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v8/v8
fee3bf095260bf657a3eea4d3d41f90c42c6c857
tools/sanitizers/sancov_merger.py
python
merge_parallel
(inputs, merge_fun=merge)
Process several merge jobs in parallel.
Process several merge jobs in parallel.
[ "Process", "several", "merge", "jobs", "in", "parallel", "." ]
def merge_parallel(inputs, merge_fun=merge): """Process several merge jobs in parallel.""" pool = Pool(CPUS) try: return pool.map(merge_fun, inputs) finally: pool.close()
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https://github.com/v8/v8/blob/fee3bf095260bf657a3eea4d3d41f90c42c6c857/tools/sanitizers/sancov_merger.py#L119-L125
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/msw/richtext.py
python
RichTextCtrl.GetCaretPositionForDefaultStyle
(*args, **kwargs)
return _richtext.RichTextCtrl_GetCaretPositionForDefaultStyle(*args, **kwargs)
GetCaretPositionForDefaultStyle(self) -> long
GetCaretPositionForDefaultStyle(self) -> long
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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/msw/richtext.py#L4128-L4130
htcondor/htcondor
4829724575176d1d6c936e4693dfd78a728569b0
bindings/python/htcondor/dags/dag.py
python
DAG.glob
(self, pattern: str)
return self.select(lambda node: fnmatch.fnmatchcase(node.name, pattern))
Return a :class:`Nodes` of the nodes in the DAG whose names match the glob ``pattern``.
Return a :class:`Nodes` of the nodes in the DAG whose names match the glob ``pattern``.
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def glob(self, pattern: str) -> node.Nodes: """ Return a :class:`Nodes` of the nodes in the DAG whose names match the glob ``pattern``. """ return self.select(lambda node: fnmatch.fnmatchcase(node.name, pattern))
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https://github.com/htcondor/htcondor/blob/4829724575176d1d6c936e4693dfd78a728569b0/bindings/python/htcondor/dags/dag.py#L324-L329
ChromiumWebApps/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
third_party/re2/lib/codereview/codereview.py
python
MySend1
(request_path, payload=None, content_type="application/octet-stream", timeout=None, force_auth=True, **kwargs)
Sends an RPC and returns the response. Args: request_path: The path to send the request to, eg /api/appversion/create. payload: The body of the request, or None to send an empty request. content_type: The Content-Type header to use. timeout: timeout in seconds; default None i.e. no timeout. (Note: for large requests on OS X, the timeout doesn't work right.) kwargs: Any keyword arguments are converted into query string parameters. Returns: The response body, as a string.
Sends an RPC and returns the response.
[ "Sends", "an", "RPC", "and", "returns", "the", "response", "." ]
def MySend1(request_path, payload=None, content_type="application/octet-stream", timeout=None, force_auth=True, **kwargs): """Sends an RPC and returns the response. Args: request_path: The path to send the request to, eg /api/appversion/create. payload: The body of the request, or None to send an empty request. content_type: The Content-Type header to use. timeout: timeout in seconds; default None i.e. no timeout. (Note: for large requests on OS X, the timeout doesn't work right.) kwargs: Any keyword arguments are converted into query string parameters. Returns: The response body, as a string. """ # TODO: Don't require authentication. Let the server say # whether it is necessary. global rpc if rpc == None: rpc = GetRpcServer(upload_options) self = rpc if not self.authenticated and force_auth: self._Authenticate() if request_path is None: return old_timeout = socket.getdefaulttimeout() socket.setdefaulttimeout(timeout) try: tries = 0 while True: tries += 1 args = dict(kwargs) url = "http://%s%s" % (self.host, request_path) if args: url += "?" + urllib.urlencode(args) req = self._CreateRequest(url=url, data=payload) req.add_header("Content-Type", content_type) try: f = self.opener.open(req) response = f.read() f.close() # Translate \r\n into \n, because Rietveld doesn't. response = response.replace('\r\n', '\n') # who knows what urllib will give us if type(response) == unicode: response = response.encode("utf-8") typecheck(response, str) return response except urllib2.HTTPError, e: if tries > 3: raise elif e.code == 401: self._Authenticate() elif e.code == 302: loc = e.info()["location"] if not loc.startswith('https://www.google.com/a') or loc.find('/ServiceLogin') < 0: return '' self._Authenticate() else: raise finally: socket.setdefaulttimeout(old_timeout)
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/third_party/re2/lib/codereview/codereview.py#L2436-L2500
intel/llvm
e6d0547e9d99b5a56430c4749f6c7e328bf221ab
libcxx/utils/libcxx/sym_check/extract.py
python
NMExtractor._want_sym
(sym)
return (sym['type'] not in bad_types and sym['name'] not in ['__bss_start', '_end', '_edata'])
Check that s is a valid symbol that we want to keep.
Check that s is a valid symbol that we want to keep.
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def _want_sym(sym): """ Check that s is a valid symbol that we want to keep. """ if sym is None or len(sym) < 2: return False if sym['name'] in extract_ignore_names: return False bad_types = ['t', 'b', 'r', 'd', 'w'] return (sym['type'] not in bad_types and sym['name'] not in ['__bss_start', '_end', '_edata'])
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https://github.com/intel/llvm/blob/e6d0547e9d99b5a56430c4749f6c7e328bf221ab/libcxx/utils/libcxx/sym_check/extract.py#L84-L94
calamares/calamares
9f6f82405b3074af7c99dc26487d2e46e4ece3e5
src/modules/bootloader/main.py
python
install_systemd_boot
(efi_directory)
Installs systemd-boot as bootloader for EFI setups. :param efi_directory:
Installs systemd-boot as bootloader for EFI setups.
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def install_systemd_boot(efi_directory): """ Installs systemd-boot as bootloader for EFI setups. :param efi_directory: """ libcalamares.utils.debug("Bootloader: systemd-boot") install_path = libcalamares.globalstorage.value("rootMountPoint") install_efi_directory = install_path + efi_directory uuid = get_uuid() distribution = get_bootloader_entry_name() distribution_translated = distribution.translate(file_name_sanitizer) loader_path = os.path.join(install_efi_directory, "loader", "loader.conf") subprocess.call(["bootctl", "--path={!s}".format(install_efi_directory), "install"]) create_systemd_boot_conf(install_path, efi_directory, uuid, distribution, distribution_translated, "default") if "fallback" in libcalamares.job.configuration: create_systemd_boot_conf(install_path, efi_directory, uuid, distribution, distribution_translated, "fallback") create_loader(loader_path, distribution_translated)
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https://github.com/calamares/calamares/blob/9f6f82405b3074af7c99dc26487d2e46e4ece3e5/src/modules/bootloader/main.py#L469-L500
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/math_ops.py
python
_may_reduce_to_scalar
(keepdims, axis, output)
return output
Set a reduction's output shape to be a scalar if we are certain.
Set a reduction's output shape to be a scalar if we are certain.
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def _may_reduce_to_scalar(keepdims, axis, output): """Set a reduction's output shape to be a scalar if we are certain.""" if not common_shapes.has_fully_defined_shape(output) and (not keepdims) and ( axis is None): output.set_shape(()) return output
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/math_ops.py#L1454-L1459
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_misc.py
python
Process.Detach
(*args, **kwargs)
return _misc_.Process_Detach(*args, **kwargs)
Detach(self)
Detach(self)
[ "Detach", "(", "self", ")" ]
def Detach(*args, **kwargs): """Detach(self)""" return _misc_.Process_Detach(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_misc.py#L2015-L2017
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
tools/idl_parser/idl_parser.py
python
IDLParser.p_Arguments
(self, p)
Arguments : ',' Argument Arguments |
Arguments : ',' Argument Arguments |
[ "Arguments", ":", "Argument", "Arguments", "|" ]
def p_Arguments(self, p): """Arguments : ',' Argument Arguments |""" if len(p) > 1: p[0] = ListFromConcat(p[2], p[3])
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/idl_parser/idl_parser.py#L690-L694
PaddlePaddle/Paddle
1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c
python/paddle/fluid/layers/sequence_lod.py
python
sequence_concat
(input, name=None)
return out
:api_attr: Static Graph **Notes: The Op only receives LoDTensor as input. If your input is Tensor, please use concat Op.(fluid.layers.** :ref:`api_fluid_layers_concat` ). This operator only supports LoDTensor as input. It concatenates the multiple LoDTensor from input by the LoD information, and outputs the concatenated LoDTensor. .. code-block:: text input is a list of LoDTensor: input = [x1, x2] where: x1.lod = [[0, 3, 5]] x1.data = [[1], [2], [3], [4], [5]] x1.shape = [5, 1] x2.lod = [[0, 2, 4]] x2.data = [[6], [7], [8], [9]] x2.shape = [4, 1] and should satisfy: len(x1.lod[0]) == len(x2.lod[0]) output is LoDTensor: out.lod = [[0, 3+2, 5+4]] out.data = [[1], [2], [3], [6], [7], [4], [5], [8], [9]] out.shape = [9, 1] Args: input(list of Variable): List of LoDTensor to be concatenated. The length of each LoDTensor should be same. The data type can be float32, float64 or int64. name(str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name` . Returns: Variable: Output the concatenated LoDTensor. The data type is same as input. Examples: .. code-block:: python import paddle paddle.enable_static() x = paddle.static.data(name='x', shape=[-1, 10], dtype='float32', lod_level=1) y = paddle.static.data(name='y', shape=[-1, 10], dtype='float32', lod_level=1) out = paddle.static.nn.sequence_concat(input=[x, y])
:api_attr: Static Graph
[ ":", "api_attr", ":", "Static", "Graph" ]
def sequence_concat(input, name=None): """ :api_attr: Static Graph **Notes: The Op only receives LoDTensor as input. If your input is Tensor, please use concat Op.(fluid.layers.** :ref:`api_fluid_layers_concat` ). This operator only supports LoDTensor as input. It concatenates the multiple LoDTensor from input by the LoD information, and outputs the concatenated LoDTensor. .. code-block:: text input is a list of LoDTensor: input = [x1, x2] where: x1.lod = [[0, 3, 5]] x1.data = [[1], [2], [3], [4], [5]] x1.shape = [5, 1] x2.lod = [[0, 2, 4]] x2.data = [[6], [7], [8], [9]] x2.shape = [4, 1] and should satisfy: len(x1.lod[0]) == len(x2.lod[0]) output is LoDTensor: out.lod = [[0, 3+2, 5+4]] out.data = [[1], [2], [3], [6], [7], [4], [5], [8], [9]] out.shape = [9, 1] Args: input(list of Variable): List of LoDTensor to be concatenated. The length of each LoDTensor should be same. The data type can be float32, float64 or int64. name(str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name` . Returns: Variable: Output the concatenated LoDTensor. The data type is same as input. Examples: .. code-block:: python import paddle paddle.enable_static() x = paddle.static.data(name='x', shape=[-1, 10], dtype='float32', lod_level=1) y = paddle.static.data(name='y', shape=[-1, 10], dtype='float32', lod_level=1) out = paddle.static.nn.sequence_concat(input=[x, y]) """ assert not in_dygraph_mode(), ( "sequence layer is not supported in dygraph mode yet.") helper = LayerHelper('sequence_concat', **locals()) check_type(input, 'input', list, 'fluid.layers.sequence_concat') for i, input_x in enumerate(input): check_variable_and_dtype(input_x, 'input[' + str(i) + ']', ['int64', 'float32', 'float64'], 'fluid.layers.sequence_concat') out = helper.create_variable_for_type_inference(dtype=helper.input_dtype()) helper.append_op( type='sequence_concat', inputs={'X': input}, outputs={'Out': [out]}) return out
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https://github.com/PaddlePaddle/Paddle/blob/1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c/python/paddle/fluid/layers/sequence_lod.py#L380-L440
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/joblib/joblib/externals/cloudpickle/cloudpickle.py
python
_find_imported_submodules
(code, top_level_dependencies)
return subimports
Find currently imported submodules used by a function. Submodules used by a function need to be detected and referenced for the function to work correctly at depickling time. Because submodules can be referenced as attribute of their parent package (``package.submodule``), we need a special introspection technique that does not rely on GLOBAL-related opcodes to find references of them in a code object. Example: ``` import concurrent.futures import cloudpickle def func(): x = concurrent.futures.ThreadPoolExecutor if __name__ == '__main__': cloudpickle.dumps(func) ``` The globals extracted by cloudpickle in the function's state include the concurrent package, but not its submodule (here, concurrent.futures), which is the module used by func. Find_imported_submodules will detect the usage of concurrent.futures. Saving this module alongside with func will ensure that calling func once depickled does not fail due to concurrent.futures not being imported
Find currently imported submodules used by a function.
[ "Find", "currently", "imported", "submodules", "used", "by", "a", "function", "." ]
def _find_imported_submodules(code, top_level_dependencies): """ Find currently imported submodules used by a function. Submodules used by a function need to be detected and referenced for the function to work correctly at depickling time. Because submodules can be referenced as attribute of their parent package (``package.submodule``), we need a special introspection technique that does not rely on GLOBAL-related opcodes to find references of them in a code object. Example: ``` import concurrent.futures import cloudpickle def func(): x = concurrent.futures.ThreadPoolExecutor if __name__ == '__main__': cloudpickle.dumps(func) ``` The globals extracted by cloudpickle in the function's state include the concurrent package, but not its submodule (here, concurrent.futures), which is the module used by func. Find_imported_submodules will detect the usage of concurrent.futures. Saving this module alongside with func will ensure that calling func once depickled does not fail due to concurrent.futures not being imported """ subimports = [] # check if any known dependency is an imported package for x in top_level_dependencies: if (isinstance(x, types.ModuleType) and hasattr(x, '__package__') and x.__package__): # check if the package has any currently loaded sub-imports prefix = x.__name__ + '.' # A concurrent thread could mutate sys.modules, # make sure we iterate over a copy to avoid exceptions for name in list(sys.modules): # Older versions of pytest will add a "None" module to # sys.modules. if name is not None and name.startswith(prefix): # check whether the function can address the sub-module tokens = set(name[len(prefix):].split('.')) if not tokens - set(code.co_names): subimports.append(sys.modules[name]) return subimports
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/joblib/joblib/externals/cloudpickle/cloudpickle.py#L352-L396
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/_controls.py
python
TextAttr.GetOutlineLevel
(*args, **kwargs)
return _controls_.TextAttr_GetOutlineLevel(*args, **kwargs)
GetOutlineLevel(self) -> int
GetOutlineLevel(self) -> int
[ "GetOutlineLevel", "(", "self", ")", "-", ">", "int" ]
def GetOutlineLevel(*args, **kwargs): """GetOutlineLevel(self) -> int""" return _controls_.TextAttr_GetOutlineLevel(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_controls.py#L1764-L1766
nnrg/opennero
43e12a1bcba6e228639db3886fec1dc47ddc24cb
mods/Roomba/RLAgent.py
python
TabularRLAgent.start
(self, time, sensors)
return self.previous_action
Called to figure out the first action given the first sensors @param time current time @param sensors a DoubleVector of sensors for the agent (use len() and [])
Called to figure out the first action given the first sensors
[ "Called", "to", "figure", "out", "the", "first", "action", "given", "the", "first", "sensors" ]
def start(self, time, sensors): """ Called to figure out the first action given the first sensors @param time current time @param sensors a DoubleVector of sensors for the agent (use len() and []) """ self.previous_sensors = sensors self.previous_action = self.get_epsilon_greedy(sensors) return self.previous_action
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https://github.com/nnrg/opennero/blob/43e12a1bcba6e228639db3886fec1dc47ddc24cb/mods/Roomba/RLAgent.py#L128-L136
giuspen/cherrytree
84712f206478fcf9acf30174009ad28c648c6344
pygtk2/modules/core.py
python
CherryTree.on_text_removal
(self, sourcebuffer, start_iter, end_iter)
Text removal callback
Text removal callback
[ "Text", "removal", "callback" ]
def on_text_removal(self, sourcebuffer, start_iter, end_iter): """Text removal callback""" if self.user_active and self.curr_tree_iter: self.state_machine.text_variation(self.treestore[self.curr_tree_iter][3], sourcebuffer.get_text(start_iter, end_iter))
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https://github.com/giuspen/cherrytree/blob/84712f206478fcf9acf30174009ad28c648c6344/pygtk2/modules/core.py#L3537-L3541
v8/v8
fee3bf095260bf657a3eea4d3d41f90c42c6c857
tools/sanitizers/sancov_formatter.py
python
split
(options)
Implements the 'split' action of this tool.
Implements the 'split' action of this tool.
[ "Implements", "the", "split", "action", "of", "this", "tool", "." ]
def split(options): """Implements the 'split' action of this tool.""" # Load existing json data file for splitting. with open(options.json_input, 'r') as f: data = json.load(f) logging.info('Splitting off %d coverage files from %s', len(data['files']), options.json_input) for file_name, coverage in data['files'].iteritems(): # Preserve relative directories that are part of the file name. file_path = os.path.join(options.output_dir, file_name + '.json') try: os.makedirs(os.path.dirname(file_path)) except OSError: # Ignore existing directories. pass with open(file_path, 'w') as f: # Flat-copy the old dict. new_data = dict(data) # Update current file. new_data['files'] = {file_name: coverage} # Write json data. json.dump(new_data, f, sort_keys=True)
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https://github.com/v8/v8/blob/fee3bf095260bf657a3eea4d3d41f90c42c6c857/tools/sanitizers/sancov_formatter.py#L383-L409
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/third_party/gsutil/third_party/boto/boto/emr/connection.py
python
EmrConnection.terminate_jobflows
(self, jobflow_ids)
return self.get_status('TerminateJobFlows', params, verb='POST')
Terminate an Elastic MapReduce job flow :type jobflow_ids: list :param jobflow_ids: A list of job flow IDs
Terminate an Elastic MapReduce job flow
[ "Terminate", "an", "Elastic", "MapReduce", "job", "flow" ]
def terminate_jobflows(self, jobflow_ids): """ Terminate an Elastic MapReduce job flow :type jobflow_ids: list :param jobflow_ids: A list of job flow IDs """ params = {} self.build_list_params(params, jobflow_ids, 'JobFlowIds.member') return self.get_status('TerminateJobFlows', params, verb='POST')
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/third_party/boto/boto/emr/connection.py#L317-L326
turi-code/SFrame
796b9bdfb2fa1b881d82080754643c7e68629cd2
oss_src/unity/python/sframe/data_structures/sgraph.py
python
SGraph.__init__
(self, vertices=None, edges=None, vid_field='__id', src_field='__src_id', dst_field='__dst_id', _proxy=None)
__init__(vertices=None, edges=None, vid_field='__id', src_field='__src_id', dst_field='__dst_id') By default, construct an empty graph when vertices and edges are None. Otherwise construct an SGraph with given vertices and edges. Parameters ---------- vertices : SFrame, optional An SFrame containing vertex id columns and optional vertex data columns. edges : SFrame, optional An SFrame containing source and target id columns and optional edge data columns. vid_field : str, optional The name of vertex id column in the `vertices` SFrame. src_field : str, optional The name of source id column in the `edges` SFrame. dst_field : str, optional The name of target id column in the `edges` SFrame.
__init__(vertices=None, edges=None, vid_field='__id', src_field='__src_id', dst_field='__dst_id')
[ "__init__", "(", "vertices", "=", "None", "edges", "=", "None", "vid_field", "=", "__id", "src_field", "=", "__src_id", "dst_field", "=", "__dst_id", ")" ]
def __init__(self, vertices=None, edges=None, vid_field='__id', src_field='__src_id', dst_field='__dst_id', _proxy=None): """ __init__(vertices=None, edges=None, vid_field='__id', src_field='__src_id', dst_field='__dst_id') By default, construct an empty graph when vertices and edges are None. Otherwise construct an SGraph with given vertices and edges. Parameters ---------- vertices : SFrame, optional An SFrame containing vertex id columns and optional vertex data columns. edges : SFrame, optional An SFrame containing source and target id columns and optional edge data columns. vid_field : str, optional The name of vertex id column in the `vertices` SFrame. src_field : str, optional The name of source id column in the `edges` SFrame. dst_field : str, optional The name of target id column in the `edges` SFrame. """ if (_proxy is None): self.__proxy__ = UnityGraphProxy(glconnect.get_client()) if vertices is not None: self.__proxy__ = self.add_vertices(vertices, vid_field).__proxy__ if edges is not None: self.__proxy__ = self.add_edges(edges, src_field, dst_field).__proxy__ else: self.__proxy__ = _proxy self._vertices = GFrame(self, VERTEX_GFRAME) self._edges = GFrame(self, EDGE_GFRAME)
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https://github.com/turi-code/SFrame/blob/796b9bdfb2fa1b881d82080754643c7e68629cd2/oss_src/unity/python/sframe/data_structures/sgraph.py#L221-L257
htcondor/htcondor
4829724575176d1d6c936e4693dfd78a728569b0
src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/Skype4Py/skype.py
python
ISkype.DeleteGroup
(self, GroupId)
Deletes a custom contact group. Users in the contact group are moved to the All Contacts (hardwired) contact group. @param GroupId: Group identifier. Get it from L{IGroup.Id}. @type GroupId: int @see: L{CreateGroup}
Deletes a custom contact group.
[ "Deletes", "a", "custom", "contact", "group", "." ]
def DeleteGroup(self, GroupId): '''Deletes a custom contact group. Users in the contact group are moved to the All Contacts (hardwired) contact group. @param GroupId: Group identifier. Get it from L{IGroup.Id}. @type GroupId: int @see: L{CreateGroup} ''' self._DoCommand('DELETE GROUP %s' % GroupId)
[ "def", "DeleteGroup", "(", "self", ",", "GroupId", ")", ":", "self", ".", "_DoCommand", "(", "'DELETE GROUP %s'", "%", "GroupId", ")" ]
https://github.com/htcondor/htcondor/blob/4829724575176d1d6c936e4693dfd78a728569b0/src/condor_contrib/condor_pigeon/src/condor_pigeon_client/skype_linux_tools/Skype4Py/skype.py#L648-L657
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/base64.py
python
standard_b64encode
(s)
return b64encode(s)
Encode bytes-like object s using the standard Base64 alphabet. The result is returned as a bytes object.
Encode bytes-like object s using the standard Base64 alphabet.
[ "Encode", "bytes", "-", "like", "object", "s", "using", "the", "standard", "Base64", "alphabet", "." ]
def standard_b64encode(s): """Encode bytes-like object s using the standard Base64 alphabet. The result is returned as a bytes object. """ return b64encode(s)
[ "def", "standard_b64encode", "(", "s", ")", ":", "return", "b64encode", "(", "s", ")" ]
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/base64.py#L90-L95
amd/OpenCL-caffe
638543108517265366c18ae5821f3096cf5cf34a
python/caffe/pycaffe.py
python
_Net_set_input_arrays
(self, data, labels)
return self._set_input_arrays(data, labels)
Set input arrays of the in-memory MemoryDataLayer. (Note: this is only for networks declared with the memory data layer.)
Set input arrays of the in-memory MemoryDataLayer. (Note: this is only for networks declared with the memory data layer.)
[ "Set", "input", "arrays", "of", "the", "in", "-", "memory", "MemoryDataLayer", ".", "(", "Note", ":", "this", "is", "only", "for", "networks", "declared", "with", "the", "memory", "data", "layer", ".", ")" ]
def _Net_set_input_arrays(self, data, labels): """ Set input arrays of the in-memory MemoryDataLayer. (Note: this is only for networks declared with the memory data layer.) """ if labels.ndim == 1: labels = np.ascontiguousarray(labels[:, np.newaxis, np.newaxis, np.newaxis]) return self._set_input_arrays(data, labels)
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https://github.com/amd/OpenCL-caffe/blob/638543108517265366c18ae5821f3096cf5cf34a/python/caffe/pycaffe.py#L227-L235
miyosuda/TensorFlowAndroidMNIST
7b5a4603d2780a8a2834575706e9001977524007
jni-build/jni/include/tensorflow/contrib/distributions/python/ops/beta.py
python
Beta.dtype
(self)
return self._a_b_sum.dtype
dtype of samples from this distribution.
dtype of samples from this distribution.
[ "dtype", "of", "samples", "from", "this", "distribution", "." ]
def dtype(self): """dtype of samples from this distribution.""" return self._a_b_sum.dtype
[ "def", "dtype", "(", "self", ")", ":", "return", "self", ".", "_a_b_sum", ".", "dtype" ]
https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/tensorflow/contrib/distributions/python/ops/beta.py#L169-L171
mindspore-ai/mindspore
fb8fd3338605bb34fa5cea054e535a8b1d753fab
mindspore/python/mindspore/train/summary/_writer_pool.py
python
WriterPool.write
(self, data)
Write the event to file. Args: data (Optional[str, Tuple[list, int]]): The data to write.
Write the event to file.
[ "Write", "the", "event", "to", "file", "." ]
def write(self, data) -> None: """ Write the event to file. Args: data (Optional[str, Tuple[list, int]]): The data to write. """ self._queue.put(('WRITE', data))
[ "def", "write", "(", "self", ",", "data", ")", "->", "None", ":", "self", ".", "_queue", ".", "put", "(", "(", "'WRITE'", ",", "data", ")", ")" ]
https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/train/summary/_writer_pool.py#L170-L177
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/tools/Editra/src/extern/aui/auibook.py
python
AuiTabCtrl.OnMotion
(self, event)
Handles the ``wx.EVT_MOTION`` event for :class:`AuiTabCtrl`. :param `event`: a :class:`MouseEvent` event to be processed.
Handles the ``wx.EVT_MOTION`` event for :class:`AuiTabCtrl`.
[ "Handles", "the", "wx", ".", "EVT_MOTION", "event", "for", ":", "class", ":", "AuiTabCtrl", "." ]
def OnMotion(self, event): """ Handles the ``wx.EVT_MOTION`` event for :class:`AuiTabCtrl`. :param `event`: a :class:`MouseEvent` event to be processed. """ pos = event.GetPosition() # check if the mouse is hovering above a button button = self.ButtonHitTest(pos.x, pos.y) wnd = self.TabHitTest(pos.x, pos.y) if wnd is not None: mouse_tab = self.GetIdxFromWindow(wnd) if not self._pages[mouse_tab].enabled: self._hover_button = None return if self._on_button: return if button: if self._hover_button and button != self._hover_button: self._hover_button.cur_state = AUI_BUTTON_STATE_NORMAL self._hover_button = None self.Refresh() self.Update() if button.cur_state != AUI_BUTTON_STATE_HOVER: button.cur_state = AUI_BUTTON_STATE_HOVER self.Refresh() self.Update() self._hover_button = button return else: if self._hover_button: self._hover_button.cur_state = AUI_BUTTON_STATE_NORMAL self._hover_button = None self.Refresh() self.Update() if not event.LeftIsDown() or self._click_pt == wx.Point(-1, -1): return if not self.HasCapture(): return wnd = self.TabHitTest(pos.x, pos.y) if not self._is_dragging: drag_x_threshold = wx.SystemSettings.GetMetric(wx.SYS_DRAG_X) drag_y_threshold = wx.SystemSettings.GetMetric(wx.SYS_DRAG_Y) if abs(pos.x - self._click_pt.x) > drag_x_threshold or \ abs(pos.y - self._click_pt.y) > drag_y_threshold: self._is_dragging = True if self._drag_image: self._drag_image.EndDrag() del self._drag_image self._drag_image = None if self._agwFlags & AUI_NB_DRAW_DND_TAB: # Create the custom draw image from the icons and the text of the item mouse_tab = self.GetIdxFromWindow(wnd) page = self._pages[mouse_tab] tab_button = self._tab_close_buttons[mouse_tab] self._drag_image = TabDragImage(self, page, tab_button.cur_state, self._art) if self._agwFlags & AUI_NB_TAB_FLOAT: self._drag_image.BeginDrag(wx.Point(0,0), self, fullScreen=True) else: self._drag_image.BeginDragBounded(wx.Point(0,0), self, self.GetParent()) # Capture the mouse cursor position offset relative to # The tab image location self._drag_img_offset = (pos[0] - page.rect.x, pos[1] - page.rect.y) self._drag_image.Show() if not wnd: evt2 = AuiNotebookEvent(wxEVT_COMMAND_AUINOTEBOOK_BEGIN_DRAG, self.GetId()) evt2.SetSelection(self.GetIdxFromWindow(self._click_tab)) evt2.SetOldSelection(evt2.GetSelection()) evt2.SetEventObject(self) self.GetEventHandler().ProcessEvent(evt2) if evt2.GetDispatched(): return evt3 = AuiNotebookEvent(wxEVT_COMMAND_AUINOTEBOOK_DRAG_MOTION, self.GetId()) evt3.SetSelection(self.GetIdxFromWindow(self._click_tab)) evt3.SetOldSelection(evt3.GetSelection()) evt3.SetEventObject(self) self.GetEventHandler().ProcessEvent(evt3) if self._drag_image: # Apply the drag images offset pos -= self._drag_img_offset self._drag_image.Move(pos)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/tools/Editra/src/extern/aui/auibook.py#L2152-L2258
apple/turicreate
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
deps/src/libxml2-2.9.1/python/libxml2class.py
python
uCSIsCJKCompatibility
(code)
return ret
Check whether the character is part of CJKCompatibility UCS Block
Check whether the character is part of CJKCompatibility UCS Block
[ "Check", "whether", "the", "character", "is", "part", "of", "CJKCompatibility", "UCS", "Block" ]
def uCSIsCJKCompatibility(code): """Check whether the character is part of CJKCompatibility UCS Block """ ret = libxml2mod.xmlUCSIsCJKCompatibility(code) return ret
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https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/deps/src/libxml2-2.9.1/python/libxml2class.py#L1399-L1403
OpenNebula/one
982e09706fc444ae60a8ad2f818d6a795cbbdab4
src/oca/python/pyone/__init__.py
python
OneServer.__init__
(self, uri, session, timeout=None, **options)
Override the constructor to take the authentication or session Will also configure the socket timeout :param uri: OpenNebula endpoint :param session: OpenNebula authentication session :param timeout: Socket timetout :param options: additional options for ServerProxy
Override the constructor to take the authentication or session Will also configure the socket timeout :param uri: OpenNebula endpoint :param session: OpenNebula authentication session :param timeout: Socket timetout :param options: additional options for ServerProxy
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def __init__(self, uri, session, timeout=None, **options): """ Override the constructor to take the authentication or session Will also configure the socket timeout :param uri: OpenNebula endpoint :param session: OpenNebula authentication session :param timeout: Socket timetout :param options: additional options for ServerProxy """ self.__session = session if timeout: # note that this will affect other classes using sockets too. socket.setdefaulttimeout(timeout) # register helpers: self.__helpers = { "marketapp.export": marketapp_export } transport = RequestsTransport() transport.set_https(uri.startswith('https')) xmlrpc.client.ServerProxy.__init__( self, uri, transport=transport, **options)
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https://github.com/OpenNebula/one/blob/982e09706fc444ae60a8ad2f818d6a795cbbdab4/src/oca/python/pyone/__init__.py#L190-L217
wlanjie/AndroidFFmpeg
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib-tk/Tkinter.py
python
Misc.tkraise
(self, aboveThis=None)
Raise this widget in the stacking order.
Raise this widget in the stacking order.
[ "Raise", "this", "widget", "in", "the", "stacking", "order", "." ]
def tkraise(self, aboveThis=None): """Raise this widget in the stacking order.""" self.tk.call('raise', self._w, aboveThis)
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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#L717-L719
pytorch/pytorch
7176c92687d3cc847cc046bf002269c6949a21c2
torch/ao/quantization/quantization_mappings.py
python
get_default_qconfig_propagation_list
()
return copy.deepcopy(QCONFIG_PROPAGATE_MODULE_CLASS_LIST)
Get the default list of module types that we'll attach qconfig attribute to in prepare
Get the default list of module types that we'll attach qconfig attribute to in prepare
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def get_default_qconfig_propagation_list() -> Set[Callable]: ''' Get the default list of module types that we'll attach qconfig attribute to in prepare ''' QCONFIG_PROPAGATE_MODULE_CLASS_LIST = ( (set(DEFAULT_STATIC_QUANT_MODULE_MAPPINGS.keys()) | set(DEFAULT_QAT_MODULE_MAPPINGS.keys()) | set(DEFAULT_DYNAMIC_QUANT_MODULE_MAPPINGS.keys()) | _INCLUDE_QCONFIG_PROPAGATE_LIST) ) return copy.deepcopy(QCONFIG_PROPAGATE_MODULE_CLASS_LIST)
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https://github.com/pytorch/pytorch/blob/7176c92687d3cc847cc046bf002269c6949a21c2/torch/ao/quantization/quantization_mappings.py#L244-L254
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/specs/python/specs_lib.py
python
debug
(mode=True)
Turn on/off debugging mode. Debugging mode prints more information about the construction of a network. Args: mode: True if turned on, False otherwise
Turn on/off debugging mode.
[ "Turn", "on", "/", "off", "debugging", "mode", "." ]
def debug(mode=True): """Turn on/off debugging mode. Debugging mode prints more information about the construction of a network. Args: mode: True if turned on, False otherwise """ global debug_ debug_ = mode
[ "def", "debug", "(", "mode", "=", "True", ")", ":", "global", "debug_", "debug_", "=", "mode" ]
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/specs/python/specs_lib.py#L228-L238
miyosuda/TensorFlowAndroidDemo
35903e0221aa5f109ea2dbef27f20b52e317f42d
jni-build/jni/include/tensorflow/python/platform/benchmark.py
python
Benchmark._get_name
(self, overwrite_name)
return name
Returns full name of class and method calling report_benchmark.
Returns full name of class and method calling report_benchmark.
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def _get_name(self, overwrite_name): """Returns full name of class and method calling report_benchmark.""" # Find the caller method (outermost Benchmark class) stack = inspect.stack() calling_class = None name = None for frame in stack[::-1]: f_locals = frame[0].f_locals f_self = f_locals.get("self", None) if isinstance(f_self, Benchmark): calling_class = f_self # Get the outermost stack Benchmark call name = frame[3] # Get the method name break if calling_class is None: raise ValueError("Unable to determine calling Benchmark class.") # Use the method name, or overwrite_name is provided. name = overwrite_name or name # Prefix the name with the class name. class_name = type(calling_class).__name__ name = "%s.%s" % (class_name, name) return name
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https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/tensorflow/python/platform/benchmark.py#L127-L149
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_windows.py
python
TopLevelWindow.SetIcons
(*args, **kwargs)
return _windows_.TopLevelWindow_SetIcons(*args, **kwargs)
SetIcons(self, wxIconBundle icons)
SetIcons(self, wxIconBundle icons)
[ "SetIcons", "(", "self", "wxIconBundle", "icons", ")" ]
def SetIcons(*args, **kwargs): """SetIcons(self, wxIconBundle icons)""" return _windows_.TopLevelWindow_SetIcons(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_windows.py#L437-L439
googleprojectzero/BrokenType
cf49a52b8e35b7d684fc8bc6b2ea8b923c177c2e
truetype-generator/truetype_generate.py
python
TTXParser._Handler_TTGlyph
(self, path, node)
Resets the number of contours and points in the glyph (because there is a new one), and inserts a child <instructions> tag if one is not already present, in order to have TrueType instructions executed for all glyphs in the font.
Resets the number of contours and points in the glyph (because there is a new one), and inserts a child <instructions> tag if one is not already present, in order to have TrueType instructions executed for all glyphs in the font.
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def _Handler_TTGlyph(self, path, node): """Resets the number of contours and points in the glyph (because there is a new one), and inserts a child <instructions> tag if one is not already present, in order to have TrueType instructions executed for all glyphs in the font. """ self._contours_in_glyph = 0 self._points_in_glyph = 0 # Only add the instructions for glyphs which have at least one contour. if (node.find("contour") != None) and (node.find("instructions") == None): instructions_node = ET.SubElement(node, "instructions") ET.SubElement(instructions_node, "assembly")
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https://github.com/googleprojectzero/BrokenType/blob/cf49a52b8e35b7d684fc8bc6b2ea8b923c177c2e/truetype-generator/truetype_generate.py#L671-L682
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/grid.py
python
PyGridTableBase.Destroy
(*args, **kwargs)
return _grid.PyGridTableBase_Destroy(*args, **kwargs)
Destroy(self) Deletes the C++ object this Python object is a proxy for.
Destroy(self)
[ "Destroy", "(", "self", ")" ]
def Destroy(*args, **kwargs): """ Destroy(self) Deletes the C++ object this Python object is a proxy for. """ args[0].this.own(False) return _grid.PyGridTableBase_Destroy(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/grid.py#L941-L948
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/dashboard/dashboard/change_internal_only.py
python
ChangeInternalOnlyHandler._UpdateBot
(self, bot_name, internal_only, cursor=None)
Starts updating internal_only for the given bot and associated data.
Starts updating internal_only for the given bot and associated data.
[ "Starts", "updating", "internal_only", "for", "the", "given", "bot", "and", "associated", "data", "." ]
def _UpdateBot(self, bot_name, internal_only, cursor=None): """Starts updating internal_only for the given bot and associated data.""" master, bot = bot_name.split('/') bot_key = ndb.Key('Master', master, 'Bot', bot) if not cursor: # First time updating for this Bot. bot_entity = bot_key.get() if bot_entity.internal_only != internal_only: bot_entity.internal_only = internal_only bot_entity.put() else: cursor = datastore_query.Cursor(urlsafe=cursor) # Fetch a certain number of TestMetadata entities starting from cursor. See: # https://developers.google.com/appengine/docs/python/ndb/queryclass # Start update tasks for each existing subordinate TestMetadata. test_query = graph_data.TestMetadata.query( graph_data.TestMetadata.master_name == master, graph_data.TestMetadata.bot_name == bot) test_keys, next_cursor, more = test_query.fetch_page( _MAX_TESTS_TO_PUT, start_cursor=cursor, keys_only=True) for test_key in test_keys: taskqueue.add( url='/change_internal_only', params={ 'test': test_key.urlsafe(), 'internal_only': 'true' if internal_only else 'false', }, queue_name=_QUEUE_NAME) if more: taskqueue.add( url='/change_internal_only', params={ 'bots': bot_name, 'cursor': next_cursor.urlsafe(), 'internal_only': 'true' if internal_only else 'false', }, queue_name=_QUEUE_NAME)
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/dashboard/dashboard/change_internal_only.py#L109-L150
rapidsai/cudf
d5b2448fc69f17509304d594f029d0df56984962
python/cudf/cudf/core/multiindex.py
python
MultiIndex.get_loc
(self, key, method=None, tolerance=None)
return mask
Get location for a label or a tuple of labels. The location is returned as an integer/slice or boolean mask. Parameters ---------- key : label or tuple of labels (one for each level) method : None Returns ------- loc : int, slice object or boolean mask - If index is unique, search result is unique, return a single int. - If index is monotonic, index is returned as a slice object. - Otherwise, cudf attempts a best effort to convert the search result into a slice object, and will return a boolean mask if failed to do so. Notice this can deviate from Pandas behavior in some situations. Examples -------- >>> import cudf >>> mi = cudf.MultiIndex.from_tuples( ... [('a', 'd'), ('b', 'e'), ('b', 'f')]) >>> mi.get_loc('b') slice(1, 3, None) >>> mi.get_loc(('b', 'e')) 1 >>> non_monotonic_non_unique_idx = cudf.MultiIndex.from_tuples( ... [('c', 'd'), ('b', 'e'), ('a', 'f'), ('b', 'e')]) >>> non_monotonic_non_unique_idx.get_loc('b') # differ from pandas slice(1, 4, 2) .. pandas-compat:: **MultiIndex.get_loc** The return types of this function may deviates from the method provided by Pandas. If the index is neither lexicographically sorted nor unique, a best effort attempt is made to coerce the found indices into a slice. For example: .. code-block:: >>> import pandas as pd >>> import cudf >>> x = pd.MultiIndex.from_tuples([ ... (2, 1, 1), (1, 2, 3), (1, 2, 1), ... (1, 1, 1), (1, 1, 1), (2, 2, 1), ... ]) >>> x.get_loc(1) array([False, True, True, True, True, False]) >>> cudf.from_pandas(x).get_loc(1) slice(1, 5, 1)
Get location for a label or a tuple of labels.
[ "Get", "location", "for", "a", "label", "or", "a", "tuple", "of", "labels", "." ]
def get_loc(self, key, method=None, tolerance=None): """ Get location for a label or a tuple of labels. The location is returned as an integer/slice or boolean mask. Parameters ---------- key : label or tuple of labels (one for each level) method : None Returns ------- loc : int, slice object or boolean mask - If index is unique, search result is unique, return a single int. - If index is monotonic, index is returned as a slice object. - Otherwise, cudf attempts a best effort to convert the search result into a slice object, and will return a boolean mask if failed to do so. Notice this can deviate from Pandas behavior in some situations. Examples -------- >>> import cudf >>> mi = cudf.MultiIndex.from_tuples( ... [('a', 'd'), ('b', 'e'), ('b', 'f')]) >>> mi.get_loc('b') slice(1, 3, None) >>> mi.get_loc(('b', 'e')) 1 >>> non_monotonic_non_unique_idx = cudf.MultiIndex.from_tuples( ... [('c', 'd'), ('b', 'e'), ('a', 'f'), ('b', 'e')]) >>> non_monotonic_non_unique_idx.get_loc('b') # differ from pandas slice(1, 4, 2) .. pandas-compat:: **MultiIndex.get_loc** The return types of this function may deviates from the method provided by Pandas. If the index is neither lexicographically sorted nor unique, a best effort attempt is made to coerce the found indices into a slice. For example: .. code-block:: >>> import pandas as pd >>> import cudf >>> x = pd.MultiIndex.from_tuples([ ... (2, 1, 1), (1, 2, 3), (1, 2, 1), ... (1, 1, 1), (1, 1, 1), (2, 2, 1), ... ]) >>> x.get_loc(1) array([False, True, True, True, True, False]) >>> cudf.from_pandas(x).get_loc(1) slice(1, 5, 1) """ if tolerance is not None: raise NotImplementedError( "Parameter tolerance is unsupported yet." ) if method is not None: raise NotImplementedError( "only the default get_loc method is currently supported for" " MultiIndex" ) is_sorted = ( self.is_monotonic_increasing or self.is_monotonic_decreasing ) is_unique = self.is_unique key = (key,) if not isinstance(key, tuple) else key # Handle partial key search. If length of `key` is less than `nlevels`, # Only search levels up to `len(key)` level. key_as_table = cudf.core.frame.Frame( {i: column.as_column(k, length=1) for i, k in enumerate(key)} ) partial_index = self.__class__._from_data( data=self._data.select_by_index(slice(key_as_table._num_columns)) ) (lower_bound, upper_bound, sort_inds,) = _lexsorted_equal_range( partial_index, key_as_table, is_sorted ) if lower_bound == upper_bound: raise KeyError(key) if is_unique and lower_bound + 1 == upper_bound: # Indices are unique (Pandas constraint), search result is unique, # return int. return ( lower_bound if is_sorted else sort_inds.element_indexing(lower_bound) ) if is_sorted: # In monotonic index, lex search result is continuous. A slice for # the range is returned. return slice(lower_bound, upper_bound) true_inds = sort_inds.slice(lower_bound, upper_bound).values true_inds = _maybe_indices_to_slice(true_inds) if isinstance(true_inds, slice): return true_inds # Not sorted and not unique. Return a boolean mask mask = cupy.full(self._data.nrows, False) mask[true_inds] = True return mask
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https://github.com/rapidsai/cudf/blob/d5b2448fc69f17509304d594f029d0df56984962/python/cudf/cudf/core/multiindex.py#L1537-L1646
GoSSIP-SJTU/TripleDoggy
03648d6b19c812504b14e8b98c8c7b3f443f4e54
tools/clang/bindings/python/clang/cindex.py
python
Diagnostic.category_number
(self)
return conf.lib.clang_getDiagnosticCategory(self)
The category number for this diagnostic or 0 if unavailable.
The category number for this diagnostic or 0 if unavailable.
[ "The", "category", "number", "for", "this", "diagnostic", "or", "0", "if", "unavailable", "." ]
def category_number(self): """The category number for this diagnostic or 0 if unavailable.""" return conf.lib.clang_getDiagnosticCategory(self)
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https://github.com/GoSSIP-SJTU/TripleDoggy/blob/03648d6b19c812504b14e8b98c8c7b3f443f4e54/tools/clang/bindings/python/clang/cindex.py#L446-L448
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/msw/_controls.py
python
ListCtrl.SetItemState
(*args, **kwargs)
return _controls_.ListCtrl_SetItemState(*args, **kwargs)
SetItemState(self, long item, long state, long stateMask) -> bool
SetItemState(self, long item, long state, long stateMask) -> bool
[ "SetItemState", "(", "self", "long", "item", "long", "state", "long", "stateMask", ")", "-", ">", "bool" ]
def SetItemState(*args, **kwargs): """SetItemState(self, long item, long state, long stateMask) -> bool""" return _controls_.ListCtrl_SetItemState(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/_controls.py#L4535-L4537
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/ipython/py2/IPython/core/shellapp.py
python
InteractiveShellApp.init_code
(self)
run the pre-flight code, specified via exec_lines
run the pre-flight code, specified via exec_lines
[ "run", "the", "pre", "-", "flight", "code", "specified", "via", "exec_lines" ]
def init_code(self): """run the pre-flight code, specified via exec_lines""" self._run_startup_files() self._run_exec_lines() self._run_exec_files() # Hide variables defined here from %who etc. if self.hide_initial_ns: self.shell.user_ns_hidden.update(self.shell.user_ns) # command-line execution (ipython -i script.py, ipython -m module) # should *not* be excluded from %whos self._run_cmd_line_code() self._run_module() # flush output, so itwon't be attached to the first cell sys.stdout.flush() sys.stderr.flush()
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/ipython/py2/IPython/core/shellapp.py#L263-L280
krishauser/Klampt
972cc83ea5befac3f653c1ba20f80155768ad519
Python/python2_version/klampt/model/coordinates.py
python
Frame.worldRotation
(self)
return self._worldCoordinates[0]
Returns an element of SO(3) denoting the rotation from this frame to world coordinates
Returns an element of SO(3) denoting the rotation from this frame to world coordinates
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def worldRotation(self): """Returns an element of SO(3) denoting the rotation from this frame to world coordinates""" return self._worldCoordinates[0]
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https://github.com/krishauser/Klampt/blob/972cc83ea5befac3f653c1ba20f80155768ad519/Python/python2_version/klampt/model/coordinates.py#L59-L62
ChromiumWebApps/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
tools/valgrind/common.py
python
PlatformNames
()
Return an array of string to be used in paths for the platform (e.g. suppressions, gtest filters, ignore files etc.) The first element of the array describes the 'main' platform
Return an array of string to be used in paths for the platform (e.g. suppressions, gtest filters, ignore files etc.) The first element of the array describes the 'main' platform
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def PlatformNames(): """Return an array of string to be used in paths for the platform (e.g. suppressions, gtest filters, ignore files etc.) The first element of the array describes the 'main' platform """ if IsLinux(): return ['linux'] if IsMac(): return ['mac'] if IsWindows(): names = ['win32'] version_name = WindowsVersionName() if version_name is not None: names.append('win-%s' % version_name) return names raise NotImplementedError('Unknown platform "%s".' % sys.platform)
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/tools/valgrind/common.py#L147-L162
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
third_party/catapult/telemetry/third_party/modulegraph/setup.py
python
_extractall
(self, path=".", members=None)
Extract all members from the archive to the current working directory and set owner, modification time and permissions on directories afterwards. `path' specifies a different directory to extract to. `members' is optional and must be a subset of the list returned by getmembers().
Extract all members from the archive to the current working directory and set owner, modification time and permissions on directories afterwards. `path' specifies a different directory to extract to. `members' is optional and must be a subset of the list returned by getmembers().
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def _extractall(self, path=".", members=None): """Extract all members from the archive to the current working directory and set owner, modification time and permissions on directories afterwards. `path' specifies a different directory to extract to. `members' is optional and must be a subset of the list returned by getmembers(). """ import copy import operator from tarfile import ExtractError directories = [] if members is None: members = self for tarinfo in members: if tarinfo.isdir(): # Extract directories with a safe mode. directories.append(tarinfo) tarinfo = copy.copy(tarinfo) tarinfo.mode = 448 # decimal for oct 0700 self.extract(tarinfo, path) # Reverse sort directories. if sys.version_info < (2, 4): def sorter(dir1, dir2): return cmp(dir1.name, dir2.name) directories.sort(sorter) directories.reverse() else: directories.sort(key=operator.attrgetter('name'), reverse=True) # Set correct owner, mtime and filemode on directories. for tarinfo in directories: dirpath = os.path.join(path, tarinfo.name) try: self.chown(tarinfo, dirpath) self.utime(tarinfo, dirpath) self.chmod(tarinfo, dirpath) except ExtractError: e = sys.exc_info()[1] if self.errorlevel > 1: raise else: self._dbg(1, "tarfile: %s" % e)
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/telemetry/third_party/modulegraph/setup.py#L472-L516
weolar/miniblink49
1c4678db0594a4abde23d3ebbcc7cd13c3170777
third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/irc/irclib.py
python
Event.__init__
(self, eventtype, source, target, arguments=None)
Constructor of Event objects. Arguments: eventtype -- A string describing the event. source -- The originator of the event (a nick mask or a server). target -- The target of the event (a nick or a channel). arguments -- Any event specific arguments.
Constructor of Event objects.
[ "Constructor", "of", "Event", "objects", "." ]
def __init__(self, eventtype, source, target, arguments=None): """Constructor of Event objects. Arguments: eventtype -- A string describing the event. source -- The originator of the event (a nick mask or a server). target -- The target of the event (a nick or a channel). arguments -- Any event specific arguments. """ self._eventtype = eventtype self._source = source self._target = target if arguments: self._arguments = arguments else: self._arguments = []
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https://github.com/weolar/miniblink49/blob/1c4678db0594a4abde23d3ebbcc7cd13c3170777/third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/irc/irclib.py#L1119-L1138
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/_core.py
python
SizerItem.GetFlag
(*args, **kwargs)
return _core_.SizerItem_GetFlag(*args, **kwargs)
GetFlag(self) -> int Get the flag value for this item.
GetFlag(self) -> int
[ "GetFlag", "(", "self", ")", "-", ">", "int" ]
def GetFlag(*args, **kwargs): """ GetFlag(self) -> int Get the flag value for this item. """ return _core_.SizerItem_GetFlag(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_core.py#L14211-L14217
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
tools/json_schema_compiler/cpp_type_generator.py
python
CppTypeGenerator.__init__
(self, model, schema_loader, default_namespace=None)
Creates a cpp_type_generator. The given root_namespace should be of the format extensions::api::sub. The generator will generate code suitable for use in the given model's namespace.
Creates a cpp_type_generator. The given root_namespace should be of the format extensions::api::sub. The generator will generate code suitable for use in the given model's namespace.
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def __init__(self, model, schema_loader, default_namespace=None): """Creates a cpp_type_generator. The given root_namespace should be of the format extensions::api::sub. The generator will generate code suitable for use in the given model's namespace. """ self._default_namespace = default_namespace if self._default_namespace is None: self._default_namespace = model.namespaces.values()[0] self._schema_loader = schema_loader
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/json_schema_compiler/cpp_type_generator.py#L28-L36
baidu-research/tensorflow-allreduce
66d5b855e90b0949e9fa5cca5599fd729a70e874
tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py
python
DNNLinearCombinedRegressor.predict_scores
(self, x=None, input_fn=None, batch_size=None, as_iterable=True)
return preds[key]
Returns predicted scores for given features. Args: x: features. input_fn: Input function. If set, x must be None. batch_size: Override default batch size. as_iterable: If True, return an iterable which keeps yielding predictions for each example until inputs are exhausted. Note: The inputs must terminate if you want the iterable to terminate (e.g. be sure to pass num_epochs=1 if you are using something like read_batch_features). Returns: Numpy array of predicted scores (or an iterable of predicted scores if as_iterable is True). If `label_dimension == 1`, the shape of the output is `[batch_size]`, otherwise the shape is `[batch_size, label_dimension]`.
Returns predicted scores for given features.
[ "Returns", "predicted", "scores", "for", "given", "features", "." ]
def predict_scores(self, x=None, input_fn=None, batch_size=None, as_iterable=True): """Returns predicted scores for given features. Args: x: features. input_fn: Input function. If set, x must be None. batch_size: Override default batch size. as_iterable: If True, return an iterable which keeps yielding predictions for each example until inputs are exhausted. Note: The inputs must terminate if you want the iterable to terminate (e.g. be sure to pass num_epochs=1 if you are using something like read_batch_features). Returns: Numpy array of predicted scores (or an iterable of predicted scores if as_iterable is True). If `label_dimension == 1`, the shape of the output is `[batch_size]`, otherwise the shape is `[batch_size, label_dimension]`. """ key = prediction_key.PredictionKey.SCORES preds = super(DNNLinearCombinedRegressor, self).predict( x=x, input_fn=input_fn, batch_size=batch_size, outputs=[key], as_iterable=as_iterable) if as_iterable: return (pred[key] for pred in preds) return preds[key]
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https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py#L1097-L1124
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
tools/cygprofile/symbol_extractor.py
python
SymbolInfosFromBinary
(binary_filename)
Runs objdump to get all the symbols from a binary. Args: binary_filename: path to the binary. Returns: A list of SymbolInfo from the binary.
Runs objdump to get all the symbols from a binary.
[ "Runs", "objdump", "to", "get", "all", "the", "symbols", "from", "a", "binary", "." ]
def SymbolInfosFromBinary(binary_filename): """Runs objdump to get all the symbols from a binary. Args: binary_filename: path to the binary. Returns: A list of SymbolInfo from the binary. """ command = (symbol.ToolPath('objdump'), '-t', '-w', binary_filename) p = subprocess.Popen(command, shell=False, stdout=subprocess.PIPE) try: result = _SymbolInfosFromStream(p.stdout) return result finally: p.stdout.close() p.wait()
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/tools/cygprofile/symbol_extractor.py#L84-L100
FreeCAD/FreeCAD
ba42231b9c6889b89e064d6d563448ed81e376ec
src/Mod/TemplatePyMod/DocumentObject.py
python
DocumentObject.getEnumerationsOfProperty
(self,attr)
return self.__object__.getEnumerationsOfProperty(attr)
returns the documentation string of a given property
returns the documentation string of a given property
[ "returns", "the", "documentation", "string", "of", "a", "given", "property" ]
def getEnumerationsOfProperty(self,attr): "returns the documentation string of a given property" return self.__object__.getEnumerationsOfProperty(attr)
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https://github.com/FreeCAD/FreeCAD/blob/ba42231b9c6889b89e064d6d563448ed81e376ec/src/Mod/TemplatePyMod/DocumentObject.py#L83-L85
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/idlelib/browser.py
python
ChildBrowserTreeItem.GetText
(self)
Return the name of the function/class to display.
Return the name of the function/class to display.
[ "Return", "the", "name", "of", "the", "function", "/", "class", "to", "display", "." ]
def GetText(self): "Return the name of the function/class to display." name = self.name if self.isfunction: return "def " + name + "(...)" else: return "class " + name
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/idlelib/browser.py#L199-L205
apple/swift-lldb
d74be846ef3e62de946df343e8c234bde93a8912
scripts/Python/static-binding/lldb.py
python
SBTrace.GetMetaData
(self, error, buf, offset, thread_id)
return _lldb.SBTrace_GetMetaData(self, error, buf, offset, thread_id)
GetMetaData(SBTrace self, SBError error, void * buf, size_t offset, lldb::tid_t thread_id) -> size_t
GetMetaData(SBTrace self, SBError error, void * buf, size_t offset, lldb::tid_t thread_id) -> size_t
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def GetMetaData(self, error, buf, offset, thread_id): """GetMetaData(SBTrace self, SBError error, void * buf, size_t offset, lldb::tid_t thread_id) -> size_t""" return _lldb.SBTrace_GetMetaData(self, error, buf, offset, thread_id)
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https://github.com/apple/swift-lldb/blob/d74be846ef3e62de946df343e8c234bde93a8912/scripts/Python/static-binding/lldb.py#L12237-L12239
husixu1/HUST-Homeworks
fbf6ed749eacab6e14bffea83703aadaf9324828
DataMining/src/randomCF.py
python
userDistanceTable
(table)
get user-user distance table from original table :param table: the original table :return: user-user similarity sparse matrix, in the form of 2-level dictionary
get user-user distance table from original table :param table: the original table :return: user-user similarity sparse matrix, in the form of 2-level dictionary
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def userDistanceTable(table): """get user-user distance table from original table :param table: the original table :return: user-user similarity sparse matrix, in the form of 2-level dictionary """ #itemUserTable = table.T #for users in itemUserTable: # for user in users: # user pass
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https://github.com/husixu1/HUST-Homeworks/blob/fbf6ed749eacab6e14bffea83703aadaf9324828/DataMining/src/randomCF.py#L34-L44
adobe/chromium
cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7
native_client_sdk/src/build_tools/build_utils.py
python
VersionString
()
return 'native_client_sdk_%s' % '_'.join(GetVersionNumbers())
Returns the version of native client based on the svn revision number.
Returns the version of native client based on the svn revision number.
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def VersionString(): '''Returns the version of native client based on the svn revision number.''' return 'native_client_sdk_%s' % '_'.join(GetVersionNumbers())
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https://github.com/adobe/chromium/blob/cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7/native_client_sdk/src/build_tools/build_utils.py#L190-L192
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/lib/agw/ultimatelistctrl.py
python
UltimateListItem.SetData
(self, data)
Sets client data for the item. :param `data`: the client data associated to the item. :note: Please note that client data is associated with the item and not with subitems.
Sets client data for the item.
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def SetData(self, data): """ Sets client data for the item. :param `data`: the client data associated to the item. :note: Please note that client data is associated with the item and not with subitems. """ self._mask |= ULC_MASK_DATA self._data = data
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/ultimatelistctrl.py#L1552-L1563
Netflix/NfWebCrypto
499faf4eb9f9ccf0b21dc728e974970f54bd6c52
plugin/ppapi/ppapi/generators/idl_gen_pnacl.py
python
PnaclGen.ArgsNeedWrapping
(self, args)
return False
Return true if any parameter in the list needs wrapping.
Return true if any parameter in the list needs wrapping.
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def ArgsNeedWrapping(self, args): """Return true if any parameter in the list needs wrapping. """ for arg in args: (type_str, name, array_dims, more_args) = arg if self.TypeNeedsWrapping(type_str, array_dims): return True return False
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https://github.com/Netflix/NfWebCrypto/blob/499faf4eb9f9ccf0b21dc728e974970f54bd6c52/plugin/ppapi/ppapi/generators/idl_gen_pnacl.py#L100-L107
ChromiumWebApps/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
tools/telemetry/third_party/png/png.py
python
read_pnm_header
(infile, supported=('P5','P6'))
return header[0], header[1], header[2], depth, header[3]
Read a PNM header, returning (format,width,height,depth,maxval). `width` and `height` are in pixels. `depth` is the number of channels in the image; for PBM and PGM it is synthesized as 1, for PPM as 3; for PAM images it is read from the header. `maxval` is synthesized (as 1) for PBM images.
Read a PNM header, returning (format,width,height,depth,maxval). `width` and `height` are in pixels. `depth` is the number of channels in the image; for PBM and PGM it is synthesized as 1, for PPM as 3; for PAM images it is read from the header. `maxval` is synthesized (as 1) for PBM images.
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def read_pnm_header(infile, supported=('P5','P6')): """ Read a PNM header, returning (format,width,height,depth,maxval). `width` and `height` are in pixels. `depth` is the number of channels in the image; for PBM and PGM it is synthesized as 1, for PPM as 3; for PAM images it is read from the header. `maxval` is synthesized (as 1) for PBM images. """ # Generally, see http://netpbm.sourceforge.net/doc/ppm.html # and http://netpbm.sourceforge.net/doc/pam.html supported = [strtobytes(x) for x in supported] # Technically 'P7' must be followed by a newline, so by using # rstrip() we are being liberal in what we accept. I think this # is acceptable. type = infile.read(3).rstrip() if type not in supported: raise NotImplementedError('file format %s not supported' % type) if type == strtobytes('P7'): # PAM header parsing is completely different. return read_pam_header(infile) # Expected number of tokens in header (3 for P4, 4 for P6) expected = 4 pbm = ('P1', 'P4') if type in pbm: expected = 3 header = [type] # We have to read the rest of the header byte by byte because the # final whitespace character (immediately following the MAXVAL in # the case of P6) may not be a newline. Of course all PNM files in # the wild use a newline at this point, so it's tempting to use # readline; but it would be wrong. def getc(): c = infile.read(1) if not c: raise Error('premature EOF reading PNM header') return c c = getc() while True: # Skip whitespace that precedes a token. while c.isspace(): c = getc() # Skip comments. while c == '#': while c not in '\n\r': c = getc() if not c.isdigit(): raise Error('unexpected character %s found in header' % c) # According to the specification it is legal to have comments # that appear in the middle of a token. # This is bonkers; I've never seen it; and it's a bit awkward to # code good lexers in Python (no goto). So we break on such # cases. token = strtobytes('') while c.isdigit(): token += c c = getc() # Slight hack. All "tokens" are decimal integers, so convert # them here. header.append(int(token)) if len(header) == expected: break # Skip comments (again) while c == '#': while c not in '\n\r': c = getc() if not c.isspace(): raise Error('expected header to end with whitespace, not %s' % c) if type in pbm: # synthesize a MAXVAL header.append(1) depth = (1,3)[type == strtobytes('P6')] return header[0], header[1], header[2], depth, header[3]
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/tools/telemetry/third_party/png/png.py#L3598-L3675
panda3d/panda3d
833ad89ebad58395d0af0b7ec08538e5e4308265
direct/src/filter/CommonFilters.py
python
CommonFilters.setBlurSharpen
(self, amount=0.0)
return self.reconfigure(fullrebuild, "BlurSharpen")
Enables the blur/sharpen filter. If the 'amount' parameter is 1.0, it will not have any effect. A value of 0.0 means fully blurred, and a value higher than 1.0 sharpens the image.
Enables the blur/sharpen filter. If the 'amount' parameter is 1.0, it will not have any effect. A value of 0.0 means fully blurred, and a value higher than 1.0 sharpens the image.
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def setBlurSharpen(self, amount=0.0): """Enables the blur/sharpen filter. If the 'amount' parameter is 1.0, it will not have any effect. A value of 0.0 means fully blurred, and a value higher than 1.0 sharpens the image.""" fullrebuild = ("BlurSharpen" not in self.configuration) self.configuration["BlurSharpen"] = amount return self.reconfigure(fullrebuild, "BlurSharpen")
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https://github.com/panda3d/panda3d/blob/833ad89ebad58395d0af0b7ec08538e5e4308265/direct/src/filter/CommonFilters.py#L555-L560
BlzFans/wke
b0fa21158312e40c5fbd84682d643022b6c34a93
cygwin/lib/python2.6/nntplib.py
python
NNTP.post
(self, f)
return self.getresp()
Process a POST command. Arguments: - f: file containing the article Returns: - resp: server response if successful
Process a POST command. Arguments: - f: file containing the article Returns: - resp: server response if successful
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def post(self, f): """Process a POST command. Arguments: - f: file containing the article Returns: - resp: server response if successful""" resp = self.shortcmd('POST') # Raises error_??? if posting is not allowed if resp[0] != '3': raise NNTPReplyError(resp) while 1: line = f.readline() if not line: break if line[-1] == '\n': line = line[:-1] if line[:1] == '.': line = '.' + line self.putline(line) self.putline('.') return self.getresp()
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https://github.com/BlzFans/wke/blob/b0fa21158312e40c5fbd84682d643022b6c34a93/cygwin/lib/python2.6/nntplib.py#L549-L569
ucsb-seclab/difuze
bb59a12ff87ad5ae45d9c60e349891bf80d72877
helper_scripts/components/bear_llvm_build.py
python
build_drivers
(compilation_commands, linker_commands, kernel_src_dir, target_arch, clang_path, llvm_link_path, llvm_bit_code_out, is_clang_build)
return True
The main method that performs the building and linking of the driver files. :param compilation_commands: Parsed compilation commands from the json. :param linker_commands: Parsed linker commands from the json. :param kernel_src_dir: Path to the kernel source directory. :param target_arch: Number representing target architecture. :param clang_path: Path to clang. :param llvm_link_path: Path to llvm-link :param llvm_bit_code_out: Folder where all the linked bitcode files should be stored. :param is_clang_build: Flag to indicate that this is a clang build. :return: True
The main method that performs the building and linking of the driver files. :param compilation_commands: Parsed compilation commands from the json. :param linker_commands: Parsed linker commands from the json. :param kernel_src_dir: Path to the kernel source directory. :param target_arch: Number representing target architecture. :param clang_path: Path to clang. :param llvm_link_path: Path to llvm-link :param llvm_bit_code_out: Folder where all the linked bitcode files should be stored. :param is_clang_build: Flag to indicate that this is a clang build. :return: True
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def build_drivers(compilation_commands, linker_commands, kernel_src_dir, target_arch, clang_path, llvm_link_path, llvm_bit_code_out, is_clang_build): """ The main method that performs the building and linking of the driver files. :param compilation_commands: Parsed compilation commands from the json. :param linker_commands: Parsed linker commands from the json. :param kernel_src_dir: Path to the kernel source directory. :param target_arch: Number representing target architecture. :param clang_path: Path to clang. :param llvm_link_path: Path to llvm-link :param llvm_bit_code_out: Folder where all the linked bitcode files should be stored. :param is_clang_build: Flag to indicate that this is a clang build. :return: True """ output_llvm_sh_file = os.path.join(llvm_bit_code_out, 'llvm_build.sh') fp_out = open(output_llvm_sh_file, 'w') fp_out.write("#!/bin/bash\n") log_info("Writing all compilation commands to", output_llvm_sh_file) all_compilation_commands = [] obj_bc_map = {} for curr_compilation_command in compilation_commands: if is_clang_build: wd, obj_file, bc_file, build_str = _get_llvm_build_str_from_llvm(clang_path, curr_compilation_command.curr_args, kernel_src_dir, target_arch, curr_compilation_command.work_dir, curr_compilation_command.src_file, curr_compilation_command.output_file, llvm_bit_code_out) else: wd, obj_file, bc_file, build_str = _get_llvm_build_str(clang_path, curr_compilation_command.curr_args, kernel_src_dir, target_arch, curr_compilation_command.work_dir, curr_compilation_command.src_file, curr_compilation_command.output_file, llvm_bit_code_out) all_compilation_commands.append((wd, build_str)) obj_bc_map[obj_file] = bc_file fp_out.write("cd " + wd + ";" + build_str + "\n") fp_out.close() log_info("Got", len(all_compilation_commands), "compilation commands.") log_info("Running compilation commands in multiprocessing modea.") p = Pool(cpu_count()) return_vals = p.map(run_program_with_wd, all_compilation_commands) log_success("Finished running compilation commands.") output_llvm_sh_file = os.path.join(llvm_bit_code_out, 'llvm_link_cmds.sh') fp_out = open(output_llvm_sh_file, 'w') fp_out.write("#!/bin/bash\n") log_info("Writing all linker commands to", output_llvm_sh_file) all_linker_commands = [] recursive_linker_commands = [] for curr_linked_command in linker_commands: curr_ret_val = _get_llvm_link_str(llvm_link_path, kernel_src_dir, curr_linked_command.input_files, obj_bc_map, curr_linked_command.output_file, curr_linked_command.work_dir, llvm_bit_code_out) if curr_ret_val is not None: wd, obj_file, bc_file, build_str = curr_ret_val all_linker_commands.append((wd, build_str)) obj_bc_map[obj_file] = bc_file fp_out.write("cd " + wd + ";" + build_str + "\n") else: # these are recursive linker commands. recursive_linker_commands.append(curr_linked_command) log_info("Got", len(all_linker_commands), "regular linker commands.") log_info("Running linker commands in multiprocessing mode.") p = Pool(cpu_count()) return_vals = p.map(run_program_with_wd, all_linker_commands) log_success("Finished running linker commands.") if len(recursive_linker_commands) > 0: log_info("Got", len(recursive_linker_commands), " recursive linker commands.") _process_recursive_linker_commands(recursive_linker_commands, kernel_src_dir, llvm_link_path, llvm_bit_code_out, obj_bc_map, fp_out) fp_out.close() return True
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https://github.com/ucsb-seclab/difuze/blob/bb59a12ff87ad5ae45d9c60e349891bf80d72877/helper_scripts/components/bear_llvm_build.py#L302-L379
apache/trafodion
8455c839ad6b6d7b6e04edda5715053095b78046
install/python-installer/scripts/httplib2/__init__.py
python
Authentication.request
(self, method, request_uri, headers, content)
Modify the request headers to add the appropriate Authorization header. Over-ride this in sub-classes.
Modify the request headers to add the appropriate Authorization header. Over-ride this in sub-classes.
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def request(self, method, request_uri, headers, content): """Modify the request headers to add the appropriate Authorization header. Over-ride this in sub-classes.""" pass
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https://github.com/apache/trafodion/blob/8455c839ad6b6d7b6e04edda5715053095b78046/install/python-installer/scripts/httplib2/__init__.py#L497-L500
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_internal/utils/filesystem.py
python
find_files
(path, pattern)
return result
Returns a list of absolute paths of files beneath path, recursively, with filenames which match the UNIX-style shell glob pattern.
Returns a list of absolute paths of files beneath path, recursively,
[ "Returns", "a", "list", "of", "absolute", "paths", "of", "files", "beneath", "path", "recursively" ]
def find_files(path, pattern): # type: (str, str) -> List[str] """Returns a list of absolute paths of files beneath path, recursively, with filenames which match the UNIX-style shell glob pattern.""" result = [] # type: List[str] for root, _, files in os.walk(path): matches = fnmatch.filter(files, pattern) result.extend(os.path.join(root, f) for f in matches) return result
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_internal/utils/filesystem.py#L327-L343
h2oai/deepwater
80e345c582e6ef912a31f42707a2f31c01b064da
docs/sphinxext/apigen.py
python
ApiDocWriter._parse_lines
(self, linesource)
return functions, classes
Parse lines of text for functions and classes
Parse lines of text for functions and classes
[ "Parse", "lines", "of", "text", "for", "functions", "and", "classes" ]
def _parse_lines(self, linesource): ''' Parse lines of text for functions and classes ''' functions = [] classes = [] for line in linesource: if line.startswith('def ') and line.count('('): # exclude private stuff name = self._get_object_name(line) if not name.startswith('_'): functions.append(name) elif line.startswith('class '): # exclude private stuff name = self._get_object_name(line) if not name.startswith('_'): classes.append(name) else: pass functions.sort() classes.sort() return functions, classes
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https://github.com/h2oai/deepwater/blob/80e345c582e6ef912a31f42707a2f31c01b064da/docs/sphinxext/apigen.py#L172-L191
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/psutil/_pslinux.py
python
sensors_fans
()
return dict(ret)
Return hardware fans info (for CPU and other peripherals) as a dict including hardware label and current speed. Implementation notes: - /sys/class/hwmon looks like the most recent interface to retrieve this info, and this implementation relies on it only (old distros will probably use something else) - lm-sensors on Ubuntu 16.04 relies on /sys/class/hwmon
Return hardware fans info (for CPU and other peripherals) as a dict including hardware label and current speed.
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def sensors_fans(): """Return hardware fans info (for CPU and other peripherals) as a dict including hardware label and current speed. Implementation notes: - /sys/class/hwmon looks like the most recent interface to retrieve this info, and this implementation relies on it only (old distros will probably use something else) - lm-sensors on Ubuntu 16.04 relies on /sys/class/hwmon """ ret = collections.defaultdict(list) basenames = glob.glob('/sys/class/hwmon/hwmon*/fan*_*') if not basenames: # CentOS has an intermediate /device directory: # https://github.com/giampaolo/psutil/issues/971 basenames = glob.glob('/sys/class/hwmon/hwmon*/device/fan*_*') basenames = sorted(set([x.split('_')[0] for x in basenames])) for base in basenames: try: current = int(cat(base + '_input')) except (IOError, OSError) as err: warnings.warn("ignoring %r" % err, RuntimeWarning) continue unit_name = cat(os.path.join(os.path.dirname(base), 'name'), binary=False) label = cat(base + '_label', fallback='', binary=False) ret[unit_name].append(_common.sfan(label, current)) return dict(ret)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/psutil/_pslinux.py#L1293-L1322
windystrife/UnrealEngine_NVIDIAGameWorks
b50e6338a7c5b26374d66306ebc7807541ff815e
Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/pythonwin/pywin/docking/DockingBar.py
python
DockingBar.OnWindowPosChanged
(self, msg)
return 0
LPARAM used with WM_WINDOWPOSCHANGED: typedef struct { HWND hwnd; HWND hwndInsertAfter; int x; int y; int cx; int cy; UINT flags;} WINDOWPOS;
LPARAM used with WM_WINDOWPOSCHANGED: typedef struct { HWND hwnd; HWND hwndInsertAfter; int x; int y; int cx; int cy; UINT flags;} WINDOWPOS;
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def OnWindowPosChanged(self, msg): if self.GetSafeHwnd()==0 or self.dialog is None: return 0 lparam = msg[3] """ LPARAM used with WM_WINDOWPOSCHANGED: typedef struct { HWND hwnd; HWND hwndInsertAfter; int x; int y; int cx; int cy; UINT flags;} WINDOWPOS; """ format = "PPiiiii" bytes = win32ui.GetBytes( lparam, struct.calcsize(format) ) hwnd, hwndAfter, x, y, cx, cy, flags = struct.unpack(format, bytes) if self.bInRecalcNC: rc = self.GetClientRect() self.dialog.MoveWindow(rc) return 0 # Find on which side are we docked nDockBarID = self.GetParent().GetDlgCtrlID() # Return if dropped at same location # no docking side change and no size change if (nDockBarID == self.nDockBarID) and \ (flags & win32con.SWP_NOSIZE) and \ ((self._obj_.dwStyle & afxres.CBRS_BORDER_ANY) != afxres.CBRS_BORDER_ANY): return self.nDockBarID = nDockBarID # Force recalc the non-client area self.bInRecalcNC = 1 try: swpflags = win32con.SWP_NOSIZE | win32con.SWP_NOMOVE | win32con.SWP_NOZORDER | win32con.SWP_FRAMECHANGED self.SetWindowPos(0, (0,0,0,0), swpflags) finally: self.bInRecalcNC = 0 return 0
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https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/pythonwin/pywin/docking/DockingBar.py#L163-L202
v8/v8
fee3bf095260bf657a3eea4d3d41f90c42c6c857
tools/grokdump.py
python
InspectionShell.do_ko
(self, address)
return self.do_known_oldspace(address)
see known_oldspace
see known_oldspace
[ "see", "known_oldspace" ]
def do_ko(self, address): """ see known_oldspace """ return self.do_known_oldspace(address)
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https://github.com/v8/v8/blob/fee3bf095260bf657a3eea4d3d41f90c42c6c857/tools/grokdump.py#L3719-L3721
InsightSoftwareConsortium/ITK
87acfce9a93d928311c38bc371b666b515b9f19d
Modules/ThirdParty/pygccxml/src/pygccxml/declarations/declaration.py
python
declaration_t.__lt__
(self, other)
return self._get__cmp__data() < other._get__cmp__data()
.. code-block:: python if not isinstance( other, self.__class__ ): return self.__class__.__name__ < other.__class__.__name__ return self._get__cmp__data() < other._get__cmp__data()
.. code-block:: python
[ "..", "code", "-", "block", "::", "python" ]
def __lt__(self, other): """ .. code-block:: python if not isinstance( other, self.__class__ ): return self.__class__.__name__ < other.__class__.__name__ return self._get__cmp__data() < other._get__cmp__data() """ if not isinstance(other, self.__class__): return self.__class__.__name__ < other.__class__.__name__ return self._get__cmp__data() < other._get__cmp__data()
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https://github.com/InsightSoftwareConsortium/ITK/blob/87acfce9a93d928311c38bc371b666b515b9f19d/Modules/ThirdParty/pygccxml/src/pygccxml/declarations/declaration.py#L126-L138
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/scipy/scipy/cluster/vq.py
python
py_vq
(obs, code_book, check_finite=True)
return code, sqrt(min_dist)
Python version of vq algorithm. The algorithm computes the euclidian distance between each observation and every frame in the code_book. Parameters ---------- obs : ndarray Expects a rank 2 array. Each row is one observation. code_book : ndarray Code book to use. Same format than obs. Should have same number of features (eg columns) than obs. check_finite : bool, optional Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs. Default: True Returns ------- code : ndarray code[i] gives the label of the ith obversation, that its code is code_book[code[i]]. mind_dist : ndarray min_dist[i] gives the distance between the ith observation and its corresponding code. Notes ----- This function is slower than the C version but works for all input types. If the inputs have the wrong types for the C versions of the function, this one is called as a last resort. It is about 20 times slower than the C version.
Python version of vq algorithm.
[ "Python", "version", "of", "vq", "algorithm", "." ]
def py_vq(obs, code_book, check_finite=True): """ Python version of vq algorithm. The algorithm computes the euclidian distance between each observation and every frame in the code_book. Parameters ---------- obs : ndarray Expects a rank 2 array. Each row is one observation. code_book : ndarray Code book to use. Same format than obs. Should have same number of features (eg columns) than obs. check_finite : bool, optional Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs. Default: True Returns ------- code : ndarray code[i] gives the label of the ith obversation, that its code is code_book[code[i]]. mind_dist : ndarray min_dist[i] gives the distance between the ith observation and its corresponding code. Notes ----- This function is slower than the C version but works for all input types. If the inputs have the wrong types for the C versions of the function, this one is called as a last resort. It is about 20 times slower than the C version. """ obs = _asarray_validated(obs, check_finite=check_finite) code_book = _asarray_validated(code_book, check_finite=check_finite) # n = number of observations # d = number of features if np.ndim(obs) == 1: if not np.ndim(obs) == np.ndim(code_book): raise ValueError( "Observation and code_book should have the same rank") else: return _py_vq_1d(obs, code_book) else: (n, d) = shape(obs) # code books and observations should have same number of features and same # shape if not np.ndim(obs) == np.ndim(code_book): raise ValueError("Observation and code_book should have the same rank") elif not d == code_book.shape[1]: raise ValueError("Code book(%d) and obs(%d) should have the same " "number of features (eg columns)""" % (code_book.shape[1], d)) code = zeros(n, dtype=int) min_dist = zeros(n) for i in range(n): dist = np.sum((obs[i] - code_book) ** 2, 1) code[i] = argmin(dist) min_dist[i] = dist[code[i]] return code, sqrt(min_dist)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/cluster/vq.py#L228-L295
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/distutils/_shell_utils.py
python
CommandLineParser.split
(cmd)
Split a command line string into a list of arguments
Split a command line string into a list of arguments
[ "Split", "a", "command", "line", "string", "into", "a", "list", "of", "arguments" ]
def split(cmd): """ Split a command line string into a list of arguments """ raise NotImplementedError
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/distutils/_shell_utils.py#L30-L32
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemFramework/v1/AWS/common-code/lib/requests/sessions.py
python
SessionRedirectMixin.rebuild_method
(self, prepared_request, response)
When being redirected we may want to change the method of the request based on certain specs or browser behavior.
When being redirected we may want to change the method of the request based on certain specs or browser behavior.
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def rebuild_method(self, prepared_request, response): """When being redirected we may want to change the method of the request based on certain specs or browser behavior. """ method = prepared_request.method # https://tools.ietf.org/html/rfc7231#section-6.4.4 if response.status_code == codes.see_other and method != 'HEAD': method = 'GET' # Do what the browsers do, despite standards... # First, turn 302s into GETs. if response.status_code == codes.found and method != 'HEAD': method = 'GET' # Second, if a POST is responded to with a 301, turn it into a GET. # This bizarre behaviour is explained in Issue 1704. if response.status_code == codes.moved and method == 'POST': method = 'GET' prepared_request.method = method
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemFramework/v1/AWS/common-code/lib/requests/sessions.py#L314-L334
redpony/cdec
f7c4899b174d86bc70b40b1cae68dcad364615cb
python/cdec/configobj.py
python
InterpolationEngine._parse_match
(self, match)
Implementation-dependent helper function. Will be passed a match object corresponding to the interpolation key we just found (e.g., "%(foo)s" or "$foo"). Should look up that key in the appropriate config file section (using the ``_fetch()`` helper function) and return a 3-tuple: (key, value, section) ``key`` is the name of the key we're looking for ``value`` is the value found for that key ``section`` is a reference to the section where it was found ``key`` and ``section`` should be None if no further interpolation should be performed on the resulting value (e.g., if we interpolated "$$" and returned "$").
Implementation-dependent helper function.
[ "Implementation", "-", "dependent", "helper", "function", "." ]
def _parse_match(self, match): """Implementation-dependent helper function. Will be passed a match object corresponding to the interpolation key we just found (e.g., "%(foo)s" or "$foo"). Should look up that key in the appropriate config file section (using the ``_fetch()`` helper function) and return a 3-tuple: (key, value, section) ``key`` is the name of the key we're looking for ``value`` is the value found for that key ``section`` is a reference to the section where it was found ``key`` and ``section`` should be None if no further interpolation should be performed on the resulting value (e.g., if we interpolated "$$" and returned "$"). """ raise NotImplementedError()
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https://github.com/redpony/cdec/blob/f7c4899b174d86bc70b40b1cae68dcad364615cb/python/cdec/configobj.py#L403-L419
weolar/miniblink49
1c4678db0594a4abde23d3ebbcc7cd13c3170777
third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/irc/irclib.py
python
IRC.process_once
(self, timeout=0)
Process data from connections once. Arguments: timeout -- How long the select() call should wait if no data is available. This method should be called periodically to check and process incoming data, if there are any. If that seems boring, look at the process_forever method.
Process data from connections once.
[ "Process", "data", "from", "connections", "once", "." ]
def process_once(self, timeout=0): """Process data from connections once. Arguments: timeout -- How long the select() call should wait if no data is available. This method should be called periodically to check and process incoming data, if there are any. If that seems boring, look at the process_forever method. """ sockets = map(lambda x: x._get_socket(), self.connections) sockets = filter(lambda x: x != None, sockets) if sockets: (i, o, e) = select.select(sockets, [], [], timeout) self.process_data(i) else: time.sleep(timeout) self.process_timeout()
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https://github.com/weolar/miniblink49/blob/1c4678db0594a4abde23d3ebbcc7cd13c3170777/third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/irc/irclib.py#L198-L217
Xilinx/Vitis-AI
fc74d404563d9951b57245443c73bef389f3657f
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/signal/fft_ops.py
python
_rfft_grad_helper
(rank, irfft_fn)
return _grad
Returns a gradient function for an RFFT of the provided rank.
Returns a gradient function for an RFFT of the provided rank.
[ "Returns", "a", "gradient", "function", "for", "an", "RFFT", "of", "the", "provided", "rank", "." ]
def _rfft_grad_helper(rank, irfft_fn): """Returns a gradient function for an RFFT of the provided rank.""" # Can't happen because we don't register a gradient for RFFT3D. assert rank in (1, 2), "Gradient for RFFT3D is not implemented." def _grad(op, grad): """A gradient function for RFFT with the provided `rank` and `irfft_fn`.""" fft_length = op.inputs[1] input_shape = _array_ops.shape(op.inputs[0]) is_even = _math_ops.cast(1 - (fft_length[-1] % 2), _dtypes.complex64) def _tile_for_broadcasting(matrix, t): expanded = _array_ops.reshape( matrix, _array_ops.concat([ _array_ops.ones([_array_ops.rank(t) - 2], _dtypes.int32), _array_ops.shape(matrix) ], 0)) return _array_ops.tile( expanded, _array_ops.concat([_array_ops.shape(t)[:-2], [1, 1]], 0)) def _mask_matrix(length): """Computes t_n = exp(sqrt(-1) * pi * n^2 / line_len).""" # TODO(rjryan): Speed up computation of twiddle factors using the # following recurrence relation and cache them across invocations of RFFT. # # t_n = exp(sqrt(-1) * pi * n^2 / line_len) # for n = 0, 1,..., line_len-1. # For n > 2, use t_n = t_{n-1}^2 / t_{n-2} * t_1^2 a = _array_ops.tile( _array_ops.expand_dims(_math_ops.range(length), 0), (length, 1)) b = _array_ops.transpose(a, [1, 0]) return _math_ops.exp( -2j * np.pi * _math_ops.cast(a * b, _dtypes.complex64) / _math_ops.cast(length, _dtypes.complex64)) def _ymask(length): """A sequence of [1+0j, -1+0j, 1+0j, -1+0j, ...] with length `length`.""" return _math_ops.cast(1 - 2 * (_math_ops.range(length) % 2), _dtypes.complex64) y0 = grad[..., 0:1] if rank == 1: ym = grad[..., -1:] extra_terms = y0 + is_even * ym * _ymask(input_shape[-1]) elif rank == 2: # Create a mask matrix for y0 and ym. base_mask = _mask_matrix(input_shape[-2]) # Tile base_mask to match y0 in shape so that we can batch-matmul the # inner 2 dimensions. tiled_mask = _tile_for_broadcasting(base_mask, y0) y0_term = _math_ops.matmul(tiled_mask, _math_ops.conj(y0)) extra_terms = y0_term ym = grad[..., -1:] ym_term = _math_ops.matmul(tiled_mask, _math_ops.conj(ym)) inner_dim = input_shape[-1] ym_term = _array_ops.tile( ym_term, _array_ops.concat([ _array_ops.ones([_array_ops.rank(grad) - 1], _dtypes.int32), [inner_dim] ], 0)) * _ymask(inner_dim) extra_terms += is_even * ym_term # The gradient of RFFT is the IRFFT of the incoming gradient times a scaling # factor, plus some additional terms to make up for the components dropped # due to Hermitian symmetry. input_size = _math_ops.cast( _fft_size_for_grad(op.inputs[0], rank), _dtypes.float32) the_irfft = irfft_fn(grad, fft_length) return 0.5 * (the_irfft * input_size + _math_ops.real(extra_terms)), None return _grad
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/ops/signal/fft_ops.py#L218-L295
microsoft/checkedc-clang
a173fefde5d7877b7750e7ce96dd08cf18baebf2
clang/utils/check_cfc/obj_diff.py
python
dump_debug
(objfile)
return [line for line in out.split(os.linesep) if keep_line(line)]
Dump all of the debug info from a file.
Dump all of the debug info from a file.
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def dump_debug(objfile): """Dump all of the debug info from a file.""" p = subprocess.Popen([disassembler, '-WliaprmfsoRt', objfile], stdout=subprocess.PIPE, stderr=subprocess.PIPE) (out, err) = p.communicate() if p.returncode or err: print("Dump debug failed: {}".format(objfile)) sys.exit(1) return [line for line in out.split(os.linesep) if keep_line(line)]
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https://github.com/microsoft/checkedc-clang/blob/a173fefde5d7877b7750e7ce96dd08cf18baebf2/clang/utils/check_cfc/obj_diff.py#L30-L37
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/ops/variables.py
python
RefVariable.__init__
( self, # pylint: disable=super-init-not-called initial_value=None, trainable=None, collections=None, validate_shape=True, caching_device=None, name=None, variable_def=None, dtype=None, expected_shape=None, import_scope=None, constraint=None, synchronization=None, aggregation=None, shape=None)
Creates a new variable with value `initial_value`. The new variable is added to the graph collections listed in `collections`, which defaults to `[GraphKeys.GLOBAL_VARIABLES]`. If `trainable` is `True` the variable is also added to the graph collection `GraphKeys.TRAINABLE_VARIABLES`. This constructor creates both a `variable` Op and an `assign` Op to set the variable to its initial value. Args: initial_value: A `Tensor`, or Python object convertible to a `Tensor`, which is the initial value for the Variable. The initial value must have a shape specified unless `validate_shape` is set to False. Can also be a callable with no argument that returns the initial value when called. In that case, `dtype` must be specified. (Note that initializer functions from init_ops.py must first be bound to a shape before being used here.) trainable: If `True`, also adds the variable to the graph collection `GraphKeys.TRAINABLE_VARIABLES`. This collection is used as the default list of variables to use by the `Optimizer` classes. Defaults to `True`, unless `synchronization` is set to `ON_READ`, in which case it defaults to `False`. collections: List of graph collections keys. The new variable is added to these collections. Defaults to `[GraphKeys.GLOBAL_VARIABLES]`. validate_shape: If `False`, allows the variable to be initialized with a value of unknown shape. If `True`, the default, the shape of `initial_value` must be known. caching_device: Optional device string describing where the Variable should be cached for reading. Defaults to the Variable's device. If not `None`, caches on another device. Typical use is to cache on the device where the Ops using the Variable reside, to deduplicate copying through `Switch` and other conditional statements. name: Optional name for the variable. Defaults to `'Variable'` and gets uniquified automatically. variable_def: `VariableDef` protocol buffer. If not `None`, recreates the Variable object with its contents, referencing the variable's nodes in the graph, which must already exist. The graph is not changed. `variable_def` and the other arguments are mutually exclusive. dtype: If set, initial_value will be converted to the given type. If `None`, either the datatype will be kept (if `initial_value` is a Tensor), or `convert_to_tensor` will decide. expected_shape: A TensorShape. If set, initial_value is expected to have this shape. import_scope: Optional `string`. Name scope to add to the `Variable.` Only used when initializing from protocol buffer. constraint: An optional projection function to be applied to the variable after being updated by an `Optimizer` (e.g. used to implement norm constraints or value constraints for layer weights). The function must take as input the unprojected Tensor representing the value of the variable and return the Tensor for the projected value (which must have the same shape). Constraints are not safe to use when doing asynchronous distributed training. synchronization: Indicates when a distributed a variable will be aggregated. Accepted values are constants defined in the class `tf.VariableSynchronization`. By default the synchronization is set to `AUTO` and the current `DistributionStrategy` chooses when to synchronize. aggregation: Indicates how a distributed variable will be aggregated. Accepted values are constants defined in the class `tf.VariableAggregation`. shape: (optional) The shape of this variable. If None, the shape of `initial_value` will be used. When setting this argument to `tf.TensorShape(None)` (representing an unspecified shape), the variable can be assigned with values of different shapes. Raises: ValueError: If both `variable_def` and initial_value are specified. ValueError: If the initial value is not specified, or does not have a shape and `validate_shape` is `True`. RuntimeError: If eager execution is enabled.
Creates a new variable with value `initial_value`.
[ "Creates", "a", "new", "variable", "with", "value", "initial_value", "." ]
def __init__( self, # pylint: disable=super-init-not-called initial_value=None, trainable=None, collections=None, validate_shape=True, caching_device=None, name=None, variable_def=None, dtype=None, expected_shape=None, import_scope=None, constraint=None, synchronization=None, aggregation=None, shape=None): """Creates a new variable with value `initial_value`. The new variable is added to the graph collections listed in `collections`, which defaults to `[GraphKeys.GLOBAL_VARIABLES]`. If `trainable` is `True` the variable is also added to the graph collection `GraphKeys.TRAINABLE_VARIABLES`. This constructor creates both a `variable` Op and an `assign` Op to set the variable to its initial value. Args: initial_value: A `Tensor`, or Python object convertible to a `Tensor`, which is the initial value for the Variable. The initial value must have a shape specified unless `validate_shape` is set to False. Can also be a callable with no argument that returns the initial value when called. In that case, `dtype` must be specified. (Note that initializer functions from init_ops.py must first be bound to a shape before being used here.) trainable: If `True`, also adds the variable to the graph collection `GraphKeys.TRAINABLE_VARIABLES`. This collection is used as the default list of variables to use by the `Optimizer` classes. Defaults to `True`, unless `synchronization` is set to `ON_READ`, in which case it defaults to `False`. collections: List of graph collections keys. The new variable is added to these collections. Defaults to `[GraphKeys.GLOBAL_VARIABLES]`. validate_shape: If `False`, allows the variable to be initialized with a value of unknown shape. If `True`, the default, the shape of `initial_value` must be known. caching_device: Optional device string describing where the Variable should be cached for reading. Defaults to the Variable's device. If not `None`, caches on another device. Typical use is to cache on the device where the Ops using the Variable reside, to deduplicate copying through `Switch` and other conditional statements. name: Optional name for the variable. Defaults to `'Variable'` and gets uniquified automatically. variable_def: `VariableDef` protocol buffer. If not `None`, recreates the Variable object with its contents, referencing the variable's nodes in the graph, which must already exist. The graph is not changed. `variable_def` and the other arguments are mutually exclusive. dtype: If set, initial_value will be converted to the given type. If `None`, either the datatype will be kept (if `initial_value` is a Tensor), or `convert_to_tensor` will decide. expected_shape: A TensorShape. If set, initial_value is expected to have this shape. import_scope: Optional `string`. Name scope to add to the `Variable.` Only used when initializing from protocol buffer. constraint: An optional projection function to be applied to the variable after being updated by an `Optimizer` (e.g. used to implement norm constraints or value constraints for layer weights). The function must take as input the unprojected Tensor representing the value of the variable and return the Tensor for the projected value (which must have the same shape). Constraints are not safe to use when doing asynchronous distributed training. synchronization: Indicates when a distributed a variable will be aggregated. Accepted values are constants defined in the class `tf.VariableSynchronization`. By default the synchronization is set to `AUTO` and the current `DistributionStrategy` chooses when to synchronize. aggregation: Indicates how a distributed variable will be aggregated. Accepted values are constants defined in the class `tf.VariableAggregation`. shape: (optional) The shape of this variable. If None, the shape of `initial_value` will be used. When setting this argument to `tf.TensorShape(None)` (representing an unspecified shape), the variable can be assigned with values of different shapes. Raises: ValueError: If both `variable_def` and initial_value are specified. ValueError: If the initial value is not specified, or does not have a shape and `validate_shape` is `True`. RuntimeError: If eager execution is enabled. """ self._in_graph_mode = True if variable_def: # If variable_def is provided, recreates the variable from its fields. if initial_value: raise ValueError("variable_def and initial_value are mutually " "exclusive.") self._init_from_proto(variable_def, import_scope=import_scope) else: # Create from initial_value. self._init_from_args( initial_value=initial_value, trainable=trainable, collections=collections, validate_shape=validate_shape, caching_device=caching_device, name=name, dtype=dtype, expected_shape=expected_shape, constraint=constraint, synchronization=synchronization, aggregation=aggregation, shape=shape)
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/ops/variables.py#L1550-L1659
gnuradio/gnuradio
09c3c4fa4bfb1a02caac74cb5334dfe065391e3b
docs/doxygen/doxyxml/base.py
python
Base._get_dict_members
(self, cat=None)
return self._dict_members[cat]
For given category a dictionary is returned mapping member names to members of that category. For names that are duplicated the name is mapped to None.
For given category a dictionary is returned mapping member names to members of that category. For names that are duplicated the name is mapped to None.
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def _get_dict_members(self, cat=None): """ For given category a dictionary is returned mapping member names to members of that category. For names that are duplicated the name is mapped to None. """ self.confirm_no_error() if cat not in self._dict_members: new_dict = {} for mem in self.in_category(cat): if mem.name() not in new_dict: new_dict[mem.name()] = mem else: new_dict[mem.name()] = self.Duplicate self._dict_members[cat] = new_dict return self._dict_members[cat]
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https://github.com/gnuradio/gnuradio/blob/09c3c4fa4bfb1a02caac74cb5334dfe065391e3b/docs/doxygen/doxyxml/base.py#L111-L126
CRYTEK/CRYENGINE
232227c59a220cbbd311576f0fbeba7bb53b2a8c
Editor/Python/windows/Lib/site-packages/pip/_vendor/requests/packages/urllib3/packages/ordered_dict.py
python
OrderedDict.fromkeys
(cls, iterable, value=None)
return d
OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S and values equal to v (which defaults to None).
OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S and values equal to v (which defaults to None).
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def fromkeys(cls, iterable, value=None): '''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S and values equal to v (which defaults to None). ''' d = cls() for key in iterable: d[key] = value return d
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https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Editor/Python/windows/Lib/site-packages/pip/_vendor/requests/packages/urllib3/packages/ordered_dict.py#L225-L233
rbgirshick/caffe-fast-rcnn
28a579eaf0668850705598b3075b8969f22226d9
python/caffe/pycaffe.py
python
_Net_blobs
(self)
return OrderedDict(zip(self._blob_names, self._blobs))
An OrderedDict (bottom to top, i.e., input to output) of network blobs indexed by name
An OrderedDict (bottom to top, i.e., input to output) of network blobs indexed by name
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def _Net_blobs(self): """ An OrderedDict (bottom to top, i.e., input to output) of network blobs indexed by name """ return OrderedDict(zip(self._blob_names, self._blobs))
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https://github.com/rbgirshick/caffe-fast-rcnn/blob/28a579eaf0668850705598b3075b8969f22226d9/python/caffe/pycaffe.py#L22-L27
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/Jinja2/py2/jinja2/compiler.py
python
CodeGenerator.visit_Block
(self, node, frame)
Call a block and register it for the template.
Call a block and register it for the template.
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def visit_Block(self, node, frame): """Call a block and register it for the template.""" level = 0 if frame.toplevel: # if we know that we are a child template, there is no need to # check if we are one if self.has_known_extends: return if self.extends_so_far > 0: self.writeline("if parent_template is None:") self.indent() level += 1 if node.scoped: context = self.derive_context(frame) else: context = self.get_context_ref() if ( supports_yield_from and not self.environment.is_async and frame.buffer is None ): self.writeline( "yield from context.blocks[%r][0](%s)" % (node.name, context), node ) else: loop = self.environment.is_async and "async for" or "for" self.writeline( "%s event in context.blocks[%r][0](%s):" % (loop, node.name, context), node, ) self.indent() self.simple_write("event", frame) self.outdent() self.outdent(level)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/Jinja2/py2/jinja2/compiler.py#L836-L872
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/lib/agw/flatmenu.py
python
FlatMenuItem.GetTextColour
(self)
return self._textColour
Returns this :class:`FlatMenuItem` foreground text colour.
Returns this :class:`FlatMenuItem` foreground text colour.
[ "Returns", "this", ":", "class", ":", "FlatMenuItem", "foreground", "text", "colour", "." ]
def GetTextColour(self): """ Returns this :class:`FlatMenuItem` foreground text colour. """ return self._textColour
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/flatmenu.py#L5271-L5274
seqan/seqan
f5f658343c366c9c3d44ba358ffc9317e78a09ed
util/py_lib/clang/cindex.py
python
Cursor.get_definition
(self)
return Cursor_def(self)
If the cursor is a reference to a declaration or a declaration of some entity, return a cursor that points to the definition of that entity.
If the cursor is a reference to a declaration or a declaration of some entity, return a cursor that points to the definition of that entity.
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def get_definition(self): """ If the cursor is a reference to a declaration or a declaration of some entity, return a cursor that points to the definition of that entity. """ # TODO: Should probably check that this is either a reference or # declaration prior to issuing the lookup. return Cursor_def(self)
[ "def", "get_definition", "(", "self", ")", ":", "# TODO: Should probably check that this is either a reference or", "# declaration prior to issuing the lookup.", "return", "Cursor_def", "(", "self", ")" ]
https://github.com/seqan/seqan/blob/f5f658343c366c9c3d44ba358ffc9317e78a09ed/util/py_lib/clang/cindex.py#L833-L841
deepmodeling/deepmd-kit
159e45d248b0429844fb6a8cb3b3a201987c8d79
deepmd/env.py
python
get_tf_session_config
()
return config
Configure tensorflow session. Returns ------- Any session configure object
Configure tensorflow session.
[ "Configure", "tensorflow", "session", "." ]
def get_tf_session_config() -> Any: """Configure tensorflow session. Returns ------- Any session configure object """ set_tf_default_nthreads() intra, inter = get_tf_default_nthreads() config = tf.ConfigProto( gpu_options=tf.GPUOptions(allow_growth=True), intra_op_parallelism_threads=intra, inter_op_parallelism_threads=inter ) return config
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https://github.com/deepmodeling/deepmd-kit/blob/159e45d248b0429844fb6a8cb3b3a201987c8d79/deepmd/env.py#L111-L125
facebook/openr
ed38bdfd6bf290084bfab4821b59f83e7b59315d
build/fbcode_builder/getdeps/copytree.py
python
find_eden_root
(dirpath)
If the specified directory is inside an EdenFS checkout, returns the canonical absolute path to the root of that checkout. Returns None if the specified directory is not in an EdenFS checkout.
If the specified directory is inside an EdenFS checkout, returns the canonical absolute path to the root of that checkout.
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def find_eden_root(dirpath): """If the specified directory is inside an EdenFS checkout, returns the canonical absolute path to the root of that checkout. Returns None if the specified directory is not in an EdenFS checkout. """ if is_windows(): repo_type, repo_root = containing_repo_type(dirpath) if repo_root is not None: if os.path.exists(os.path.join(repo_root, ".eden", "config")): return os.path.realpath(repo_root) return None try: return os.readlink(os.path.join(dirpath, ".eden", "root")) except OSError: return None
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https://github.com/facebook/openr/blob/ed38bdfd6bf290084bfab4821b59f83e7b59315d/build/fbcode_builder/getdeps/copytree.py#L29-L45
tensorflow/tensorflow
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
tensorflow/python/tpu/session_support.py
python
WorkerHeartbeatManager.ping
(self, request=None, timeout_in_ms=60000)
return parsed_results
Ping all workers, returning the parsed status results.
Ping all workers, returning the parsed status results.
[ "Ping", "all", "workers", "returning", "the", "parsed", "status", "results", "." ]
def ping(self, request=None, timeout_in_ms=60000): """Ping all workers, returning the parsed status results.""" if request is None: request = event_pb2.WorkerHeartbeatRequest() options = config_pb2.RunOptions(timeout_in_ms=timeout_in_ms) results = self._session.run( self._ops, feed_dict={self._request_placeholder: request.SerializeToString()}, options=options) parsed_results = [ event_pb2.WorkerHeartbeatResponse.FromString(res_pb) for res_pb in results ] logging.debug('Ping results: %s', parsed_results) return parsed_results
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https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/tpu/session_support.py#L105-L120
soui3/soui
c588024b2f4f6d3fadb53c1bfed5ccf00d0b7046
third-part/jsoncpp/doxybuild.py
python
cd
(newdir)
http://stackoverflow.com/questions/431684/how-do-i-cd-in-python
http://stackoverflow.com/questions/431684/how-do-i-cd-in-python
[ "http", ":", "//", "stackoverflow", ".", "com", "/", "questions", "/", "431684", "/", "how", "-", "do", "-", "i", "-", "cd", "-", "in", "-", "python" ]
def cd(newdir): """ http://stackoverflow.com/questions/431684/how-do-i-cd-in-python """ prevdir = os.getcwd() os.chdir(newdir) try: yield finally: os.chdir(prevdir)
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https://github.com/soui3/soui/blob/c588024b2f4f6d3fadb53c1bfed5ccf00d0b7046/third-part/jsoncpp/doxybuild.py#L15-L24
benoitsteiner/tensorflow-opencl
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
tensorflow/python/training/coordinator.py
python
Coordinator.__init__
(self, clean_stop_exception_types=None)
Create a new Coordinator. Args: clean_stop_exception_types: Optional tuple of Exception types that should cause a clean stop of the coordinator. If an exception of one of these types is reported to `request_stop(ex)` the coordinator will behave as if `request_stop(None)` was called. Defaults to `(tf.errors.OutOfRangeError,)` which is used by input queues to signal the end of input. When feeding training data from a Python iterator it is common to add `StopIteration` to this list.
Create a new Coordinator.
[ "Create", "a", "new", "Coordinator", "." ]
def __init__(self, clean_stop_exception_types=None): """Create a new Coordinator. Args: clean_stop_exception_types: Optional tuple of Exception types that should cause a clean stop of the coordinator. If an exception of one of these types is reported to `request_stop(ex)` the coordinator will behave as if `request_stop(None)` was called. Defaults to `(tf.errors.OutOfRangeError,)` which is used by input queues to signal the end of input. When feeding training data from a Python iterator it is common to add `StopIteration` to this list. """ if clean_stop_exception_types is None: clean_stop_exception_types = (errors.OutOfRangeError,) self._clean_stop_exception_types = tuple(clean_stop_exception_types) # Protects all attributes. self._lock = threading.Lock() # Event set when threads must stop. self._stop_event = threading.Event() # Python exc_info to report. # If not None, it should hold the returned value of sys.exc_info(), which is # a tuple containing exception (type, value, traceback). self._exc_info_to_raise = None # True if we have called join() already. self._joined = False # Set of threads registered for joining when join() is called. These # threads will be joined in addition to the threads passed to the join() # call. It's ok if threads are both registered and passed to the join() # call. self._registered_threads = set()
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https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/training/coordinator.py#L128-L157
stan-dev/math
5fd79f89933269a4ca4d8dd1fde2a36d53d4768c
lib/boost_1.75.0/tools/build/src/build/type.py
python
base
(type)
return __types[type]['base']
Returns a base type for the given type or nothing in case the given type is not derived.
Returns a base type for the given type or nothing in case the given type is not derived.
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def base(type): """Returns a base type for the given type or nothing in case the given type is not derived.""" assert isinstance(type, basestring) return __types[type]['base']
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https://github.com/stan-dev/math/blob/5fd79f89933269a4ca4d8dd1fde2a36d53d4768c/lib/boost_1.75.0/tools/build/src/build/type.py#L175-L179
llvm/llvm-project
ffa6262cb4e2a335d26416fad39a581b4f98c5f4
llvm/bindings/python/llvm/object.py
python
Symbol.cache
(self)
Cache all cacheable properties.
Cache all cacheable properties.
[ "Cache", "all", "cacheable", "properties", "." ]
def cache(self): """Cache all cacheable properties.""" getattr(self, 'name') getattr(self, 'address') getattr(self, 'size')
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https://github.com/llvm/llvm-project/blob/ffa6262cb4e2a335d26416fad39a581b4f98c5f4/llvm/bindings/python/llvm/object.py#L343-L347
hanpfei/chromium-net
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
build/android/pylib/valgrind_tools.py
python
AddressSanitizerTool.CopyFiles
(cls, device)
Copies ASan tools to the device.
Copies ASan tools to the device.
[ "Copies", "ASan", "tools", "to", "the", "device", "." ]
def CopyFiles(cls, device): """Copies ASan tools to the device.""" libs = glob.glob(os.path.join(DIR_SOURCE_ROOT, 'third_party/llvm-build/Release+Asserts/', 'lib/clang/*/lib/linux/', 'libclang_rt.asan-arm-android.so')) assert len(libs) == 1 subprocess.call( [os.path.join( DIR_SOURCE_ROOT, 'tools/android/asan/third_party/asan_device_setup.sh'), '--device', str(device), '--lib', libs[0], '--extra-options', AddressSanitizerTool.EXTRA_OPTIONS]) device.WaitUntilFullyBooted()
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/build/android/pylib/valgrind_tools.py#L43-L57
apache/incubator-weex
5c25f0b59f7ac90703c363e7261f60bd06356dbe
weex_core/tools/cpplint.py
python
ExpectingFunctionArgs
(clean_lines, linenum)
return (Match(r'^\s*MOCK_(CONST_)?METHOD\d+(_T)?\(', line) or (linenum >= 2 and (Match(r'^\s*MOCK_(?:CONST_)?METHOD\d+(?:_T)?\((?:\S+,)?\s*$', clean_lines.elided[linenum - 1]) or Match(r'^\s*MOCK_(?:CONST_)?METHOD\d+(?:_T)?\(\s*$', clean_lines.elided[linenum - 2]) or Search(r'\bstd::m?function\s*\<\s*$', clean_lines.elided[linenum - 1]))))
Checks whether where function type arguments are expected. Args: clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. Returns: True if the line at 'linenum' is inside something that expects arguments of function types.
Checks whether where function type arguments are expected.
[ "Checks", "whether", "where", "function", "type", "arguments", "are", "expected", "." ]
def ExpectingFunctionArgs(clean_lines, linenum): """Checks whether where function type arguments are expected. Args: clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. Returns: True if the line at 'linenum' is inside something that expects arguments of function types. """ line = clean_lines.elided[linenum] return (Match(r'^\s*MOCK_(CONST_)?METHOD\d+(_T)?\(', line) or (linenum >= 2 and (Match(r'^\s*MOCK_(?:CONST_)?METHOD\d+(?:_T)?\((?:\S+,)?\s*$', clean_lines.elided[linenum - 1]) or Match(r'^\s*MOCK_(?:CONST_)?METHOD\d+(?:_T)?\(\s*$', clean_lines.elided[linenum - 2]) or Search(r'\bstd::m?function\s*\<\s*$', clean_lines.elided[linenum - 1]))))
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https://github.com/apache/incubator-weex/blob/5c25f0b59f7ac90703c363e7261f60bd06356dbe/weex_core/tools/cpplint.py#L5324-L5343
shedskin/shedskin
ae88dbca7b1d9671cd8be448cb0b497122758936
examples/c64/cpu.py
python
CPU.EOR
(self, opcode)
exclusive OR
exclusive OR
[ "exclusive", "OR" ]
def EOR(self, opcode): """ exclusive OR """ reference_value = self.read_register(S_A) addressing_mode = CPU.EOR_addressing_modes[opcode] value = self.load_value_advancing(addressing_mode) result = value ^ reference_value self.write_register(S_A, result) self.update_flags_by_number(result)
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https://github.com/shedskin/shedskin/blob/ae88dbca7b1d9671cd8be448cb0b497122758936/examples/c64/cpu.py#L1335-L1342
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/jira/client.py
python
JIRA.delete_board
(self, id)
Delete an agile board.
Delete an agile board.
[ "Delete", "an", "agile", "board", "." ]
def delete_board(self, id): """Delete an agile board.""" board = Board(self._options, self._session, raw={'id': id}) board.delete()
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/jira/client.py#L3229-L3232
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/numpy/py3/numpy/lib/_datasource.py
python
Repository.open
(self, path, mode='r', encoding=None, newline=None)
return DataSource.open(self, self._fullpath(path), mode, encoding=encoding, newline=newline)
Open and return file-like object prepending Repository base URL. If `path` is an URL, it will be downloaded, stored in the DataSource directory and opened from there. Parameters ---------- path : str Local file path or URL to open. This may, but does not have to, include the `baseurl` with which the `Repository` was initialized. mode : {'r', 'w', 'a'}, optional Mode to open `path`. Mode 'r' for reading, 'w' for writing, 'a' to append. Available modes depend on the type of object specified by `path`. Default is 'r'. encoding : {None, str}, optional Open text file with given encoding. The default encoding will be what `io.open` uses. newline : {None, str}, optional Newline to use when reading text file. Returns ------- out : file object File object.
Open and return file-like object prepending Repository base URL.
[ "Open", "and", "return", "file", "-", "like", "object", "prepending", "Repository", "base", "URL", "." ]
def open(self, path, mode='r', encoding=None, newline=None): """ Open and return file-like object prepending Repository base URL. If `path` is an URL, it will be downloaded, stored in the DataSource directory and opened from there. Parameters ---------- path : str Local file path or URL to open. This may, but does not have to, include the `baseurl` with which the `Repository` was initialized. mode : {'r', 'w', 'a'}, optional Mode to open `path`. Mode 'r' for reading, 'w' for writing, 'a' to append. Available modes depend on the type of object specified by `path`. Default is 'r'. encoding : {None, str}, optional Open text file with given encoding. The default encoding will be what `io.open` uses. newline : {None, str}, optional Newline to use when reading text file. Returns ------- out : file object File object. """ return DataSource.open(self, self._fullpath(path), mode, encoding=encoding, newline=newline)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/numpy/py3/numpy/lib/_datasource.py#L654-L684
LiquidPlayer/LiquidCore
9405979363f2353ac9a71ad8ab59685dd7f919c9
deps/node-10.15.3/tools/jinja2/environment.py
python
Environment.get_or_select_template
(self, template_name_or_list, parent=None, globals=None)
return self.select_template(template_name_or_list, parent, globals)
Does a typecheck and dispatches to :meth:`select_template` if an iterable of template names is given, otherwise to :meth:`get_template`. .. versionadded:: 2.3
Does a typecheck and dispatches to :meth:`select_template` if an iterable of template names is given, otherwise to :meth:`get_template`.
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def get_or_select_template(self, template_name_or_list, parent=None, globals=None): """Does a typecheck and dispatches to :meth:`select_template` if an iterable of template names is given, otherwise to :meth:`get_template`. .. versionadded:: 2.3 """ if isinstance(template_name_or_list, string_types): return self.get_template(template_name_or_list, parent, globals) elif isinstance(template_name_or_list, Template): return template_name_or_list return self.select_template(template_name_or_list, parent, globals)
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https://github.com/LiquidPlayer/LiquidCore/blob/9405979363f2353ac9a71ad8ab59685dd7f919c9/deps/node-10.15.3/tools/jinja2/environment.py#L860-L872
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/configparser/backports/configparser/__init__.py
python
RawConfigParser.get
(self, section, option, **kwargs)
Get an option value for a given section. If `vars' is provided, it must be a dictionary. The option is looked up in `vars' (if provided), `section', and in `DEFAULTSECT' in that order. If the key is not found and `fallback' is provided, it is used as a fallback value. `None' can be provided as a `fallback' value. If interpolation is enabled and the optional argument `raw' is False, all interpolations are expanded in the return values. Arguments `raw', `vars', and `fallback' are keyword only. The section DEFAULT is special.
Get an option value for a given section.
[ "Get", "an", "option", "value", "for", "a", "given", "section", "." ]
def get(self, section, option, **kwargs): """Get an option value for a given section. If `vars' is provided, it must be a dictionary. The option is looked up in `vars' (if provided), `section', and in `DEFAULTSECT' in that order. If the key is not found and `fallback' is provided, it is used as a fallback value. `None' can be provided as a `fallback' value. If interpolation is enabled and the optional argument `raw' is False, all interpolations are expanded in the return values. Arguments `raw', `vars', and `fallback' are keyword only. The section DEFAULT is special. """ # keyword-only arguments raw = kwargs.get('raw', False) vars = kwargs.get('vars', None) fallback = kwargs.get('fallback', _UNSET) try: d = self._unify_values(section, vars) except NoSectionError: if fallback is _UNSET: raise else: return fallback option = self.optionxform(option) try: value = d[option] except KeyError: if fallback is _UNSET: raise NoOptionError(option, section) else: return fallback if raw or value is None: return value else: return self._interpolation.before_get(self, section, option, value, d)
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/configparser/backports/configparser/__init__.py#L837-L876
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_cocoa/stc.py
python
StyledTextCtrl.DelLineRight
(*args, **kwargs)
return _stc.StyledTextCtrl_DelLineRight(*args, **kwargs)
DelLineRight(self) Delete forwards from the current position to the end of the line.
DelLineRight(self)
[ "DelLineRight", "(", "self", ")" ]
def DelLineRight(*args, **kwargs): """ DelLineRight(self) Delete forwards from the current position to the end of the line. """ return _stc.StyledTextCtrl_DelLineRight(*args, **kwargs)
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/stc.py#L5154-L5160
natanielruiz/android-yolo
1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f
jni-build/jni/include/tensorflow/contrib/quantization/tools/quantize_graph.py
python
unique_node_name_from_input
(node_name)
return node_name.replace(":", "__port__").replace("^", "__hat__")
Replaces invalid characters in input names to get a unique node name.
Replaces invalid characters in input names to get a unique node name.
[ "Replaces", "invalid", "characters", "in", "input", "names", "to", "get", "a", "unique", "node", "name", "." ]
def unique_node_name_from_input(node_name): """Replaces invalid characters in input names to get a unique node name.""" return node_name.replace(":", "__port__").replace("^", "__hat__")
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https://github.com/natanielruiz/android-yolo/blob/1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f/jni-build/jni/include/tensorflow/contrib/quantization/tools/quantize_graph.py#L173-L175
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/windows/Lib/logging/__init__.py
python
LoggerAdapter.isEnabledFor
(self, level)
return self.logger.isEnabledFor(level)
Is this logger enabled for level 'level'?
Is this logger enabled for level 'level'?
[ "Is", "this", "logger", "enabled", "for", "level", "level", "?" ]
def isEnabledFor(self, level): """ Is this logger enabled for level 'level'? """ return self.logger.isEnabledFor(level)
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/logging/__init__.py#L1768-L1772
CRYTEK/CRYENGINE
232227c59a220cbbd311576f0fbeba7bb53b2a8c
Code/Tools/waf-1.7.13/waflib/Tools/python.py
python
check_python_version
(conf, minver=None)
Check if the python interpreter is found matching a given minimum version. minver should be a tuple, eg. to check for python >= 2.4.2 pass (2,4,2) as minver. If successful, PYTHON_VERSION is defined as 'MAJOR.MINOR' (eg. '2.4') of the actual python version found, and PYTHONDIR is defined, pointing to the site-packages directory appropriate for this python version, where modules/packages/extensions should be installed. :param minver: minimum version :type minver: tuple of int
Check if the python interpreter is found matching a given minimum version. minver should be a tuple, eg. to check for python >= 2.4.2 pass (2,4,2) as minver.
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def check_python_version(conf, minver=None): """ Check if the python interpreter is found matching a given minimum version. minver should be a tuple, eg. to check for python >= 2.4.2 pass (2,4,2) as minver. If successful, PYTHON_VERSION is defined as 'MAJOR.MINOR' (eg. '2.4') of the actual python version found, and PYTHONDIR is defined, pointing to the site-packages directory appropriate for this python version, where modules/packages/extensions should be installed. :param minver: minimum version :type minver: tuple of int """ assert minver is None or isinstance(minver, tuple) pybin = conf.env['PYTHON'] if not pybin: conf.fatal('could not find the python executable') # Get python version string cmd = pybin + ['-c', 'import sys\nfor x in sys.version_info: print(str(x))'] Logs.debug('python: Running python command %r' % cmd) lines = conf.cmd_and_log(cmd).split() assert len(lines) == 5, "found %i lines, expected 5: %r" % (len(lines), lines) pyver_tuple = (int(lines[0]), int(lines[1]), int(lines[2]), lines[3], int(lines[4])) # compare python version with the minimum required result = (minver is None) or (pyver_tuple >= minver) if result: # define useful environment variables pyver = '.'.join([str(x) for x in pyver_tuple[:2]]) conf.env['PYTHON_VERSION'] = pyver if 'PYTHONDIR' in conf.environ: pydir = conf.environ['PYTHONDIR'] else: if Utils.is_win32: (python_LIBDEST, pydir) = conf.get_python_variables( ["get_config_var('LIBDEST') or ''", "get_python_lib(standard_lib=0, prefix=%r) or ''" % conf.env['PREFIX']]) else: python_LIBDEST = None (pydir,) = conf.get_python_variables( ["get_python_lib(standard_lib=0, prefix=%r) or ''" % conf.env['PREFIX']]) if python_LIBDEST is None: if conf.env['LIBDIR']: python_LIBDEST = os.path.join(conf.env['LIBDIR'], "python" + pyver) else: python_LIBDEST = os.path.join(conf.env['PREFIX'], "lib", "python" + pyver) if 'PYTHONARCHDIR' in conf.environ: pyarchdir = conf.environ['PYTHONARCHDIR'] else: (pyarchdir, ) = conf.get_python_variables( ["get_python_lib(plat_specific=1, standard_lib=0, prefix=%r) or ''" % conf.env['PREFIX']]) if not pyarchdir: pyarchdir = pydir if hasattr(conf, 'define'): # conf.define is added by the C tool, so may not exist conf.define('PYTHONDIR', pydir) conf.define('PYTHONARCHDIR', pyarchdir) conf.env['PYTHONDIR'] = pydir conf.env['PYTHONARCHDIR'] = pyarchdir # Feedback pyver_full = '.'.join(map(str, pyver_tuple[:3])) if minver is None: conf.msg('Checking for python version', pyver_full) else: minver_str = '.'.join(map(str, minver)) conf.msg('Checking for python version', pyver_tuple, ">= %s" % (minver_str,) and 'GREEN' or 'YELLOW') if not result: conf.fatal('The python version is too old, expecting %r' % (minver,))
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https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Code/Tools/waf-1.7.13/waflib/Tools/python.py#L375-L449
abseil/abseil-cpp
73316fc3c565e5998983b0fb502d938ccddcded2
absl/abseil.podspec.gen.py
python
write_podspec_map
(f, cur_map, depth)
Writes podspec from rule map recursively.
Writes podspec from rule map recursively.
[ "Writes", "podspec", "from", "rule", "map", "recursively", "." ]
def write_podspec_map(f, cur_map, depth): """Writes podspec from rule map recursively.""" for key, value in sorted(cur_map.items()): indent = " " * (depth + 1) f.write("{indent}{var0}.subspec '{key}' do |{var1}|\n".format( indent=indent, key=key, var0=get_spec_var(depth), var1=get_spec_var(depth + 1))) if isinstance(value, dict): write_podspec_map(f, value, depth + 1) else: write_podspec_rule(f, value, depth + 1) f.write("{indent}end\n".format(indent=indent))
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https://github.com/abseil/abseil-cpp/blob/73316fc3c565e5998983b0fb502d938ccddcded2/absl/abseil.podspec.gen.py#L158-L171
rdkit/rdkit
ede860ae316d12d8568daf5ee800921c3389c84e
rdkit/utils/chemdraw.py
python
CloseChemDrawDoc
()
force chemdraw to save the active document NOTE: the extension of the filename will determine the format used to save the file.
force chemdraw to save the active document
[ "force", "chemdraw", "to", "save", "the", "active", "document" ]
def CloseChemDrawDoc(): """force chemdraw to save the active document NOTE: the extension of the filename will determine the format used to save the file. """ d = cdApp.ActiveDocument d.Close()
[ "def", "CloseChemDrawDoc", "(", ")", ":", "d", "=", "cdApp", ".", "ActiveDocument", "d", ".", "Close", "(", ")" ]
https://github.com/rdkit/rdkit/blob/ede860ae316d12d8568daf5ee800921c3389c84e/rdkit/utils/chemdraw.py#L209-L216
SequoiaDB/SequoiaDB
2894ed7e5bd6fe57330afc900cf76d0ff0df9f64
tools/server/php_linux/libxml2/lib/python2.4/site-packages/libxml2.py
python
isBaseChar
(ch)
return ret
This function is DEPRECATED. Use xmlIsBaseChar_ch or xmlIsBaseCharQ instead
This function is DEPRECATED. Use xmlIsBaseChar_ch or xmlIsBaseCharQ instead
[ "This", "function", "is", "DEPRECATED", ".", "Use", "xmlIsBaseChar_ch", "or", "xmlIsBaseCharQ", "instead" ]
def isBaseChar(ch): """This function is DEPRECATED. Use xmlIsBaseChar_ch or xmlIsBaseCharQ instead """ ret = libxml2mod.xmlIsBaseChar(ch) return ret
[ "def", "isBaseChar", "(", "ch", ")", ":", "ret", "=", "libxml2mod", ".", "xmlIsBaseChar", "(", "ch", ")", "return", "ret" ]
https://github.com/SequoiaDB/SequoiaDB/blob/2894ed7e5bd6fe57330afc900cf76d0ff0df9f64/tools/server/php_linux/libxml2/lib/python2.4/site-packages/libxml2.py#L971-L975
microsoft/ivy
9f3c7ecc0b2383129fdd0953e10890d98d09a82d
ivy/ivy_parser.py
python
p_schdecl_fresh_relation_rel
(p)
schdecl : FRESH RELATION rels
schdecl : FRESH RELATION rels
[ "schdecl", ":", "FRESH", "RELATION", "rels" ]
def p_schdecl_fresh_relation_rel(p): 'schdecl : FRESH RELATION rels' p[0] = [FreshConstantDecl(x.args[0]) if isinstance(x,ConstantDecl) else x for x in p[3]]
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https://github.com/microsoft/ivy/blob/9f3c7ecc0b2383129fdd0953e10890d98d09a82d/ivy/ivy_parser.py#L551-L553
apple/turicreate
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
deps/src/libxml2-2.9.1/python/libxml2class.py
python
xmlDtd.dtdElementDesc
(self, name)
return __tmp
Search the DTD for the description of this element
Search the DTD for the description of this element
[ "Search", "the", "DTD", "for", "the", "description", "of", "this", "element" ]
def dtdElementDesc(self, name): """Search the DTD for the description of this element """ ret = libxml2mod.xmlGetDtdElementDesc(self._o, name) if ret is None:raise treeError('xmlGetDtdElementDesc() failed') __tmp = xmlElement(_obj=ret) return __tmp
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https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/deps/src/libxml2-2.9.1/python/libxml2class.py#L4965-L4970