[", "-", "1", "]", ".", "value", "conv", "=", "tf", ".", "layers", ".", "conv2d", "(", "conv", ",", "filters", "=", "input_dim", ",", "kernel_size", "=", "1", ",", "padding", "=", "'valid'", ",", "activation", "=", "tf", ".", "nn", ".", "relu", ")", "conv", "=", "tf", ".", "layers", ".", "batch_normalization", "(", "conv", ")", "# shortcut connections that turn the network into its counterpart", "# residual function (identity shortcut)", "net", "=", "conv", "+", "net", "try", ":", "# upscale to the next group size", "next_group", "=", "groups", "[", "group_i", "+", "1", "]", "with", "tf", ".", "variable_scope", "(", "'block_%d/conv_upscale'", "%", "group_i", ")", ":", "net", "=", "tf", ".", "layers", ".", "conv2d", "(", "net", ",", "filters", "=", "next_group", ".", "num_filters", ",", "kernel_size", "=", "1", ",", "padding", "=", "'same'", ",", "activation", "=", "None", ",", "bias_initializer", "=", "None", ")", "except", "IndexError", ":", "pass", "net_shape", "=", "net", ".", "get_shape", "(", ")", ".", "as_list", "(", ")", "net", "=", "tf", ".", "nn", ".", "avg_pool", "(", "net", ",", "ksize", "=", "[", "1", ",", "net_shape", "[", "1", "]", ",", "net_shape", "[", "2", "]", ",", "1", "]", ",", "strides", "=", "[", "1", ",", "1", ",", "1", ",", "1", "]", ",", "padding", "=", "'VALID'", ")", "net_shape", "=", "net", ".", "get_shape", "(", ")", ".", "as_list", "(", ")", "net", "=", "tf", ".", "reshape", "(", "net", ",", "[", "-", "1", ",", "net_shape", "[", "1", "]", "*", "net_shape", "[", "2", "]", "*", "net_shape", "[", "3", "]", "]", ")", "# Compute logits (1 per class) and compute loss.", "logits", "=", "tf", ".", "layers", ".", "dense", "(", "net", ",", "N_DIGITS", ",", "activation", "=", "None", ")", "# Compute predictions.", "predicted_classes", "=", "tf", ".", "argmax", "(", "logits", ",", "1", ")", "if", "mode", "==", "tf", ".", "estimator", ".", "ModeKeys", ".", "PREDICT", ":", "predictions", "=", "{", "'class'", ":", "predicted_classes", ",", "'prob'", ":", "tf", ".", "nn", ".", "softmax", "(", "logits", ")", "}", "return", "tf", ".", "estimator", ".", "EstimatorSpec", "(", "mode", ",", "predictions", "=", "predictions", ")", "# Compute loss.", "onehot_labels", "=", "tf", ".", "one_hot", "(", "tf", ".", "cast", "(", "labels", ",", "tf", ".", "int32", ")", ",", "N_DIGITS", ",", "1", ",", "0", ")", "loss", "=", "tf", ".", "losses", ".", "softmax_cross_entropy", "(", "onehot_labels", "=", "onehot_labels", ",", "logits", "=", "logits", ")", "# Create training op.", "if", "mode", "==", "tf", ".", "estimator", ".", "ModeKeys", ".", "TRAIN", ":", "optimizer", "=", "tf", ".", "train", ".", "AdagradOptimizer", "(", "learning_rate", "=", "0.01", ")", "train_op", "=", "optimizer", ".", "minimize", "(", "loss", ",", "global_step", "=", "tf", ".", "train", ".", "get_global_step", "(", ")", ")", "return", "tf", ".", "estimator", ".", "EstimatorSpec", "(", "mode", ",", "loss", "=", "loss", ",", "train_op", "=", "train_op", ")", "# Compute evaluation metrics.", "eval_metric_ops", "=", "{", "'accuracy'", ":", "tf", ".", "metrics", ".", "accuracy", "(", "labels", "=", "labels", ",", "predictions", "=", "predicted_classes", ")", "}", "return", "tf", ".", "estimator", ".", "EstimatorSpec", "(", "mode", ",", "loss", "=", "loss", ",", "eval_metric_ops", "=", "eval_metric_ops", ")" ]
https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/examples/learn/resnet.py#L37-L170
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/propgrid.py
python
PropertyGrid.GetSelectionForegroundColour
(*args, **kwargs)
return _propgrid.PropertyGrid_GetSelectionForegroundColour(*args, **kwargs)
GetSelectionForegroundColour(self) -> Colour
GetSelectionForegroundColour(self) -> Colour
[ "GetSelectionForegroundColour", "(", "self", ")", "-", ">", "Colour" ]
def GetSelectionForegroundColour(*args, **kwargs): """GetSelectionForegroundColour(self) -> Colour""" return _propgrid.PropertyGrid_GetSelectionForegroundColour(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/propgrid.py#L2134-L2136
hughperkins/tf-coriander
970d3df6c11400ad68405f22b0c42a52374e94ca
tensorflow/contrib/bayesflow/python/ops/stochastic_gradient_estimators.py
python
get_score_function_with_constant_baseline
(baseline, name="ScoreFunction")
return score_function_with_constant_baseline
Score function estimator with constant baseline. Args: baseline: `Tensor` to be subtracted from loss. name: name to prepend ops with. Returns: Callable score function estimator that takes the `DistributionTensor`, the sampled `value`, and the downstream `loss`, and subtracts the provided `baseline` from the `loss`.
Score function estimator with constant baseline.
[ "Score", "function", "estimator", "with", "constant", "baseline", "." ]
def get_score_function_with_constant_baseline(baseline, name="ScoreFunction"): """Score function estimator with constant baseline. Args: baseline: `Tensor` to be subtracted from loss. name: name to prepend ops with. Returns: Callable score function estimator that takes the `DistributionTensor`, the sampled `value`, and the downstream `loss`, and subtracts the provided `baseline` from the `loss`. """ def score_function_with_constant_baseline(dist_tensor, value, loss): return score_function(dist_tensor, value, loss, baseline, name) return score_function_with_constant_baseline
[ "def", "get_score_function_with_constant_baseline", "(", "baseline", ",", "name", "=", "\"ScoreFunction\"", ")", ":", "def", "score_function_with_constant_baseline", "(", "dist_tensor", ",", "value", ",", "loss", ")", ":", "return", "score_function", "(", "dist_tensor", ",", "value", ",", "loss", ",", "baseline", ",", "name", ")", "return", "score_function_with_constant_baseline" ]
https://github.com/hughperkins/tf-coriander/blob/970d3df6c11400ad68405f22b0c42a52374e94ca/tensorflow/contrib/bayesflow/python/ops/stochastic_gradient_estimators.py#L124-L140
idaholab/moose
9eeebc65e098b4c30f8205fb41591fd5b61eb6ff
python/peacock/base/OutputWidgetBase.py
python
OutputWidgetBase._callbackPythonButton
(self)
Open dialog and write script.
Open dialog and write script.
[ "Open", "dialog", "and", "write", "script", "." ]
def _callbackPythonButton(self): """ Open dialog and write script. """ dialog = QtWidgets.QFileDialog() dialog.setWindowTitle('Write Python Script') dialog.setNameFilter('Python Files (*.py)') dialog.setFileMode(QtWidgets.QFileDialog.AnyFile) dialog.setAcceptMode(QtWidgets.QFileDialog.AcceptSave) dialog.setOption(QtWidgets.QFileDialog.DontUseNativeDialog) if dialog.exec_() == QtWidgets.QDialog.Accepted: filename = str(dialog.selectedFiles()[0]) self.write.emit(filename)
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https://github.com/idaholab/moose/blob/9eeebc65e098b4c30f8205fb41591fd5b61eb6ff/python/peacock/base/OutputWidgetBase.py#L65-L78
protocolbuffers/protobuf
b5ab0b7a18b7336c60130f4ddb2d97c51792f896
python/google/protobuf/descriptor_pool.py
python
DescriptorPool.FindEnumTypeByName
(self, full_name)
return self._enum_descriptors[full_name]
Loads the named enum descriptor from the pool. Args: full_name (str): The full name of the enum descriptor to load. Returns: EnumDescriptor: The enum descriptor for the named type. Raises: KeyError: if the enum cannot be found in the pool.
Loads the named enum descriptor from the pool.
[ "Loads", "the", "named", "enum", "descriptor", "from", "the", "pool", "." ]
def FindEnumTypeByName(self, full_name): """Loads the named enum descriptor from the pool. Args: full_name (str): The full name of the enum descriptor to load. Returns: EnumDescriptor: The enum descriptor for the named type. Raises: KeyError: if the enum cannot be found in the pool. """ full_name = _NormalizeFullyQualifiedName(full_name) if full_name not in self._enum_descriptors: self._FindFileContainingSymbolInDb(full_name) return self._enum_descriptors[full_name]
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https://github.com/protocolbuffers/protobuf/blob/b5ab0b7a18b7336c60130f4ddb2d97c51792f896/python/google/protobuf/descriptor_pool.py#L519-L535
y123456yz/reading-and-annotate-mongodb-3.6
93280293672ca7586dc24af18132aa61e4ed7fcf
mongo/src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Tool/msvc.py
python
generate
(env)
Add Builders and construction variables for MSVC++ to an Environment.
Add Builders and construction variables for MSVC++ to an Environment.
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def generate(env): """Add Builders and construction variables for MSVC++ to an Environment.""" static_obj, shared_obj = SCons.Tool.createObjBuilders(env) # TODO(batch): shouldn't reach in to cmdgen this way; necessary # for now to bypass the checks in Builder.DictCmdGenerator.__call__() # and allow .cc and .cpp to be compiled in the same command line. static_obj.cmdgen.source_ext_match = False shared_obj.cmdgen.source_ext_match = False for suffix in CSuffixes: static_obj.add_action(suffix, CAction) shared_obj.add_action(suffix, ShCAction) static_obj.add_emitter(suffix, static_object_emitter) shared_obj.add_emitter(suffix, shared_object_emitter) for suffix in CXXSuffixes: static_obj.add_action(suffix, CXXAction) shared_obj.add_action(suffix, ShCXXAction) static_obj.add_emitter(suffix, static_object_emitter) shared_obj.add_emitter(suffix, shared_object_emitter) env['CCPDBFLAGS'] = SCons.Util.CLVar(['${(PDB and "/Z7") or ""}']) env['CCPCHFLAGS'] = SCons.Util.CLVar(['${(PCH and "/Yu%s \\\"/Fp%s\\\""%(PCHSTOP or "",File(PCH))) or ""}']) env['_MSVC_OUTPUT_FLAG'] = msvc_output_flag env['_CCCOMCOM'] = '$CPPFLAGS $_CPPDEFFLAGS $_CPPINCFLAGS $CCPCHFLAGS $CCPDBFLAGS' env['CC'] = 'cl' env['CCFLAGS'] = SCons.Util.CLVar('/nologo') env['CFLAGS'] = SCons.Util.CLVar('') env['CCCOM'] = '${TEMPFILE("$CC $_MSVC_OUTPUT_FLAG /c $CHANGED_SOURCES $CFLAGS $CCFLAGS $_CCCOMCOM","$CCCOMSTR")}' env['SHCC'] = '$CC' env['SHCCFLAGS'] = SCons.Util.CLVar('$CCFLAGS') env['SHCFLAGS'] = SCons.Util.CLVar('$CFLAGS') env['SHCCCOM'] = '${TEMPFILE("$SHCC $_MSVC_OUTPUT_FLAG /c $CHANGED_SOURCES $SHCFLAGS $SHCCFLAGS $_CCCOMCOM","$SHCCCOMSTR")}' env['CXX'] = '$CC' env['CXXFLAGS'] = SCons.Util.CLVar('$( /TP $)') env['CXXCOM'] = '${TEMPFILE("$CXX $_MSVC_OUTPUT_FLAG /c $CHANGED_SOURCES $CXXFLAGS $CCFLAGS $_CCCOMCOM","$CXXCOMSTR")}' env['SHCXX'] = '$CXX' env['SHCXXFLAGS'] = SCons.Util.CLVar('$CXXFLAGS') env['SHCXXCOM'] = '${TEMPFILE("$SHCXX $_MSVC_OUTPUT_FLAG /c $CHANGED_SOURCES $SHCXXFLAGS $SHCCFLAGS $_CCCOMCOM","$SHCXXCOMSTR")}' env['CPPDEFPREFIX'] = '/D' env['CPPDEFSUFFIX'] = '' env['INCPREFIX'] = '/I' env['INCSUFFIX'] = '' # env.Append(OBJEMITTER = [static_object_emitter]) # env.Append(SHOBJEMITTER = [shared_object_emitter]) env['STATIC_AND_SHARED_OBJECTS_ARE_THE_SAME'] = 1 env['RC'] = 'rc' env['RCFLAGS'] = SCons.Util.CLVar('') env['RCSUFFIXES']=['.rc','.rc2'] env['RCCOM'] = '$RC $_CPPDEFFLAGS $_CPPINCFLAGS $RCFLAGS /fo$TARGET $SOURCES' env['BUILDERS']['RES'] = res_builder env['OBJPREFIX'] = '' env['OBJSUFFIX'] = '.obj' env['SHOBJPREFIX'] = '$OBJPREFIX' env['SHOBJSUFFIX'] = '$OBJSUFFIX' # Set-up ms tools paths msvc_setup_env_once(env) env['CFILESUFFIX'] = '.c' env['CXXFILESUFFIX'] = '.cc' env['PCHPDBFLAGS'] = SCons.Util.CLVar(['${(PDB and "/Yd") or ""}']) env['PCHCOM'] = '$CXX /Fo${TARGETS[1]} $CXXFLAGS $CCFLAGS $CPPFLAGS $_CPPDEFFLAGS $_CPPINCFLAGS /c $SOURCES /Yc$PCHSTOP /Fp${TARGETS[0]} $CCPDBFLAGS $PCHPDBFLAGS' env['BUILDERS']['PCH'] = pch_builder if 'ENV' not in env: env['ENV'] = {} if 'SystemRoot' not in env['ENV']: # required for dlls in the winsxs folders env['ENV']['SystemRoot'] = SCons.Platform.win32.get_system_root()
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https://github.com/y123456yz/reading-and-annotate-mongodb-3.6/blob/93280293672ca7586dc24af18132aa61e4ed7fcf/mongo/src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Tool/msvc.py#L198-L269
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/training/tracking/util.py
python
_LoadStatus.assert_nontrivial_match
(self)
Raises an exception if only the root object matched.
Raises an exception if only the root object matched.
[ "Raises", "an", "exception", "if", "only", "the", "root", "object", "matched", "." ]
def assert_nontrivial_match(self): """Raises an exception if only the root object matched.""" pass
[ "def", "assert_nontrivial_match", "(", "self", ")", ":", "pass" ]
https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/training/tracking/util.py#L694-L696
lhmRyan/deep-supervised-hashing-DSH
631901f82e2ab031fbac33f914a5b08ef8e21d57
python/caffe/io.py
python
blobproto_to_array
(blob, return_diff=False)
Convert a blob proto to an array. In default, we will just return the data, unless return_diff is True, in which case we will return the diff.
Convert a blob proto to an array. In default, we will just return the data, unless return_diff is True, in which case we will return the diff.
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def blobproto_to_array(blob, return_diff=False): """ Convert a blob proto to an array. In default, we will just return the data, unless return_diff is True, in which case we will return the diff. """ # Read the data into an array if return_diff: data = np.array(blob.diff) else: data = np.array(blob.data) # Reshape the array if blob.HasField('num') or blob.HasField('channels') or blob.HasField('height') or blob.HasField('width'): # Use legacy 4D shape return data.reshape(blob.num, blob.channels, blob.height, blob.width) else: return data.reshape(blob.shape.dim)
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https://github.com/lhmRyan/deep-supervised-hashing-DSH/blob/631901f82e2ab031fbac33f914a5b08ef8e21d57/python/caffe/io.py#L18-L34
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/_controls.py
python
SpinCtrlDouble.SetValue
(*args, **kwargs)
return _controls_.SpinCtrlDouble_SetValue(*args, **kwargs)
SetValue(self, double value)
SetValue(self, double value)
[ "SetValue", "(", "self", "double", "value", ")" ]
def SetValue(*args, **kwargs): """SetValue(self, double value)""" return _controls_.SpinCtrlDouble_SetValue(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_controls.py#L2512-L2514
stan-dev/math
5fd79f89933269a4ca4d8dd1fde2a36d53d4768c
lib/cpplint_1.4.5/cpplint.py
python
_BlockInfo.CheckEnd
(self, filename, clean_lines, linenum, error)
Run checks that applies to text after the closing brace. This is mostly used for checking end of namespace comments. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. error: The function to call with any errors found.
Run checks that applies to text after the closing brace.
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def CheckEnd(self, filename, clean_lines, linenum, error): """Run checks that applies to text after the closing brace. This is mostly used for checking end of namespace comments. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. error: The function to call with any errors found. """ pass
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https://github.com/stan-dev/math/blob/5fd79f89933269a4ca4d8dd1fde2a36d53d4768c/lib/cpplint_1.4.5/cpplint.py#L2462-L2473
MVIG-SJTU/RMPE
5188c230ec800c12be7369c3619615bc9b020aa4
examples/pycaffe/tools.py
python
SimpleTransformer.set_mean
(self, mean)
Set the mean to subtract for centering the data.
Set the mean to subtract for centering the data.
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def set_mean(self, mean): """ Set the mean to subtract for centering the data. """ self.mean = mean
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https://github.com/MVIG-SJTU/RMPE/blob/5188c230ec800c12be7369c3619615bc9b020aa4/examples/pycaffe/tools.py#L15-L19
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/x86/toolchain/lib/python2.7/lib2to3/pygram.py
python
Symbols.__init__
(self, grammar)
Initializer. Creates an attribute for each grammar symbol (nonterminal), whose value is the symbol's type (an int >= 256).
Initializer.
[ "Initializer", "." ]
def __init__(self, grammar): """Initializer. Creates an attribute for each grammar symbol (nonterminal), whose value is the symbol's type (an int >= 256). """ for name, symbol in grammar.symbol2number.iteritems(): setattr(self, name, symbol)
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/lib2to3/pygram.py#L22-L29
google/mysql-protobuf
467cda676afaa49e762c5c9164a43f6ad31a1fbf
storage/ndb/mcc/remote_clusterhost.py
python
RemoteClusterHost._exec_cmdv
(self, cmdv, procCtrl, stdinFile)
return self._exec_cmdln(' '.join([quote_if_contains_space(a) for a in cmdv]), procCtrl, stdinFile)
Execute an OS command vector on the remote host. cmdv - complete command vector (argv) of the OS command procCtrl - procCtrl object from message which controls how the process is started (blocking vs non-blocking and output reporting)
Execute an OS command vector on the remote host. cmdv - complete command vector (argv) of the OS command procCtrl - procCtrl object from message which controls how the process is started (blocking vs non-blocking and output reporting)
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def _exec_cmdv(self, cmdv, procCtrl, stdinFile): """Execute an OS command vector on the remote host. cmdv - complete command vector (argv) of the OS command procCtrl - procCtrl object from message which controls how the process is started (blocking vs non-blocking and output reporting) """ assert isinstance(cmdv, list) return self._exec_cmdln(' '.join([quote_if_contains_space(a) for a in cmdv]), procCtrl, stdinFile)
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https://github.com/google/mysql-protobuf/blob/467cda676afaa49e762c5c9164a43f6ad31a1fbf/storage/ndb/mcc/remote_clusterhost.py#L279-L287
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/msw/_gdi.py
python
RegionFromBitmapColour
(*args, **kwargs)
return val
RegionFromBitmapColour(Bitmap bmp, Colour transColour, int tolerance=0) -> Region
RegionFromBitmapColour(Bitmap bmp, Colour transColour, int tolerance=0) -> Region
[ "RegionFromBitmapColour", "(", "Bitmap", "bmp", "Colour", "transColour", "int", "tolerance", "=", "0", ")", "-", ">", "Region" ]
def RegionFromBitmapColour(*args, **kwargs): """RegionFromBitmapColour(Bitmap bmp, Colour transColour, int tolerance=0) -> Region""" val = _gdi_.new_RegionFromBitmapColour(*args, **kwargs) return val
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/_gdi.py#L1740-L1743
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/gsutil/third_party/boto/boto/rds/__init__.py
python
RDSConnection.get_log_file
(self, dbinstance_id, log_file_name, marker=None, number_of_lines=None, max_records=None)
return logfile
Download a log file from RDS :type instance_id: str :param instance_id: The identifier of a DBInstance. :type log_file_name: str :param log_file_name: The name of the log file to retrieve :type marker: str :param marker: A marker returned from a previous call to this method, or 0 to indicate the start of file. If no marker is specified, this will fetch log lines from the end of file instead. :type number_of_lines: int :param marker: The maximium number of lines to be returned.
Download a log file from RDS
[ "Download", "a", "log", "file", "from", "RDS" ]
def get_log_file(self, dbinstance_id, log_file_name, marker=None, number_of_lines=None, max_records=None): """ Download a log file from RDS :type instance_id: str :param instance_id: The identifier of a DBInstance. :type log_file_name: str :param log_file_name: The name of the log file to retrieve :type marker: str :param marker: A marker returned from a previous call to this method, or 0 to indicate the start of file. If no marker is specified, this will fetch log lines from the end of file instead. :type number_of_lines: int :param marker: The maximium number of lines to be returned. """ params = { 'DBInstanceIdentifier': dbinstance_id, 'LogFileName': log_file_name, } if marker: params['Marker'] = marker if number_of_lines: params['NumberOfLines'] = number_of_lines if max_records: params['MaxRecords'] = max_records logfile = self.get_object('DownloadDBLogFilePortion', params, LogFileObject) if logfile: logfile.log_filename = log_file_name logfile.dbinstance_id = dbinstance_id return logfile
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/third_party/boto/boto/rds/__init__.py#L1124-L1162
mindspore-ai/mindspore
fb8fd3338605bb34fa5cea054e535a8b1d753fab
mindspore/python/mindspore/ops/_op_impl/aicpu/mirror_pad.py
python
_mirror_pad_aicpu
()
return
MirrorPad AiCPU register
MirrorPad AiCPU register
[ "MirrorPad", "AiCPU", "register" ]
def _mirror_pad_aicpu(): """MirrorPad AiCPU register""" return
[ "def", "_mirror_pad_aicpu", "(", ")", ":", "return" ]
https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/ops/_op_impl/aicpu/mirror_pad.py#L50-L52
windystrife/UnrealEngine_NVIDIAGameWorks
b50e6338a7c5b26374d66306ebc7807541ff815e
Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/idlelib/tabbedpages.py
python
TabSet.add_tab
(self, tab_name)
Add a new tab with the name given in tab_name.
Add a new tab with the name given in tab_name.
[ "Add", "a", "new", "tab", "with", "the", "name", "given", "in", "tab_name", "." ]
def add_tab(self, tab_name): """Add a new tab with the name given in tab_name.""" if not tab_name: raise InvalidNameError("Invalid Tab name: '%s'" % tab_name) if tab_name in self._tab_names: raise AlreadyExistsError("Tab named '%s' already exists" %tab_name) self._tab_names.append(tab_name) self._arrange_tabs()
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https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/idlelib/tabbedpages.py#L68-L76
psi4/psi4
be533f7f426b6ccc263904e55122899b16663395
psi4/driver/qcdb/libmintspointgrp.py
python
IrreducibleRepresentation.__str__
(self, out=None)
This prints the irrep to the given file, or stdout if none is given. The second argument is an optional string of spaces to offset by.
This prints the irrep to the given file, or stdout if none is given. The second argument is an optional string of spaces to offset by.
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def __str__(self, out=None): """This prints the irrep to the given file, or stdout if none is given. The second argument is an optional string of spaces to offset by. """ if self.g == 0: return text = " %-5s" % (self.symb) for i in range(self.g): text += " %6.3f" % (self.character(i)) text += " | %d t, %d R\n" % (self.PYntrans, self.PYnrot) for d in range(self.nproj()): text += " " for i in range(self.g): text += " %6.3f" % (self.p(d, i)) text += "\n" if out is None: return text else: with open(out, mode='w') as handle: handle.write(text)
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https://github.com/psi4/psi4/blob/be533f7f426b6ccc263904e55122899b16663395/psi4/driver/qcdb/libmintspointgrp.py#L805-L830
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/propgrid.py
python
PropertyGridPage.GetStatePtr
(*args)
return _propgrid.PropertyGridPage_GetStatePtr(*args)
GetStatePtr(self) GetStatePtr(self)
GetStatePtr(self) GetStatePtr(self)
[ "GetStatePtr", "(", "self", ")", "GetStatePtr", "(", "self", ")" ]
def GetStatePtr(*args): """ GetStatePtr(self) GetStatePtr(self) """ return _propgrid.PropertyGridPage_GetStatePtr(*args)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/propgrid.py#L3371-L3376
eclipse/sumo
7132a9b8b6eea734bdec38479026b4d8c4336d03
tools/simpla/_pvehicle.py
python
PVehicle.__init__
(self, ID, controlInterval)
Constructor(string, float) Create a PVehicle representing a SUMOVehicle for the PlatoonManager. The controlInterval is only piped through to the singelton platoon created by the vehicle.
Constructor(string, float)
[ "Constructor", "(", "string", "float", ")" ]
def __init__(self, ID, controlInterval): '''Constructor(string, float) Create a PVehicle representing a SUMOVehicle for the PlatoonManager. The controlInterval is only piped through to the singelton platoon created by the vehicle. ''' # vehicle ID (should be the one used in SUMO) self._ID = ID # vehicle state (is updated by platoon manager in every step) self.state = pVehicleState(ID) # store the vehicle's vTypes, speedfactors and lanechangemodes self._vTypes = dict() self._speedFactors = dict() self._laneChangeModes = dict() # original vtype, speedFactor and lanechangemodes self._vTypes[PlatoonMode.NONE] = traci.vehicle.getTypeID(ID) self._speedFactors[PlatoonMode.NONE] = traci.vehicle.getSpeedFactor(ID) # This is the default mode self._laneChangeModes[PlatoonMode.NONE] = 0b1001010101 # vTypes, speedFactors and lanechangemodes parametrizing the platoon behaviour for mode in [PlatoonMode.LEADER, PlatoonMode.FOLLOWER, PlatoonMode.CATCHUP, PlatoonMode.CATCHUP_FOLLOWER]: self._vTypes[mode] = self._determinePlatoonVType(mode) self._laneChangeModes[mode] = cfg.LC_MODE[mode] self._speedFactors[mode] = cfg.SPEEDFACTOR[mode] self._speedFactors[PlatoonMode.NONE] = traci.vehicletype.getSpeedFactor(self._vTypes[PlatoonMode.NONE]) # Initialize platoon mode to none self._currentPlatoonMode = PlatoonMode.NONE # the active speed factor is decreased as the waiting time for a mode switch rises # (assuming that the main hindrance to switching is too close following) self._activeSpeedFactor = cfg.SPEEDFACTOR[self._currentPlatoonMode] # The switch impatience factor determines the magnitude of the effect # that an increasing waiting time has on the active speed factor: # activeSpeedFactor = modeSpecificSpeedFactor/(1+impatienceFactor*waitingTime) self._switchImpatienceFactor = cfg.SWITCH_IMPATIENCE_FACTOR # create a new platoon containing only this vehicle self._platoon = Platoon([self], controlInterval) # the time left until splitting from a platoon if loosing coherence as a follower self._timeUntilSplit = cfg.PLATOON_SPLIT_TIME # Whether split conditions are fulfilled (i.e. leader in th platoon # is not found directly in front of the vehicle) self._splitConditions = False # waiting time for switching into different modes self._switchWaitingTime = {} self.resetSwitchWaitingTime()
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https://github.com/eclipse/sumo/blob/7132a9b8b6eea734bdec38479026b4d8c4336d03/tools/simpla/_pvehicle.py#L65-L111
yuxng/PoseCNN
9f3dd7b7bce21dcafc05e8f18ccc90da3caabd04
lib/datasets/shapenet_single.py
python
shapenet_single.label_path_at
(self, i)
return self.label_path_from_index(self.image_index[i])
Return the absolute path to metadata i in the image sequence.
Return the absolute path to metadata i in the image sequence.
[ "Return", "the", "absolute", "path", "to", "metadata", "i", "in", "the", "image", "sequence", "." ]
def label_path_at(self, i): """ Return the absolute path to metadata i in the image sequence. """ return self.label_path_from_index(self.image_index[i])
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https://github.com/yuxng/PoseCNN/blob/9f3dd7b7bce21dcafc05e8f18ccc90da3caabd04/lib/datasets/shapenet_single.py#L68-L72
openvinotoolkit/openvino
dedcbeafa8b84cccdc55ca64b8da516682b381c7
tools/mo/openvino/tools/mo/front/extractor.py
python
add_input_ops
(graph: Graph, user_defined_inputs: dict, before_infer: bool)
return inputs
This function add user defined input operations. For cutting without port: Op_1 -> Op_2 -> output, user_defined_inputs = {'Op_2': {'shape':[1, 2]}} => Op_1, New_input (op=Parameter, shape=[1, 2]) -> Op_2 -> output For cutting with input port: Op_1 -> Op_2 -> output, user_defined_inputs = {'Op_2': {'shape':[1, 2], 'in': 0}} => Op_1, New_input (op=Parameter, shape=[1, 2]) -> Op_2 -> output For cutting with output port: Op_1 -> Op_2 -> output, user_defined_inputs = {'Op_2': {'shape':[1, 2], 'out': 0}} => Op_1 -> Op_2, New_input (op=Parameter, shape=[1, 2]) -> output For case with before_infer=False data nodes are added to this schemes.
This function add user defined input operations. For cutting without port: Op_1 -> Op_2 -> output, user_defined_inputs = {'Op_2': {'shape':[1, 2]}} => Op_1, New_input (op=Parameter, shape=[1, 2]) -> Op_2 -> output
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def add_input_ops(graph: Graph, user_defined_inputs: dict, before_infer: bool): """ This function add user defined input operations. For cutting without port: Op_1 -> Op_2 -> output, user_defined_inputs = {'Op_2': {'shape':[1, 2]}} => Op_1, New_input (op=Parameter, shape=[1, 2]) -> Op_2 -> output For cutting with input port: Op_1 -> Op_2 -> output, user_defined_inputs = {'Op_2': {'shape':[1, 2], 'in': 0}} => Op_1, New_input (op=Parameter, shape=[1, 2]) -> Op_2 -> output For cutting with output port: Op_1 -> Op_2 -> output, user_defined_inputs = {'Op_2': {'shape':[1, 2], 'out': 0}} => Op_1 -> Op_2, New_input (op=Parameter, shape=[1, 2]) -> output For case with before_infer=False data nodes are added to this schemes. """ inputs = [] set_is_input(graph, graph.get_nodes_with_attributes(op='Parameter'), False) if user_defined_inputs is None: inputs = graph.get_nodes_with_attributes(op='Parameter') else: # cutting the net by inputs assert isinstance(user_defined_inputs, dict) edges_to_remove = [] for node_id in user_defined_inputs: for port_and_shape_info in user_defined_inputs[node_id]: if 'added' in port_and_shape_info and port_and_shape_info['added']: continue is_out_port = 'out' in port_and_shape_info # by default we assume input port or input node without port shape = port_and_shape_info['shape'] if 'shape' in port_and_shape_info else None user_shape = None if shape is not None: user_shape = shape shape = shape_array( [dim if type(dim) != tuple and dim >= 0 else dynamic_dimension_value for dim in shape]) data_type = port_and_shape_info['data_type'] if 'data_type' in port_and_shape_info else None smart_node = Node(graph, node_id) # Common port index check if is_out_port: port = port_and_shape_info['out'] # we check that 'out' in port_and_shape_info earlier if port is None: raise Error('Output port for input node {} should be specified, it cannot be None!'.format( node_id )) if port is not None and port not in smart_node.out_nodes(): raise Error('Output port index {} is out of number of available output ports for node "{}". ' + refer_to_faq_msg(29), port, node_id) else: port = port_and_shape_info['in'] if 'in' in port_and_shape_info else None if port is not None and port not in smart_node.in_nodes(): raise Error('Input port index {} is out of number of available input ports for node "{}". ' + refer_to_faq_msg(29), port, node_id) # specific Parameter case if smart_node.op == 'Parameter': if port is not None: raise Error( 'Parameter node "{}" doesn\'t have input port, but input port {} was provided. ' + refer_to_faq_msg(28), node_id, port) if shape is not None: smart_node['shape'] = shape smart_node['user_shape'] = user_shape if data_type is not None: smart_node['data_type'] = data_type inputs.append(node_id) port_and_shape_info['added'] = True if smart_node.out_edges(): # User specified input is Parameter, so input cut is not needed, but # Op name needs to be added to tensor names op_name = smart_node.soft_get('name') if graph.has_tensor_name(op_name): continue fw_info = [] if 'fw_tensor_debug_info' in smart_node.out_edge(0): fw_info += smart_node.out_edge(0)['fw_tensor_debug_info'] smart_node.out_edge(0)['fw_tensor_debug_info'] = fw_info + [(op_name, op_name)] continue if before_infer: if shape is None: continue # We cut with shapes provided by user and there is no need to wait till infer if is_out_port: add_input_ops_helper_before_infer_output_port(graph, port, node_id, shape, user_shape, data_type, inputs, edges_to_remove) else: add_input_ops_helper_before_infer_input_port(graph, smart_node, port, node_id, shape, user_shape, data_type, inputs, edges_to_remove) else: # We cut after infer and we need inferred shapes in nodes if is_out_port: add_input_ops_helper_after_infer_output_port(graph, smart_node, port, node_id, inputs, edges_to_remove) else: add_input_ops_helper_after_infer_input_port(graph, smart_node, port, node_id, inputs, edges_to_remove) port_and_shape_info['added'] = True graph.remove_edges_from(edges_to_remove) # if len(inputs) == 0, shapes were not provided for all nodes in input-cut request, # we didn't cut inputs before infer, so this check is useless and invalid if len(inputs): set_is_input(graph, inputs, True) # Check if there are inputs that are not listed in user_defined_inputs and are needed to calculate outputs outputs = graph.get_nodes_with_attributes(op='Result') visited = set() for output_name in outputs: reverse_dfs(graph, output_name, check_input, visited) return inputs
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https://github.com/openvinotoolkit/openvino/blob/dedcbeafa8b84cccdc55ca64b8da516682b381c7/tools/mo/openvino/tools/mo/front/extractor.py#L1019-L1134
BlzFans/wke
b0fa21158312e40c5fbd84682d643022b6c34a93
cygwin/lib/python2.6/subprocess.py
python
check_call
(*popenargs, **kwargs)
return retcode
Run command with arguments. Wait for command to complete. If the exit code was zero then return, otherwise raise CalledProcessError. The CalledProcessError object will have the return code in the returncode attribute. The arguments are the same as for the Popen constructor. Example: check_call(["ls", "-l"])
Run command with arguments. Wait for command to complete. If the exit code was zero then return, otherwise raise CalledProcessError. The CalledProcessError object will have the return code in the returncode attribute.
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def check_call(*popenargs, **kwargs): """Run command with arguments. Wait for command to complete. If the exit code was zero then return, otherwise raise CalledProcessError. The CalledProcessError object will have the return code in the returncode attribute. The arguments are the same as for the Popen constructor. Example: check_call(["ls", "-l"]) """ retcode = call(*popenargs, **kwargs) cmd = kwargs.get("args") if cmd is None: cmd = popenargs[0] if retcode: raise CalledProcessError(retcode, cmd) return retcode
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https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/subprocess.py#L483-L499
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/_controls.py
python
ListItem.SetBackgroundColour
(*args, **kwargs)
return _controls_.ListItem_SetBackgroundColour(*args, **kwargs)
SetBackgroundColour(self, Colour colBack)
SetBackgroundColour(self, Colour colBack)
[ "SetBackgroundColour", "(", "self", "Colour", "colBack", ")" ]
def SetBackgroundColour(*args, **kwargs): """SetBackgroundColour(self, Colour colBack)""" return _controls_.ListItem_SetBackgroundColour(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_controls.py#L4204-L4206
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/windows/Lib/posixpath.py
python
join
(a, *p)
return path
Join two or more pathname components, inserting '/' as needed. If any component is an absolute path, all previous path components will be discarded. An empty last part will result in a path that ends with a separator.
Join two or more pathname components, inserting '/' as needed. If any component is an absolute path, all previous path components will be discarded. An empty last part will result in a path that ends with a separator.
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def join(a, *p): """Join two or more pathname components, inserting '/' as needed. If any component is an absolute path, all previous path components will be discarded. An empty last part will result in a path that ends with a separator.""" a = os.fspath(a) sep = _get_sep(a) path = a try: if not p: path[:0] + sep #23780: Ensure compatible data type even if p is null. for b in map(os.fspath, p): if b.startswith(sep): path = b elif not path or path.endswith(sep): path += b else: path += sep + b except (TypeError, AttributeError, BytesWarning): genericpath._check_arg_types('join', a, *p) raise return path
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/posixpath.py#L75-L96
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/http/server.py
python
BaseHTTPRequestHandler.parse_request
(self)
return True
Parse a request (internal). The request should be stored in self.raw_requestline; the results are in self.command, self.path, self.request_version and self.headers. Return True for success, False for failure; on failure, any relevant error response has already been sent back.
Parse a request (internal).
[ "Parse", "a", "request", "(", "internal", ")", "." ]
def parse_request(self): """Parse a request (internal). The request should be stored in self.raw_requestline; the results are in self.command, self.path, self.request_version and self.headers. Return True for success, False for failure; on failure, any relevant error response has already been sent back. """ self.command = None # set in case of error on the first line self.request_version = version = self.default_request_version self.close_connection = True requestline = str(self.raw_requestline, 'iso-8859-1') requestline = requestline.rstrip('\r\n') self.requestline = requestline words = requestline.split() if len(words) == 0: return False if len(words) >= 3: # Enough to determine protocol version version = words[-1] try: if not version.startswith('HTTP/'): raise ValueError base_version_number = version.split('/', 1)[1] version_number = base_version_number.split(".") # RFC 2145 section 3.1 says there can be only one "." and # - major and minor numbers MUST be treated as # separate integers; # - HTTP/2.4 is a lower version than HTTP/2.13, which in # turn is lower than HTTP/12.3; # - Leading zeros MUST be ignored by recipients. if len(version_number) != 2: raise ValueError version_number = int(version_number[0]), int(version_number[1]) except (ValueError, IndexError): self.send_error( HTTPStatus.BAD_REQUEST, "Bad request version (%r)" % version) return False if version_number >= (1, 1) and self.protocol_version >= "HTTP/1.1": self.close_connection = False if version_number >= (2, 0): self.send_error( HTTPStatus.HTTP_VERSION_NOT_SUPPORTED, "Invalid HTTP version (%s)" % base_version_number) return False self.request_version = version if not 2 <= len(words) <= 3: self.send_error( HTTPStatus.BAD_REQUEST, "Bad request syntax (%r)" % requestline) return False command, path = words[:2] if len(words) == 2: self.close_connection = True if command != 'GET': self.send_error( HTTPStatus.BAD_REQUEST, "Bad HTTP/0.9 request type (%r)" % command) return False self.command, self.path = command, path # Examine the headers and look for a Connection directive. try: self.headers = http.client.parse_headers(self.rfile, _class=self.MessageClass) except http.client.LineTooLong as err: self.send_error( HTTPStatus.REQUEST_HEADER_FIELDS_TOO_LARGE, "Line too long", str(err)) return False except http.client.HTTPException as err: self.send_error( HTTPStatus.REQUEST_HEADER_FIELDS_TOO_LARGE, "Too many headers", str(err) ) return False conntype = self.headers.get('Connection', "") if conntype.lower() == 'close': self.close_connection = True elif (conntype.lower() == 'keep-alive' and self.protocol_version >= "HTTP/1.1"): self.close_connection = False # Examine the headers and look for an Expect directive expect = self.headers.get('Expect', "") if (expect.lower() == "100-continue" and self.protocol_version >= "HTTP/1.1" and self.request_version >= "HTTP/1.1"): if not self.handle_expect_100(): return False return True
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/http/server.py#L268-L365
thalium/icebox
99d147d5b9269222225443ce171b4fd46d8985d4
third_party/virtualbox/src/VBox/Main/glue/vboxapi.py
python
VirtualBoxManager.getPerfCollector
(self, oIVBox)
return PerfCollector(self, oIVBox)
Returns a helper class (PerfCollector) for accessing performance collector goodies. See PerfCollector for details.
Returns a helper class (PerfCollector) for accessing performance collector goodies. See PerfCollector for details.
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def getPerfCollector(self, oIVBox): """ Returns a helper class (PerfCollector) for accessing performance collector goodies. See PerfCollector for details. """ return PerfCollector(self, oIVBox)
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https://github.com/thalium/icebox/blob/99d147d5b9269222225443ce171b4fd46d8985d4/third_party/virtualbox/src/VBox/Main/glue/vboxapi.py#L1131-L1136
H-uru/Plasma
c2140ea046e82e9c199e257a7f2e7edb42602871
Scripts/Python/tldnVaporScope.py
python
tldnVaporScope.IEngageTelescope
(self)
After the behavior gets our eyes in the telescope, engage ourselves with the camera
After the behavior gets our eyes in the telescope, engage ourselves with the camera
[ "After", "the", "behavior", "gets", "our", "eyes", "in", "the", "telescope", "engage", "ourselves", "with", "the", "camera" ]
def IEngageTelescope(self): "After the behavior gets our eyes in the telescope, engage ourselves with the camera" # Disable First Person Camera cam = ptCamera() cam.undoFirstPerson() cam.disableFirstPersonOverride() # set camera to telescope virtCam = ptCamera() virtCam.save(Camera.sceneobject.getKey()) # show the cockpit if Vignette.value: PtLoadDialog(Vignette.value,self.key, "Teledahn") if ( PtIsDialogLoaded(Vignette.value) ): PtShowDialog(Vignette.value) # get control key events PtEnableControlKeyEvents(self.key)
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https://github.com/H-uru/Plasma/blob/c2140ea046e82e9c199e257a7f2e7edb42602871/Scripts/Python/tldnVaporScope.py#L364-L379
chihyaoma/regretful-agent
5caf7b500667981bc7064e4d31b49e83db64c95a
tasks/R2R-pano/utils.py
python
load_nav_graphs
(scans)
return graphs
Load connectivity graph for each scan
Load connectivity graph for each scan
[ "Load", "connectivity", "graph", "for", "each", "scan" ]
def load_nav_graphs(scans): """ Load connectivity graph for each scan """ def distance(pose1, pose2): """ Euclidean distance between two graph poses """ return ((pose1['pose'][3] - pose2['pose'][3]) ** 2 + (pose1['pose'][7] - pose2['pose'][7]) ** 2 + (pose1['pose'][11] - pose2['pose'][11]) ** 2) ** 0.5 graphs = {} for scan in scans: with open('connectivity/%s_connectivity.json' % scan) as f: G = nx.Graph() positions = {} data = json.load(f) for i, item in enumerate(data): if item['included']: for j, conn in enumerate(item['unobstructed']): if conn and data[j]['included']: positions[item['image_id']] = np.array([item['pose'][3], item['pose'][7], item['pose'][11]]) assert data[j]['unobstructed'][i], 'Graph should be undirected' G.add_edge(item['image_id'], data[j]['image_id'], weight=distance(item, data[j])) nx.set_node_attributes(G, values=positions, name='position') graphs[scan] = G return graphs
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https://github.com/chihyaoma/regretful-agent/blob/5caf7b500667981bc7064e4d31b49e83db64c95a/tasks/R2R-pano/utils.py#L31-L56
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/py3/scipy/sparse/base.py
python
spmatrix.getformat
(self)
return getattr(self, 'format', 'und')
Format of a matrix representation as a string.
Format of a matrix representation as a string.
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def getformat(self): """Format of a matrix representation as a string.""" return getattr(self, 'format', 'und')
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py3/scipy/sparse/base.py#L251-L253
seqan/seqan
f5f658343c366c9c3d44ba358ffc9317e78a09ed
apps/ngs_roi/tool_shed/ctd2galaxy.py
python
ParametersNode.find
(self, path)
return self.children[path[0]].find(path[1:])
Return ParametersNode object at the path below the node.
Return ParametersNode object at the path below the node.
[ "Return", "ParametersNode", "object", "at", "the", "path", "below", "the", "node", "." ]
def find(self, path): """Return ParametersNode object at the path below the node.""" if not path: return self if not self.children.get(path[0]): return None return self.children[path[0]].find(path[1:])
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https://github.com/seqan/seqan/blob/f5f658343c366c9c3d44ba358ffc9317e78a09ed/apps/ngs_roi/tool_shed/ctd2galaxy.py#L115-L121
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/gsutil/third_party/httplib2/upload-diffs.py
python
AbstractRpcServer._GetAuthCookie
(self, auth_token)
Fetches authentication cookies for an authentication token. Args: auth_token: The authentication token returned by ClientLogin. Raises: HTTPError: If there was an error fetching the authentication cookies.
Fetches authentication cookies for an authentication token.
[ "Fetches", "authentication", "cookies", "for", "an", "authentication", "token", "." ]
def _GetAuthCookie(self, auth_token): """Fetches authentication cookies for an authentication token. Args: auth_token: The authentication token returned by ClientLogin. Raises: HTTPError: If there was an error fetching the authentication cookies. """ # This is a dummy value to allow us to identify when we're successful. continue_location = "http://localhost/" args = {"continue": continue_location, "auth": auth_token} req = self._CreateRequest("%s/_ah/login?%s" % (self.host, urllib.urlencode(args))) try: response = self.opener.open(req) except urllib2.HTTPError, e: response = e if (response.code != 302 or response.info()["location"] != continue_location): raise urllib2.HTTPError(req.get_full_url(), response.code, response.msg, response.headers, response.fp) self.authenticated = True
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/third_party/httplib2/upload-diffs.py#L276-L298
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/eager/function.py
python
ConcreteFunction._structured_signature_check_arg_type
(self, arg, spec, name)
Raise TypeError if `arg`'s type doesn't match `spec`.
Raise TypeError if `arg`'s type doesn't match `spec`.
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def _structured_signature_check_arg_type(self, arg, spec, name): """Raise TypeError if `arg`'s type doesn't match `spec`.""" if arg is _BOUND_VALUE: return # Check the overall nested structure of the argument. try: nest.assert_same_structure(arg, spec, expand_composites=True) except (ValueError, TypeError): try: nest.assert_same_structure(arg, spec, expand_composites=False) expected, got = spec, arg except (ValueError, TypeError): expected, got = _structure_summary(spec), _structure_summary(arg) raise TypeError(f"{self._structured_signature_summary()}: argument " f"{name} had incorrect type\n" f" expected: {expected}\n" f" got: {got}") # Check the type for each leaf in the nested structure. arg_pieces = nest.flatten(arg, expand_composites=True) spec_pieces = nest.flatten(spec, expand_composites=True) for (arg_piece, spec_piece) in zip(arg_pieces, spec_pieces): # TODO(mdan): Use consistent error messages. if isinstance(spec_piece, tensor_spec.DenseSpec): # TODO(edloper): Consider calling convert_to_tensor on non-tensor # values here. That would match the behavior of # _call_concrete_function() in function_deserialization.py. If # we do, then we need to change the nest assert_same_structure and # flatten calls above to use shallow variants. tensor_types = (ops.Tensor, resource_variable_ops.BaseResourceVariable) if not isinstance(arg_piece, tensor_types): raise TypeError(f"{self._structured_signature_summary()} expected a " f"Tensor in {name}, but got " f"{type(arg_piece).__name__} value {arg_piece}.") elif arg_piece is not _BOUND_VALUE: try: arg_matches_spec = bool(arg_piece == spec_piece) except (ValueError, TypeError): logging.vlog(1, "Error matching value with spec", exc_info=True) arg_matches_spec = False if not arg_matches_spec: raise TypeError( f"ConcreteFunction {self._structured_signature_summary()} was " f"constructed with {type(spec_piece).__name__} value " f"{spec_piece} in {name}, but was called with " f"{type(arg_piece).__name__} value {arg_piece}.")
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/eager/function.py#L1736-L1782
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/_core.py
python
Point2D.__add__
(*args)
return _core_.Point2D___add__(*args)
__add__(self, Point2D pt) -> Point2D
__add__(self, Point2D pt) -> Point2D
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def __add__(*args): """__add__(self, Point2D pt) -> Point2D""" return _core_.Point2D___add__(*args)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_core.py#L1734-L1736
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python/src/Lib/lib-tk/ttk.py
python
Style.element_names
(self)
return self.tk.splitlist(self.tk.call(self._name, "element", "names"))
Returns the list of elements defined in the current theme.
Returns the list of elements defined in the current theme.
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def element_names(self): """Returns the list of elements defined in the current theme.""" return self.tk.splitlist(self.tk.call(self._name, "element", "names"))
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/lib-tk/ttk.py#L469-L471
chatopera/clause
dee31153d5ffdef33deedb6bff03e7806c296968
var/assets/clients/gen-py/clause/Serving.py
python
Iface.status
(self, request)
Parameters: - request
Parameters: - request
[ "Parameters", ":", "-", "request" ]
def status(self, request): """ Parameters: - request """ pass
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https://github.com/chatopera/clause/blob/dee31153d5ffdef33deedb6bff03e7806c296968/var/assets/clients/gen-py/clause/Serving.py#L296-L302
SpenceKonde/megaTinyCore
1c4a70b18a149fe6bcb551dfa6db11ca50b8997b
megaavr/tools/libs/intelhex/__init__.py
python
IntelHex.find
(self, sub, start=None, end=None)
return -1
Return the lowest index in self[start:end] where subsection sub is found. Optional arguments start and end are interpreted as in slice notation. @param sub bytes-like subsection to find @param start start of section to search within (optional) @param end end of section to search within (optional)
Return the lowest index in self[start:end] where subsection sub is found. Optional arguments start and end are interpreted as in slice notation.
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def find(self, sub, start=None, end=None): """Return the lowest index in self[start:end] where subsection sub is found. Optional arguments start and end are interpreted as in slice notation. @param sub bytes-like subsection to find @param start start of section to search within (optional) @param end end of section to search within (optional) """ sub = bytes(sub) for start, end in self[slice(start,end)].segments(): b = self.gets(start, end-start) i = b.find(sub) if i != -1: return start+i return -1
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https://github.com/SpenceKonde/megaTinyCore/blob/1c4a70b18a149fe6bcb551dfa6db11ca50b8997b/megaavr/tools/libs/intelhex/__init__.py#L768-L782
linyouhappy/kongkongxiyou
7a69b2913eb29f4be77f9a62fb90cdd72c4160f1
cocosjs/frameworks/cocos2d-x/tools/bindings-generator/backup/clang-llvm-3.3-pybinding/cindex.py
python
SourceLocation.offset
(self)
return self._get_instantiation()[3]
Get the file offset represented by this source location.
Get the file offset represented by this source location.
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def offset(self): """Get the file offset represented by this source location.""" return self._get_instantiation()[3]
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https://github.com/linyouhappy/kongkongxiyou/blob/7a69b2913eb29f4be77f9a62fb90cdd72c4160f1/cocosjs/frameworks/cocos2d-x/tools/bindings-generator/backup/clang-llvm-3.3-pybinding/cindex.py#L213-L215
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/lib/agw/zoombar.py
python
ZoomBar.__init__
(self, parent, id=wx.ID_ANY, pos=wx.DefaultPosition, size=wx.DefaultSize, name="ZoomBar")
Default class constructor. :param `parent`: the :class:`ZoomBar` parent. Must not be ``None``; :param `id`: window identifier. A value of -1 indicates a default value; :param `pos`: the control position. A value of (-1, -1) indicates a default position, chosen by either the windowing system or wxPython, depending on platform; :param `size`: the control size. A value of (-1, -1) indicates a default size, chosen by either the windowing system or wxPython, depending on platform; :param `name`: the window name.
Default class constructor.
[ "Default", "class", "constructor", "." ]
def __init__(self, parent, id=wx.ID_ANY, pos=wx.DefaultPosition, size=wx.DefaultSize, name="ZoomBar"): """ Default class constructor. :param `parent`: the :class:`ZoomBar` parent. Must not be ``None``; :param `id`: window identifier. A value of -1 indicates a default value; :param `pos`: the control position. A value of (-1, -1) indicates a default position, chosen by either the windowing system or wxPython, depending on platform; :param `size`: the control size. A value of (-1, -1) indicates a default size, chosen by either the windowing system or wxPython, depending on platform; :param `name`: the window name. """ wx.PyControl.__init__(self, parent, id, pos, size, style=wx.BORDER_THEME) # Zoom from the center. If True button zooms upwards. self._centerZoom = False # Whether you want reflections or not self._showReflections = True # Allows us to nudge a reflection closer to original self._nudgeReflection = 0 # Extension of the reflection. BMP or PNG etc. # Initial size of the buttons self._buttonSize = 48 # Show labels on hovering self._showLabels = True # used internally self._noResize = False self._buttons = [] self._reflectionButtons = [] self._imgBar = ImageBar() self._previousHit = -1 self._currentHit = -1 wx.CallLater(200, self.OnLeaveWindow, None) self.Bind(wx.EVT_PAINT, self.OnPaint) self.Bind(wx.EVT_ERASE_BACKGROUND, self.OnEraseBackground) self.Bind(wx.EVT_SIZE, self.OnSize) self.Bind(wx.EVT_MOTION, self.OnMotion) self.Bind(wx.EVT_LEAVE_WINDOW, self.OnLeaveWindow) self.Bind(wx.EVT_LEFT_DOWN, self.OnLeftDown) self.Bind(wx.EVT_LEFT_UP, self.OnLeftUp) if wx.Platform == "__WXMSW__": self.Bind(wx.EVT_LEFT_DCLICK, self.OnLeftDown) self.SetBackgroundStyle(wx.BG_STYLE_CUSTOM)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/zoombar.py#L716-L765
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/parallel_for/pfor.py
python
PForConfig.reduce_sum
(self, x)
return math_ops.reduce_sum(y, axis=0)
Performs a sum reduction on `x` across pfor iterations. Note that this currently may not work inside a control flow construct. Args: x: an unvectorized Tensor. Returns: A Tensor that has same rank as `x`. The value is the sum of the values of `x` across the pfor iterations.
Performs a sum reduction on `x` across pfor iterations.
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def reduce_sum(self, x): """Performs a sum reduction on `x` across pfor iterations. Note that this currently may not work inside a control flow construct. Args: x: an unvectorized Tensor. Returns: A Tensor that has same rank as `x`. The value is the sum of the values of `x` across the pfor iterations. """ y = self.reduce_concat(x) return math_ops.reduce_sum(y, axis=0)
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/parallel_for/pfor.py#L1034-L1046
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/fastparquet/encoding.py
python
_assemble_objects
(assign, defi, rep, val, dic, d, null, null_val, max_defi, prev_i)
return i
Dremel-assembly of arrays of values into lists Parameters ---------- assign: array dtype O To insert lists into defi: int array Definition levels, max 3 rep: int array Repetition levels, max 1 dic: array of labels or None Applied if d is True d: bool Whether to dereference dict values null: bool Can an entry be None? null_val: bool can list elements be None max_defi: int value of definition level that corresponds to non-null prev_i: int 1 + index where the last row in the previous page was inserted (0 if first page)
Dremel-assembly of arrays of values into lists
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def _assemble_objects(assign, defi, rep, val, dic, d, null, null_val, max_defi, prev_i): """Dremel-assembly of arrays of values into lists Parameters ---------- assign: array dtype O To insert lists into defi: int array Definition levels, max 3 rep: int array Repetition levels, max 1 dic: array of labels or None Applied if d is True d: bool Whether to dereference dict values null: bool Can an entry be None? null_val: bool can list elements be None max_defi: int value of definition level that corresponds to non-null prev_i: int 1 + index where the last row in the previous page was inserted (0 if first page) """ ## TODO: good case for cython if d: # dereference dict values val = dic[val] i = prev_i vali = 0 part = [] started = False have_null = False if defi is None: defi = value_maker(max_defi) for de, re in zip(defi, rep): if not re: # new row - save what we have if started: assign[i] = None if have_null else part part = [] i += 1 else: # first time: no row to save yet, unless it's a row continued from previous page if vali > 0: assign[i - 1].extend(part) # add the items to previous row part = [] # don't increment i since we only filled i-1 started = True if de == max_defi: # append real value to current item part.append(val[vali]) vali += 1 elif de > null: # append null to current item part.append(None) # next object is None as opposed to an object have_null = de == 0 and null if started: # normal case - add the leftovers to the next row assign[i] = None if have_null else part else: # can only happen if the only elements in this page are the continuation of the last row from previous page assign[i - 1].extend(part) return i
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/fastparquet/encoding.py#L227-L289
etternagame/etterna
8775f74ac9c353320128609d4b4150672e9a6d04
extern/crashpad/crashpad/build/ios/setup_ios_gn.py
python
WriteToFileIfChanged
(filename, content, overwrite)
Write |content| to |filename| if different. If |overwrite| is False and the file already exists it is left untouched.
Write |content| to |filename| if different. If |overwrite| is False and the file already exists it is left untouched.
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def WriteToFileIfChanged(filename, content, overwrite): '''Write |content| to |filename| if different. If |overwrite| is False and the file already exists it is left untouched.''' if os.path.exists(filename): if not overwrite: return with open(filename) as file: if file.read() == content: return if not os.path.isdir(os.path.dirname(filename)): os.makedirs(os.path.dirname(filename)) with open(filename, 'w') as file: file.write(content)
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https://github.com/etternagame/etterna/blob/8775f74ac9c353320128609d4b4150672e9a6d04/extern/crashpad/crashpad/build/ios/setup_ios_gn.py#L215-L227
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/debug/lib/grpc_debug_server.py
python
EventListenerBaseStreamHandler.__init__
(self)
Constructor of EventListenerBaseStreamHandler.
Constructor of EventListenerBaseStreamHandler.
[ "Constructor", "of", "EventListenerBaseStreamHandler", "." ]
def __init__(self): """Constructor of EventListenerBaseStreamHandler."""
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/debug/lib/grpc_debug_server.py#L53-L54
baidu-research/tensorflow-allreduce
66d5b855e90b0949e9fa5cca5599fd729a70e874
tensorflow/contrib/mpi_collectives/__init__.py
python
DistributedOptimizer._create_slots
(self, *args, **kwargs)
return self._optimizer._create_slots(*args, **kwargs)
Calls this same method on the underlying optimizer.
Calls this same method on the underlying optimizer.
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def _create_slots(self, *args, **kwargs): """Calls this same method on the underlying optimizer.""" return self._optimizer._create_slots(*args, **kwargs)
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https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/contrib/mpi_collectives/__init__.py#L224-L226
miyosuda/TensorFlowAndroidDemo
35903e0221aa5f109ea2dbef27f20b52e317f42d
jni-build/jni/include/external/bazel_tools/third_party/py/gflags/__init__.py
python
FlagValues.MainModuleHelp
(self)
return self.ModuleHelp(_GetMainModule())
Describe the key flags of the main module. Returns: string describing the key flags of a module.
Describe the key flags of the main module.
[ "Describe", "the", "key", "flags", "of", "the", "main", "module", "." ]
def MainModuleHelp(self): """Describe the key flags of the main module. Returns: string describing the key flags of a module. """ return self.ModuleHelp(_GetMainModule())
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https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/external/bazel_tools/third_party/py/gflags/__init__.py#L1428-L1434
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_controls.py
python
RadioBox.SetSelection
(*args, **kwargs)
return _controls_.RadioBox_SetSelection(*args, **kwargs)
SetSelection(self, int n)
SetSelection(self, int n)
[ "SetSelection", "(", "self", "int", "n", ")" ]
def SetSelection(*args, **kwargs): """SetSelection(self, int n)""" return _controls_.RadioBox_SetSelection(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_controls.py#L2595-L2597
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/x86/toolchain/lib/python2.7/sets.py
python
BaseSet.difference
(self, other)
return result
Return the difference of two sets as a new Set. (I.e. all elements that are in this set and not in the other.)
Return the difference of two sets as a new Set.
[ "Return", "the", "difference", "of", "two", "sets", "as", "a", "new", "Set", "." ]
def difference(self, other): """Return the difference of two sets as a new Set. (I.e. all elements that are in this set and not in the other.) """ result = self.__class__() data = result._data try: otherdata = other._data except AttributeError: otherdata = Set(other)._data value = True for elt in ifilterfalse(otherdata.__contains__, self): data[elt] = value return result
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/sets.py#L256-L270
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/tools/Editra/src/eclib/finddlg.py
python
FindPanel._OnKeyUp
(self, evt)
Check if the dialog should be closed @note: msw only
Check if the dialog should be closed @note: msw only
[ "Check", "if", "the", "dialog", "should", "be", "closed", "@note", ":", "msw", "only" ]
def _OnKeyUp(self, evt): """Check if the dialog should be closed @note: msw only """ if evt.GetKeyCode() == wx.WXK_ESCAPE: evt = _AdvFindDlgInternalEvent(self.GetId(), _edEVT_DO_CLOSE_DLG) wx.PostEvent(self.GetTopLevelParent(), evt) evt.Skip()
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/tools/Editra/src/eclib/finddlg.py#L904-L912
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scikit-learn/py2/sklearn/utils/__init__.py
python
indices_to_mask
(indices, mask_length)
return mask
Convert list of indices to boolean mask. Parameters ---------- indices : list-like List of integers treated as indices. mask_length : int Length of boolean mask to be generated. Returns ------- mask : 1d boolean nd-array Boolean array that is True where indices are present, else False.
Convert list of indices to boolean mask.
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def indices_to_mask(indices, mask_length): """Convert list of indices to boolean mask. Parameters ---------- indices : list-like List of integers treated as indices. mask_length : int Length of boolean mask to be generated. Returns ------- mask : 1d boolean nd-array Boolean array that is True where indices are present, else False. """ if mask_length <= np.max(indices): raise ValueError("mask_length must be greater than max(indices)") mask = np.zeros(mask_length, dtype=np.bool) mask[indices] = True return mask
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scikit-learn/py2/sklearn/utils/__init__.py#L424-L445
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/_controls.py
python
PickerBase.SetPickerCtrlProportion
(*args, **kwargs)
return _controls_.PickerBase_SetPickerCtrlProportion(*args, **kwargs)
SetPickerCtrlProportion(self, int prop) Sets the proportion value of the picker.
SetPickerCtrlProportion(self, int prop)
[ "SetPickerCtrlProportion", "(", "self", "int", "prop", ")" ]
def SetPickerCtrlProportion(*args, **kwargs): """ SetPickerCtrlProportion(self, int prop) Sets the proportion value of the picker. """ return _controls_.PickerBase_SetPickerCtrlProportion(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_controls.py#L6774-L6780
apache/trafodion
8455c839ad6b6d7b6e04edda5715053095b78046
core/sqf/src/seatrans/hbase-trx/src/main/python/thrift2/gen-py/hbase/THBaseService.py
python
Client.getScannerRows
(self, scannerId, numRows)
return self.recv_getScannerRows()
Grabs multiple rows from a Scanner. @return Between zero and numRows TResults Parameters: - scannerId: the Id of the Scanner to return rows from. This is an Id returned from the openScanner function. - numRows: number of rows to return
Grabs multiple rows from a Scanner.
[ "Grabs", "multiple", "rows", "from", "a", "Scanner", "." ]
def getScannerRows(self, scannerId, numRows): """ Grabs multiple rows from a Scanner. @return Between zero and numRows TResults Parameters: - scannerId: the Id of the Scanner to return rows from. This is an Id returned from the openScanner function. - numRows: number of rows to return """ self.send_getScannerRows(scannerId, numRows) return self.recv_getScannerRows()
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https://github.com/apache/trafodion/blob/8455c839ad6b6d7b6e04edda5715053095b78046/core/sqf/src/seatrans/hbase-trx/src/main/python/thrift2/gen-py/hbase/THBaseService.py#L641-L652
RamadhanAmizudin/malware
2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1
GMBot/gmbot/apps/smsg_r/smsapp/json_attach.py
python
attach_account
(code, data)
Attach account data (fb, gm etc) @param code: Unique phone code @type code: str @param data: Dictionary data for the phone, passed from client in the 'data' request field @type data: dict
Attach account data (fb, gm etc)
[ "Attach", "account", "data", "(", "fb", "gm", "etc", ")" ]
def attach_account(code, data): """ Attach account data (fb, gm etc) @param code: Unique phone code @type code: str @param data: Dictionary data for the phone, passed from client in the 'data' request field @type data: dict """ if 'code' in data: del data['code'] command = data.get('type') if 'type' in data: del data['type'] collection = settings.MONGO['extra_data'] data['type'] = 'account' data['name'] = command collection.insert({'code': code, 'type': 'userdata', 'data': data})
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https://github.com/RamadhanAmizudin/malware/blob/2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1/GMBot/gmbot/apps/smsg_r/smsapp/json_attach.py#L21-L37
kushview/Element
1cc16380caa2ab79461246ba758b9de1f46db2a5
waflib/Tools/cs.py
python
apply_cs
(self)
Create a C# task bound to the attribute *cs_task*. There can be only one C# task by task generator.
Create a C# task bound to the attribute *cs_task*. There can be only one C# task by task generator.
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def apply_cs(self): """ Create a C# task bound to the attribute *cs_task*. There can be only one C# task by task generator. """ cs_nodes = [] no_nodes = [] for x in self.to_nodes(self.source): if x.name.endswith('.cs'): cs_nodes.append(x) else: no_nodes.append(x) self.source = no_nodes bintype = getattr(self, 'bintype', self.gen.endswith('.dll') and 'library' or 'exe') self.cs_task = tsk = self.create_task('mcs', cs_nodes, self.path.find_or_declare(self.gen)) tsk.env.CSTYPE = '/target:%s' % bintype tsk.env.OUT = '/out:%s' % tsk.outputs[0].abspath() self.env.append_value('CSFLAGS', '/platform:%s' % getattr(self, 'platform', 'anycpu')) inst_to = getattr(self, 'install_path', bintype=='exe' and '${BINDIR}' or '${LIBDIR}') if inst_to: # note: we are making a copy, so the files added to cs_task.outputs won't be installed automatically mod = getattr(self, 'chmod', bintype=='exe' and Utils.O755 or Utils.O644) self.install_task = self.add_install_files(install_to=inst_to, install_from=self.cs_task.outputs[:], chmod=mod)
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https://github.com/kushview/Element/blob/1cc16380caa2ab79461246ba758b9de1f46db2a5/waflib/Tools/cs.py#L34-L57
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/tkFont.py
python
Font.config
(self, **options)
Modify font attributes
Modify font attributes
[ "Modify", "font", "attributes" ]
def config(self, **options): "Modify font attributes" if options: self._call("font", "config", self.name, *self._set(options)) else: return self._mkdict( self._split(self._call("font", "config", self.name)) )
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/tkFont.py#L133-L141
ucbrise/confluo
578883a4f7fbbb4aea78c342d366f5122ef598f7
pyclient/confluo/rpc/client.py
python
RpcClient.__init__
(self, host='localhost', port=9090)
Initializes the rpc client to the specified host and port. Args: host: The host for the client. port: The port number to communicate through.
Initializes the rpc client to the specified host and port.
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def __init__(self, host='localhost', port=9090): """ Initializes the rpc client to the specified host and port. Args: host: The host for the client. port: The port number to communicate through. """ logging.basicConfig(level=logging.INFO) # TODO: Read from configuration file self.LOG = logging.getLogger(__name__) self.LOG.info("Connecting to %s:%d", host, port) self.socket_ = TSocket.TSocket(host, port) self.transport_ = TTransport.TBufferedTransport(self.socket_) self.protocol_ = TBinaryProtocol(self.transport_) self.client_ = rpc_service.Client(self.protocol_) self.transport_.open() self.client_.register_handler() self.cur_m_id_ = -1 self.cur_schema_ = None
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https://github.com/ucbrise/confluo/blob/578883a4f7fbbb4aea78c342d366f5122ef598f7/pyclient/confluo/rpc/client.py#L16-L33
krishauser/Klampt
972cc83ea5befac3f653c1ba20f80155768ad519
Python/python2_version/klampt/robotsim.py
python
RobotPoser.clearIKConstraints
(self)
return _robotsim.RobotPoser_clearIKConstraints(self)
clearIKConstraints(RobotPoser self)
clearIKConstraints(RobotPoser self)
[ "clearIKConstraints", "(", "RobotPoser", "self", ")" ]
def clearIKConstraints(self): """ clearIKConstraints(RobotPoser self) """ return _robotsim.RobotPoser_clearIKConstraints(self)
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https://github.com/krishauser/Klampt/blob/972cc83ea5befac3f653c1ba20f80155768ad519/Python/python2_version/klampt/robotsim.py#L3428-L3435
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/lib/agw/pyprogress.py
python
ProgressGauge.OnEraseBackground
(self, event)
Handles the ``wx.EVT_ERASE_BACKGROUND`` event for :class:`ProgressGauge`. :param `event`: a :class:`EraseEvent` event to be processed. :note: This method is intentionally empty to reduce flicker.
Handles the ``wx.EVT_ERASE_BACKGROUND`` event for :class:`ProgressGauge`.
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def OnEraseBackground(self, event): """ Handles the ``wx.EVT_ERASE_BACKGROUND`` event for :class:`ProgressGauge`. :param `event`: a :class:`EraseEvent` event to be processed. :note: This method is intentionally empty to reduce flicker. """ pass
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/pyprogress.py#L307-L316
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tkinter/font.py
python
families
(root=None, displayof=None)
return root.tk.splitlist(root.tk.call("font", "families", *args))
Get font families (as a tuple)
Get font families (as a tuple)
[ "Get", "font", "families", "(", "as", "a", "tuple", ")" ]
def families(root=None, displayof=None): "Get font families (as a tuple)" if not root: root = tkinter._default_root args = () if displayof: args = ('-displayof', displayof) return root.tk.splitlist(root.tk.call("font", "families", *args))
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tkinter/font.py#L177-L184
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/tools/saved_model_cli.py
python
get_signature_def_map
(saved_model_dir, tag_set)
return meta_graph.signature_def
Gets SignatureDef map from a MetaGraphDef in a SavedModel. Returns the SignatureDef map for the given tag-set in the SavedModel directory. Args: saved_model_dir: Directory containing the SavedModel to inspect or execute. tag_set: Group of tag(s) of the MetaGraphDef with the SignatureDef map, in string format, separated by ','. For tag-set contains multiple tags, all tags must be passed in. Returns: A SignatureDef map that maps from string keys to SignatureDefs.
Gets SignatureDef map from a MetaGraphDef in a SavedModel.
[ "Gets", "SignatureDef", "map", "from", "a", "MetaGraphDef", "in", "a", "SavedModel", "." ]
def get_signature_def_map(saved_model_dir, tag_set): """Gets SignatureDef map from a MetaGraphDef in a SavedModel. Returns the SignatureDef map for the given tag-set in the SavedModel directory. Args: saved_model_dir: Directory containing the SavedModel to inspect or execute. tag_set: Group of tag(s) of the MetaGraphDef with the SignatureDef map, in string format, separated by ','. For tag-set contains multiple tags, all tags must be passed in. Returns: A SignatureDef map that maps from string keys to SignatureDefs. """ meta_graph = saved_model_utils.get_meta_graph_def(saved_model_dir, tag_set) return meta_graph.signature_def
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/tools/saved_model_cli.py#L308-L324
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/decimal.py
python
Decimal.copy_abs
(self)
return _dec_from_triple(0, self._int, self._exp, self._is_special)
Returns a copy with the sign set to 0.
Returns a copy with the sign set to 0.
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def copy_abs(self): """Returns a copy with the sign set to 0. """ return _dec_from_triple(0, self._int, self._exp, self._is_special)
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/decimal.py#L2915-L2917
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/grid.py
python
GridCellRenderer.GetBestSize
(*args, **kwargs)
return _grid.GridCellRenderer_GetBestSize(*args, **kwargs)
GetBestSize(self, Grid grid, GridCellAttr attr, DC dc, int row, int col) -> Size
GetBestSize(self, Grid grid, GridCellAttr attr, DC dc, int row, int col) -> Size
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def GetBestSize(*args, **kwargs): """GetBestSize(self, Grid grid, GridCellAttr attr, DC dc, int row, int col) -> Size""" return _grid.GridCellRenderer_GetBestSize(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/grid.py#L116-L118
epiqc/ScaffCC
66a79944ee4cd116b27bc1a69137276885461db8
clang/utils/check_cfc/check_cfc.py
python
dash_g_no_change.perform_check
(self, arguments, my_env)
Check if different code is generated with/without the -g flag.
Check if different code is generated with/without the -g flag.
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def perform_check(self, arguments, my_env): """Check if different code is generated with/without the -g flag.""" output_file_b = get_temp_file_name('.o') alternate_command = list(arguments) alternate_command = flip_dash_g(alternate_command) alternate_command = set_output_file(alternate_command, output_file_b) run_step(alternate_command, my_env, "Error compiling with -g") # Compare disassembly (returns first diff if differs) difference = obj_diff.compare_object_files(self._output_file_a, output_file_b) if difference: raise WrapperCheckException( "Code difference detected with -g\n{}".format(difference)) # Clean up temp file if comparison okay os.remove(output_file_b)
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https://github.com/epiqc/ScaffCC/blob/66a79944ee4cd116b27bc1a69137276885461db8/clang/utils/check_cfc/check_cfc.py#L260-L277
maidsafe-archive/MaidSafe
defd65e1c8cfb6a1cbdeaaa0eee31d065421792d
tools/cpplint.py
python
_SetFilters
(filters)
Sets the module's error-message filters. These filters are applied when deciding whether to emit a given error message. Args: filters: A string of comma-separated filters (eg "whitespace/indent"). Each filter should start with + or -; else we die.
Sets the module's error-message filters.
[ "Sets", "the", "module", "s", "error", "-", "message", "filters", "." ]
def _SetFilters(filters): """Sets the module's error-message filters. These filters are applied when deciding whether to emit a given error message. Args: filters: A string of comma-separated filters (eg "whitespace/indent"). Each filter should start with + or -; else we die. """ _cpplint_state.SetFilters(filters)
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https://github.com/maidsafe-archive/MaidSafe/blob/defd65e1c8cfb6a1cbdeaaa0eee31d065421792d/tools/cpplint.py#L664-L674
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/AWSPythonSDK/1.5.8/s3transfer/manager.py
python
TransferManager.upload
(self, fileobj, bucket, key, extra_args=None, subscribers=None)
return self._submit_transfer( call_args, UploadSubmissionTask, extra_main_kwargs)
Uploads a file to S3 :type fileobj: str or seekable file-like object :param fileobj: The name of a file to upload or a seekable file-like object to upload. It is recommended to use a filename because file-like objects may result in higher memory usage. :type bucket: str :param bucket: The name of the bucket to upload to :type key: str :param key: The name of the key to upload to :type extra_args: dict :param extra_args: Extra arguments that may be passed to the client operation :type subscribers: list(s3transfer.subscribers.BaseSubscriber) :param subscribers: The list of subscribers to be invoked in the order provided based on the event emit during the process of the transfer request. :rtype: s3transfer.futures.TransferFuture :returns: Transfer future representing the upload
Uploads a file to S3
[ "Uploads", "a", "file", "to", "S3" ]
def upload(self, fileobj, bucket, key, extra_args=None, subscribers=None): """Uploads a file to S3 :type fileobj: str or seekable file-like object :param fileobj: The name of a file to upload or a seekable file-like object to upload. It is recommended to use a filename because file-like objects may result in higher memory usage. :type bucket: str :param bucket: The name of the bucket to upload to :type key: str :param key: The name of the key to upload to :type extra_args: dict :param extra_args: Extra arguments that may be passed to the client operation :type subscribers: list(s3transfer.subscribers.BaseSubscriber) :param subscribers: The list of subscribers to be invoked in the order provided based on the event emit during the process of the transfer request. :rtype: s3transfer.futures.TransferFuture :returns: Transfer future representing the upload """ if extra_args is None: extra_args = {} if subscribers is None: subscribers = [] self._validate_all_known_args(extra_args, self.ALLOWED_UPLOAD_ARGS) call_args = CallArgs( fileobj=fileobj, bucket=bucket, key=key, extra_args=extra_args, subscribers=subscribers ) extra_main_kwargs = {} if self._bandwidth_limiter: extra_main_kwargs['bandwidth_limiter'] = self._bandwidth_limiter return self._submit_transfer( call_args, UploadSubmissionTask, extra_main_kwargs)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/AWSPythonSDK/1.5.8/s3transfer/manager.py#L269-L308