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bigartm/bigartm
47e37f982de87aa67bfd475ff1f39da696b181b3
utils/cpplint.py
python
_BackupFilters
()
Saves the current filter list to backup storage.
Saves the current filter list to backup storage.
[ "Saves", "the", "current", "filter", "list", "to", "backup", "storage", "." ]
def _BackupFilters(): """ Saves the current filter list to backup storage.""" _cpplint_state.BackupFilters()
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https://github.com/bigartm/bigartm/blob/47e37f982de87aa67bfd475ff1f39da696b181b3/utils/cpplint.py#L905-L907
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/lib/masked/numctrl.py
python
NumCtrl.SetMax
(self, max=None)
return bRet
Sets the maximum value of the control. If a value of None is provided, then the control will have no explicit maximum value. If the value specified is less than the current minimum value, then the function returns False and the maximum will not change from its current setting. On success, the function returns True. If successful and the current value is greater than the new upper bound, if the control is limited the value will be automatically adjusted to this maximum value; if not limited, the value in the control will be colored as invalid. If max > the max value allowed by the width of the control, the function will return False, and the max will not be set.
Sets the maximum value of the control. If a value of None is provided, then the control will have no explicit maximum value. If the value specified is less than the current minimum value, then the function returns False and the maximum will not change from its current setting. On success, the function returns True.
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def SetMax(self, max=None): """ Sets the maximum value of the control. If a value of None is provided, then the control will have no explicit maximum value. If the value specified is less than the current minimum value, then the function returns False and the maximum will not change from its current setting. On success, the function returns True. If successful and the current value is greater than the new upper bound, if the control is limited the value will be automatically adjusted to this maximum value; if not limited, the value in the control will be colored as invalid. If max > the max value allowed by the width of the control, the function will return False, and the max will not be set. """ if( self._min is None or max is None or (self._min is not None and self._min <= max) ): try: self.SetParameters(max=max) bRet = True except ValueError: bRet = False else: bRet = False return bRet
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/masked/numctrl.py#L1350-L1377
HackWebRTC/webrtc
7abfc990c00ab35090fff285fcf635d1d7892433
rtc_tools/compare_videos.py
python
_RunFrameAnalyzer
(options, yuv_directory=None)
return frame_analyzer.returncode
Run frame analyzer to compare the videos and print output.
Run frame analyzer to compare the videos and print output.
[ "Run", "frame", "analyzer", "to", "compare", "the", "videos", "and", "print", "output", "." ]
def _RunFrameAnalyzer(options, yuv_directory=None): """Run frame analyzer to compare the videos and print output.""" cmd = [ options.frame_analyzer, '--label=%s' % options.label, '--reference_file=%s' % options.ref_video, '--test_file=%s' % options.test_video, '--width=%d' % options.yuv_frame_width, '--height=%d' % options.yuv_frame_height, ] if options.chartjson_result_file: cmd.append('--chartjson_result_file=%s' % options.chartjson_result_file) if options.aligned_output_file: cmd.append('--aligned_output_file=%s' % options.aligned_output_file) if yuv_directory: cmd.append('--yuv_directory=%s' % yuv_directory) frame_analyzer = subprocess.Popen(cmd, stdin=_DevNull(), stdout=sys.stdout, stderr=sys.stderr) frame_analyzer.wait() if frame_analyzer.returncode != 0: print('Failed to run frame analyzer.') return frame_analyzer.returncode
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https://github.com/HackWebRTC/webrtc/blob/7abfc990c00ab35090fff285fcf635d1d7892433/rtc_tools/compare_videos.py#L88-L109
mingchen/protobuf-ios
0958df34558cd54cb7b6e6ca5c8855bf3d475046
compiler/python/google/protobuf/service.py
python
RpcController.StartCancel
(self)
Initiate cancellation. Advises the RPC system that the caller desires that the RPC call be canceled. The RPC system may cancel it immediately, may wait awhile and then cancel it, or may not even cancel the call at all. If the call is canceled, the "done" callback will still be called and the RpcController will indicate that the call failed at that time.
Initiate cancellation.
[ "Initiate", "cancellation", "." ]
def StartCancel(self): """Initiate cancellation. Advises the RPC system that the caller desires that the RPC call be canceled. The RPC system may cancel it immediately, may wait awhile and then cancel it, or may not even cancel the call at all. If the call is canceled, the "done" callback will still be called and the RpcController will indicate that the call failed at that time. """ raise NotImplementedError
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https://github.com/mingchen/protobuf-ios/blob/0958df34558cd54cb7b6e6ca5c8855bf3d475046/compiler/python/google/protobuf/service.py#L150-L159
Cantera/cantera
0119484b261967ccb55a0066c020599cacc312e4
site_scons/buildutils.py
python
Option._build_description
(self, backticks: bool = True, indent: int = 3)
return f"{'':<{indent}}{description}\n"
Assemble description block (help text)
Assemble description block (help text)
[ "Assemble", "description", "block", "(", "help", "text", ")" ]
def _build_description(self, backticks: bool = True, indent: int = 3) -> str: """Assemble description block (help text)""" if not backticks: # Help text, wrapped and indented self.set_wrapper_indent(indent) out = self.wrapper.wrap(re.sub(r"\s+", " ", self.description)) return "\n".join(out) + "\n" # assemble description linebreak = "\n" + " " * indent description = linebreak.join(self.description.split("\n")) pat = r'"([a-zA-Z0-9\-\+\*$_.,: =/\'\\]+)"' double_quoted = [] for item in re.findall(pat, description): # enclose double-quoted strings in '``' found = f'"{item}"' double_quoted += [found] replacement = f"``{found}``" description = description.replace(found, replacement) pat = r"\'([a-zA-Z0-9\-\+\*$_.,:=/\\]+)\'" for item in re.findall(pat, description): # replace "'" for single-quoted words by '``'; do not replace "'" when # whitespace is enclosed or if word is part of double-quoted string if any([item in dq for dq in double_quoted]): continue found = f"'{item}'" replacement = found.replace("'", "``") description = description.replace(found, replacement) pat = r"\*([^\*]+)" asterisks = re.findall(pat, description) if len(asterisks) == 1: # catch unbalanced '*', for example in '*nix' found = f"*{asterisks[0]}" replacement = f"\{found}" description = description.replace(found, replacement) return f"{'':<{indent}}{description}\n"
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https://github.com/Cantera/cantera/blob/0119484b261967ccb55a0066c020599cacc312e4/site_scons/buildutils.py#L141-L178
google/or-tools
2cb85b4eead4c38e1c54b48044f92087cf165bce
examples/python/cvrptw_plot.py
python
Customers.return_dem_callback
(self)
return dem_return
Return a callback function that gives the demands. Returns: function: dem_return(a) A function that takes the 'from' node index and returns the distance in km.
Return a callback function that gives the demands.
[ "Return", "a", "callback", "function", "that", "gives", "the", "demands", "." ]
def return_dem_callback(self): """ Return a callback function that gives the demands. Returns: function: dem_return(a) A function that takes the 'from' node index and returns the distance in km. """ def dem_return(from_index): # Convert from routing variable Index to distance matrix NodeIndex. from_node = self.manager.IndexToNode(from_index) return (self.customers[from_node].demand) return dem_return
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https://github.com/google/or-tools/blob/2cb85b4eead4c38e1c54b48044f92087cf165bce/examples/python/cvrptw_plot.py#L285-L299
ChromiumWebApps/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
third_party/jinja2/loaders.py
python
BaseLoader.load
(self, environment, name, globals=None)
return environment.template_class.from_code(environment, code, globals, uptodate)
Loads a template. This method looks up the template in the cache or loads one by calling :meth:`get_source`. Subclasses should not override this method as loaders working on collections of other loaders (such as :class:`PrefixLoader` or :class:`ChoiceLoader`) will not call this method but `get_source` directly.
Loads a template. This method looks up the template in the cache or loads one by calling :meth:`get_source`. Subclasses should not override this method as loaders working on collections of other loaders (such as :class:`PrefixLoader` or :class:`ChoiceLoader`) will not call this method but `get_source` directly.
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def load(self, environment, name, globals=None): """Loads a template. This method looks up the template in the cache or loads one by calling :meth:`get_source`. Subclasses should not override this method as loaders working on collections of other loaders (such as :class:`PrefixLoader` or :class:`ChoiceLoader`) will not call this method but `get_source` directly. """ code = None if globals is None: globals = {} # first we try to get the source for this template together # with the filename and the uptodate function. source, filename, uptodate = self.get_source(environment, name) # try to load the code from the bytecode cache if there is a # bytecode cache configured. bcc = environment.bytecode_cache if bcc is not None: bucket = bcc.get_bucket(environment, name, filename, source) code = bucket.code # if we don't have code so far (not cached, no longer up to # date) etc. we compile the template if code is None: code = environment.compile(source, name, filename) # if the bytecode cache is available and the bucket doesn't # have a code so far, we give the bucket the new code and put # it back to the bytecode cache. if bcc is not None and bucket.code is None: bucket.code = code bcc.set_bucket(bucket) return environment.template_class.from_code(environment, code, globals, uptodate)
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/third_party/jinja2/loaders.py#L100-L135
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/py2/scipy/stats/_multivariate.py
python
ortho_group_gen.rvs
(self, dim, size=1, random_state=None)
return H
Draw random samples from O(N). Parameters ---------- dim : integer Dimension of rotation space (N). size : integer, optional Number of samples to draw (default 1). Returns ------- rvs : ndarray or scalar Random size N-dimensional matrices, dimension (size, dim, dim)
Draw random samples from O(N).
[ "Draw", "random", "samples", "from", "O", "(", "N", ")", "." ]
def rvs(self, dim, size=1, random_state=None): """ Draw random samples from O(N). Parameters ---------- dim : integer Dimension of rotation space (N). size : integer, optional Number of samples to draw (default 1). Returns ------- rvs : ndarray or scalar Random size N-dimensional matrices, dimension (size, dim, dim) """ random_state = self._get_random_state(random_state) size = int(size) if size > 1: return np.array([self.rvs(dim, size=1, random_state=random_state) for i in range(size)]) dim = self._process_parameters(dim) H = np.eye(dim) for n in range(dim): x = random_state.normal(size=(dim-n,)) # random sign, 50/50, but chosen carefully to avoid roundoff error D = np.sign(x[0]) if x[0] != 0 else 1 x[0] += D*np.sqrt((x*x).sum()) # Householder transformation Hx = -D*(np.eye(dim-n) - 2.*np.outer(x, x)/(x*x).sum()) mat = np.eye(dim) mat[n:, n:] = Hx H = np.dot(H, mat) return H
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py2/scipy/stats/_multivariate.py#L3501-L3538
miyosuda/TensorFlowAndroidMNIST
7b5a4603d2780a8a2834575706e9001977524007
jni-build/jni/include/external/bazel_tools/third_party/py/gflags/__init__.py
python
FlagValues.__GetFlagFileLines
(self, filename, parsed_file_list)
return flag_line_list
Returns the useful (!=comments, etc) lines from a file with flags. Args: filename: A string, the name of the flag file. parsed_file_list: A list of the names of the files we have already read. MUTATED BY THIS FUNCTION. Returns: List of strings. See the note below. NOTE(springer): This function checks for a nested --flagfile=<foo> tag and handles the lower file recursively. It returns a list of all the lines that _could_ contain command flags. This is EVERYTHING except whitespace lines and comments (lines starting with '#' or '//').
Returns the useful (!=comments, etc) lines from a file with flags.
[ "Returns", "the", "useful", "(", "!", "=", "comments", "etc", ")", "lines", "from", "a", "file", "with", "flags", "." ]
def __GetFlagFileLines(self, filename, parsed_file_list): """Returns the useful (!=comments, etc) lines from a file with flags. Args: filename: A string, the name of the flag file. parsed_file_list: A list of the names of the files we have already read. MUTATED BY THIS FUNCTION. Returns: List of strings. See the note below. NOTE(springer): This function checks for a nested --flagfile=<foo> tag and handles the lower file recursively. It returns a list of all the lines that _could_ contain command flags. This is EVERYTHING except whitespace lines and comments (lines starting with '#' or '//'). """ line_list = [] # All line from flagfile. flag_line_list = [] # Subset of lines w/o comments, blanks, flagfile= tags. try: file_obj = open(filename, 'r') except IOError, e_msg: raise CantOpenFlagFileError('ERROR:: Unable to open flagfile: %s' % e_msg) line_list = file_obj.readlines() file_obj.close() parsed_file_list.append(filename) # This is where we check each line in the file we just read. for line in line_list: if line.isspace(): pass # Checks for comment (a line that starts with '#'). elif line.startswith('#') or line.startswith('//'): pass # Checks for a nested "--flagfile=<bar>" flag in the current file. # If we find one, recursively parse down into that file. elif self.__IsFlagFileDirective(line): sub_filename = self.ExtractFilename(line) # We do a little safety check for reparsing a file we've already done. if not sub_filename in parsed_file_list: included_flags = self.__GetFlagFileLines(sub_filename, parsed_file_list) flag_line_list.extend(included_flags) else: # Case of hitting a circularly included file. sys.stderr.write('Warning: Hit circular flagfile dependency: %s\n' % (sub_filename,)) else: # Any line that's not a comment or a nested flagfile should get # copied into 2nd position. This leaves earlier arguments # further back in the list, thus giving them higher priority. flag_line_list.append(line.strip()) return flag_line_list
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https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/external/bazel_tools/third_party/py/gflags/__init__.py#L1552-L1604
sdhash/sdhash
b9eff63e4e5867e910f41fd69032bbb1c94a2a5e
sdhash-ui/cherrypy/wsgiserver/wsgiserver3.py
python
WSGIGateway.get_environ
(self)
Return a new environ dict targeting the given wsgi.version
Return a new environ dict targeting the given wsgi.version
[ "Return", "a", "new", "environ", "dict", "targeting", "the", "given", "wsgi", ".", "version" ]
def get_environ(self): """Return a new environ dict targeting the given wsgi.version""" raise NotImplemented
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https://github.com/sdhash/sdhash/blob/b9eff63e4e5867e910f41fd69032bbb1c94a2a5e/sdhash-ui/cherrypy/wsgiserver/wsgiserver3.py#L1822-L1824
davidstutz/mesh-voxelization
81a237c3b345062e364b180a8a4fc7ac98e107a4
examples/fill_occupancy.py
python
read_hdf5
(file, key = 'tensor')
return tensor
Read a tensor, i.e. numpy array, from HDF5. :param file: path to file to read :type file: str :param key: key to read :type key: str :return: tensor :rtype: numpy.ndarray
Read a tensor, i.e. numpy array, from HDF5.
[ "Read", "a", "tensor", "i", ".", "e", ".", "numpy", "array", "from", "HDF5", "." ]
def read_hdf5(file, key = 'tensor'): """ Read a tensor, i.e. numpy array, from HDF5. :param file: path to file to read :type file: str :param key: key to read :type key: str :return: tensor :rtype: numpy.ndarray """ assert os.path.exists(file), 'file %s not found' % file h5f = h5py.File(file, 'r') assert key in h5f.keys(), 'key %s not found in file %s' % (key, file) tensor = h5f[key][()] h5f.close() return tensor
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https://github.com/davidstutz/mesh-voxelization/blob/81a237c3b345062e364b180a8a4fc7ac98e107a4/examples/fill_occupancy.py#L34-L54
baidu/tera
dbcd28af792d879d961bf9fc7eb60de81b437646
src/sdk/python/TeraSdk.py
python
ScanDescriptor.SetPackInterval
(self, interval)
设置scan操作的超时时长,单位ms 服务端在scan操作达到约 interval 毫秒后尽快返回给client结果 Args: iinterval(long): 一次scan的超时时长,单位ms
设置scan操作的超时时长,单位ms 服务端在scan操作达到约 interval 毫秒后尽快返回给client结果
[ "设置scan操作的超时时长,单位ms", "服务端在scan操作达到约", "interval", "毫秒后尽快返回给client结果" ]
def SetPackInterval(self, interval): """ 设置scan操作的超时时长,单位ms 服务端在scan操作达到约 interval 毫秒后尽快返回给client结果 Args: iinterval(long): 一次scan的超时时长,单位ms """ lib.tera_scan_descriptor_set_pack_interval(self.desc, interval)
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https://github.com/baidu/tera/blob/dbcd28af792d879d961bf9fc7eb60de81b437646/src/sdk/python/TeraSdk.py#L110-L118
cyberbotics/webots
af7fa7d68dcf7b4550f1f2e132092b41e83698fc
projects/default/controllers/sumo_supervisor/SumoSupervisor.py
python
SumoSupervisor.update_vehicles_position_and_velocity
(self, step, rotateWheels)
Update the actual position (using angular and linear velocities) of all the vehicles in Webots.
Update the actual position (using angular and linear velocities) of all the vehicles in Webots.
[ "Update", "the", "actual", "position", "(", "using", "angular", "and", "linear", "velocities", ")", "of", "all", "the", "vehicles", "in", "Webots", "." ]
def update_vehicles_position_and_velocity(self, step, rotateWheels): """Update the actual position (using angular and linear velocities) of all the vehicles in Webots.""" for i in range(0, self.vehicleNumber): if self.vehicles[i].inUse: self.vehicles[i].translation.setSFVec3f(self.vehicles[i].currentPos) self.vehicles[i].rotation.setSFRotation(self.vehicles[i].currentRot) velocity = [] velocity.append(self.vehicles[i].targetPos[0] - self.vehicles[i].currentPos[0]) velocity.append(self.vehicles[i].targetPos[1] - self.vehicles[i].currentPos[1]) velocity.append(self.vehicles[i].targetPos[2] - self.vehicles[i].currentPos[2]) for j in range(0, 3): diffAngle = self.vehicles[i].currentAngles[j] - self.vehicles[i].targetAngles[j] diffAngle = (diffAngle + 2*math.pi) % (2*math.pi) if (diffAngle > math.pi): diffAngle -= 2*math.pi velocity.append(diffAngle) velocity[:] = [1000 * x / step for x in velocity] self.vehicles[i].node.setVelocity(velocity) if rotateWheels: angularVelocity = [0, self.vehicles[i].speed / self.vehicles[i].wheelRadius, 0] for wheelAngularVelocity in self.vehicles[i].wheelsAngularVelocity: wheelAngularVelocity.setSFVec3f(angularVelocity)
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https://github.com/cyberbotics/webots/blob/af7fa7d68dcf7b4550f1f2e132092b41e83698fc/projects/default/controllers/sumo_supervisor/SumoSupervisor.py#L324-L345
SoarGroup/Soar
a1c5e249499137a27da60533c72969eef3b8ab6b
scons/scons-local-4.1.0/SCons/Node/FS.py
python
FS.VariantDir
(self, variant_dir, src_dir, duplicate=1)
Link the supplied variant directory to the source directory for purposes of building files.
Link the supplied variant directory to the source directory for purposes of building files.
[ "Link", "the", "supplied", "variant", "directory", "to", "the", "source", "directory", "for", "purposes", "of", "building", "files", "." ]
def VariantDir(self, variant_dir, src_dir, duplicate=1): """Link the supplied variant directory to the source directory for purposes of building files.""" if not isinstance(src_dir, SCons.Node.Node): src_dir = self.Dir(src_dir) if not isinstance(variant_dir, SCons.Node.Node): variant_dir = self.Dir(variant_dir) if src_dir.is_under(variant_dir): raise SCons.Errors.UserError("Source directory cannot be under variant directory.") if variant_dir.srcdir: if variant_dir.srcdir == src_dir: return # We already did this. raise SCons.Errors.UserError("'%s' already has a source directory: '%s'."%(variant_dir, variant_dir.srcdir)) variant_dir.link(src_dir, duplicate)
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https://github.com/SoarGroup/Soar/blob/a1c5e249499137a27da60533c72969eef3b8ab6b/scons/scons-local-4.1.0/SCons/Node/FS.py#L1413-L1427
PaddlePaddle/Paddle
1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c
python/paddle/dataset/common.py
python
cluster_files_reader
(files_pattern, trainer_count, trainer_id, loader=pickle.load)
return reader
Create a reader that yield element from the given files, select a file set according trainer count and trainer_id :param files_pattern: the files which generating by split(...) :param trainer_count: total trainer count :param trainer_id: the trainer rank id :param loader: is a callable function that load object from file, this function will be called as loader(f) and f is a file object. Default is cPickle.load
Create a reader that yield element from the given files, select a file set according trainer count and trainer_id
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def cluster_files_reader(files_pattern, trainer_count, trainer_id, loader=pickle.load): """ Create a reader that yield element from the given files, select a file set according trainer count and trainer_id :param files_pattern: the files which generating by split(...) :param trainer_count: total trainer count :param trainer_id: the trainer rank id :param loader: is a callable function that load object from file, this function will be called as loader(f) and f is a file object. Default is cPickle.load """ def reader(): if not callable(loader): raise TypeError("loader should be callable.") file_list = glob.glob(files_pattern) file_list.sort() my_file_list = [] for idx, fn in enumerate(file_list): if idx % trainer_count == trainer_id: print("append file: %s" % fn) my_file_list.append(fn) for fn in my_file_list: with open(fn, "r") as f: lines = loader(f) for line in lines: yield line return reader
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https://github.com/PaddlePaddle/Paddle/blob/1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c/python/paddle/dataset/common.py#L167-L199
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/parallel_for/pfor.py
python
PFor.all_indices_partitioned
(self)
return self._all_indices_partitioned
all_indices_partitioned property. Returns: True if we are inside a control flow construct and not all pfor iterations may be active.
all_indices_partitioned property.
[ "all_indices_partitioned", "property", "." ]
def all_indices_partitioned(self): """all_indices_partitioned property. Returns: True if we are inside a control flow construct and not all pfor iterations may be active. """ return self._all_indices_partitioned
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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#L1446-L1453
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib-tk/Tkinter.py
python
Listbox.get
(self, first, last=None)
Get list of items from FIRST to LAST (not included).
Get list of items from FIRST to LAST (not included).
[ "Get", "list", "of", "items", "from", "FIRST", "to", "LAST", "(", "not", "included", ")", "." ]
def get(self, first, last=None): """Get list of items from FIRST to LAST (not included).""" if last: return self.tk.splitlist(self.tk.call( self._w, 'get', first, last)) else: return self.tk.call(self._w, 'get', first)
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib-tk/Tkinter.py#L2566-L2572
carla-simulator/carla
8854804f4d7748e14d937ec763a2912823a7e5f5
PythonAPI/carla/agents/navigation/behavior_agent.py
python
BehaviorAgent.pedestrian_avoid_manager
(self, waypoint)
return walker_state, walker, distance
This module is in charge of warning in case of a collision with any pedestrian. :param location: current location of the agent :param waypoint: current waypoint of the agent :return vehicle_state: True if there is a walker nearby, False if not :return vehicle: nearby walker :return distance: distance to nearby walker
This module is in charge of warning in case of a collision with any pedestrian.
[ "This", "module", "is", "in", "charge", "of", "warning", "in", "case", "of", "a", "collision", "with", "any", "pedestrian", "." ]
def pedestrian_avoid_manager(self, waypoint): """ This module is in charge of warning in case of a collision with any pedestrian. :param location: current location of the agent :param waypoint: current waypoint of the agent :return vehicle_state: True if there is a walker nearby, False if not :return vehicle: nearby walker :return distance: distance to nearby walker """ walker_list = self._world.get_actors().filter("*walker.pedestrian*") def dist(w): return w.get_location().distance(waypoint.transform.location) walker_list = [w for w in walker_list if dist(w) < 10] if self._direction == RoadOption.CHANGELANELEFT: walker_state, walker, distance = self._vehicle_obstacle_detected(walker_list, max( self._behavior.min_proximity_threshold, self._speed_limit / 2), up_angle_th=90, lane_offset=-1) elif self._direction == RoadOption.CHANGELANERIGHT: walker_state, walker, distance = self._vehicle_obstacle_detected(walker_list, max( self._behavior.min_proximity_threshold, self._speed_limit / 2), up_angle_th=90, lane_offset=1) else: walker_state, walker, distance = self._vehicle_obstacle_detected(walker_list, max( self._behavior.min_proximity_threshold, self._speed_limit / 3), up_angle_th=60) return walker_state, walker, distance
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https://github.com/carla-simulator/carla/blob/8854804f4d7748e14d937ec763a2912823a7e5f5/PythonAPI/carla/agents/navigation/behavior_agent.py#L169-L195
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_vendor/pyparsing.py
python
ParseBaseException.__getattr__
(self, aname)
supported attributes by name are: - lineno - returns the line number of the exception text - col - returns the column number of the exception text - line - returns the line containing the exception text
supported attributes by name are: - lineno - returns the line number of the exception text - col - returns the column number of the exception text - line - returns the line containing the exception text
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def __getattr__(self, aname): """supported attributes by name are: - lineno - returns the line number of the exception text - col - returns the column number of the exception text - line - returns the line containing the exception text """ if aname == "lineno": return lineno(self.loc, self.pstr) elif aname in ("col", "column"): return col(self.loc, self.pstr) elif aname == "line": return line(self.loc, self.pstr) else: raise AttributeError(aname)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_vendor/pyparsing.py#L323-L336
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/path.py/path.py
python
FastPath.__prepare
(self, pattern, normcase=None)
return pattern, normcase
Prepares a fmatch_pattern for use with ``FastPath.__fnmatch`. `pattern` - A filename pattern with wildcards, for example ``'*.py'``. If the pattern contains a `normcase` attribute, it is applied to the name and path prior to comparison. `normcase` - (optional) A function used to normalize the pattern and filename before matching. Defaults to :meth:`self.module`, which defaults to :meth:`os.path.normcase`. .. seealso:: :func:`FastPath.__fnmatch`
Prepares a fmatch_pattern for use with ``FastPath.__fnmatch`. `pattern` - A filename pattern with wildcards, for example ``'*.py'``. If the pattern contains a `normcase` attribute, it is applied to the name and path prior to comparison. `normcase` - (optional) A function used to normalize the pattern and filename before matching. Defaults to :meth:`self.module`, which defaults to :meth:`os.path.normcase`. .. seealso:: :func:`FastPath.__fnmatch`
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def __prepare(self, pattern, normcase=None): """ Prepares a fmatch_pattern for use with ``FastPath.__fnmatch`. `pattern` - A filename pattern with wildcards, for example ``'*.py'``. If the pattern contains a `normcase` attribute, it is applied to the name and path prior to comparison. `normcase` - (optional) A function used to normalize the pattern and filename before matching. Defaults to :meth:`self.module`, which defaults to :meth:`os.path.normcase`. .. seealso:: :func:`FastPath.__fnmatch` """ if not normcase: normcase = getattr(pattern, 'normcase', self.module.normcase) pattern = normcase(pattern) return pattern, normcase
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/path.py/path.py#L1881-L1894
deepmind/reverb
ef3c8f0be1b720a741d2dee335e15e44668c291a
reverb/structured_writer.py
python
infer_signature
(configs: Sequence[Config], step_spec: reverb_types.SpecNest)
return tree.map_structure_with_path(_validate_and_convert_to_spec, *patterns)
Infers the table signature from the configs that generate its items. Args: configs: All the configs used to generate items for the table. step_spec: A structured example of the step that will be appended to the `StructuredWriter`. Returns: A nested structure of `TensorSpec` describing the trajectories of the table. Raises: ValueError: If no configs are provided. ValueError: If configs doesn't produce trajectories of identical structure. ValueError: If configs targets does not all target the same table. ValueError: If configs produce trajectories with incompatible tensors (i.e. tensors cannot be concatenated).
Infers the table signature from the configs that generate its items.
[ "Infers", "the", "table", "signature", "from", "the", "configs", "that", "generate", "its", "items", "." ]
def infer_signature(configs: Sequence[Config], step_spec: reverb_types.SpecNest) -> reverb_types.SpecNest: """Infers the table signature from the configs that generate its items. Args: configs: All the configs used to generate items for the table. step_spec: A structured example of the step that will be appended to the `StructuredWriter`. Returns: A nested structure of `TensorSpec` describing the trajectories of the table. Raises: ValueError: If no configs are provided. ValueError: If configs doesn't produce trajectories of identical structure. ValueError: If configs targets does not all target the same table. ValueError: If configs produce trajectories with incompatible tensors (i.e. tensors cannot be concatenated). """ if not configs: raise ValueError('At least one config must be provided.') if any(c.pattern_structure != configs[0].pattern_structure for c in configs): raise ValueError( 'All configs must have exactly the same pattern_structure.') if any(c.table != configs[0].table for c in configs): raise ValueError( f'All configs must target the same table but provided configs ' f'included {", ".join(sorted(set(c.table for c in configs)))}.') flat_step_spec = tree.flatten(step_spec) def _validate_and_convert_to_spec(path, *nodes): # Check that all nodes share the same dtype. dtypes = [flat_step_spec[node.flat_source_index].dtype for node in nodes] if any(dtype != dtypes[0] for dtype in dtypes): raise ValueError( f'Configs produce trajectories with multiple dtypes at {path}. ' f'Got {dtypes}.') # Create shapes for all nodes. shapes = [] for node in nodes: shape = list(flat_step_spec[node.flat_source_index].shape) if node.HasField('start'): length = (node.stop - node.start) // (node.step or 1) shape = [length, *shape] shapes.append(tensor_shape.TensorShape(shape)) # Check that all shapes are either completely identical or at least # identical in all dimensions but the first. if (any(shape.rank != shapes[0].rank for shape in shapes) or (shapes[0].rank > 1 and any(shape[1:] != shapes[0][1:] for shape in shapes))): raise ValueError( f'Configs produce trajectories with incompatible shapes at {path}. ' f'Got {shapes}.') # Merge the shapes into a single shape. If the first dimension varies then # we set the leading dimension as undefined. if all(shape == shapes[0] for shape in shapes): merged_shape = shapes[0] else: merged_shape = [None, *shapes[0][1:]] return tensor_spec.TensorSpec( shape=merged_shape, dtype=dtypes[0], name='/'.join(str(x) for x in path)) patterns = [unpack_pattern(config) for config in configs] return tree.map_structure_with_path(_validate_and_convert_to_spec, *patterns)
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https://github.com/deepmind/reverb/blob/ef3c8f0be1b720a741d2dee335e15e44668c291a/reverb/structured_writer.py#L308-L381
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/slim/python/slim/nets/alexnet.py
python
alexnet_v2
(inputs, num_classes=1000, is_training=True, dropout_keep_prob=0.5, spatial_squeeze=True, scope='alexnet_v2')
AlexNet version 2. Described in: http://arxiv.org/pdf/1404.5997v2.pdf Parameters from: github.com/akrizhevsky/cuda-convnet2/blob/master/layers/ layers-imagenet-1gpu.cfg Note: All the fully_connected layers have been transformed to conv2d layers. To use in classification mode, resize input to 224x224. To use in fully convolutional mode, set spatial_squeeze to false. The LRN layers have been removed and change the initializers from random_normal_initializer to xavier_initializer. Args: inputs: a tensor of size [batch_size, height, width, channels]. num_classes: number of predicted classes. is_training: whether or not the model is being trained. dropout_keep_prob: the probability that activations are kept in the dropout layers during training. spatial_squeeze: whether or not should squeeze the spatial dimensions of the outputs. Useful to remove unnecessary dimensions for classification. scope: Optional scope for the variables. Returns: the last op containing the log predictions and end_points dict.
AlexNet version 2.
[ "AlexNet", "version", "2", "." ]
def alexnet_v2(inputs, num_classes=1000, is_training=True, dropout_keep_prob=0.5, spatial_squeeze=True, scope='alexnet_v2'): """AlexNet version 2. Described in: http://arxiv.org/pdf/1404.5997v2.pdf Parameters from: github.com/akrizhevsky/cuda-convnet2/blob/master/layers/ layers-imagenet-1gpu.cfg Note: All the fully_connected layers have been transformed to conv2d layers. To use in classification mode, resize input to 224x224. To use in fully convolutional mode, set spatial_squeeze to false. The LRN layers have been removed and change the initializers from random_normal_initializer to xavier_initializer. Args: inputs: a tensor of size [batch_size, height, width, channels]. num_classes: number of predicted classes. is_training: whether or not the model is being trained. dropout_keep_prob: the probability that activations are kept in the dropout layers during training. spatial_squeeze: whether or not should squeeze the spatial dimensions of the outputs. Useful to remove unnecessary dimensions for classification. scope: Optional scope for the variables. Returns: the last op containing the log predictions and end_points dict. """ with variable_scope.variable_scope(scope, 'alexnet_v2', [inputs]) as sc: end_points_collection = sc.original_name_scope + '_end_points' # Collect outputs for conv2d, fully_connected and max_pool2d. with arg_scope( [layers.conv2d, layers_lib.fully_connected, layers_lib.max_pool2d], outputs_collections=[end_points_collection]): net = layers.conv2d( inputs, 64, [11, 11], 4, padding='VALID', scope='conv1') net = layers_lib.max_pool2d(net, [3, 3], 2, scope='pool1') net = layers.conv2d(net, 192, [5, 5], scope='conv2') net = layers_lib.max_pool2d(net, [3, 3], 2, scope='pool2') net = layers.conv2d(net, 384, [3, 3], scope='conv3') net = layers.conv2d(net, 384, [3, 3], scope='conv4') net = layers.conv2d(net, 256, [3, 3], scope='conv5') net = layers_lib.max_pool2d(net, [3, 3], 2, scope='pool5') # Use conv2d instead of fully_connected layers. with arg_scope( [layers.conv2d], weights_initializer=trunc_normal(0.005), biases_initializer=init_ops.constant_initializer(0.1)): net = layers.conv2d(net, 4096, [5, 5], padding='VALID', scope='fc6') net = layers_lib.dropout( net, dropout_keep_prob, is_training=is_training, scope='dropout6') net = layers.conv2d(net, 4096, [1, 1], scope='fc7') net = layers_lib.dropout( net, dropout_keep_prob, is_training=is_training, scope='dropout7') net = layers.conv2d( net, num_classes, [1, 1], activation_fn=None, normalizer_fn=None, biases_initializer=init_ops.zeros_initializer(), scope='fc8') # Convert end_points_collection into a end_point dict. end_points = utils.convert_collection_to_dict(end_points_collection) if spatial_squeeze: net = array_ops.squeeze(net, [1, 2], name='fc8/squeezed') end_points[sc.name + '/fc8'] = net return net, end_points
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/slim/python/slim/nets/alexnet.py#L63-L135
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
tools/site_compare/drivers/win32/mouse.py
python
PressButton
(down, button='left')
Simulate a mouse button press or release at the current mouse location. Args: down: whether the button is pressed or released button: which button is pressed Returns: None
Simulate a mouse button press or release at the current mouse location.
[ "Simulate", "a", "mouse", "button", "press", "or", "release", "at", "the", "current", "mouse", "location", "." ]
def PressButton(down, button='left'): """Simulate a mouse button press or release at the current mouse location. Args: down: whether the button is pressed or released button: which button is pressed Returns: None """ # Put the mouse_event flags in a convenient dictionary by button flags = { 'left': (win32con.MOUSEEVENTF_LEFTUP, win32con.MOUSEEVENTF_LEFTDOWN), 'middle': (win32con.MOUSEEVENTF_MIDDLEUP, win32con.MOUSEEVENTF_MIDDLEDOWN), 'right': (win32con.MOUSEEVENTF_RIGHTUP, win32con.MOUSEEVENTF_RIGHTDOWN) } # hit the button win32api.mouse_event(flags[button][down], 0, 0)
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/site_compare/drivers/win32/mouse.py#L47-L66
windystrife/UnrealEngine_NVIDIAGameWorks
b50e6338a7c5b26374d66306ebc7807541ff815e
Engine/Extras/Maya_AnimationRiggingTools/ARTv1/MayaTools/General/Scripts/ART_skeletonBuilder_UI.py
python
SkeletonBuilder_UI.faceInfo_UI_Cancel
(self, *args)
Closes the faceInfo user interface @author chrise
Closes the faceInfo user interface
[ "Closes", "the", "faceInfo", "user", "interface" ]
def faceInfo_UI_Cancel(self, *args): ''' Closes the faceInfo user interface @author chrise ''' cmds.deleteUI("faceInfo_UI")
[ "def", "faceInfo_UI_Cancel", "(", "self", ",", "*", "args", ")", ":", "cmds", ".", "deleteUI", "(", "\"faceInfo_UI\"", ")" ]
https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Extras/Maya_AnimationRiggingTools/ARTv1/MayaTools/General/Scripts/ART_skeletonBuilder_UI.py#L2957-L2962
mantidproject/mantid
03deeb89254ec4289edb8771e0188c2090a02f32
qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/reduce4circleControl.py
python
CWSCDReductionControl.add_k_shift_vector
(self, k_x, k_y, k_z)
return return_k_index
Add a k-shift vector :param k_x: :param k_y: :param k_z: :return: k_index of the (k_x, k_y, k_z)
Add a k-shift vector :param k_x: :param k_y: :param k_z: :return: k_index of the (k_x, k_y, k_z)
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def add_k_shift_vector(self, k_x, k_y, k_z): """ Add a k-shift vector :param k_x: :param k_y: :param k_z: :return: k_index of the (k_x, k_y, k_z) """ # check assert isinstance(k_x, float), 'Kx is wrong' assert isinstance(k_y, float), 'Ky is wrong' assert isinstance(k_z, float), 'Kz is wrong' k_shift_vector = (k_x, k_y, k_z) self._kShiftDict[self._kVectorIndex] = [k_shift_vector, []] # make progress return_k_index = self._kVectorIndex self._kVectorIndex += 1 return return_k_index
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https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/reduce4circleControl.py#L293-L313
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/dataview.py
python
DataViewIndexListModel.RowChanged
(*args, **kwargs)
return _dataview.DataViewIndexListModel_RowChanged(*args, **kwargs)
RowChanged(self, unsigned int row) Call this after a row has been changed.
RowChanged(self, unsigned int row)
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def RowChanged(*args, **kwargs): """ RowChanged(self, unsigned int row) Call this after a row has been changed. """ return _dataview.DataViewIndexListModel_RowChanged(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/dataview.py#L871-L877
ricardoquesada/Spidermonkey
4a75ea2543408bd1b2c515aa95901523eeef7858
build/upload.py
python
OptionalEnvironmentVariable
(v)
return None
Return the value of the environment variable named v, or None if it's unset (or empty).
Return the value of the environment variable named v, or None if it's unset (or empty).
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def OptionalEnvironmentVariable(v): """Return the value of the environment variable named v, or None if it's unset (or empty).""" if v in os.environ and os.environ[v] != "": return os.environ[v] return None
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https://github.com/ricardoquesada/Spidermonkey/blob/4a75ea2543408bd1b2c515aa95901523eeef7858/build/upload.py#L37-L42
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/graphy/graphy/backends/google_chart_api/encoders.py
python
LineChartEncoder._GetLineStyles
(self, chart)
return util.JoinLists(line_style = styles)
Get LineStyle parameters.
Get LineStyle parameters.
[ "Get", "LineStyle", "parameters", "." ]
def _GetLineStyles(self, chart): """Get LineStyle parameters.""" styles = [] for series in chart.data: style = series.style if style: styles.append('%s,%s,%s' % (style.width, style.on, style.off)) else: # If one style is missing, they must all be missing # TODO: Add a test for this; throw a more meaningful exception assert (not styles) return util.JoinLists(line_style = styles)
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/graphy/graphy/backends/google_chart_api/encoders.py#L220-L231
google/filament
d21f092645b8e1e312307cbf89f1484891347c63
third_party/spirv-tools/utils/generate_grammar_tables.py
python
generate_capability_arrays
(caps)
return '\n'.join(arrays)
Returns the arrays of capabilities. Arguments: - caps: a sequence of sequence of capability names
Returns the arrays of capabilities.
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def generate_capability_arrays(caps): """Returns the arrays of capabilities. Arguments: - caps: a sequence of sequence of capability names """ caps = sorted(set([tuple(c) for c in caps if c])) arrays = [ 'static const SpvCapability {}[] = {};'.format( get_capability_array_name(c), compose_capability_list(c)) for c in caps] return '\n'.join(arrays)
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https://github.com/google/filament/blob/d21f092645b8e1e312307cbf89f1484891347c63/third_party/spirv-tools/utils/generate_grammar_tables.py#L95-L106
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/setuptools/msvc.py
python
EnvironmentInfo.return_env
(self, exists=True)
return env
Return environment dict. Parameters ---------- exists: bool It True, only return existing paths. Return ------ dict environment
Return environment dict.
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def return_env(self, exists=True): """ Return environment dict. Parameters ---------- exists: bool It True, only return existing paths. Return ------ dict environment """ env = dict( include=self._build_paths('include', [self.VCIncludes, self.OSIncludes, self.UCRTIncludes, self.NetFxSDKIncludes], exists), lib=self._build_paths('lib', [self.VCLibraries, self.OSLibraries, self.FxTools, self.UCRTLibraries, self.NetFxSDKLibraries], exists), libpath=self._build_paths('libpath', [self.VCLibraries, self.FxTools, self.VCStoreRefs, self.OSLibpath], exists), path=self._build_paths('path', [self.VCTools, self.VSTools, self.VsTDb, self.SdkTools, self.SdkSetup, self.FxTools, self.MSBuild, self.HTMLHelpWorkshop, self.FSharp], exists), ) if self.vs_ver >= 14 and isfile(self.VCRuntimeRedist): env['py_vcruntime_redist'] = self.VCRuntimeRedist return env
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/setuptools/msvc.py#L1720-L1768
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/uuid.py
python
_windll_getnode
()
Get the hardware address on Windows using ctypes.
Get the hardware address on Windows using ctypes.
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def _windll_getnode(): """Get the hardware address on Windows using ctypes.""" import ctypes _load_system_functions() _buffer = ctypes.create_string_buffer(16) if _UuidCreate(_buffer) == 0: return UUID(bytes=bytes_(_buffer.raw)).node
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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/uuid.py#L654-L660
vslavik/poedit
f7a9daa0a10037e090aa0a86f5ce0f24ececdf6a
deps/boost/tools/build/src/build/targets.py
python
BasicTarget.match
(self, property_set_, debug)
Returns the alternative condition for this alternative, if the condition is satisfied by 'property_set'.
Returns the alternative condition for this alternative, if the condition is satisfied by 'property_set'.
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def match (self, property_set_, debug): """ Returns the alternative condition for this alternative, if the condition is satisfied by 'property_set'. """ # The condition is composed of all base non-conditional properties. # It's not clear if we should expand 'self.requirements_' or not. # For one thing, it would be nice to be able to put # <toolset>msvc-6.0 # in requirements. # On the other hand, if we have <variant>release in condition it # does not make sense to require <optimization>full to be in # build request just to select this variant. assert isinstance(property_set_, property_set.PropertySet) bcondition = self.requirements_.base () ccondition = self.requirements_.conditional () condition = b2.util.set.difference (bcondition, ccondition) if debug: print " next alternative: required properties:", [str(p) for p in condition] if b2.util.set.contains (condition, property_set_.all()): if debug: print " matched" return condition else: return None
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https://github.com/vslavik/poedit/blob/f7a9daa0a10037e090aa0a86f5ce0f24ececdf6a/deps/boost/tools/build/src/build/targets.py#L1103-L1131
Polidea/SiriusObfuscator
b0e590d8130e97856afe578869b83a209e2b19be
SymbolExtractorAndRenamer/swift/utils/gyb.py
python
strip_trailing_nl
(s)
return s[:-1] if s.endswith('\n') else s
If s ends with a newline, drop it; else return s intact
If s ends with a newline, drop it; else return s intact
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def strip_trailing_nl(s): """If s ends with a newline, drop it; else return s intact""" return s[:-1] if s.endswith('\n') else s
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https://github.com/Polidea/SiriusObfuscator/blob/b0e590d8130e97856afe578869b83a209e2b19be/SymbolExtractorAndRenamer/swift/utils/gyb.py#L40-L42
miyosuda/TensorFlowAndroidDemo
35903e0221aa5f109ea2dbef27f20b52e317f42d
jni-build/jni/include/tensorflow/python/framework/tensor_shape.py
python
as_dimension
(value)
Converts the given value to a Dimension. A Dimenson input will be returned unmodified. An input of `None` will be converted to an unknown Dimension. An integer input will be converted to a Dimension with that value. Args: value: The value to be converted. Returns: A Dimension corresponding to the given value.
Converts the given value to a Dimension.
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def as_dimension(value): """Converts the given value to a Dimension. A Dimenson input will be returned unmodified. An input of `None` will be converted to an unknown Dimension. An integer input will be converted to a Dimension with that value. Args: value: The value to be converted. Returns: A Dimension corresponding to the given value. """ if isinstance(value, Dimension): return value else: return Dimension(value)
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https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/tensorflow/python/framework/tensor_shape.py#L358-L374
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/_misc.py
python
Joystick.GetPollingMin
(*args, **kwargs)
return _misc_.Joystick_GetPollingMin(*args, **kwargs)
GetPollingMin(self) -> int
GetPollingMin(self) -> int
[ "GetPollingMin", "(", "self", ")", "-", ">", "int" ]
def GetPollingMin(*args, **kwargs): """GetPollingMin(self) -> int""" return _misc_.Joystick_GetPollingMin(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_misc.py#L2226-L2228
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/propgrid.py
python
EditEnumProperty.__init__
(self, *args)
__init__(self, String label, String name, wxChar labels, long values, String value) -> EditEnumProperty __init__(self, String label=(*wxPGProperty::sm_wxPG_LABEL), String name=(*wxPGProperty::sm_wxPG_LABEL), wxArrayString labels=wxArrayString(), wxArrayInt values=wxArrayInt(), String value=wxEmptyString) -> EditEnumProperty __init__(self, String label, String name, PGChoices choices, String value=wxEmptyString) -> EditEnumProperty __init__(self, String label, String name, wxChar labels, long values, PGChoices choicesCache, String value) -> EditEnumProperty
__init__(self, String label, String name, wxChar labels, long values, String value) -> EditEnumProperty __init__(self, String label=(*wxPGProperty::sm_wxPG_LABEL), String name=(*wxPGProperty::sm_wxPG_LABEL), wxArrayString labels=wxArrayString(), wxArrayInt values=wxArrayInt(), String value=wxEmptyString) -> EditEnumProperty __init__(self, String label, String name, PGChoices choices, String value=wxEmptyString) -> EditEnumProperty __init__(self, String label, String name, wxChar labels, long values, PGChoices choicesCache, String value) -> EditEnumProperty
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def __init__(self, *args): """ __init__(self, String label, String name, wxChar labels, long values, String value) -> EditEnumProperty __init__(self, String label=(*wxPGProperty::sm_wxPG_LABEL), String name=(*wxPGProperty::sm_wxPG_LABEL), wxArrayString labels=wxArrayString(), wxArrayInt values=wxArrayInt(), String value=wxEmptyString) -> EditEnumProperty __init__(self, String label, String name, PGChoices choices, String value=wxEmptyString) -> EditEnumProperty __init__(self, String label, String name, wxChar labels, long values, PGChoices choicesCache, String value) -> EditEnumProperty """ _propgrid.EditEnumProperty_swiginit(self,_propgrid.new_EditEnumProperty(*args))
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/propgrid.py#L3015-L3027
htcondor/htcondor
4829724575176d1d6c936e4693dfd78a728569b0
src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/twitter.py
python
Status.AsDict
(self)
return data
A dict representation of this twitter.Status instance. The return value uses the same key names as the JSON representation. Return: A dict representing this twitter.Status instance
A dict representation of this twitter.Status instance.
[ "A", "dict", "representation", "of", "this", "twitter", ".", "Status", "instance", "." ]
def AsDict(self): '''A dict representation of this twitter.Status instance. The return value uses the same key names as the JSON representation. Return: A dict representing this twitter.Status instance ''' data = {} if self.created_at: data['created_at'] = self.created_at if self.id: data['id'] = self.id if self.text: data['text'] = self.text if self.user: data['user'] = self.user.AsDict() return data
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https://github.com/htcondor/htcondor/blob/4829724575176d1d6c936e4693dfd78a728569b0/src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/twitter.py#L249-L266
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/msw/xrc.py
python
XmlSubclassFactory.__init__
(self, *args, **kwargs)
__init__(self) -> XmlSubclassFactory
__init__(self) -> XmlSubclassFactory
[ "__init__", "(", "self", ")", "-", ">", "XmlSubclassFactory" ]
def __init__(self, *args, **kwargs): """__init__(self) -> XmlSubclassFactory""" _xrc.XmlSubclassFactory_swiginit(self,_xrc.new_XmlSubclassFactory(*args, **kwargs)) XmlSubclassFactory._setCallbackInfo(self, self, XmlSubclassFactory)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/xrc.py#L278-L281
TGAC/KAT
e8870331de2b4bb0a1b3b91c6afb8fb9d59e9216
deps/boost/tools/build/src/build/property.py
python
PropertyMap.find
(self, properties)
return self.find_replace (properties)
Return the value associated with properties or any subset of it. If more than one subset has value assigned to it, return the value for the longest subset, if it's unique.
Return the value associated with properties or any subset of it. If more than one subset has value assigned to it, return the value for the longest subset, if it's unique.
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def find (self, properties): """ Return the value associated with properties or any subset of it. If more than one subset has value assigned to it, return the value for the longest subset, if it's unique. """ assert is_iterable_typed(properties, basestring) return self.find_replace (properties)
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https://github.com/TGAC/KAT/blob/e8870331de2b4bb0a1b3b91c6afb8fb9d59e9216/deps/boost/tools/build/src/build/property.py#L598-L605
mantidproject/mantid
03deeb89254ec4289edb8771e0188c2090a02f32
qt/python/mantidqt/mantidqt/plotting/markers.py
python
VerticalMarker.mouse_move_stop
(self)
Stop moving.
Stop moving.
[ "Stop", "moving", "." ]
def mouse_move_stop(self): """ Stop moving. """ self.is_moving = False
[ "def", "mouse_move_stop", "(", "self", ")", ":", "self", ".", "is_moving", "=", "False" ]
https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/python/mantidqt/mantidqt/plotting/markers.py#L339-L343
H-uru/Plasma
c2140ea046e82e9c199e257a7f2e7edb42602871
Scripts/Python/xDialogClothingBB.py
python
xDialogClothingBB.IWhatShirtAmIWearing
(self,avatar)
return kNoShirtIdx
Find out what shirt we are already wearing - returns index
Find out what shirt we are already wearing - returns index
[ "Find", "out", "what", "shirt", "we", "are", "already", "wearing", "-", "returns", "index" ]
def IWhatShirtAmIWearing(self,avatar): "Find out what shirt we are already wearing - returns index" global ShirtNames worn = avatar.avatar.getAvatarClothingList() #PtDebugPrint("xDialogClothingBB: I am currently wearing ",worn) for item in worn: try: shirtIdx = ShirtNames.index(item) return shirtIdx except ValueError: # see if its a shirt... maybe they are wearing something that is not in their closet if item[-len(kShirtIdentifier):] == kShirtIdentifier: ShirtNames.append(item) try: shirtIdx = ShirtNames.index(item) return shirtIdx except ValueError: pass return kNoShirtIdx
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https://github.com/H-uru/Plasma/blob/c2140ea046e82e9c199e257a7f2e7edb42602871/Scripts/Python/xDialogClothingBB.py#L195-L213
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/closure_linter/closure_linter/tokenutil.py
python
InsertTokenAfter
(new_token, token)
Insert new_token after token. Args: new_token: A token to be added to the stream token: A token already in the stream
Insert new_token after token.
[ "Insert", "new_token", "after", "token", "." ]
def InsertTokenAfter(new_token, token): """Insert new_token after token. Args: new_token: A token to be added to the stream token: A token already in the stream """ new_token.previous = token new_token.next = token.next new_token.metadata = copy.copy(token.metadata) if token.IsCode(): new_token.metadata.last_code = token if new_token.IsCode(): following_token = token.next while following_token and following_token.metadata.last_code == token: following_token.metadata.last_code = new_token following_token = following_token.next token.next = new_token if new_token.next: new_token.next.previous = new_token if new_token.start_index is None: if new_token.line_number == token.line_number: new_token.start_index = token.start_index + len(token.string) else: new_token.start_index = 0 iterator = new_token.next while iterator and iterator.line_number == new_token.line_number: iterator.start_index += len(new_token.string) iterator = iterator.next
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/closure_linter/closure_linter/tokenutil.py#L290-L324
HKUST-Aerial-Robotics/VINS-Mobile
ab1c4ffb8d3ea1fcc01c4f5c651abc0c390807f9
VINS_ThirdPartyLib/ceres-solver/internal/ceres/generate_eliminator_specialization.py
python
Specialize
()
Generate specialization code and the conditionals to instantiate it.
Generate specialization code and the conditionals to instantiate it.
[ "Generate", "specialization", "code", "and", "the", "conditionals", "to", "instantiate", "it", "." ]
def Specialize(): """ Generate specialization code and the conditionals to instantiate it. """ f = open("schur_eliminator.cc", "w") f.write(HEADER) f.write(FACTORY_FILE_HEADER) for row_block_size, e_block_size, f_block_size in SPECIALIZATIONS: output = SpecializationFilename("generated/schur_eliminator", row_block_size, e_block_size, f_block_size) + ".cc" fptr = open(output, "w") fptr.write(HEADER) template = SPECIALIZATION_FILE if (row_block_size == "Eigen::Dynamic" and e_block_size == "Eigen::Dynamic" and f_block_size == "Eigen::Dynamic"): template = DYNAMIC_FILE fptr.write(template % (row_block_size, e_block_size, f_block_size)) fptr.close() f.write(FACTORY_CONDITIONAL % (row_block_size, e_block_size, f_block_size, row_block_size, e_block_size, f_block_size)) f.write(FACTORY_FOOTER) f.close()
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https://github.com/HKUST-Aerial-Robotics/VINS-Mobile/blob/ab1c4ffb8d3ea1fcc01c4f5c651abc0c390807f9/VINS_ThirdPartyLib/ceres-solver/internal/ceres/generate_eliminator_specialization.py#L195-L227
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/setuptools/sandbox.py
python
override_temp
(replacement)
Monkey-patch tempfile.tempdir with replacement, ensuring it exists
Monkey-patch tempfile.tempdir with replacement, ensuring it exists
[ "Monkey", "-", "patch", "tempfile", ".", "tempdir", "with", "replacement", "ensuring", "it", "exists" ]
def override_temp(replacement): """ Monkey-patch tempfile.tempdir with replacement, ensuring it exists """ pkg_resources.py31compat.makedirs(replacement, exist_ok=True) saved = tempfile.tempdir tempfile.tempdir = replacement try: yield finally: tempfile.tempdir = saved
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/setuptools/sandbox.py#L69-L82
apple/swift-lldb
d74be846ef3e62de946df343e8c234bde93a8912
scripts/Python/static-binding/lldb.py
python
SBSection.GetPermissions
(self)
return _lldb.SBSection_GetPermissions(self)
GetPermissions(SBSection self) -> uint32_t
GetPermissions(SBSection self) -> uint32_t
[ "GetPermissions", "(", "SBSection", "self", ")", "-", ">", "uint32_t" ]
def GetPermissions(self): """GetPermissions(SBSection self) -> uint32_t""" return _lldb.SBSection_GetPermissions(self)
[ "def", "GetPermissions", "(", "self", ")", ":", "return", "_lldb", ".", "SBSection_GetPermissions", "(", "self", ")" ]
https://github.com/apple/swift-lldb/blob/d74be846ef3e62de946df343e8c234bde93a8912/scripts/Python/static-binding/lldb.py#L9325-L9327
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/cuda/cudadrv/driver.py
python
Context.enable_peer_access
(self, peer_context, flags=0)
Enable peer access between the current context and the peer context
Enable peer access between the current context and the peer context
[ "Enable", "peer", "access", "between", "the", "current", "context", "and", "the", "peer", "context" ]
def enable_peer_access(self, peer_context, flags=0): """Enable peer access between the current context and the peer context """ assert flags == 0, '*flags* is reserved and MUST be zero' driver.cuCtxEnablePeerAccess(peer_context, flags)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/cuda/cudadrv/driver.py#L863-L867
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/MimeWriter.py
python
MimeWriter.nextpart
(self)
return self.__class__(self._fp)
Returns a new instance of MimeWriter which represents an individual part in a multipart message. This may be used to write the part as well as used for creating recursively complex multipart messages. The message must first be initialized with the startmultipartbody() method before using the nextpart() method.
Returns a new instance of MimeWriter which represents an individual part in a multipart message.
[ "Returns", "a", "new", "instance", "of", "MimeWriter", "which", "represents", "an", "individual", "part", "in", "a", "multipart", "message", "." ]
def nextpart(self): """Returns a new instance of MimeWriter which represents an individual part in a multipart message. This may be used to write the part as well as used for creating recursively complex multipart messages. The message must first be initialized with the startmultipartbody() method before using the nextpart() method. """ self._fp.write("\n--" + self._boundary + "\n") return self.__class__(self._fp)
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/MimeWriter.py#L163-L174
libornovax/master_thesis_code
6eca474ed3cae673afde010caef338cf7349f839
caffe/scripts/cpp_lint.py
python
CheckCaffeRandom
(filename, clean_lines, linenum, error)
Checks for calls to C random functions (rand, rand_r, random, ...). Caffe code should (almost) always use the caffe_rng_* functions rather than these, as the internal state of these C functions is independent of the native Caffe RNG system which should produce deterministic results for a fixed Caffe seed set using Caffe::set_random_seed(...). 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.
Checks for calls to C random functions (rand, rand_r, random, ...).
[ "Checks", "for", "calls", "to", "C", "random", "functions", "(", "rand", "rand_r", "random", "...", ")", "." ]
def CheckCaffeRandom(filename, clean_lines, linenum, error): """Checks for calls to C random functions (rand, rand_r, random, ...). Caffe code should (almost) always use the caffe_rng_* functions rather than these, as the internal state of these C functions is independent of the native Caffe RNG system which should produce deterministic results for a fixed Caffe seed set using Caffe::set_random_seed(...). Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. error: The function to call with any errors found. """ line = clean_lines.elided[linenum] for function in c_random_function_list: ix = line.find(function) # Comparisons made explicit for clarity -- pylint: disable=g-explicit-bool-comparison if ix >= 0 and (ix == 0 or (not line[ix - 1].isalnum() and line[ix - 1] not in ('_', '.', '>'))): error(filename, linenum, 'caffe/random_fn', 2, 'Use caffe_rng_rand() (or other caffe_rng_* function) instead of ' + function + ') to ensure results are deterministic for a fixed Caffe seed.')
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https://github.com/libornovax/master_thesis_code/blob/6eca474ed3cae673afde010caef338cf7349f839/caffe/scripts/cpp_lint.py#L1640-L1663
Lavender105/DFF
152397cec4a3dac2aa86e92a65cc27e6c8016ab9
pytorch-encoding/encoding/nn/syncbn.py
python
_SyncBatchNorm._data_parallel_master
(self, intermediates)
return outputs
Reduce the sum and square-sum, compute the statistics, and broadcast it.
Reduce the sum and square-sum, compute the statistics, and broadcast it.
[ "Reduce", "the", "sum", "and", "square", "-", "sum", "compute", "the", "statistics", "and", "broadcast", "it", "." ]
def _data_parallel_master(self, intermediates): """Reduce the sum and square-sum, compute the statistics, and broadcast it.""" # Always using same "device order" makes the ReduceAdd operation faster. # Thanks to:: Tete Xiao (http://tetexiao.com/) intermediates = sorted(intermediates, key=lambda i: i[1].sum.get_device()) to_reduce = [i[1][:2] for i in intermediates] to_reduce = [j for i in to_reduce for j in i] # flatten target_gpus = [i[1].sum.get_device() for i in intermediates] sum_size = sum([i[1].sum_size for i in intermediates]) sum_, ssum = ReduceAddCoalesced.apply(target_gpus[0], 2, *to_reduce) mean, inv_std = self._compute_mean_std(sum_, ssum, sum_size) broadcasted = Broadcast.apply(target_gpus, mean, inv_std) outputs = [] for i, rec in enumerate(intermediates): outputs.append((rec[0], _MasterMessage(*broadcasted[i*2:i*2+2]))) return outputs
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https://github.com/Lavender105/DFF/blob/152397cec4a3dac2aa86e92a65cc27e6c8016ab9/pytorch-encoding/encoding/nn/syncbn.py#L70-L91
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/requests/cookies.py
python
RequestsCookieJar.list_domains
(self)
return domains
Utility method to list all the domains in the jar.
Utility method to list all the domains in the jar.
[ "Utility", "method", "to", "list", "all", "the", "domains", "in", "the", "jar", "." ]
def list_domains(self): """Utility method to list all the domains in the jar.""" domains = [] for cookie in iter(self): if cookie.domain not in domains: domains.append(cookie.domain) return domains
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/requests/cookies.py#L270-L276
microsoft/CNTK
e9396480025b9ca457d26b6f33dd07c474c6aa04
Examples/Image/Detection/utils/nms_wrapper.py
python
apply_nms_to_test_set_results
(all_boxes, nms_threshold, conf_threshold, use_gpu_nms, device_id)
return nms_boxes, nms_keepIndices
Applies nms to the results of multiple images. Args: all_boxes: shape of all_boxes: e.g. 21 classes x 4952 images x 58 rois x 5 coords+score nms_threshold: the threshold for discarding overlapping ROIs in nms conf_threshold: a minimum value for the score of an ROI. ROIs with lower score will be discarded Returns: nms_boxes - the reduced set of rois after nms nmsKeepIndices - the indices of the ROIs to keep after nms
Applies nms to the results of multiple images.
[ "Applies", "nms", "to", "the", "results", "of", "multiple", "images", "." ]
def apply_nms_to_test_set_results(all_boxes, nms_threshold, conf_threshold, use_gpu_nms, device_id): ''' Applies nms to the results of multiple images. Args: all_boxes: shape of all_boxes: e.g. 21 classes x 4952 images x 58 rois x 5 coords+score nms_threshold: the threshold for discarding overlapping ROIs in nms conf_threshold: a minimum value for the score of an ROI. ROIs with lower score will be discarded Returns: nms_boxes - the reduced set of rois after nms nmsKeepIndices - the indices of the ROIs to keep after nms ''' num_classes = len(all_boxes) num_images = len(all_boxes[0]) nms_boxes = [[[] for _ in range(num_images)] for _ in range(num_classes)] nms_keepIndices = [[[] for _ in range(num_images)] for _ in range(num_classes)] for cls_ind in range(num_classes): for im_ind in range(num_images): dets = all_boxes[cls_ind][im_ind] if len(dets) == 0: continue if len(dets) == 1: keep = [0] else: keep = nms(dets.astype(np.float32), nms_threshold, use_gpu_nms, device_id) # also filter out low confidences if conf_threshold > 0: keep_conf_idx = np.where(dets[:, -1] > conf_threshold) keep = list(set(keep_conf_idx[0]).intersection(keep)) if len(keep) == 0: continue nms_boxes[cls_ind][im_ind] = dets[keep, :].copy() nms_keepIndices[cls_ind][im_ind] = keep return nms_boxes, nms_keepIndices
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https://github.com/microsoft/CNTK/blob/e9396480025b9ca457d26b6f33dd07c474c6aa04/Examples/Image/Detection/utils/nms_wrapper.py#L61-L100
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/graphviz/py3/graphviz/dot.py
python
Dot.__iter__
(self, subgraph=False)
Yield the DOT source code line by line (as graph or subgraph).
Yield the DOT source code line by line (as graph or subgraph).
[ "Yield", "the", "DOT", "source", "code", "line", "by", "line", "(", "as", "graph", "or", "subgraph", ")", "." ]
def __iter__(self, subgraph=False): """Yield the DOT source code line by line (as graph or subgraph).""" if self.comment: yield self._comment % self.comment if subgraph: if self.strict: raise ValueError('subgraphs cannot be strict') head = self._subgraph if self.name else self._subgraph_plain else: head = self._head_strict if self.strict else self._head yield head % (self._quote(self.name) + ' ' if self.name else '') for kw in ('graph', 'node', 'edge'): attrs = getattr(self, f'{kw}_attr') if attrs: yield self._attr % (kw, self._attr_list(None, attrs)) for line in self.body: yield line yield self._tail
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/graphviz/py3/graphviz/dot.py#L95-L116
epam/Indigo
30e40b4b1eb9bae0207435a26cfcb81ddcc42be1
api/python/indigo/__init__.py
python
IndigoObject.getBond
(self, idx)
return self.dispatcher.IndigoObject( self.dispatcher, self.dispatcher._checkResult( Indigo._lib.indigoGetBond(self.id, idx) ), )
Molecule method returns bond by index Args: idx (int): bond index Returns: IndigoObject: bond object
Molecule method returns bond by index
[ "Molecule", "method", "returns", "bond", "by", "index" ]
def getBond(self, idx): """Molecule method returns bond by index Args: idx (int): bond index Returns: IndigoObject: bond object """ self.dispatcher._setSessionId() return self.dispatcher.IndigoObject( self.dispatcher, self.dispatcher._checkResult( Indigo._lib.indigoGetBond(self.id, idx) ), )
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https://github.com/epam/Indigo/blob/30e40b4b1eb9bae0207435a26cfcb81ddcc42be1/api/python/indigo/__init__.py#L2620-L2635
apiaryio/snowcrash
b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3
tools/gyp/pylib/gyp/xcode_emulation.py
python
XcodeSettings.GetInstallNameBase
(self)
return install_base
Return DYLIB_INSTALL_NAME_BASE for this target.
Return DYLIB_INSTALL_NAME_BASE for this target.
[ "Return", "DYLIB_INSTALL_NAME_BASE", "for", "this", "target", "." ]
def GetInstallNameBase(self): """Return DYLIB_INSTALL_NAME_BASE for this target.""" # Xcode sets this for shared_libraries, and for nonbundled loadable_modules. if (self.spec['type'] != 'shared_library' and (self.spec['type'] != 'loadable_module' or self._IsBundle())): return None install_base = self.GetPerTargetSetting( 'DYLIB_INSTALL_NAME_BASE', default='/Library/Frameworks' if self._IsBundle() else '/usr/local/lib') return install_base
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https://github.com/apiaryio/snowcrash/blob/b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3/tools/gyp/pylib/gyp/xcode_emulation.py#L690-L699
natanielruiz/android-yolo
1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f
jni-build/jni/include/tensorflow/python/training/server_lib.py
python
Server.__init__
(self, server_or_cluster_def, job_name=None, task_index=None, protocol=None, config=None, start=True)
Creates a new server with the given definition. The `job_name`, `task_index`, and `protocol` arguments are optional, and override any information provided in `server_or_cluster_def`. Args: server_or_cluster_def: A `tf.train.ServerDef` or `tf.train.ClusterDef` protocol buffer, or a `tf.train.ClusterSpec` object, describing the server to be created and/or the cluster of which it is a member. job_name: (Optional.) Specifies the name of the job of which the server is a member. Defaults to the value in `server_or_cluster_def`, if specified. task_index: (Optional.) Specifies the task index of the server in its job. Defaults to the value in `server_or_cluster_def`, if specified. Otherwise defaults to 0 if the server's job has only one task. protocol: (Optional.) Specifies the protocol to be used by the server. Acceptable values include `"grpc"`. Defaults to the value in `server_or_cluster_def`, if specified. Otherwise defaults to `"grpc"`. config: (Options.) A `tf.ConfigProto` that specifies default configuration options for all sessions that run on this server. start: (Optional.) Boolean, indicating whether to start the server after creating it. Defaults to `True`. Raises: tf.errors.OpError: Or one of its subclasses if an error occurs while creating the TensorFlow server.
Creates a new server with the given definition.
[ "Creates", "a", "new", "server", "with", "the", "given", "definition", "." ]
def __init__(self, server_or_cluster_def, job_name=None, task_index=None, protocol=None, config=None, start=True): """Creates a new server with the given definition. The `job_name`, `task_index`, and `protocol` arguments are optional, and override any information provided in `server_or_cluster_def`. Args: server_or_cluster_def: A `tf.train.ServerDef` or `tf.train.ClusterDef` protocol buffer, or a `tf.train.ClusterSpec` object, describing the server to be created and/or the cluster of which it is a member. job_name: (Optional.) Specifies the name of the job of which the server is a member. Defaults to the value in `server_or_cluster_def`, if specified. task_index: (Optional.) Specifies the task index of the server in its job. Defaults to the value in `server_or_cluster_def`, if specified. Otherwise defaults to 0 if the server's job has only one task. protocol: (Optional.) Specifies the protocol to be used by the server. Acceptable values include `"grpc"`. Defaults to the value in `server_or_cluster_def`, if specified. Otherwise defaults to `"grpc"`. config: (Options.) A `tf.ConfigProto` that specifies default configuration options for all sessions that run on this server. start: (Optional.) Boolean, indicating whether to start the server after creating it. Defaults to `True`. Raises: tf.errors.OpError: Or one of its subclasses if an error occurs while creating the TensorFlow server. """ self._server_def = _make_server_def(server_or_cluster_def, job_name, task_index, protocol, config) with errors.raise_exception_on_not_ok_status() as status: self._server = pywrap_tensorflow.PyServer_New( self._server_def.SerializeToString(), status) if start: self.start()
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https://github.com/natanielruiz/android-yolo/blob/1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f/jni-build/jni/include/tensorflow/python/training/server_lib.py#L114-L155
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/richtext.py
python
RichTextBuffer.EndBold
(*args, **kwargs)
return _richtext.RichTextBuffer_EndBold(*args, **kwargs)
EndBold(self) -> bool
EndBold(self) -> bool
[ "EndBold", "(", "self", ")", "-", ">", "bool" ]
def EndBold(*args, **kwargs): """EndBold(self) -> bool""" return _richtext.RichTextBuffer_EndBold(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/richtext.py#L2337-L2339
apache/incubator-mxnet
f03fb23f1d103fec9541b5ae59ee06b1734a51d9
python/mxnet/image/detection.py
python
DetRandomCropAug.__call__
(self, src, label)
return (src, label)
Augmenter implementation body
Augmenter implementation body
[ "Augmenter", "implementation", "body" ]
def __call__(self, src, label): """Augmenter implementation body""" crop = self._random_crop_proposal(label, src.shape[0], src.shape[1]) if crop: x, y, w, h, label = crop src = fixed_crop(src, x, y, w, h, None) return (src, label)
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https://github.com/apache/incubator-mxnet/blob/f03fb23f1d103fec9541b5ae59ee06b1734a51d9/python/mxnet/image/detection.py#L206-L212
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/distribute/cross_device_ops.py
python
_ConcatAndSplitPacker.pack
(self, grouped_grads_and_vars)
return device_grad_packs
Pack tensors.
Pack tensors.
[ "Pack", "tensors", "." ]
def pack(self, grouped_grads_and_vars): """Pack tensors.""" self.grouped_grads_and_vars = grouped_grads_and_vars self.all_device_shapes = [] self.all_device_sizes = [] device_grad_packs = [] for device_grads_and_vars in grouped_grads_and_vars: with ops.colocate_with(device_grads_and_vars[0][0]): # Flatten all the grads. flat_grads = [ array_ops.reshape(g, [-1]) for g, _ in device_grads_and_vars ] # Remember the original shape of all the grads. device_shapes = [array_ops.shape(g) for g, _ in device_grads_and_vars] # Remember the original sizes of all the grads. device_sizes = [array_ops.size(g) for g, _ in device_grads_and_vars] # Concat all the flat grads into a big flat tensor. concat_grads = array_ops.concat(flat_grads, 0) # Split the big tensor into num_splits packs. In cases where the # total size is not divisible num_splits, the last pack gets # more elements. # TODO(zhengxq): it is also possible to optimize away all the concat # as well. num_splits = self.num_packs # The array_ops.size function will sometimes remove static shapes. So if # all gradient shapes are defined, we use another method to get the # total size. # TODO(yuefengz): move this logic to array_ops.size. if all(g.shape.is_fully_defined() for g, _ in device_grads_and_vars): total_grad_size = sum( [g.shape.num_elements() for g, _ in device_grads_and_vars]) else: total_grad_size = array_ops.size(concat_grads) split_size = total_grad_size // num_splits split_size_last = total_grad_size - split_size * (num_splits - 1) split_sizes = [split_size] * (num_splits - 1) + [split_size_last] grad_packs = array_ops.split(concat_grads, split_sizes) # Ready to aggregate the repacked gradients, with fake variables. # TODO(zhengxq): It is hacky to have to use fake variables. # We should remove the need for variables in # aggregate_gradients_using*. device_grad_packs.append(zip(grad_packs, [None] * num_splits)) self.all_device_shapes.append(device_shapes) self.all_device_sizes.append(device_sizes) return device_grad_packs
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/distribute/cross_device_ops.py#L726-L776
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib2to3/pytree.py
python
WildcardPattern.__init__
(self, content=None, min=0, max=HUGE, name=None)
Initializer. Args: content: optional sequence of subsequences of patterns; if absent, matches one node; if present, each subsequence is an alternative [*] min: optional minimum number of times to match, default 0 max: optional maximum number of times to match, default HUGE name: optional name assigned to this match [*] Thus, if content is [[a, b, c], [d, e], [f, g, h]] this is equivalent to (a b c | d e | f g h); if content is None, this is equivalent to '.' in regular expression terms. The min and max parameters work as follows: min=0, max=maxint: .* min=1, max=maxint: .+ min=0, max=1: .? min=1, max=1: . If content is not None, replace the dot with the parenthesized list of alternatives, e.g. (a b c | d e | f g h)*
Initializer.
[ "Initializer", "." ]
def __init__(self, content=None, min=0, max=HUGE, name=None): """ Initializer. Args: content: optional sequence of subsequences of patterns; if absent, matches one node; if present, each subsequence is an alternative [*] min: optional minimum number of times to match, default 0 max: optional maximum number of times to match, default HUGE name: optional name assigned to this match [*] Thus, if content is [[a, b, c], [d, e], [f, g, h]] this is equivalent to (a b c | d e | f g h); if content is None, this is equivalent to '.' in regular expression terms. The min and max parameters work as follows: min=0, max=maxint: .* min=1, max=maxint: .+ min=0, max=1: .? min=1, max=1: . If content is not None, replace the dot with the parenthesized list of alternatives, e.g. (a b c | d e | f g h)* """ assert 0 <= min <= max <= HUGE, (min, max) if content is not None: content = tuple(map(tuple, content)) # Protect against alterations # Check sanity of alternatives assert len(content), repr(content) # Can't have zero alternatives for alt in content: assert len(alt), repr(alt) # Can have empty alternatives self.content = content self.min = min self.max = max self.name = name
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib2to3/pytree.py#L653-L686
jiaxiang-wu/quantized-cnn
4d020e17026df90e40111d219e3eb74e0afb1588
cpplint.py
python
NestingState.InExternC
(self)
return self.stack and isinstance(self.stack[-1], _ExternCInfo)
Check if we are currently one level inside an 'extern "C"' block. Returns: True if top of the stack is an extern block, False otherwise.
Check if we are currently one level inside an 'extern "C"' block.
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def InExternC(self): """Check if we are currently one level inside an 'extern "C"' block. Returns: True if top of the stack is an extern block, False otherwise. """ return self.stack and isinstance(self.stack[-1], _ExternCInfo)
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https://github.com/jiaxiang-wu/quantized-cnn/blob/4d020e17026df90e40111d219e3eb74e0afb1588/cpplint.py#L2242-L2248
PlatformLab/Arachne
e67391471007174dd4002dc2c160628e19c284e8
scripts/cpplint.py
python
ParseNolintSuppressions
(filename, raw_line, linenum, error)
Updates the global list of line error-suppressions. Parses any NOLINT comments on the current line, updating the global error_suppressions store. Reports an error if the NOLINT comment was malformed. Args: filename: str, the name of the input file. raw_line: str, the line of input text, with comments. linenum: int, the number of the current line. error: function, an error handler.
Updates the global list of line error-suppressions.
[ "Updates", "the", "global", "list", "of", "line", "error", "-", "suppressions", "." ]
def ParseNolintSuppressions(filename, raw_line, linenum, error): """Updates the global list of line error-suppressions. Parses any NOLINT comments on the current line, updating the global error_suppressions store. Reports an error if the NOLINT comment was malformed. Args: filename: str, the name of the input file. raw_line: str, the line of input text, with comments. linenum: int, the number of the current line. error: function, an error handler. """ matched = Search(r'\bNOLINT(NEXTLINE)?\b(\([^)]+\))?', raw_line) if matched: if matched.group(1): suppressed_line = linenum + 1 else: suppressed_line = linenum category = matched.group(2) if category in (None, '(*)'): # => "suppress all" _error_suppressions.setdefault(None, set()).add(suppressed_line) else: if category.startswith('(') and category.endswith(')'): category = category[1:-1] if category in _ERROR_CATEGORIES: _error_suppressions.setdefault(category, set()).add(suppressed_line) elif category not in _LEGACY_ERROR_CATEGORIES: error(filename, linenum, 'readability/nolint', 5, 'Unknown NOLINT error category: %s' % category)
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https://github.com/PlatformLab/Arachne/blob/e67391471007174dd4002dc2c160628e19c284e8/scripts/cpplint.py#L571-L600
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/py2/scipy/stats/_continuous_distns.py
python
levy_stable_gen._pdf_from_cf_with_fft
(cf, h=0.01, q=9)
return (x, density)
Calculates pdf from cf using fft. Using region around 0 with N=2**q points separated by distance h. As suggested by [MS].
Calculates pdf from cf using fft. Using region around 0 with N=2**q points separated by distance h. As suggested by [MS].
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def _pdf_from_cf_with_fft(cf, h=0.01, q=9): """Calculates pdf from cf using fft. Using region around 0 with N=2**q points separated by distance h. As suggested by [MS]. """ N = 2**q n = np.arange(1,N+1) density = ((-1)**(n-1-N/2))*np.fft.fft(((-1)**(n-1))*cf(2*np.pi*(n-1-N/2)/h/N))/h/N x = (n-1-N/2)*h return (x, density)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py2/scipy/stats/_continuous_distns.py#L3804-L3812
SmingHub/Sming
cde389ed030905694983121a32f9028976b57194
Sming/Components/Storage/Tools/hwconfig/common.py
python
fixpath
(path)
return path
Paths in Windows can get a little weird
Paths in Windows can get a little weird
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def fixpath(path): """Paths in Windows can get a little weird """ if len(path) > 2 and path[1] != ':' and platform.system() == 'Windows' and path[2] == '/': return path[1] + ':' + path[2:] return path
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https://github.com/SmingHub/Sming/blob/cde389ed030905694983121a32f9028976b57194/Sming/Components/Storage/Tools/hwconfig/common.py#L25-L29
windystrife/UnrealEngine_NVIDIAGameWorks
b50e6338a7c5b26374d66306ebc7807541ff815e
Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/lib-tk/turtle.py
python
RawTurtle.begin_poly
(self)
Start recording the vertices of a polygon. No argument. Start recording the vertices of a polygon. Current turtle position is first point of polygon. Example (for a Turtle instance named turtle): >>> turtle.begin_poly()
Start recording the vertices of a polygon.
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def begin_poly(self): """Start recording the vertices of a polygon. No argument. Start recording the vertices of a polygon. Current turtle position is first point of polygon. Example (for a Turtle instance named turtle): >>> turtle.begin_poly() """ self._poly = [self._position] self._creatingPoly = True
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https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/lib-tk/turtle.py#L3305-L3317
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/windows/Lib/site-packages/requests/utils.py
python
unquote_header_value
(value, is_filename=False)
return value
r"""Unquotes a header value. (Reversal of :func:`quote_header_value`). This does not use the real unquoting but what browsers are actually using for quoting. :param value: the header value to unquote. :rtype: str
r"""Unquotes a header value. (Reversal of :func:`quote_header_value`). This does not use the real unquoting but what browsers are actually using for quoting.
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def unquote_header_value(value, is_filename=False): r"""Unquotes a header value. (Reversal of :func:`quote_header_value`). This does not use the real unquoting but what browsers are actually using for quoting. :param value: the header value to unquote. :rtype: str """ if value and value[0] == value[-1] == '"': # this is not the real unquoting, but fixing this so that the # RFC is met will result in bugs with internet explorer and # probably some other browsers as well. IE for example is # uploading files with "C:\foo\bar.txt" as filename value = value[1:-1] # if this is a filename and the starting characters look like # a UNC path, then just return the value without quotes. Using the # replace sequence below on a UNC path has the effect of turning # the leading double slash into a single slash and then # _fix_ie_filename() doesn't work correctly. See #458. if not is_filename or value[:2] != '\\\\': return value.replace('\\\\', '\\').replace('\\"', '"') return value
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/site-packages/requests/utils.py#L384-L406
hpi-xnor/BMXNet-v2
af2b1859eafc5c721b1397cef02f946aaf2ce20d
python/mxnet/gluon/model_zoo/vision/densenet.py
python
densenet161
(**kwargs)
return get_densenet(161, **kwargs)
r"""Densenet-BC 161-layer model from the `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`_ paper. Parameters ---------- pretrained : bool, default False Whether to load the pretrained weights for model. ctx : Context, default CPU The context in which to load the pretrained weights. root : str, default '$MXNET_HOME/models' Location for keeping the model parameters.
r"""Densenet-BC 161-layer model from the `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`_ paper.
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def densenet161(**kwargs): r"""Densenet-BC 161-layer model from the `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`_ paper. Parameters ---------- pretrained : bool, default False Whether to load the pretrained weights for model. ctx : Context, default CPU The context in which to load the pretrained weights. root : str, default '$MXNET_HOME/models' Location for keeping the model parameters. """ return get_densenet(161, **kwargs)
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https://github.com/hpi-xnor/BMXNet-v2/blob/af2b1859eafc5c721b1397cef02f946aaf2ce20d/python/mxnet/gluon/model_zoo/vision/densenet.py#L163-L176
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/scipy/stats/stats.py
python
tmin
(a, lowerlimit=None, axis=0, inclusive=True, nan_policy='propagate')
return res
Compute the trimmed minimum This function finds the miminum value of an array `a` along the specified axis, but only considering values greater than a specified lower limit. Parameters ---------- a : array_like array of values lowerlimit : None or float, optional Values in the input array less than the given limit will be ignored. When lowerlimit is None, then all values are used. The default value is None. axis : int or None, optional Axis along which to operate. Default is 0. If None, compute over the whole array `a`. inclusive : {True, False}, optional This flag determines whether values exactly equal to the lower limit are included. The default value is True. nan_policy : {'propagate', 'raise', 'omit'}, optional Defines how to handle when input contains nan. 'propagate' returns nan, 'raise' throws an error, 'omit' performs the calculations ignoring nan values. Default is 'propagate'. Returns ------- tmin : float, int or ndarray Examples -------- >>> from scipy import stats >>> x = np.arange(20) >>> stats.tmin(x) 0 >>> stats.tmin(x, 13) 13 >>> stats.tmin(x, 13, inclusive=False) 14
Compute the trimmed minimum
[ "Compute", "the", "trimmed", "minimum" ]
def tmin(a, lowerlimit=None, axis=0, inclusive=True, nan_policy='propagate'): """ Compute the trimmed minimum This function finds the miminum value of an array `a` along the specified axis, but only considering values greater than a specified lower limit. Parameters ---------- a : array_like array of values lowerlimit : None or float, optional Values in the input array less than the given limit will be ignored. When lowerlimit is None, then all values are used. The default value is None. axis : int or None, optional Axis along which to operate. Default is 0. If None, compute over the whole array `a`. inclusive : {True, False}, optional This flag determines whether values exactly equal to the lower limit are included. The default value is True. nan_policy : {'propagate', 'raise', 'omit'}, optional Defines how to handle when input contains nan. 'propagate' returns nan, 'raise' throws an error, 'omit' performs the calculations ignoring nan values. Default is 'propagate'. Returns ------- tmin : float, int or ndarray Examples -------- >>> from scipy import stats >>> x = np.arange(20) >>> stats.tmin(x) 0 >>> stats.tmin(x, 13) 13 >>> stats.tmin(x, 13, inclusive=False) 14 """ a, axis = _chk_asarray(a, axis) am = _mask_to_limits(a, (lowerlimit, None), (inclusive, False)) contains_nan, nan_policy = _contains_nan(am, nan_policy) if contains_nan and nan_policy == 'omit': am = ma.masked_invalid(am) res = ma.minimum.reduce(am, axis).data if res.ndim == 0: return res[()] return res
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/stats/stats.py#L594-L650
eclipse/omr
056e7c9ce9d503649190bc5bd9931fac30b4e4bc
jitbuilder/apigen/genutils.py
python
APIService.sets_allocators
(self)
return "sets-allocators" in self.__flags()
Returns whether the service sets class allocators.
Returns whether the service sets class allocators.
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def sets_allocators(self): """Returns whether the service sets class allocators.""" return "sets-allocators" in self.__flags()
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https://github.com/eclipse/omr/blob/056e7c9ce9d503649190bc5bd9931fac30b4e4bc/jitbuilder/apigen/genutils.py#L196-L198
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/numpy/py2/numpy/core/setup.py
python
is_npy_no_signal
()
return sys.platform == 'win32'
Return True if the NPY_NO_SIGNAL symbol must be defined in configuration header.
Return True if the NPY_NO_SIGNAL symbol must be defined in configuration header.
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def is_npy_no_signal(): """Return True if the NPY_NO_SIGNAL symbol must be defined in configuration header.""" return sys.platform == 'win32'
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/numpy/py2/numpy/core/setup.py#L76-L79
mhammond/pywin32
44afd86ba8485194df93234639243252deeb40d5
com/win32com/servers/interp.py
python
Interpreter.Exec
(self, exp)
Execute a statement.
Execute a statement.
[ "Execute", "a", "statement", "." ]
def Exec(self, exp): """Execute a statement.""" if type(exp) != str: raise Exception(desc="Must be a string", scode=winerror.DISP_E_TYPEMISMATCH) exec(str(exp), self.dict)
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https://github.com/mhammond/pywin32/blob/44afd86ba8485194df93234639243252deeb40d5/com/win32com/servers/interp.py#L39-L43
microsoft/checkedc-clang
a173fefde5d7877b7750e7ce96dd08cf18baebf2
lldb/third_party/Python/module/ptyprocess-0.6.0/ptyprocess/ptyprocess.py
python
PtyProcessUnicode.write
(self, s)
return super(PtyProcessUnicode, self).write(b)
Write the unicode string ``s`` to the pseudoterminal. Returns the number of bytes written.
Write the unicode string ``s`` to the pseudoterminal.
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def write(self, s): """Write the unicode string ``s`` to the pseudoterminal. Returns the number of bytes written. """ b = s.encode(self.encoding) return super(PtyProcessUnicode, self).write(b)
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https://github.com/microsoft/checkedc-clang/blob/a173fefde5d7877b7750e7ce96dd08cf18baebf2/lldb/third_party/Python/module/ptyprocess-0.6.0/ptyprocess/ptyprocess.py#L830-L836
ChromiumWebApps/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
tools/cr/cr/actions/installer.py
python
Installer.Install
(self, context, targets, arguments)
Installs a target somewhere so that it is ready to run.
Installs a target somewhere so that it is ready to run.
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def Install(self, context, targets, arguments): """Installs a target somewhere so that it is ready to run.""" raise NotImplementedError('Must be overridden.')
[ "def", "Install", "(", "self", ",", "context", ",", "targets", ",", "arguments", ")", ":", "raise", "NotImplementedError", "(", "'Must be overridden.'", ")" ]
https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/tools/cr/cr/actions/installer.py#L29-L31
bh107/bohrium
5b83e7117285fefc7779ed0e9acb0f8e74c7e068
thirdparty/pyratemp/pyratemp.py
python
Parser.parse
(self, template)
return self._parse(template)
Parse a template. :Parameters: - `template`: template-unicode-string :Returns: the resulting parse-tree :Exceptions: - `TemplateSyntaxError`: for template-syntax-errors - `TemplateIncludeError`: if template-inclusion failed - `TemplateException`
Parse a template.
[ "Parse", "a", "template", "." ]
def parse(self, template): """Parse a template. :Parameters: - `template`: template-unicode-string :Returns: the resulting parse-tree :Exceptions: - `TemplateSyntaxError`: for template-syntax-errors - `TemplateIncludeError`: if template-inclusion failed - `TemplateException` """ self._includestack = [(None, template)] # for error-messages (_errpos) return self._parse(template)
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https://github.com/bh107/bohrium/blob/5b83e7117285fefc7779ed0e9acb0f8e74c7e068/thirdparty/pyratemp/pyratemp.py#L541-L553
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/richtext.py
python
RichTextCtrl.GetCaretPositionForDefaultStyle
(*args, **kwargs)
return _richtext.RichTextCtrl_GetCaretPositionForDefaultStyle(*args, **kwargs)
GetCaretPositionForDefaultStyle(self) -> long
GetCaretPositionForDefaultStyle(self) -> long
[ "GetCaretPositionForDefaultStyle", "(", "self", ")", "-", ">", "long" ]
def GetCaretPositionForDefaultStyle(*args, **kwargs): """GetCaretPositionForDefaultStyle(self) -> long""" return _richtext.RichTextCtrl_GetCaretPositionForDefaultStyle(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/richtext.py#L4124-L4126
gem5/gem5
141cc37c2d4b93959d4c249b8f7e6a8b2ef75338
ext/ply/example/unicalc/calc.py
python
p_expression_binop
(p)
expression : expression PLUS expression | expression MINUS expression | expression TIMES expression | expression DIVIDE expression
expression : expression PLUS expression | expression MINUS expression | expression TIMES expression | expression DIVIDE expression
[ "expression", ":", "expression", "PLUS", "expression", "|", "expression", "MINUS", "expression", "|", "expression", "TIMES", "expression", "|", "expression", "DIVIDE", "expression" ]
def p_expression_binop(p): '''expression : expression PLUS expression | expression MINUS expression | expression TIMES expression | expression DIVIDE expression''' if p[2] == u'+' : p[0] = p[1] + p[3] elif p[2] == u'-': p[0] = p[1] - p[3] elif p[2] == u'*': p[0] = p[1] * p[3] elif p[2] == u'/': p[0] = p[1] / p[3]
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https://github.com/gem5/gem5/blob/141cc37c2d4b93959d4c249b8f7e6a8b2ef75338/ext/ply/example/unicalc/calc.py#L72-L80
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/_misc.py
python
DateTime.ToGMT
(*args, **kwargs)
return _misc_.DateTime_ToGMT(*args, **kwargs)
ToGMT(self, bool noDST=False) -> DateTime
ToGMT(self, bool noDST=False) -> DateTime
[ "ToGMT", "(", "self", "bool", "noDST", "=", "False", ")", "-", ">", "DateTime" ]
def ToGMT(*args, **kwargs): """ToGMT(self, bool noDST=False) -> DateTime""" return _misc_.DateTime_ToGMT(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_misc.py#L3946-L3948
deepmind/reverb
ef3c8f0be1b720a741d2dee335e15e44668c291a
configure.py
python
reset_configure_bazelrc
()
Reset file that contains customized config settings.
Reset file that contains customized config settings.
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def reset_configure_bazelrc(): """Reset file that contains customized config settings.""" open(_REVERB_BAZELRC, 'w').close()
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https://github.com/deepmind/reverb/blob/ef3c8f0be1b720a741d2dee335e15e44668c291a/configure.py#L229-L231
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/gsutil/third_party/boto/boto/beanstalk/layer1.py
python
Layer1.create_application_version
(self, application_name, version_label, description=None, s3_bucket=None, s3_key=None, auto_create_application=None)
return self._get_response('CreateApplicationVersion', params)
Creates an application version for the specified application. :type application_name: string :param application_name: The name of the application. If no application is found with this name, and AutoCreateApplication is false, returns an InvalidParameterValue error. :type version_label: string :param version_label: A label identifying this version. Constraint: Must be unique per application. If an application version already exists with this label for the specified application, AWS Elastic Beanstalk returns an InvalidParameterValue error. :type description: string :param description: Describes this version. :type s3_bucket: string :param s3_bucket: The Amazon S3 bucket where the data is located. :type s3_key: string :param s3_key: The Amazon S3 key where the data is located. Both s3_bucket and s3_key must be specified in order to use a specific source bundle. If both of these values are not specified the sample application will be used. :type auto_create_application: boolean :param auto_create_application: Determines how the system behaves if the specified application for this version does not already exist: true: Automatically creates the specified application for this version if it does not already exist. false: Returns an InvalidParameterValue if the specified application for this version does not already exist. Default: false Valid Values: true | false :raises: TooManyApplicationsException, TooManyApplicationVersionsException, InsufficientPrivilegesException, S3LocationNotInServiceRegionException
Creates an application version for the specified application.
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def create_application_version(self, application_name, version_label, description=None, s3_bucket=None, s3_key=None, auto_create_application=None): """Creates an application version for the specified application. :type application_name: string :param application_name: The name of the application. If no application is found with this name, and AutoCreateApplication is false, returns an InvalidParameterValue error. :type version_label: string :param version_label: A label identifying this version. Constraint: Must be unique per application. If an application version already exists with this label for the specified application, AWS Elastic Beanstalk returns an InvalidParameterValue error. :type description: string :param description: Describes this version. :type s3_bucket: string :param s3_bucket: The Amazon S3 bucket where the data is located. :type s3_key: string :param s3_key: The Amazon S3 key where the data is located. Both s3_bucket and s3_key must be specified in order to use a specific source bundle. If both of these values are not specified the sample application will be used. :type auto_create_application: boolean :param auto_create_application: Determines how the system behaves if the specified application for this version does not already exist: true: Automatically creates the specified application for this version if it does not already exist. false: Returns an InvalidParameterValue if the specified application for this version does not already exist. Default: false Valid Values: true | false :raises: TooManyApplicationsException, TooManyApplicationVersionsException, InsufficientPrivilegesException, S3LocationNotInServiceRegionException """ params = {'ApplicationName': application_name, 'VersionLabel': version_label} if description: params['Description'] = description if s3_bucket and s3_key: params['SourceBundle.S3Bucket'] = s3_bucket params['SourceBundle.S3Key'] = s3_key if auto_create_application: params['AutoCreateApplication'] = self._encode_bool( auto_create_application) return self._get_response('CreateApplicationVersion', params)
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/third_party/boto/boto/beanstalk/layer1.py#L104-L156
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python3/src/Lib/calendar.py
python
isleap
(year)
return year % 4 == 0 and (year % 100 != 0 or year % 400 == 0)
Return True for leap years, False for non-leap years.
Return True for leap years, False for non-leap years.
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def isleap(year): """Return True for leap years, False for non-leap years.""" return year % 4 == 0 and (year % 100 != 0 or year % 400 == 0)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/calendar.py#L100-L102
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/data/ops/dataset_ops.py
python
from_variant
(variant, structure)
return _VariantDataset(variant, structure)
Constructs a dataset from the given variant and (nested) structure. Args: variant: A scalar `tf.variant` tensor representing a dataset. structure: A (nested) structure of `tf.TypeSpec` objects representing the structure of each element in the dataset. Returns: A `tf.data.Dataset` instance.
Constructs a dataset from the given variant and (nested) structure.
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def from_variant(variant, structure): """Constructs a dataset from the given variant and (nested) structure. Args: variant: A scalar `tf.variant` tensor representing a dataset. structure: A (nested) structure of `tf.TypeSpec` objects representing the structure of each element in the dataset. Returns: A `tf.data.Dataset` instance. """ return _VariantDataset(variant, structure)
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/data/ops/dataset_ops.py#L4277-L4288
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/mapreduce/mapreduce/datastore_range_iterators.py
python
AbstractKeyRangeIterator.__iter__
(self)
Iter.
Iter.
[ "Iter", "." ]
def __iter__(self): """Iter.""" raise NotImplementedError()
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/mapreduce/mapreduce/datastore_range_iterators.py#L384-L386
maidsafe-archive/MaidSafe
defd65e1c8cfb6a1cbdeaaa0eee31d065421792d
tools/cpplint.py
python
ParseNolintSuppressions
(filename, raw_line, linenum, error)
Updates the global list of error-suppressions. Parses any NOLINT comments on the current line, updating the global error_suppressions store. Reports an error if the NOLINT comment was malformed. Args: filename: str, the name of the input file. raw_line: str, the line of input text, with comments. linenum: int, the number of the current line. error: function, an error handler.
Updates the global list of error-suppressions.
[ "Updates", "the", "global", "list", "of", "error", "-", "suppressions", "." ]
def ParseNolintSuppressions(filename, raw_line, linenum, error): """Updates the global list of error-suppressions. Parses any NOLINT comments on the current line, updating the global error_suppressions store. Reports an error if the NOLINT comment was malformed. Args: filename: str, the name of the input file. raw_line: str, the line of input text, with comments. linenum: int, the number of the current line. error: function, an error handler. """ # FIXME(adonovan): "NOLINT(" is misparsed as NOLINT(*). matched = _RE_SUPPRESSION.search(raw_line) if matched: category = matched.group(1) if category in (None, '(*)'): # => "suppress all" _error_suppressions.setdefault(None, set()).add(linenum) else: if category.startswith('(') and category.endswith(')'): category = category[1:-1] if category in _ERROR_CATEGORIES: _error_suppressions.setdefault(category, set()).add(linenum) else: error(filename, linenum, 'readability/nolint', 5, 'Unknown NOLINT error category: %s' % category)
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https://github.com/maidsafe-archive/MaidSafe/blob/defd65e1c8cfb6a1cbdeaaa0eee31d065421792d/tools/cpplint.py#L363-L389
pytorch/pytorch
7176c92687d3cc847cc046bf002269c6949a21c2
benchmarks/distributed/rpc/parameter_server/server/server.py
python
ParameterServerBase.record_straggler_start
(self, key, cuda=True)
r""" A helper method that records a straggler metric for the given key. A user should call this when the first gradient for the param location is received. Args: key (str): unique id for metric within a group cuda (bool): indicator to determine if this is a CUDA metric
r""" A helper method that records a straggler metric for the given key. A user should call this when the first gradient for the param location is received. Args: key (str): unique id for metric within a group cuda (bool): indicator to determine if this is a CUDA metric
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def record_straggler_start(self, key, cuda=True): r""" A helper method that records a straggler metric for the given key. A user should call this when the first gradient for the param location is received. Args: key (str): unique id for metric within a group cuda (bool): indicator to determine if this is a CUDA metric """ self.__metrics_logger.record_start( self.PARAMETER_SERVER_STRAGGLER_METRIC, key, self.PARAM_INDEX_STRAGGLER, cuda )
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https://github.com/pytorch/pytorch/blob/7176c92687d3cc847cc046bf002269c6949a21c2/benchmarks/distributed/rpc/parameter_server/server/server.py#L82-L96
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py
python
CallWrapper.__init__
(self, func, subst, widget)
Store FUNC, SUBST and WIDGET as members.
Store FUNC, SUBST and WIDGET as members.
[ "Store", "FUNC", "SUBST", "and", "WIDGET", "as", "members", "." ]
def __init__(self, func, subst, widget): """Store FUNC, SUBST and WIDGET as members.""" self.func = func self.subst = subst self.widget = widget
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py#L1460-L1464
eclipse/omr
056e7c9ce9d503649190bc5bd9931fac30b4e4bc
jitbuilder/apigen/cppgen.py
python
CppGenerator.get_impl_type
(self, c)
return "{} *".format(self.get_impl_class_name(c.as_class())) if c.is_class() else self.builtin_type_map[c.name()]
Returns the C++ type to be used in the JitBuilder implementation for a given type name, prefixing with a given namespace if needed.
Returns the C++ type to be used in the JitBuilder implementation for a given type name, prefixing with a given namespace if needed.
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def get_impl_type(self, c): """ Returns the C++ type to be used in the JitBuilder implementation for a given type name, prefixing with a given namespace if needed. """ return "{} *".format(self.get_impl_class_name(c.as_class())) if c.is_class() else self.builtin_type_map[c.name()]
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https://github.com/eclipse/omr/blob/056e7c9ce9d503649190bc5bd9931fac30b4e4bc/jitbuilder/apigen/cppgen.py#L154-L159
benoitsteiner/tensorflow-opencl
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
tensorflow/python/ops/data_flow_ops.py
python
SparseConditionalAccumulator.take_indexed_slices_grad
(self, num_required, name=None)
return ops.IndexedSlices( indices=return_val.indices, values=return_val.values, dense_shape=return_val.shape)
Attempts to extract the average gradient from the accumulator. The operation blocks until sufficient number of gradients have been successfully applied to the accumulator. Once successful, the following actions are also triggered: - Counter of accumulated gradients is reset to 0. - Aggregated gradient is reset to 0 tensor. - Accumulator's internal time step is incremented by 1. Args: num_required: Number of gradients that needs to have been aggregated name: Optional name for the operation Returns: An IndexedSlices holding the value of the average gradient. Raises: InvalidArgumentError: If num_required < 1
Attempts to extract the average gradient from the accumulator.
[ "Attempts", "to", "extract", "the", "average", "gradient", "from", "the", "accumulator", "." ]
def take_indexed_slices_grad(self, num_required, name=None): """Attempts to extract the average gradient from the accumulator. The operation blocks until sufficient number of gradients have been successfully applied to the accumulator. Once successful, the following actions are also triggered: - Counter of accumulated gradients is reset to 0. - Aggregated gradient is reset to 0 tensor. - Accumulator's internal time step is incremented by 1. Args: num_required: Number of gradients that needs to have been aggregated name: Optional name for the operation Returns: An IndexedSlices holding the value of the average gradient. Raises: InvalidArgumentError: If num_required < 1 """ return_val = gen_data_flow_ops.sparse_accumulator_take_gradient( self._accumulator_ref, num_required, dtype=self._dtype, name=name) return ops.IndexedSlices( indices=return_val.indices, values=return_val.values, dense_shape=return_val.shape)
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https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/ops/data_flow_ops.py#L1365-L1391
gem5/gem5
141cc37c2d4b93959d4c249b8f7e6a8b2ef75338
ext/ply/example/ansic/cparse.py
python
p_direct_declarator_5
(t)
direct_declarator : direct_declarator LPAREN identifier_list RPAREN
direct_declarator : direct_declarator LPAREN identifier_list RPAREN
[ "direct_declarator", ":", "direct_declarator", "LPAREN", "identifier_list", "RPAREN" ]
def p_direct_declarator_5(t): 'direct_declarator : direct_declarator LPAREN identifier_list RPAREN ' pass
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https://github.com/gem5/gem5/blob/141cc37c2d4b93959d4c249b8f7e6a8b2ef75338/ext/ply/example/ansic/cparse.py#L289-L291
rapidsai/cudf
d5b2448fc69f17509304d594f029d0df56984962
python/cudf/cudf/core/dataframe.py
python
DataFrame.isin
(self, values)
Whether each element in the DataFrame is contained in values. Parameters ---------- values : iterable, Series, DataFrame or dict The result will only be true at a location if all the labels match. If values is a Series, that’s the index. If values is a dict, the keys must be the column names, which must match. If values is a DataFrame, then both the index and column labels must match. Returns ------- DataFrame: DataFrame of booleans showing whether each element in the DataFrame is contained in values. Examples -------- >>> import cudf >>> df = cudf.DataFrame({'num_legs': [2, 4], 'num_wings': [2, 0]}, ... index=['falcon', 'dog']) >>> df num_legs num_wings falcon 2 2 dog 4 0 When ``values`` is a list check whether every value in the DataFrame is present in the list (which animals have 0 or 2 legs or wings) >>> df.isin([0, 2]) num_legs num_wings falcon True True dog False True When ``values`` is a dict, we can pass values to check for each column separately: >>> df.isin({'num_wings': [0, 3]}) num_legs num_wings falcon False False dog False True When ``values`` is a Series or DataFrame the index and column must match. Note that 'falcon' does not match based on the number of legs in other. >>> other = cudf.DataFrame({'num_legs': [8, 2], 'num_wings': [0, 2]}, ... index=['spider', 'falcon']) >>> df.isin(other) num_legs num_wings falcon True True dog False False
Whether each element in the DataFrame is contained in values.
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def isin(self, values): """ Whether each element in the DataFrame is contained in values. Parameters ---------- values : iterable, Series, DataFrame or dict The result will only be true at a location if all the labels match. If values is a Series, that’s the index. If values is a dict, the keys must be the column names, which must match. If values is a DataFrame, then both the index and column labels must match. Returns ------- DataFrame: DataFrame of booleans showing whether each element in the DataFrame is contained in values. Examples -------- >>> import cudf >>> df = cudf.DataFrame({'num_legs': [2, 4], 'num_wings': [2, 0]}, ... index=['falcon', 'dog']) >>> df num_legs num_wings falcon 2 2 dog 4 0 When ``values`` is a list check whether every value in the DataFrame is present in the list (which animals have 0 or 2 legs or wings) >>> df.isin([0, 2]) num_legs num_wings falcon True True dog False True When ``values`` is a dict, we can pass values to check for each column separately: >>> df.isin({'num_wings': [0, 3]}) num_legs num_wings falcon False False dog False True When ``values`` is a Series or DataFrame the index and column must match. Note that 'falcon' does not match based on the number of legs in other. >>> other = cudf.DataFrame({'num_legs': [8, 2], 'num_wings': [0, 2]}, ... index=['spider', 'falcon']) >>> df.isin(other) num_legs num_wings falcon True True dog False False """ if isinstance(values, dict): result_df = DataFrame() for col in self._data.names: if col in values: val = values[col] result_df[col] = self._data[col].isin(val) else: result_df[col] = column.full( size=len(self), fill_value=False, dtype="bool" ) result_df.index = self.index return result_df elif isinstance(values, Series): values = values.reindex(self.index) result = DataFrame() # TODO: propagate nulls through isin # https://github.com/rapidsai/cudf/issues/7556 for col in self._data.names: if isinstance( self[col]._column, cudf.core.column.CategoricalColumn ) and isinstance( values._column, cudf.core.column.CategoricalColumn ): res = (self._data[col] == values._column).fillna(False) result[col] = res elif ( isinstance( self[col]._column, cudf.core.column.CategoricalColumn ) or np.issubdtype(self[col].dtype, cudf.dtype("object")) ) or ( isinstance( values._column, cudf.core.column.CategoricalColumn ) or np.issubdtype(values.dtype, cudf.dtype("object")) ): result[col] = utils.scalar_broadcast_to(False, len(self)) else: result[col] = (self._data[col] == values._column).fillna( False ) result.index = self.index return result elif isinstance(values, DataFrame): values = values.reindex(self.index) result = DataFrame() for col in self._data.names: if col in values.columns: result[col] = ( self._data[col] == values[col]._column ).fillna(False) else: result[col] = utils.scalar_broadcast_to(False, len(self)) result.index = self.index return result else: if not is_list_like(values): raise TypeError( f"only list-like or dict-like objects are " f"allowed to be passed to DataFrame.isin(), " f"you passed a " f"'{type(values).__name__}'" ) result_df = DataFrame() for col in self._data.names: result_df[col] = self._data[col].isin(values) result_df.index = self.index return result_df
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https://github.com/rapidsai/cudf/blob/d5b2448fc69f17509304d594f029d0df56984962/python/cudf/cudf/core/dataframe.py#L4993-L5125
trilinos/Trilinos
6168be6dd51e35e1cd681e9c4b24433e709df140
packages/seacas/libraries/ioss/src/visualization/catalyst/phactori/PhactoriDriver.py
python
GetXyzForNodeOrElementParallelOneBlock
(inInputCsData, inIdIsNode, inGlobalId, outXyz)
check for inGlobalId and set outXyz if present\n\n utility function called by GetXyzForNodeOrElementParallelRecurse1, this\n takes one unstructured grid as input, and sees if it has the node or element\n with id inGlobalId. If it does, the method sets outXyz to the geometric\n location of the node (xyz) or center of the element bounding box (xyz) and\n returns true, otherwise it returns false without changing outXyz\n
check for inGlobalId and set outXyz if present\n\n utility function called by GetXyzForNodeOrElementParallelRecurse1, this\n takes one unstructured grid as input, and sees if it has the node or element\n with id inGlobalId. If it does, the method sets outXyz to the geometric\n location of the node (xyz) or center of the element bounding box (xyz) and\n returns true, otherwise it returns false without changing outXyz\n
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def GetXyzForNodeOrElementParallelOneBlock(inInputCsData, inIdIsNode, inGlobalId, outXyz): "check for inGlobalId and set outXyz if present\n\n utility function called by GetXyzForNodeOrElementParallelRecurse1, this\n takes one unstructured grid as input, and sees if it has the node or element\n with id inGlobalId. If it does, the method sets outXyz to the geometric\n location of the node (xyz) or center of the element bounding box (xyz) and\n returns true, otherwise it returns false without changing outXyz\n " if PhactoriDbg(100): myDebugPrint3('GetXyzForNodeOrElementParallelOneBlock entered\n', 100) globalIdArray = None if inIdIsNode: ptOrElData = inInputCsData.GetPointData() globalIdArray = ptOrElData.GetArray('GlobalNodeId') else: ptOrElData = inInputCsData.GetCellData() globalIdArray = ptOrElData.GetArray('GlobalElementId') if globalIdArray == None: if PhactoriDbg(): myDebugPrint3(" this process/block has no Global Node or Element Id array to contain " + str(inGlobalId) + "\n") return False numTuples = globalIdArray.GetNumberOfTuples() thisProcessHasTheId = False idIndex = -1 for ii in range(0, numTuples): #myDebugPrint3(" testing " + str(ii) + " against " + str(inGlobalNodeId) + "\n") #myDebugPrint3(" type array: " + str(type(globalNodeIdArray)) + " type ii:" + str(type(ii)) + "\n") vv = globalIdArray.GetTuple1(ii) if vv == inGlobalId: thisProcessHasTheId = True idIndex = ii break if not thisProcessHasTheId: if PhactoriDbg(): myDebugPrint3(" this process/block doesn't contain id" + \ str(inGlobalId) + "\n") return False if PhactoriDbg(): myDebugPrint3(" this process/block contains id " + str(inGlobalId) + "\n") if inIdIsNode: pointsArray = inInputCsData.GetPoints() numPoints = pointsArray.GetNumberOfPoints() if idIndex >= numPoints: if PhactoriDbg(): myDebugPrint3(" this process/block has problem with index, setting xyz 0\n") outXyz[0] = 0.0 outXyz[1] = 0.0 outXyz[2] = 0.0 return False thePoint = pointsArray.GetPoint(idIndex, outXyz) if PhactoriDbg(): myDebugPrint3(" outXyz set to: " + str(outXyz) + "\n") return True else: myBounds = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0] #myCells = inInputCsData.GetCells() #oneCell = myCells.GetCell(idIndex) oneCell = inInputCsData.GetCell(idIndex) oneCell.GetBounds(myBounds) #myCells.GetCellBounds(idIndex, myBounds) #ptOrElData.GetCellBounds(idIndex, myBounds) outXyz[0] = 0.5 * (myBounds[0] + myBounds[1]) outXyz[1] = 0.5 * (myBounds[2] + myBounds[3]) outXyz[2] = 0.5 * (myBounds[4] + myBounds[5]) #xmin, xmax, ymin, ymax, zmin, zmax = myCells.GetCellBounds(idIndex) #outXyz[0] = 0.5 * (xmin + xmax) #outXyz[1] = 0.5 * (ymin + ymax) #outXyz[2] = 0.5 * (zmin + zmax) return True
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https://github.com/trilinos/Trilinos/blob/6168be6dd51e35e1cd681e9c4b24433e709df140/packages/seacas/libraries/ioss/src/visualization/catalyst/phactori/PhactoriDriver.py#L3999-L4071
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/msw/grid.py
python
Grid.GetDefaultCellTextColour
(*args, **kwargs)
return _grid.Grid_GetDefaultCellTextColour(*args, **kwargs)
GetDefaultCellTextColour(self) -> Colour
GetDefaultCellTextColour(self) -> Colour
[ "GetDefaultCellTextColour", "(", "self", ")", "-", ">", "Colour" ]
def GetDefaultCellTextColour(*args, **kwargs): """GetDefaultCellTextColour(self) -> Colour""" return _grid.Grid_GetDefaultCellTextColour(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/grid.py#L1778-L1780
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/py2/scipy/signal/ltisys.py
python
_order_complex_poles
(poles)
return ordered_poles
Check we have complex conjugates pairs and reorder P according to YT, ie real_poles, complex_i, conjugate complex_i, .... The lexicographic sort on the complex poles is added to help the user to compare sets of poles.
Check we have complex conjugates pairs and reorder P according to YT, ie real_poles, complex_i, conjugate complex_i, .... The lexicographic sort on the complex poles is added to help the user to compare sets of poles.
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def _order_complex_poles(poles): """ Check we have complex conjugates pairs and reorder P according to YT, ie real_poles, complex_i, conjugate complex_i, .... The lexicographic sort on the complex poles is added to help the user to compare sets of poles. """ ordered_poles = np.sort(poles[np.isreal(poles)]) im_poles = [] for p in np.sort(poles[np.imag(poles) < 0]): if np.conj(p) in poles: im_poles.extend((p, np.conj(p))) ordered_poles = np.hstack((ordered_poles, im_poles)) if poles.shape[0] != len(ordered_poles): raise ValueError("Complex poles must come with their conjugates") return ordered_poles
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py2/scipy/signal/ltisys.py#L2548-L2565
nasa/astrobee
9241e67e6692810d6e275abb3165b6d02f4ca5ef
scripts/git/cpplint.py
python
CheckRValueReference
(filename, clean_lines, linenum, nesting_state, error)
Check for rvalue references. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. nesting_state: A NestingState instance which maintains information about the current stack of nested blocks being parsed. error: The function to call with any errors found.
Check for rvalue references.
[ "Check", "for", "rvalue", "references", "." ]
def CheckRValueReference(filename, clean_lines, linenum, nesting_state, error): """Check for rvalue references. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. nesting_state: A NestingState instance which maintains information about the current stack of nested blocks being parsed. error: The function to call with any errors found. """ # Find lines missing spaces around &&. # TODO(unknown): currently we don't check for rvalue references # with spaces surrounding the && to avoid false positives with # boolean expressions. line = clean_lines.elided[linenum] match = Match(r"^(.*\S)&&", line) if not match: match = Match(r"(.*)&&\S", line) if (not match) or "(&&)" in line or Search(r"\boperator\s*$", match.group(1)): return # Either poorly formed && or an rvalue reference, check the context # to get a more accurate error message. Mostly we want to determine # if what's to the left of "&&" is a type or not. and_pos = len(match.group(1)) if IsRValueType(clean_lines, nesting_state, linenum, and_pos): if not IsRValueAllowed(clean_lines, linenum): error( filename, linenum, "build/c++11", 3, "RValue references are an unapproved C++ feature.", ) else: error(filename, linenum, "whitespace/operators", 3, "Missing spaces around &&")
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https://github.com/nasa/astrobee/blob/9241e67e6692810d6e275abb3165b6d02f4ca5ef/scripts/git/cpplint.py#L4049-L4085
InsightSoftwareConsortium/ITK
87acfce9a93d928311c38bc371b666b515b9f19d
Modules/ThirdParty/pygccxml/src/pygccxml/parser/directory_cache.py
python
filename_repository_t.release_filename
(self, id_)
Release a file name.
Release a file name.
[ "Release", "a", "file", "name", "." ]
def release_filename(self, id_): """Release a file name. """ entry = self.__entries.get(id_) if entry is None: raise ValueError("Invalid filename id (%d)" % id_) # Decrease reference count and check if the entry has to be removed... if entry.dec_ref_count() == 0: del self.__entries[id_] del self.__id_lut[entry.filename]
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https://github.com/InsightSoftwareConsortium/ITK/blob/87acfce9a93d928311c38bc371b666b515b9f19d/Modules/ThirdParty/pygccxml/src/pygccxml/parser/directory_cache.py#L486-L497
carla-simulator/carla
8854804f4d7748e14d937ec763a2912823a7e5f5
PythonAPI/carla/agents/navigation/local_planner.py
python
LocalPlanner.reset_vehicle
(self)
Reset the ego-vehicle
Reset the ego-vehicle
[ "Reset", "the", "ego", "-", "vehicle" ]
def reset_vehicle(self): """Reset the ego-vehicle""" self._vehicle = None
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https://github.com/carla-simulator/carla/blob/8854804f4d7748e14d937ec763a2912823a7e5f5/PythonAPI/carla/agents/navigation/local_planner.py#L110-L112
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python/src/Lib/mailbox.py
python
Mailbox.get_message
(self, key)
Return a Message representation or raise a KeyError.
Return a Message representation or raise a KeyError.
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def get_message(self, key): """Return a Message representation or raise a KeyError.""" raise NotImplementedError('Method must be implemented by subclass')
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/mailbox.py#L84-L86
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/keras/layers/recurrent.py
python
_generate_zero_filled_state
(batch_size_tensor, state_size, dtype)
Generate a zero filled tensor with shape [batch_size, state_size].
Generate a zero filled tensor with shape [batch_size, state_size].
[ "Generate", "a", "zero", "filled", "tensor", "with", "shape", "[", "batch_size", "state_size", "]", "." ]
def _generate_zero_filled_state(batch_size_tensor, state_size, dtype): """Generate a zero filled tensor with shape [batch_size, state_size].""" if batch_size_tensor is None or dtype is None: raise ValueError( 'batch_size and dtype cannot be None while constructing initial state: ' 'batch_size={}, dtype={}'.format(batch_size_tensor, dtype)) def create_zeros(unnested_state_size): flat_dims = tensor_shape.as_shape(unnested_state_size).as_list() init_state_size = [batch_size_tensor] + flat_dims return array_ops.zeros(init_state_size, dtype=dtype) if nest.is_sequence(state_size): return nest.map_structure(create_zeros, state_size) else: return create_zeros(state_size)
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/keras/layers/recurrent.py#L2755-L2770
mindspore-ai/mindspore
fb8fd3338605bb34fa5cea054e535a8b1d753fab
mindspore/python/mindspore/dataset/core/validator_helpers.py
python
check_gnn_list_of_pair_or_ndarray
(param, param_name)
Check if the input parameter is a list of tuple or numpy.ndarray. Args: param (Union[list[tuple], nd.ndarray]): param. param_name (str): param_name. Returns: Exception: TypeError if error.
Check if the input parameter is a list of tuple or numpy.ndarray.
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def check_gnn_list_of_pair_or_ndarray(param, param_name): """ Check if the input parameter is a list of tuple or numpy.ndarray. Args: param (Union[list[tuple], nd.ndarray]): param. param_name (str): param_name. Returns: Exception: TypeError if error. """ type_check(param, (list, np.ndarray), param_name) if isinstance(param, list): param_names = ["node_list[{0}]".format(i) for i in range(len(param))] type_check_list(param, (tuple,), param_names) for idx, pair in enumerate(param): if not len(pair) == 2: raise ValueError("Each member in {0} must be a pair which means length == 2. Got length {1}".format( param_names[idx], len(pair))) column_names = ["node_list[{0}], number #{1} element".format(idx, i+1) for i in range(len(pair))] type_check_list(pair, (int,), column_names) elif isinstance(param, np.ndarray): if param.ndim != 2: raise ValueError("Input ndarray must be in dimension 2. Got {0}".format(param.ndim)) if param.shape[1] != 2: raise ValueError("Each member in {0} must be a pair which means length == 2. Got length {1}".format( param_name, param.shape[1])) if not param.dtype == np.int32: raise TypeError("Each member in {0} should be of type int32. Got {1}.".format( param_name, param.dtype))
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https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/dataset/core/validator_helpers.py#L682-L711
microsoft/TSS.MSR
0f2516fca2cd9929c31d5450e39301c9bde43688
TSS.Py/src/TpmTypes.py
python
_PRIVATE.toTpm
(self, buf)
TpmMarshaller method
TpmMarshaller method
[ "TpmMarshaller", "method" ]
def toTpm(self, buf): """ TpmMarshaller method """ buf.writeSizedByteBuf(self.integrityOuter) buf.writeSizedByteBuf(self.integrityInner) buf.writeSizedObj(self.sensitive)
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https://github.com/microsoft/TSS.MSR/blob/0f2516fca2cd9929c31d5450e39301c9bde43688/TSS.Py/src/TpmTypes.py#L8459-L8463
jackaudio/jack2
21b293dbc37d42446141a08922cdec0d2550c6a0
waflib/Utils.py
python
h_fun
(fun)
Hash functions :param fun: function to hash :type fun: function :return: hash of the function :rtype: string or bytes
Hash functions
[ "Hash", "functions" ]
def h_fun(fun): """ Hash functions :param fun: function to hash :type fun: function :return: hash of the function :rtype: string or bytes """ try: return fun.code except AttributeError: if isinstance(fun, functools.partial): code = list(fun.args) # The method items() provides a sequence of tuples where the first element # represents an optional argument of the partial function application # # The sorting result outcome will be consistent because: # 1. tuples are compared in order of their elements # 2. optional argument namess are unique code.extend(sorted(fun.keywords.items())) code.append(h_fun(fun.func)) fun.code = h_list(code) return fun.code try: h = inspect.getsource(fun) except EnvironmentError: h = 'nocode' try: fun.code = h except AttributeError: pass return h
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https://github.com/jackaudio/jack2/blob/21b293dbc37d42446141a08922cdec0d2550c6a0/waflib/Utils.py#L599-L631
rsummers11/CADLab
976ed959a0b5208bb4173127a7ef732ac73a9b6f
panreas_hnn/hed-globalweight/scripts/cpp_lint.py
python
_Filters
()
return _cpplint_state.filters
Returns the module's list of output filters, as a list.
Returns the module's list of output filters, as a list.
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def _Filters(): """Returns the module's list of output filters, as a list.""" return _cpplint_state.filters
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https://github.com/rsummers11/CADLab/blob/976ed959a0b5208bb4173127a7ef732ac73a9b6f/panreas_hnn/hed-globalweight/scripts/cpp_lint.py#L792-L794