nwo
stringlengths
5
86
sha
stringlengths
40
40
path
stringlengths
4
189
language
stringclasses
1 value
identifier
stringlengths
1
94
parameters
stringlengths
2
4.03k
argument_list
stringclasses
1 value
return_statement
stringlengths
0
11.5k
docstring
stringlengths
1
33.2k
docstring_summary
stringlengths
0
5.15k
docstring_tokens
sequence
function
stringlengths
34
151k
function_tokens
sequence
url
stringlengths
90
278
baidu/AnyQ
d94d450d2aaa5f7ed73424b10aa4539835b97527
tools/common/utils.py
python
import_class
(module_path, module_name, class_name)
return getattr(module, class_name)
Load class dynamically Args: module_path: The current path of the module module_name: The module name class_name: The name of class in the import module Return: Return the attribute value of the class object
Load class dynamically Args: module_path: The current path of the module module_name: The module name class_name: The name of class in the import module Return: Return the attribute value of the class object
[ "Load", "class", "dynamically", "Args", ":", "module_path", ":", "The", "current", "path", "of", "the", "module", "module_name", ":", "The", "module", "name", "class_name", ":", "The", "name", "of", "class", "in", "the", "import", "module", "Return", ":", "Return", "the", "attribute", "value", "of", "the", "class", "object" ]
def import_class(module_path, module_name, class_name): """ Load class dynamically Args: module_path: The current path of the module module_name: The module name class_name: The name of class in the import module Return: Return the attribute value of the class object """ if module_path: sys.path.append(module_path) module = __import__(module_name) return getattr(module, class_name)
[ "def", "import_class", "(", "module_path", ",", "module_name", ",", "class_name", ")", ":", "if", "module_path", ":", "sys", ".", "path", ".", "append", "(", "module_path", ")", "module", "=", "__import__", "(", "module_name", ")", "return", "getattr", "(", "module", ",", "class_name", ")" ]
https://github.com/baidu/AnyQ/blob/d94d450d2aaa5f7ed73424b10aa4539835b97527/tools/common/utils.py#L142-L155
apple/turicreate
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
src/external/coremltools_wrap/coremltools/coremltools/converters/mil/backend/nn/passes/mlmodel_passes.py
python
transform_conv_crop
(spec)
Transforms Conv -> Crop -> BN (if present) -> Activation (if present) into Conv -> BN (if present) -> Activation (if present) -> Crop This transformation will allow Conv -> BN -> Activation fusion by changing the position of the crop layer, which does not affect the computation
Transforms Conv -> Crop -> BN (if present) -> Activation (if present) into Conv -> BN (if present) -> Activation (if present) -> Crop This transformation will allow Conv -> BN -> Activation fusion by changing the position of the crop layer, which does not affect the computation
[ "Transforms", "Conv", "-", ">", "Crop", "-", ">", "BN", "(", "if", "present", ")", "-", ">", "Activation", "(", "if", "present", ")", "into", "Conv", "-", ">", "BN", "(", "if", "present", ")", "-", ">", "Activation", "(", "if", "present", ")", "-", ">", "Crop", "This", "transformation", "will", "allow", "Conv", "-", ">", "BN", "-", ">", "Activation", "fusion", "by", "changing", "the", "position", "of", "the", "crop", "layer", "which", "does", "not", "affect", "the", "computation" ]
def transform_conv_crop(spec): """ Transforms Conv -> Crop -> BN (if present) -> Activation (if present) into Conv -> BN (if present) -> Activation (if present) -> Crop This transformation will allow Conv -> BN -> Activation fusion by changing the position of the crop layer, which does not affect the computation """ # Collect metadata out_degree = _get_blob_out_degree(spec) network_output_names = _get_network_output(spec) nn_spec = _get_nn_spec(spec) nn_layers = nn_spec.layers for i in range(0, len(nn_layers) - 2): # If Convolution output is being using as a network output or more than one layers # that's acceptable if not _is_layer(nn_layers[i], "convolution"): continue # Output of Crop layer must not be network output or used by more than one layer if not ( _is_layer(nn_layers[i + 1], "crop") and _get_input(nn_layers[i + 1]) not in network_output_names and out_degree[_get_output(nn_layers[i + 1])] == 1 ): continue layer_to_shuffle_with = -1 # Output of Batchnorm layer must not be network output or used by more than one layer if ( _is_layer(nn_layers[i + 2], "batchnorm") and out_degree[_get_output(nn_layers[i + 2])] == 1 ): layer_to_shuffle_with = i + 2 # Output of Activation layer must not be network output or used by more than one layer if ( i + 3 < len(nn_layers) and _is_layer(nn_layers[i + 3], "activation") and out_degree[_get_output(nn_layers[i + 3])] == 1 ): layer_to_shuffle_with = i + 3 if layer_to_shuffle_with == -1: continue # restructure crop layer # Conv ---> Crop ---> BN ---> Activation ---> Layer1 # In following three steps # 1. Conv --------------> BN ---> Activation ---> Layer1 # \ / # ---> Crop -- nn_layers[i].output[0] = nn_layers[i + 1].output[0] # 2. Conv ---> BN ---> Activation ---> Layer1 # \ / # -----------------Crop ---- nn_layers[i + 1].output[0] = nn_layers[layer_to_shuffle_with].output[0] # 3. Conv ---> BN ---> Activation ---> Crop ---> Layer1 nn_layers[layer_to_shuffle_with].output[0] = nn_layers[i + 1].input[0] # Add Crop layer at new position and remove from current position crop_layer = nn_layers[i + 1] nn_layers.remove(crop_layer) nn_layers.insert(layer_to_shuffle_with, crop_layer)
[ "def", "transform_conv_crop", "(", "spec", ")", ":", "# Collect metadata", "out_degree", "=", "_get_blob_out_degree", "(", "spec", ")", "network_output_names", "=", "_get_network_output", "(", "spec", ")", "nn_spec", "=", "_get_nn_spec", "(", "spec", ")", "nn_layers", "=", "nn_spec", ".", "layers", "for", "i", "in", "range", "(", "0", ",", "len", "(", "nn_layers", ")", "-", "2", ")", ":", "# If Convolution output is being using as a network output or more than one layers", "# that's acceptable", "if", "not", "_is_layer", "(", "nn_layers", "[", "i", "]", ",", "\"convolution\"", ")", ":", "continue", "# Output of Crop layer must not be network output or used by more than one layer", "if", "not", "(", "_is_layer", "(", "nn_layers", "[", "i", "+", "1", "]", ",", "\"crop\"", ")", "and", "_get_input", "(", "nn_layers", "[", "i", "+", "1", "]", ")", "not", "in", "network_output_names", "and", "out_degree", "[", "_get_output", "(", "nn_layers", "[", "i", "+", "1", "]", ")", "]", "==", "1", ")", ":", "continue", "layer_to_shuffle_with", "=", "-", "1", "# Output of Batchnorm layer must not be network output or used by more than one layer", "if", "(", "_is_layer", "(", "nn_layers", "[", "i", "+", "2", "]", ",", "\"batchnorm\"", ")", "and", "out_degree", "[", "_get_output", "(", "nn_layers", "[", "i", "+", "2", "]", ")", "]", "==", "1", ")", ":", "layer_to_shuffle_with", "=", "i", "+", "2", "# Output of Activation layer must not be network output or used by more than one layer", "if", "(", "i", "+", "3", "<", "len", "(", "nn_layers", ")", "and", "_is_layer", "(", "nn_layers", "[", "i", "+", "3", "]", ",", "\"activation\"", ")", "and", "out_degree", "[", "_get_output", "(", "nn_layers", "[", "i", "+", "3", "]", ")", "]", "==", "1", ")", ":", "layer_to_shuffle_with", "=", "i", "+", "3", "if", "layer_to_shuffle_with", "==", "-", "1", ":", "continue", "# restructure crop layer", "# Conv ---> Crop ---> BN ---> Activation ---> Layer1", "# In following three steps", "# 1. Conv --------------> BN ---> Activation ---> Layer1", "# \\ /", "# ---> Crop --", "nn_layers", "[", "i", "]", ".", "output", "[", "0", "]", "=", "nn_layers", "[", "i", "+", "1", "]", ".", "output", "[", "0", "]", "# 2. Conv ---> BN ---> Activation ---> Layer1", "# \\ /", "# -----------------Crop ----", "nn_layers", "[", "i", "+", "1", "]", ".", "output", "[", "0", "]", "=", "nn_layers", "[", "layer_to_shuffle_with", "]", ".", "output", "[", "0", "]", "# 3. Conv ---> BN ---> Activation ---> Crop ---> Layer1", "nn_layers", "[", "layer_to_shuffle_with", "]", ".", "output", "[", "0", "]", "=", "nn_layers", "[", "i", "+", "1", "]", ".", "input", "[", "0", "]", "# Add Crop layer at new position and remove from current position", "crop_layer", "=", "nn_layers", "[", "i", "+", "1", "]", "nn_layers", ".", "remove", "(", "crop_layer", ")", "nn_layers", ".", "insert", "(", "layer_to_shuffle_with", ",", "crop_layer", ")" ]
https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/src/external/coremltools_wrap/coremltools/coremltools/converters/mil/backend/nn/passes/mlmodel_passes.py#L105-L169
llvm/llvm-project
ffa6262cb4e2a335d26416fad39a581b4f98c5f4
clang/bindings/python/clang/cindex.py
python
Config.set_library_path
(path)
Set the path in which to search for libclang
Set the path in which to search for libclang
[ "Set", "the", "path", "in", "which", "to", "search", "for", "libclang" ]
def set_library_path(path): """Set the path in which to search for libclang""" if Config.loaded: raise Exception("library path must be set before before using " \ "any other functionalities in libclang.") Config.library_path = fspath(path)
[ "def", "set_library_path", "(", "path", ")", ":", "if", "Config", ".", "loaded", ":", "raise", "Exception", "(", "\"library path must be set before before using \"", "\"any other functionalities in libclang.\"", ")", "Config", ".", "library_path", "=", "fspath", "(", "path", ")" ]
https://github.com/llvm/llvm-project/blob/ffa6262cb4e2a335d26416fad39a581b4f98c5f4/clang/bindings/python/clang/cindex.py#L4105-L4111
LiquidPlayer/LiquidCore
9405979363f2353ac9a71ad8ab59685dd7f919c9
deps/node-10.15.3/tools/gyp/pylib/gyp/win_tool.py
python
WinTool.ExecManifestToRc
(self, arch, *args)
Creates a resource file pointing a SxS assembly manifest. |args| is tuple containing path to resource file, path to manifest file and resource name which can be "1" (for executables) or "2" (for DLLs).
Creates a resource file pointing a SxS assembly manifest. |args| is tuple containing path to resource file, path to manifest file and resource name which can be "1" (for executables) or "2" (for DLLs).
[ "Creates", "a", "resource", "file", "pointing", "a", "SxS", "assembly", "manifest", ".", "|args|", "is", "tuple", "containing", "path", "to", "resource", "file", "path", "to", "manifest", "file", "and", "resource", "name", "which", "can", "be", "1", "(", "for", "executables", ")", "or", "2", "(", "for", "DLLs", ")", "." ]
def ExecManifestToRc(self, arch, *args): """Creates a resource file pointing a SxS assembly manifest. |args| is tuple containing path to resource file, path to manifest file and resource name which can be "1" (for executables) or "2" (for DLLs).""" manifest_path, resource_path, resource_name = args with open(resource_path, 'wb') as output: output.write('#include <windows.h>\n%s RT_MANIFEST "%s"' % ( resource_name, os.path.abspath(manifest_path).replace('\\', '/')))
[ "def", "ExecManifestToRc", "(", "self", ",", "arch", ",", "*", "args", ")", ":", "manifest_path", ",", "resource_path", ",", "resource_name", "=", "args", "with", "open", "(", "resource_path", ",", "'wb'", ")", "as", "output", ":", "output", ".", "write", "(", "'#include <windows.h>\\n%s RT_MANIFEST \"%s\"'", "%", "(", "resource_name", ",", "os", ".", "path", ".", "abspath", "(", "manifest_path", ")", ".", "replace", "(", "'\\\\'", ",", "'/'", ")", ")", ")" ]
https://github.com/LiquidPlayer/LiquidCore/blob/9405979363f2353ac9a71ad8ab59685dd7f919c9/deps/node-10.15.3/tools/gyp/pylib/gyp/win_tool.py#L229-L237
trailofbits/llvm-sanitizer-tutorial
d29dfeec7f51fbf234fd0080f28f2b30cd0b6e99
llvm/tools/clang/bindings/python/clang/cindex.py
python
TranslationUnit.save
(self, filename)
Saves the TranslationUnit to a file. This is equivalent to passing -emit-ast to the clang frontend. The saved file can be loaded back into a TranslationUnit. Or, if it corresponds to a header, it can be used as a pre-compiled header file. If an error occurs while saving, a TranslationUnitSaveError is raised. If the error was TranslationUnitSaveError.ERROR_INVALID_TU, this means the constructed TranslationUnit was not valid at time of save. In this case, the reason(s) why should be available via TranslationUnit.diagnostics(). filename -- The path to save the translation unit to (str or PathLike).
Saves the TranslationUnit to a file.
[ "Saves", "the", "TranslationUnit", "to", "a", "file", "." ]
def save(self, filename): """Saves the TranslationUnit to a file. This is equivalent to passing -emit-ast to the clang frontend. The saved file can be loaded back into a TranslationUnit. Or, if it corresponds to a header, it can be used as a pre-compiled header file. If an error occurs while saving, a TranslationUnitSaveError is raised. If the error was TranslationUnitSaveError.ERROR_INVALID_TU, this means the constructed TranslationUnit was not valid at time of save. In this case, the reason(s) why should be available via TranslationUnit.diagnostics(). filename -- The path to save the translation unit to (str or PathLike). """ options = conf.lib.clang_defaultSaveOptions(self) result = int(conf.lib.clang_saveTranslationUnit(self, fspath(filename), options)) if result != 0: raise TranslationUnitSaveError(result, 'Error saving TranslationUnit.')
[ "def", "save", "(", "self", ",", "filename", ")", ":", "options", "=", "conf", ".", "lib", ".", "clang_defaultSaveOptions", "(", "self", ")", "result", "=", "int", "(", "conf", ".", "lib", ".", "clang_saveTranslationUnit", "(", "self", ",", "fspath", "(", "filename", ")", ",", "options", ")", ")", "if", "result", "!=", "0", ":", "raise", "TranslationUnitSaveError", "(", "result", ",", "'Error saving TranslationUnit.'", ")" ]
https://github.com/trailofbits/llvm-sanitizer-tutorial/blob/d29dfeec7f51fbf234fd0080f28f2b30cd0b6e99/llvm/tools/clang/bindings/python/clang/cindex.py#L3011-L3031
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/python/setuptools/py2/setuptools/monkey.py
python
get_unpatched_class
(cls)
return base
Protect against re-patching the distutils if reloaded Also ensures that no other distutils extension monkeypatched the distutils first.
Protect against re-patching the distutils if reloaded
[ "Protect", "against", "re", "-", "patching", "the", "distutils", "if", "reloaded" ]
def get_unpatched_class(cls): """Protect against re-patching the distutils if reloaded Also ensures that no other distutils extension monkeypatched the distutils first. """ external_bases = ( cls for cls in _get_mro(cls) if not cls.__module__.startswith('setuptools') ) base = next(external_bases) if not base.__module__.startswith('distutils'): msg = "distutils has already been patched by %r" % cls raise AssertionError(msg) return base
[ "def", "get_unpatched_class", "(", "cls", ")", ":", "external_bases", "=", "(", "cls", "for", "cls", "in", "_get_mro", "(", "cls", ")", "if", "not", "cls", ".", "__module__", ".", "startswith", "(", "'setuptools'", ")", ")", "base", "=", "next", "(", "external_bases", ")", "if", "not", "base", ".", "__module__", ".", "startswith", "(", "'distutils'", ")", ":", "msg", "=", "\"distutils has already been patched by %r\"", "%", "cls", "raise", "AssertionError", "(", "msg", ")", "return", "base" ]
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/setuptools/py2/setuptools/monkey.py#L47-L62
snap-stanford/snap-python
d53c51b0a26aa7e3e7400b014cdf728948fde80a
setup/snap.py
python
TChA.SaveTxt
(self, *args)
return _snap.TChA_SaveTxt(self, *args)
SaveTxt(TChA self, PSOut const & SOut) Parameters: SOut: PSOut const &
SaveTxt(TChA self, PSOut const & SOut)
[ "SaveTxt", "(", "TChA", "self", "PSOut", "const", "&", "SOut", ")" ]
def SaveTxt(self, *args): """ SaveTxt(TChA self, PSOut const & SOut) Parameters: SOut: PSOut const & """ return _snap.TChA_SaveTxt(self, *args)
[ "def", "SaveTxt", "(", "self", ",", "*", "args", ")", ":", "return", "_snap", ".", "TChA_SaveTxt", "(", "self", ",", "*", "args", ")" ]
https://github.com/snap-stanford/snap-python/blob/d53c51b0a26aa7e3e7400b014cdf728948fde80a/setup/snap.py#L9072-L9080
gnuradio/gnuradio
09c3c4fa4bfb1a02caac74cb5334dfe065391e3b
grc/core/FlowGraph.py
python
FlowGraph.export_data
(self)
return data
Export this flow graph to nested data. Export all block and connection data. Returns: a nested data odict
Export this flow graph to nested data. Export all block and connection data.
[ "Export", "this", "flow", "graph", "to", "nested", "data", ".", "Export", "all", "block", "and", "connection", "data", "." ]
def export_data(self): """ Export this flow graph to nested data. Export all block and connection data. Returns: a nested data odict """ def block_order(b): return not b.is_variable, b.name # todo: vars still first ?!? data = collections.OrderedDict() data['options'] = self.options_block.export_data() data['blocks'] = [b.export_data() for b in sorted(self.blocks, key=block_order) if b is not self.options_block] data['connections'] = sorted(c.export_data() for c in self.connections) data['metadata'] = {'file_format': FLOW_GRAPH_FILE_FORMAT_VERSION} return data
[ "def", "export_data", "(", "self", ")", ":", "def", "block_order", "(", "b", ")", ":", "return", "not", "b", ".", "is_variable", ",", "b", ".", "name", "# todo: vars still first ?!?", "data", "=", "collections", ".", "OrderedDict", "(", ")", "data", "[", "'options'", "]", "=", "self", ".", "options_block", ".", "export_data", "(", ")", "data", "[", "'blocks'", "]", "=", "[", "b", ".", "export_data", "(", ")", "for", "b", "in", "sorted", "(", "self", ".", "blocks", ",", "key", "=", "block_order", ")", "if", "b", "is", "not", "self", ".", "options_block", "]", "data", "[", "'connections'", "]", "=", "sorted", "(", "c", ".", "export_data", "(", ")", "for", "c", "in", "self", ".", "connections", ")", "data", "[", "'metadata'", "]", "=", "{", "'file_format'", ":", "FLOW_GRAPH_FILE_FORMAT_VERSION", "}", "return", "data" ]
https://github.com/gnuradio/gnuradio/blob/09c3c4fa4bfb1a02caac74cb5334dfe065391e3b/grc/core/FlowGraph.py#L382-L399
benoitsteiner/tensorflow-opencl
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
tensorflow/python/ops/clip_ops.py
python
clip_by_global_norm
(t_list, clip_norm, use_norm=None, name=None)
return list_clipped, use_norm
Clips values of multiple tensors by the ratio of the sum of their norms. Given a tuple or list of tensors `t_list`, and a clipping ratio `clip_norm`, this operation returns a list of clipped tensors `list_clipped` and the global norm (`global_norm`) of all tensors in `t_list`. Optionally, if you've already computed the global norm for `t_list`, you can specify the global norm with `use_norm`. To perform the clipping, the values `t_list[i]` are set to: t_list[i] * clip_norm / max(global_norm, clip_norm) where: global_norm = sqrt(sum([l2norm(t)**2 for t in t_list])) If `clip_norm > global_norm` then the entries in `t_list` remain as they are, otherwise they're all shrunk by the global ratio. Any of the entries of `t_list` that are of type `None` are ignored. This is the correct way to perform gradient clipping (for example, see [Pascanu et al., 2012](http://arxiv.org/abs/1211.5063) ([pdf](http://arxiv.org/pdf/1211.5063.pdf))). However, it is slower than `clip_by_norm()` because all the parameters must be ready before the clipping operation can be performed. Args: t_list: A tuple or list of mixed `Tensors`, `IndexedSlices`, or None. clip_norm: A 0-D (scalar) `Tensor` > 0. The clipping ratio. use_norm: A 0-D (scalar) `Tensor` of type `float` (optional). The global norm to use. If not provided, `global_norm()` is used to compute the norm. name: A name for the operation (optional). Returns: list_clipped: A list of `Tensors` of the same type as `list_t`. global_norm: A 0-D (scalar) `Tensor` representing the global norm. Raises: TypeError: If `t_list` is not a sequence.
Clips values of multiple tensors by the ratio of the sum of their norms.
[ "Clips", "values", "of", "multiple", "tensors", "by", "the", "ratio", "of", "the", "sum", "of", "their", "norms", "." ]
def clip_by_global_norm(t_list, clip_norm, use_norm=None, name=None): """Clips values of multiple tensors by the ratio of the sum of their norms. Given a tuple or list of tensors `t_list`, and a clipping ratio `clip_norm`, this operation returns a list of clipped tensors `list_clipped` and the global norm (`global_norm`) of all tensors in `t_list`. Optionally, if you've already computed the global norm for `t_list`, you can specify the global norm with `use_norm`. To perform the clipping, the values `t_list[i]` are set to: t_list[i] * clip_norm / max(global_norm, clip_norm) where: global_norm = sqrt(sum([l2norm(t)**2 for t in t_list])) If `clip_norm > global_norm` then the entries in `t_list` remain as they are, otherwise they're all shrunk by the global ratio. Any of the entries of `t_list` that are of type `None` are ignored. This is the correct way to perform gradient clipping (for example, see [Pascanu et al., 2012](http://arxiv.org/abs/1211.5063) ([pdf](http://arxiv.org/pdf/1211.5063.pdf))). However, it is slower than `clip_by_norm()` because all the parameters must be ready before the clipping operation can be performed. Args: t_list: A tuple or list of mixed `Tensors`, `IndexedSlices`, or None. clip_norm: A 0-D (scalar) `Tensor` > 0. The clipping ratio. use_norm: A 0-D (scalar) `Tensor` of type `float` (optional). The global norm to use. If not provided, `global_norm()` is used to compute the norm. name: A name for the operation (optional). Returns: list_clipped: A list of `Tensors` of the same type as `list_t`. global_norm: A 0-D (scalar) `Tensor` representing the global norm. Raises: TypeError: If `t_list` is not a sequence. """ if (not isinstance(t_list, collections.Sequence) or isinstance(t_list, six.string_types)): raise TypeError("t_list should be a sequence") t_list = list(t_list) if use_norm is None: use_norm = global_norm(t_list, name) with ops.name_scope(name, "clip_by_global_norm", t_list + [clip_norm]) as name: # Calculate L2-norm, clip elements by ratio of clip_norm to L2-norm scale = clip_norm * math_ops.minimum( 1.0 / use_norm, constant_op.constant(1.0, dtype=use_norm.dtype) / clip_norm) values = [ ops.convert_to_tensor( t.values if isinstance(t, ops.IndexedSlices) else t, name="t_%d" % i) if t is not None else t for i, t in enumerate(t_list)] values_clipped = [] for i, v in enumerate(values): if v is None: values_clipped.append(None) else: with ops.colocate_with(v): values_clipped.append( array_ops.identity(v * scale, name="%s_%d" % (name, i))) list_clipped = [ ops.IndexedSlices(c_v, t.indices, t.dense_shape) if isinstance(t, ops.IndexedSlices) else c_v for (c_v, t) in zip(values_clipped, t_list)] return list_clipped, use_norm
[ "def", "clip_by_global_norm", "(", "t_list", ",", "clip_norm", ",", "use_norm", "=", "None", ",", "name", "=", "None", ")", ":", "if", "(", "not", "isinstance", "(", "t_list", ",", "collections", ".", "Sequence", ")", "or", "isinstance", "(", "t_list", ",", "six", ".", "string_types", ")", ")", ":", "raise", "TypeError", "(", "\"t_list should be a sequence\"", ")", "t_list", "=", "list", "(", "t_list", ")", "if", "use_norm", "is", "None", ":", "use_norm", "=", "global_norm", "(", "t_list", ",", "name", ")", "with", "ops", ".", "name_scope", "(", "name", ",", "\"clip_by_global_norm\"", ",", "t_list", "+", "[", "clip_norm", "]", ")", "as", "name", ":", "# Calculate L2-norm, clip elements by ratio of clip_norm to L2-norm", "scale", "=", "clip_norm", "*", "math_ops", ".", "minimum", "(", "1.0", "/", "use_norm", ",", "constant_op", ".", "constant", "(", "1.0", ",", "dtype", "=", "use_norm", ".", "dtype", ")", "/", "clip_norm", ")", "values", "=", "[", "ops", ".", "convert_to_tensor", "(", "t", ".", "values", "if", "isinstance", "(", "t", ",", "ops", ".", "IndexedSlices", ")", "else", "t", ",", "name", "=", "\"t_%d\"", "%", "i", ")", "if", "t", "is", "not", "None", "else", "t", "for", "i", ",", "t", "in", "enumerate", "(", "t_list", ")", "]", "values_clipped", "=", "[", "]", "for", "i", ",", "v", "in", "enumerate", "(", "values", ")", ":", "if", "v", "is", "None", ":", "values_clipped", ".", "append", "(", "None", ")", "else", ":", "with", "ops", ".", "colocate_with", "(", "v", ")", ":", "values_clipped", ".", "append", "(", "array_ops", ".", "identity", "(", "v", "*", "scale", ",", "name", "=", "\"%s_%d\"", "%", "(", "name", ",", "i", ")", ")", ")", "list_clipped", "=", "[", "ops", ".", "IndexedSlices", "(", "c_v", ",", "t", ".", "indices", ",", "t", ".", "dense_shape", ")", "if", "isinstance", "(", "t", ",", "ops", ".", "IndexedSlices", ")", "else", "c_v", "for", "(", "c_v", ",", "t", ")", "in", "zip", "(", "values_clipped", ",", "t_list", ")", "]", "return", "list_clipped", ",", "use_norm" ]
https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/ops/clip_ops.py#L167-L246
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/osx_carbon/_core.py
python
Window_UnreserveControlId
(*args, **kwargs)
return _core_.Window_UnreserveControlId(*args, **kwargs)
Window_UnreserveControlId(int id, int count=1) If an ID generated from NewControlId is not assigned to a wxWindowIDRef, it must be unreserved.
Window_UnreserveControlId(int id, int count=1)
[ "Window_UnreserveControlId", "(", "int", "id", "int", "count", "=", "1", ")" ]
def Window_UnreserveControlId(*args, **kwargs): """ Window_UnreserveControlId(int id, int count=1) If an ID generated from NewControlId is not assigned to a wxWindowIDRef, it must be unreserved. """ return _core_.Window_UnreserveControlId(*args, **kwargs)
[ "def", "Window_UnreserveControlId", "(", "*", "args", ",", "*", "*", "kwargs", ")", ":", "return", "_core_", ".", "Window_UnreserveControlId", "(", "*", "args", ",", "*", "*", "kwargs", ")" ]
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_core.py#L11738-L11745
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
samples/ide/activegrid/tool/STCTextEditor.py
python
TextCtrl.MarkerDefineDefault
(self)
This must be called after the textcontrol is instantiated
This must be called after the textcontrol is instantiated
[ "This", "must", "be", "called", "after", "the", "textcontrol", "is", "instantiated" ]
def MarkerDefineDefault(self): """ This must be called after the textcontrol is instantiated """ self.MarkerDefine(TextView.MARKER_NUM, wx.stc.STC_MARK_ROUNDRECT, wx.BLACK, wx.BLUE)
[ "def", "MarkerDefineDefault", "(", "self", ")", ":", "self", ".", "MarkerDefine", "(", "TextView", ".", "MARKER_NUM", ",", "wx", ".", "stc", ".", "STC_MARK_ROUNDRECT", ",", "wx", ".", "BLACK", ",", "wx", ".", "BLUE", ")" ]
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/samples/ide/activegrid/tool/STCTextEditor.py#L1190-L1192
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python3/src/Lib/xml/sax/xmlreader.py
python
XMLReader.setFeature
(self, name, state)
Sets the state of a SAX2 feature.
Sets the state of a SAX2 feature.
[ "Sets", "the", "state", "of", "a", "SAX2", "feature", "." ]
def setFeature(self, name, state): "Sets the state of a SAX2 feature." raise SAXNotRecognizedException("Feature '%s' not recognized" % name)
[ "def", "setFeature", "(", "self", ",", "name", ",", "state", ")", ":", "raise", "SAXNotRecognizedException", "(", "\"Feature '%s' not recognized\"", "%", "name", ")" ]
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/xml/sax/xmlreader.py#L79-L81
catboost/catboost
167f64f237114a4d10b2b4ee42adb4569137debe
contrib/tools/python3/src/Lib/lib2to3/fixer_util.py
python
is_import
(node)
return node.type in (syms.import_name, syms.import_from)
Returns true if the node is an import statement.
Returns true if the node is an import statement.
[ "Returns", "true", "if", "the", "node", "is", "an", "import", "statement", "." ]
def is_import(node): """Returns true if the node is an import statement.""" return node.type in (syms.import_name, syms.import_from)
[ "def", "is_import", "(", "node", ")", ":", "return", "node", ".", "type", "in", "(", "syms", ".", "import_name", ",", "syms", ".", "import_from", ")" ]
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python3/src/Lib/lib2to3/fixer_util.py#L311-L313
ApolloAuto/apollo-platform
86d9dc6743b496ead18d597748ebabd34a513289
ros/third_party/lib_x86_64/python2.7/dist-packages/numpy/ma/mrecords.py
python
fromarrays
(arraylist, dtype=None, shape=None, formats=None, names=None, titles=None, aligned=False, byteorder=None, fill_value=None)
return _array
Creates a mrecarray from a (flat) list of masked arrays. Parameters ---------- arraylist : sequence A list of (masked) arrays. Each element of the sequence is first converted to a masked array if needed. If a 2D array is passed as argument, it is processed line by line dtype : {None, dtype}, optional Data type descriptor. shape : {None, integer}, optional Number of records. If None, shape is defined from the shape of the first array in the list. formats : {None, sequence}, optional Sequence of formats for each individual field. If None, the formats will be autodetected by inspecting the fields and selecting the highest dtype possible. names : {None, sequence}, optional Sequence of the names of each field. fill_value : {None, sequence}, optional Sequence of data to be used as filling values. Notes ----- Lists of tuples should be preferred over lists of lists for faster processing.
Creates a mrecarray from a (flat) list of masked arrays.
[ "Creates", "a", "mrecarray", "from", "a", "(", "flat", ")", "list", "of", "masked", "arrays", "." ]
def fromarrays(arraylist, dtype=None, shape=None, formats=None, names=None, titles=None, aligned=False, byteorder=None, fill_value=None): """Creates a mrecarray from a (flat) list of masked arrays. Parameters ---------- arraylist : sequence A list of (masked) arrays. Each element of the sequence is first converted to a masked array if needed. If a 2D array is passed as argument, it is processed line by line dtype : {None, dtype}, optional Data type descriptor. shape : {None, integer}, optional Number of records. If None, shape is defined from the shape of the first array in the list. formats : {None, sequence}, optional Sequence of formats for each individual field. If None, the formats will be autodetected by inspecting the fields and selecting the highest dtype possible. names : {None, sequence}, optional Sequence of the names of each field. fill_value : {None, sequence}, optional Sequence of data to be used as filling values. Notes ----- Lists of tuples should be preferred over lists of lists for faster processing. """ datalist = [getdata(x) for x in arraylist] masklist = [np.atleast_1d(getmaskarray(x)) for x in arraylist] _array = recfromarrays(datalist, dtype=dtype, shape=shape, formats=formats, names=names, titles=titles, aligned=aligned, byteorder=byteorder).view(mrecarray) _array._mask.flat = list(zip(*masklist)) if fill_value is not None: _array.fill_value = fill_value return _array
[ "def", "fromarrays", "(", "arraylist", ",", "dtype", "=", "None", ",", "shape", "=", "None", ",", "formats", "=", "None", ",", "names", "=", "None", ",", "titles", "=", "None", ",", "aligned", "=", "False", ",", "byteorder", "=", "None", ",", "fill_value", "=", "None", ")", ":", "datalist", "=", "[", "getdata", "(", "x", ")", "for", "x", "in", "arraylist", "]", "masklist", "=", "[", "np", ".", "atleast_1d", "(", "getmaskarray", "(", "x", ")", ")", "for", "x", "in", "arraylist", "]", "_array", "=", "recfromarrays", "(", "datalist", ",", "dtype", "=", "dtype", ",", "shape", "=", "shape", ",", "formats", "=", "formats", ",", "names", "=", "names", ",", "titles", "=", "titles", ",", "aligned", "=", "aligned", ",", "byteorder", "=", "byteorder", ")", ".", "view", "(", "mrecarray", ")", "_array", ".", "_mask", ".", "flat", "=", "list", "(", "zip", "(", "*", "masklist", ")", ")", "if", "fill_value", "is", "not", "None", ":", "_array", ".", "fill_value", "=", "fill_value", "return", "_array" ]
https://github.com/ApolloAuto/apollo-platform/blob/86d9dc6743b496ead18d597748ebabd34a513289/ros/third_party/lib_x86_64/python2.7/dist-packages/numpy/ma/mrecords.py#L479-L517
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/_controls.py
python
PreBitmapButton
(*args, **kwargs)
return val
PreBitmapButton() -> BitmapButton Precreate a BitmapButton for 2-phase creation.
PreBitmapButton() -> BitmapButton
[ "PreBitmapButton", "()", "-", ">", "BitmapButton" ]
def PreBitmapButton(*args, **kwargs): """ PreBitmapButton() -> BitmapButton Precreate a BitmapButton for 2-phase creation. """ val = _controls_.new_PreBitmapButton(*args, **kwargs) return val
[ "def", "PreBitmapButton", "(", "*", "args", ",", "*", "*", "kwargs", ")", ":", "val", "=", "_controls_", ".", "new_PreBitmapButton", "(", "*", "args", ",", "*", "*", "kwargs", ")", "return", "val" ]
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_controls.py#L320-L327
limbo018/DREAMPlace
146c3b9fd003d1acd52c96d9fd02e3f0a05154e4
dreamplace/BasicPlace.py
python
BasicPlace.validate
(self, placedb, pos, iteration)
return hpwl, overflow, max_density
@brief validate placement @param placedb placement database @param pos locations of cells @param iteration optimization step
[]
def validate(self, placedb, pos, iteration): """ @brief validate placement @param placedb placement database @param pos locations of cells @param iteration optimization step """ pos = torch.from_numpy(pos).to(self.device) hpwl = self.op_collections.hpwl_op(pos) #rmst_wls = self.rmst_wl_op(pos) #rmst_wl = rmst_wls.sum() overflow, max_density = self.op_collections.density_overflow_op(pos) #return hpwl, rmst_wl, overflow, max_density return hpwl, overflow, max_density
[ "def", "validate", "(", "self", ",", "placedb", ",", "pos", ",", "iteration", ")", ":", "pos", "=", "torch", ".", "from_numpy", "(", "pos", ")", ".", "to", "(", "self", ".", "device", ")", "hpwl", "=", "self", ".", "op_collections", ".", "hpwl_op", "(", "pos", ")", "#rmst_wls = self.rmst_wl_op(pos)", "#rmst_wl = rmst_wls.sum()", "overflow", ",", "max_density", "=", "self", ".", "op_collections", ".", "density_overflow_op", "(", "pos", ")", "#return hpwl, rmst_wl, overflow, max_density", "return", "hpwl", ",", "overflow", ",", "max_density" ]
https://github.com/limbo018/DREAMPlace/blob/146c3b9fd003d1acd52c96d9fd02e3f0a05154e4/dreamplace/BasicPlace.py#L1003-L1017
olliw42/storm32bgc
99d62a6130ae2950514022f50eb669c45a8cc1ba
old/betacopter/old/betacopter36dev-v005/modules/uavcan/libuavcan/dsdl_compiler/pyuavcan/uavcan/dsdl/signature.py
python
Signature.add
(self, data_bytes)
Feed ASCII string or bytes to the signature function
Feed ASCII string or bytes to the signature function
[ "Feed", "ASCII", "string", "or", "bytes", "to", "the", "signature", "function" ]
def add(self, data_bytes): '''Feed ASCII string or bytes to the signature function''' try: if isinstance(data_bytes, basestring): # Python 2.7 compatibility data_bytes = map(ord, data_bytes) except NameError: if isinstance(data_bytes, str): # This branch will be taken on Python 3 data_bytes = map(ord, data_bytes) for b in data_bytes: self._crc ^= (b << 56) & Signature.MASK64 for _ in range(8): if self._crc & (1 << 63): self._crc = ((self._crc << 1) & Signature.MASK64) ^ Signature.POLY else: self._crc <<= 1
[ "def", "add", "(", "self", ",", "data_bytes", ")", ":", "try", ":", "if", "isinstance", "(", "data_bytes", ",", "basestring", ")", ":", "# Python 2.7 compatibility", "data_bytes", "=", "map", "(", "ord", ",", "data_bytes", ")", "except", "NameError", ":", "if", "isinstance", "(", "data_bytes", ",", "str", ")", ":", "# This branch will be taken on Python 3", "data_bytes", "=", "map", "(", "ord", ",", "data_bytes", ")", "for", "b", "in", "data_bytes", ":", "self", ".", "_crc", "^=", "(", "b", "<<", "56", ")", "&", "Signature", ".", "MASK64", "for", "_", "in", "range", "(", "8", ")", ":", "if", "self", ".", "_crc", "&", "(", "1", "<<", "63", ")", ":", "self", ".", "_crc", "=", "(", "(", "self", ".", "_crc", "<<", "1", ")", "&", "Signature", ".", "MASK64", ")", "^", "Signature", ".", "POLY", "else", ":", "self", ".", "_crc", "<<=", "1" ]
https://github.com/olliw42/storm32bgc/blob/99d62a6130ae2950514022f50eb669c45a8cc1ba/old/betacopter/old/betacopter36dev-v005/modules/uavcan/libuavcan/dsdl_compiler/pyuavcan/uavcan/dsdl/signature.py#L34-L49
baidu-research/tensorflow-allreduce
66d5b855e90b0949e9fa5cca5599fd729a70e874
tensorflow/contrib/opt/python/training/drop_stale_gradient_optimizer.py
python
DropStaleGradientOptimizer.__init__
(self, opt, staleness, use_locking=False, name="DropStaleGradient")
Constructs a new DropStaleGradientOptimizer. Args: opt: The actual optimizer that will be used to compute and apply the gradients. Must be one of the Optimizer classes. staleness: The maximum staleness allowed for the optimizer. use_locking: If `True` use locks for clip update operations. name: Optional name prefix for the operations created when applying gradients. Defaults to "DropStaleGradient".
Constructs a new DropStaleGradientOptimizer.
[ "Constructs", "a", "new", "DropStaleGradientOptimizer", "." ]
def __init__(self, opt, staleness, use_locking=False, name="DropStaleGradient"): """Constructs a new DropStaleGradientOptimizer. Args: opt: The actual optimizer that will be used to compute and apply the gradients. Must be one of the Optimizer classes. staleness: The maximum staleness allowed for the optimizer. use_locking: If `True` use locks for clip update operations. name: Optional name prefix for the operations created when applying gradients. Defaults to "DropStaleGradient". """ super(DropStaleGradientOptimizer, self).__init__(use_locking, name) self._opt = opt self._staleness = staleness
[ "def", "__init__", "(", "self", ",", "opt", ",", "staleness", ",", "use_locking", "=", "False", ",", "name", "=", "\"DropStaleGradient\"", ")", ":", "super", "(", "DropStaleGradientOptimizer", ",", "self", ")", ".", "__init__", "(", "use_locking", ",", "name", ")", "self", ".", "_opt", "=", "opt", "self", ".", "_staleness", "=", "staleness" ]
https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/contrib/opt/python/training/drop_stale_gradient_optimizer.py#L44-L61
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
wx/tools/Editra/src/ed_txt.py
python
EdFile.FireModified
(self)
Fire the modified callback(s)
Fire the modified callback(s)
[ "Fire", "the", "modified", "callback", "(", "s", ")" ]
def FireModified(self): """Fire the modified callback(s)""" remove = list() for idx, mcallback in enumerate(self._mcallback): try: mcallback() except: remove.append(idx) # Cleanup any bad callbacks if len(remove): remove.reverse() for idx in remove: self._mcallback.pop(idx)
[ "def", "FireModified", "(", "self", ")", ":", "remove", "=", "list", "(", ")", "for", "idx", ",", "mcallback", "in", "enumerate", "(", "self", ".", "_mcallback", ")", ":", "try", ":", "mcallback", "(", ")", "except", ":", "remove", ".", "append", "(", "idx", ")", "# Cleanup any bad callbacks", "if", "len", "(", "remove", ")", ":", "remove", ".", "reverse", "(", ")", "for", "idx", "in", "remove", ":", "self", ".", "_mcallback", ".", "pop", "(", "idx", ")" ]
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/tools/Editra/src/ed_txt.py#L329-L342
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/pyclbr.py
python
readmodule
(module, path=None)
return res
Return Class objects for the top-level classes in module. This is the original interface, before Functions were added.
Return Class objects for the top-level classes in module.
[ "Return", "Class", "objects", "for", "the", "top", "-", "level", "classes", "in", "module", "." ]
def readmodule(module, path=None): """Return Class objects for the top-level classes in module. This is the original interface, before Functions were added. """ res = {} for key, value in _readmodule(module, path or []).items(): if isinstance(value, Class): res[key] = value return res
[ "def", "readmodule", "(", "module", ",", "path", "=", "None", ")", ":", "res", "=", "{", "}", "for", "key", ",", "value", "in", "_readmodule", "(", "module", ",", "path", "or", "[", "]", ")", ".", "items", "(", ")", ":", "if", "isinstance", "(", "value", ",", "Class", ")", ":", "res", "[", "key", "]", "=", "value", "return", "res" ]
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/pyclbr.py#L97-L107
openvinotoolkit/openvino
dedcbeafa8b84cccdc55ca64b8da516682b381c7
cmake/developer_package/cpplint/cpplint.py
python
CheckLanguage
(filename, clean_lines, linenum, file_extension, include_state, nesting_state, error)
Checks rules from the 'C++ language rules' section of cppguide.html. Some of these rules are hard to test (function overloading, using uint32 inappropriately), but we do the best we can. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. file_extension: The extension (without the dot) of the filename. include_state: An _IncludeState instance in which the headers are inserted. nesting_state: A NestingState instance which maintains information about the current stack of nested blocks being parsed. error: The function to call with any errors found.
Checks rules from the 'C++ language rules' section of cppguide.html.
[ "Checks", "rules", "from", "the", "C", "++", "language", "rules", "section", "of", "cppguide", ".", "html", "." ]
def CheckLanguage(filename, clean_lines, linenum, file_extension, include_state, nesting_state, error): """Checks rules from the 'C++ language rules' section of cppguide.html. Some of these rules are hard to test (function overloading, using uint32 inappropriately), but we do the best we can. Args: filename: The name of the current file. clean_lines: A CleansedLines instance containing the file. linenum: The number of the line to check. file_extension: The extension (without the dot) of the filename. include_state: An _IncludeState instance in which the headers are inserted. nesting_state: A NestingState instance which maintains information about the current stack of nested blocks being parsed. error: The function to call with any errors found. """ # If the line is empty or consists of entirely a comment, no need to # check it. line = clean_lines.elided[linenum] if not line: return match = _RE_PATTERN_INCLUDE.search(line) if match: CheckIncludeLine(filename, clean_lines, linenum, include_state, error) return # Reset include state across preprocessor directives. This is meant # to silence warnings for conditional includes. match = Match(r'^\s*#\s*(if|ifdef|ifndef|elif|else|endif)\b', line) if match: include_state.ResetSection(match.group(1)) # Perform other checks now that we are sure that this is not an include line CheckCasts(filename, clean_lines, linenum, error) CheckGlobalStatic(filename, clean_lines, linenum, error) CheckPrintf(filename, clean_lines, linenum, error) if IsHeaderExtension(file_extension): # TODO(unknown): check that 1-arg constructors are explicit. # How to tell it's a constructor? # (handled in CheckForNonStandardConstructs for now) # TODO(unknown): check that classes declare or disable copy/assign # (level 1 error) pass # Check if people are using the verboten C basic types. The only exception # we regularly allow is "unsigned short port" for port. if Search(r'\bshort port\b', line): if not Search(r'\bunsigned short port\b', line): error(filename, linenum, 'runtime/int', 4, 'Use "unsigned short" for ports, not "short"') else: match = Search(r'\b(short|long(?! +double)|long long)\b', line) if match: error(filename, linenum, 'runtime/int', 4, 'Use int16/int64/etc, rather than the C type %s' % match.group(1)) # Check if some verboten operator overloading is going on # TODO(unknown): catch out-of-line unary operator&: # class X {}; # int operator&(const X& x) { return 42; } // unary operator& # The trick is it's hard to tell apart from binary operator&: # class Y { int operator&(const Y& x) { return 23; } }; // binary operator& if Search(r'\boperator\s*&\s*\(\s*\)', line): error(filename, linenum, 'runtime/operator', 4, 'Unary operator& is dangerous. Do not use it.') # Check for suspicious usage of "if" like # } if (a == b) { if Search(r'\}\s*if\s*\(', line): error(filename, linenum, 'readability/braces', 4, 'Did you mean "else if"? If not, start a new line for "if".') # Check for potential format string bugs like printf(foo). # We constrain the pattern not to pick things like DocidForPrintf(foo). # Not perfect but it can catch printf(foo.c_str()) and printf(foo->c_str()) # TODO(unknown): Catch the following case. Need to change the calling # convention of the whole function to process multiple line to handle it. # printf( # boy_this_is_a_really_long_variable_that_cannot_fit_on_the_prev_line); printf_args = _GetTextInside(line, r'(?i)\b(string)?printf\s*\(') if printf_args: match = Match(r'([\w.\->()]+)$', printf_args) if match and match.group(1) != '__VA_ARGS__': function_name = re.search(r'\b((?:string)?printf)\s*\(', line, re.I).group(1) error(filename, linenum, 'runtime/printf', 4, 'Potential format string bug. Do %s("%%s", %s) instead.' % (function_name, match.group(1))) # Check for potential memset bugs like memset(buf, sizeof(buf), 0). match = Search(r'memset\s*\(([^,]*),\s*([^,]*),\s*0\s*\)', line) if match and not Match(r"^''|-?[0-9]+|0x[0-9A-Fa-f]$", match.group(2)): error(filename, linenum, 'runtime/memset', 4, 'Did you mean "memset(%s, 0, %s)"?' % (match.group(1), match.group(2))) if Search(r'\busing namespace\b', line): if Search(r'\bliterals\b', line): error(filename, linenum, 'build/namespaces_literals', 5, 'Do not use namespace using-directives. ' 'Use using-declarations instead.') else: error(filename, linenum, 'build/namespaces', 5, 'Do not use namespace using-directives. ' 'Use using-declarations instead.') # Detect variable-length arrays. match = Match(r'\s*(.+::)?(\w+) [a-z]\w*\[(.+)];', line) if (match and match.group(2) != 'return' and match.group(2) != 'delete' and match.group(3).find(']') == -1): # Split the size using space and arithmetic operators as delimiters. # If any of the resulting tokens are not compile time constants then # report the error. tokens = re.split(r'\s|\+|\-|\*|\/|<<|>>]', match.group(3)) is_const = True skip_next = False for tok in tokens: if skip_next: skip_next = False continue if Search(r'sizeof\(.+\)', tok): continue if Search(r'arraysize\(\w+\)', tok): continue tok = tok.lstrip('(') tok = tok.rstrip(')') if not tok: continue if Match(r'\d+', tok): continue if Match(r'0[xX][0-9a-fA-F]+', tok): continue if Match(r'k[A-Z0-9]\w*', tok): continue if Match(r'(.+::)?k[A-Z0-9]\w*', tok): continue if Match(r'(.+::)?[A-Z][A-Z0-9_]*', tok): continue # A catch all for tricky sizeof cases, including 'sizeof expression', # 'sizeof(*type)', 'sizeof(const type)', 'sizeof(struct StructName)' # requires skipping the next token because we split on ' ' and '*'. if tok.startswith('sizeof'): skip_next = True continue is_const = False break if not is_const: error(filename, linenum, 'runtime/arrays', 1, 'Do not use variable-length arrays. Use an appropriately named ' "('k' followed by CamelCase) compile-time constant for the size.") # Check for use of unnamed namespaces in header files. Registration # macros are typically OK, so we allow use of "namespace {" on lines # that end with backslashes. if (IsHeaderExtension(file_extension) and Search(r'\bnamespace\s*{', line) and line[-1] != '\\'): error(filename, linenum, 'build/namespaces', 4, 'Do not use unnamed namespaces in header files. See ' 'https://google-styleguide.googlecode.com/svn/trunk/cppguide.xml#Namespaces' ' for more information.')
[ "def", "CheckLanguage", "(", "filename", ",", "clean_lines", ",", "linenum", ",", "file_extension", ",", "include_state", ",", "nesting_state", ",", "error", ")", ":", "# If the line is empty or consists of entirely a comment, no need to", "# check it.", "line", "=", "clean_lines", ".", "elided", "[", "linenum", "]", "if", "not", "line", ":", "return", "match", "=", "_RE_PATTERN_INCLUDE", ".", "search", "(", "line", ")", "if", "match", ":", "CheckIncludeLine", "(", "filename", ",", "clean_lines", ",", "linenum", ",", "include_state", ",", "error", ")", "return", "# Reset include state across preprocessor directives. This is meant", "# to silence warnings for conditional includes.", "match", "=", "Match", "(", "r'^\\s*#\\s*(if|ifdef|ifndef|elif|else|endif)\\b'", ",", "line", ")", "if", "match", ":", "include_state", ".", "ResetSection", "(", "match", ".", "group", "(", "1", ")", ")", "# Perform other checks now that we are sure that this is not an include line", "CheckCasts", "(", "filename", ",", "clean_lines", ",", "linenum", ",", "error", ")", "CheckGlobalStatic", "(", "filename", ",", "clean_lines", ",", "linenum", ",", "error", ")", "CheckPrintf", "(", "filename", ",", "clean_lines", ",", "linenum", ",", "error", ")", "if", "IsHeaderExtension", "(", "file_extension", ")", ":", "# TODO(unknown): check that 1-arg constructors are explicit.", "# How to tell it's a constructor?", "# (handled in CheckForNonStandardConstructs for now)", "# TODO(unknown): check that classes declare or disable copy/assign", "# (level 1 error)", "pass", "# Check if people are using the verboten C basic types. The only exception", "# we regularly allow is \"unsigned short port\" for port.", "if", "Search", "(", "r'\\bshort port\\b'", ",", "line", ")", ":", "if", "not", "Search", "(", "r'\\bunsigned short port\\b'", ",", "line", ")", ":", "error", "(", "filename", ",", "linenum", ",", "'runtime/int'", ",", "4", ",", "'Use \"unsigned short\" for ports, not \"short\"'", ")", "else", ":", "match", "=", "Search", "(", "r'\\b(short|long(?! +double)|long long)\\b'", ",", "line", ")", "if", "match", ":", "error", "(", "filename", ",", "linenum", ",", "'runtime/int'", ",", "4", ",", "'Use int16/int64/etc, rather than the C type %s'", "%", "match", ".", "group", "(", "1", ")", ")", "# Check if some verboten operator overloading is going on", "# TODO(unknown): catch out-of-line unary operator&:", "# class X {};", "# int operator&(const X& x) { return 42; } // unary operator&", "# The trick is it's hard to tell apart from binary operator&:", "# class Y { int operator&(const Y& x) { return 23; } }; // binary operator&", "if", "Search", "(", "r'\\boperator\\s*&\\s*\\(\\s*\\)'", ",", "line", ")", ":", "error", "(", "filename", ",", "linenum", ",", "'runtime/operator'", ",", "4", ",", "'Unary operator& is dangerous. Do not use it.'", ")", "# Check for suspicious usage of \"if\" like", "# } if (a == b) {", "if", "Search", "(", "r'\\}\\s*if\\s*\\('", ",", "line", ")", ":", "error", "(", "filename", ",", "linenum", ",", "'readability/braces'", ",", "4", ",", "'Did you mean \"else if\"? If not, start a new line for \"if\".'", ")", "# Check for potential format string bugs like printf(foo).", "# We constrain the pattern not to pick things like DocidForPrintf(foo).", "# Not perfect but it can catch printf(foo.c_str()) and printf(foo->c_str())", "# TODO(unknown): Catch the following case. Need to change the calling", "# convention of the whole function to process multiple line to handle it.", "# printf(", "# boy_this_is_a_really_long_variable_that_cannot_fit_on_the_prev_line);", "printf_args", "=", "_GetTextInside", "(", "line", ",", "r'(?i)\\b(string)?printf\\s*\\('", ")", "if", "printf_args", ":", "match", "=", "Match", "(", "r'([\\w.\\->()]+)$'", ",", "printf_args", ")", "if", "match", "and", "match", ".", "group", "(", "1", ")", "!=", "'__VA_ARGS__'", ":", "function_name", "=", "re", ".", "search", "(", "r'\\b((?:string)?printf)\\s*\\('", ",", "line", ",", "re", ".", "I", ")", ".", "group", "(", "1", ")", "error", "(", "filename", ",", "linenum", ",", "'runtime/printf'", ",", "4", ",", "'Potential format string bug. Do %s(\"%%s\", %s) instead.'", "%", "(", "function_name", ",", "match", ".", "group", "(", "1", ")", ")", ")", "# Check for potential memset bugs like memset(buf, sizeof(buf), 0).", "match", "=", "Search", "(", "r'memset\\s*\\(([^,]*),\\s*([^,]*),\\s*0\\s*\\)'", ",", "line", ")", "if", "match", "and", "not", "Match", "(", "r\"^''|-?[0-9]+|0x[0-9A-Fa-f]$\"", ",", "match", ".", "group", "(", "2", ")", ")", ":", "error", "(", "filename", ",", "linenum", ",", "'runtime/memset'", ",", "4", ",", "'Did you mean \"memset(%s, 0, %s)\"?'", "%", "(", "match", ".", "group", "(", "1", ")", ",", "match", ".", "group", "(", "2", ")", ")", ")", "if", "Search", "(", "r'\\busing namespace\\b'", ",", "line", ")", ":", "if", "Search", "(", "r'\\bliterals\\b'", ",", "line", ")", ":", "error", "(", "filename", ",", "linenum", ",", "'build/namespaces_literals'", ",", "5", ",", "'Do not use namespace using-directives. '", "'Use using-declarations instead.'", ")", "else", ":", "error", "(", "filename", ",", "linenum", ",", "'build/namespaces'", ",", "5", ",", "'Do not use namespace using-directives. '", "'Use using-declarations instead.'", ")", "# Detect variable-length arrays.", "match", "=", "Match", "(", "r'\\s*(.+::)?(\\w+) [a-z]\\w*\\[(.+)];'", ",", "line", ")", "if", "(", "match", "and", "match", ".", "group", "(", "2", ")", "!=", "'return'", "and", "match", ".", "group", "(", "2", ")", "!=", "'delete'", "and", "match", ".", "group", "(", "3", ")", ".", "find", "(", "']'", ")", "==", "-", "1", ")", ":", "# Split the size using space and arithmetic operators as delimiters.", "# If any of the resulting tokens are not compile time constants then", "# report the error.", "tokens", "=", "re", ".", "split", "(", "r'\\s|\\+|\\-|\\*|\\/|<<|>>]'", ",", "match", ".", "group", "(", "3", ")", ")", "is_const", "=", "True", "skip_next", "=", "False", "for", "tok", "in", "tokens", ":", "if", "skip_next", ":", "skip_next", "=", "False", "continue", "if", "Search", "(", "r'sizeof\\(.+\\)'", ",", "tok", ")", ":", "continue", "if", "Search", "(", "r'arraysize\\(\\w+\\)'", ",", "tok", ")", ":", "continue", "tok", "=", "tok", ".", "lstrip", "(", "'('", ")", "tok", "=", "tok", ".", "rstrip", "(", "')'", ")", "if", "not", "tok", ":", "continue", "if", "Match", "(", "r'\\d+'", ",", "tok", ")", ":", "continue", "if", "Match", "(", "r'0[xX][0-9a-fA-F]+'", ",", "tok", ")", ":", "continue", "if", "Match", "(", "r'k[A-Z0-9]\\w*'", ",", "tok", ")", ":", "continue", "if", "Match", "(", "r'(.+::)?k[A-Z0-9]\\w*'", ",", "tok", ")", ":", "continue", "if", "Match", "(", "r'(.+::)?[A-Z][A-Z0-9_]*'", ",", "tok", ")", ":", "continue", "# A catch all for tricky sizeof cases, including 'sizeof expression',", "# 'sizeof(*type)', 'sizeof(const type)', 'sizeof(struct StructName)'", "# requires skipping the next token because we split on ' ' and '*'.", "if", "tok", ".", "startswith", "(", "'sizeof'", ")", ":", "skip_next", "=", "True", "continue", "is_const", "=", "False", "break", "if", "not", "is_const", ":", "error", "(", "filename", ",", "linenum", ",", "'runtime/arrays'", ",", "1", ",", "'Do not use variable-length arrays. Use an appropriately named '", "\"('k' followed by CamelCase) compile-time constant for the size.\"", ")", "# Check for use of unnamed namespaces in header files. Registration", "# macros are typically OK, so we allow use of \"namespace {\" on lines", "# that end with backslashes.", "if", "(", "IsHeaderExtension", "(", "file_extension", ")", "and", "Search", "(", "r'\\bnamespace\\s*{'", ",", "line", ")", "and", "line", "[", "-", "1", "]", "!=", "'\\\\'", ")", ":", "error", "(", "filename", ",", "linenum", ",", "'build/namespaces'", ",", "4", ",", "'Do not use unnamed namespaces in header files. See '", "'https://google-styleguide.googlecode.com/svn/trunk/cppguide.xml#Namespaces'", "' for more information.'", ")" ]
https://github.com/openvinotoolkit/openvino/blob/dedcbeafa8b84cccdc55ca64b8da516682b381c7/cmake/developer_package/cpplint/cpplint.py#L4954-L5112
aws/lumberyard
f85344403c1c2e77ec8c75deb2c116e97b713217
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/email/message.py
python
Message.__str__
(self)
return self.as_string()
Return the entire formatted message as a string.
Return the entire formatted message as a string.
[ "Return", "the", "entire", "formatted", "message", "as", "a", "string", "." ]
def __str__(self): """Return the entire formatted message as a string. """ return self.as_string()
[ "def", "__str__", "(", "self", ")", ":", "return", "self", ".", "as_string", "(", ")" ]
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/email/message.py#L132-L135
generalized-intelligence/GAAS
29ab17d3e8a4ba18edef3a57c36d8db6329fac73
deprecated/software/scene_retrieving/src/nlohmann_json/benchmarks/thirdparty/benchmark/tools/gbench/util.py
python
remove_benchmark_flags
(prefix, benchmark_flags)
return [f for f in benchmark_flags if not f.startswith(prefix)]
Return a new list containing the specified benchmark_flags except those with the specified prefix.
Return a new list containing the specified benchmark_flags except those with the specified prefix.
[ "Return", "a", "new", "list", "containing", "the", "specified", "benchmark_flags", "except", "those", "with", "the", "specified", "prefix", "." ]
def remove_benchmark_flags(prefix, benchmark_flags): """ Return a new list containing the specified benchmark_flags except those with the specified prefix. """ assert prefix.startswith('--') and prefix.endswith('=') return [f for f in benchmark_flags if not f.startswith(prefix)]
[ "def", "remove_benchmark_flags", "(", "prefix", ",", "benchmark_flags", ")", ":", "assert", "prefix", ".", "startswith", "(", "'--'", ")", "and", "prefix", ".", "endswith", "(", "'='", ")", "return", "[", "f", "for", "f", "in", "benchmark_flags", "if", "not", "f", ".", "startswith", "(", "prefix", ")", "]" ]
https://github.com/generalized-intelligence/GAAS/blob/29ab17d3e8a4ba18edef3a57c36d8db6329fac73/deprecated/software/scene_retrieving/src/nlohmann_json/benchmarks/thirdparty/benchmark/tools/gbench/util.py#L100-L106
benoitsteiner/tensorflow-opencl
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
tensorflow/python/ops/data_flow_ops.py
python
Barrier.take_many
(self, num_elements, allow_small_batch=False, timeout=None, name=None)
return ret
Takes the given number of completed elements from this barrier. This operation concatenates completed-element component tensors along the 0th dimension to make a single component tensor. If barrier has no completed elements, this operation will block until there are 'num_elements' elements to take. TODO(b/25743580): the semantics of `allow_small_batch` are experimental and may be extended to other cases in the future. TODO(ebrevdo): If a take_many(allow_small_batch=True) is blocking already when the barrier is closed, it will block for ever. Fix this by using asynchronous operations. Args: num_elements: The number of elements to take. allow_small_batch: If the barrier is closed, don't block if there are less completed elements than requested, but instead return all available completed elements. timeout: This specifies the number of milliseconds to block before returning with DEADLINE_EXCEEDED. (This option is not supported yet.) name: A name for the operation (optional). Returns: A tuple of (index, key, value_list). "index" is a int64 tensor of length num_elements containing the index of the insert_many call for which the very first component of the given element was inserted into the Barrier, starting with the value -2**63. Note, this value is different from the index of the insert_many call for which the element was completed. "key" is a string tensor of length num_elements containing the keys. "value_list" is a tuple of tensors, each one with size num_elements in the 0th dimension for each component in the barrier's values.
Takes the given number of completed elements from this barrier.
[ "Takes", "the", "given", "number", "of", "completed", "elements", "from", "this", "barrier", "." ]
def take_many(self, num_elements, allow_small_batch=False, timeout=None, name=None): """Takes the given number of completed elements from this barrier. This operation concatenates completed-element component tensors along the 0th dimension to make a single component tensor. If barrier has no completed elements, this operation will block until there are 'num_elements' elements to take. TODO(b/25743580): the semantics of `allow_small_batch` are experimental and may be extended to other cases in the future. TODO(ebrevdo): If a take_many(allow_small_batch=True) is blocking already when the barrier is closed, it will block for ever. Fix this by using asynchronous operations. Args: num_elements: The number of elements to take. allow_small_batch: If the barrier is closed, don't block if there are less completed elements than requested, but instead return all available completed elements. timeout: This specifies the number of milliseconds to block before returning with DEADLINE_EXCEEDED. (This option is not supported yet.) name: A name for the operation (optional). Returns: A tuple of (index, key, value_list). "index" is a int64 tensor of length num_elements containing the index of the insert_many call for which the very first component of the given element was inserted into the Barrier, starting with the value -2**63. Note, this value is different from the index of the insert_many call for which the element was completed. "key" is a string tensor of length num_elements containing the keys. "value_list" is a tuple of tensors, each one with size num_elements in the 0th dimension for each component in the barrier's values. """ if name is None: name = "%s_BarrierTakeMany" % self._name ret = gen_data_flow_ops._barrier_take_many(self._barrier_ref, num_elements, self._types, allow_small_batch, timeout, name=name) # NOTE(mrry): Not using a shape function because we need access to # the Barrier object. if context.in_graph_mode(): op = ret[0].op if allow_small_batch: batch_dim = None else: batch_dim = tensor_shape.Dimension( tensor_util.constant_value(op.inputs[1])) op.outputs[0].set_shape(tensor_shape.vector(batch_dim)) # indices op.outputs[1].set_shape(tensor_shape.vector(batch_dim)) # keys for output, shape in zip(op.outputs[2:], self._shapes): # value_list output.set_shape( tensor_shape.TensorShape([batch_dim]).concatenate( shape)) return ret
[ "def", "take_many", "(", "self", ",", "num_elements", ",", "allow_small_batch", "=", "False", ",", "timeout", "=", "None", ",", "name", "=", "None", ")", ":", "if", "name", "is", "None", ":", "name", "=", "\"%s_BarrierTakeMany\"", "%", "self", ".", "_name", "ret", "=", "gen_data_flow_ops", ".", "_barrier_take_many", "(", "self", ".", "_barrier_ref", ",", "num_elements", ",", "self", ".", "_types", ",", "allow_small_batch", ",", "timeout", ",", "name", "=", "name", ")", "# NOTE(mrry): Not using a shape function because we need access to", "# the Barrier object.", "if", "context", ".", "in_graph_mode", "(", ")", ":", "op", "=", "ret", "[", "0", "]", ".", "op", "if", "allow_small_batch", ":", "batch_dim", "=", "None", "else", ":", "batch_dim", "=", "tensor_shape", ".", "Dimension", "(", "tensor_util", ".", "constant_value", "(", "op", ".", "inputs", "[", "1", "]", ")", ")", "op", ".", "outputs", "[", "0", "]", ".", "set_shape", "(", "tensor_shape", ".", "vector", "(", "batch_dim", ")", ")", "# indices", "op", ".", "outputs", "[", "1", "]", ".", "set_shape", "(", "tensor_shape", ".", "vector", "(", "batch_dim", ")", ")", "# keys", "for", "output", ",", "shape", "in", "zip", "(", "op", ".", "outputs", "[", "2", ":", "]", ",", "self", ".", "_shapes", ")", ":", "# value_list", "output", ".", "set_shape", "(", "tensor_shape", ".", "TensorShape", "(", "[", "batch_dim", "]", ")", ".", "concatenate", "(", "shape", ")", ")", "return", "ret" ]
https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/ops/data_flow_ops.py#L955-L1022
OpenChemistry/tomviz
0a903679318f191cb7dd3eb5ff5bc3a7d3320d9a
acquisition/tomviz/acquisition/vendors/passive/filesystem.py
python
Monitor.get
(self)
return None
Returns the first pending file available. If there are pending files in the queue the first in the queue is return, otherwise the path if check for new files. :returns: The first pending file, None if no file is available.
Returns the first pending file available. If there are pending files in the queue the first in the queue is return, otherwise the path if check for new files.
[ "Returns", "the", "first", "pending", "file", "available", ".", "If", "there", "are", "pending", "files", "in", "the", "queue", "the", "first", "in", "the", "queue", "is", "return", "otherwise", "the", "path", "if", "check", "for", "new", "files", "." ]
def get(self): """ Returns the first pending file available. If there are pending files in the queue the first in the queue is return, otherwise the path if check for new files. :returns: The first pending file, None if no file is available. """ if self._files.empty(): self._check() try: return self._files.get(block=False) except queue.Empty: pass return None
[ "def", "get", "(", "self", ")", ":", "if", "self", ".", "_files", ".", "empty", "(", ")", ":", "self", ".", "_check", "(", ")", "try", ":", "return", "self", ".", "_files", ".", "get", "(", "block", "=", "False", ")", "except", "queue", ".", "Empty", ":", "pass", "return", "None" ]
https://github.com/OpenChemistry/tomviz/blob/0a903679318f191cb7dd3eb5ff5bc3a7d3320d9a/acquisition/tomviz/acquisition/vendors/passive/filesystem.py#L46-L63
genn-team/genn
75e1eb218cafa228bf36ae4613d1ce26e877b12c
pygenn/genn_groups.py
python
SynapseGroup.is_dense
(self)
return (self.matrix_type & SynapseMatrixConnectivity_DENSE) != 0
Tests whether synaptic connectivity uses dense format
Tests whether synaptic connectivity uses dense format
[ "Tests", "whether", "synaptic", "connectivity", "uses", "dense", "format" ]
def is_dense(self): """Tests whether synaptic connectivity uses dense format""" return (self.matrix_type & SynapseMatrixConnectivity_DENSE) != 0
[ "def", "is_dense", "(", "self", ")", ":", "return", "(", "self", ".", "matrix_type", "&", "SynapseMatrixConnectivity_DENSE", ")", "!=", "0" ]
https://github.com/genn-team/genn/blob/75e1eb218cafa228bf36ae4613d1ce26e877b12c/pygenn/genn_groups.py#L906-L908
miyosuda/TensorFlowAndroidMNIST
7b5a4603d2780a8a2834575706e9001977524007
jni-build/jni/include/tensorflow/contrib/layers/python/layers/feature_column.py
python
real_valued_column
(column_name, dimension=1, default_value=None, dtype=dtypes.float32)
Creates a _RealValuedColumn. Args: column_name: A string defining real valued column name. dimension: An integer specifying dimension of the real valued column. The default is 1. The Tensor representing the _RealValuedColumn will have the shape of [batch_size, dimension]. default_value: A single value compatible with dtype or a list of values compatible with dtype which the column takes on if data is missing. If None, then tf.parse_example will fail if an example does not contain this column. If a single value is provided, the same value will be applied as the default value for every dimension. If a list of values is provided, the length of the list should be equal to the value of `dimension`. dtype: defines the type of values. Default value is tf.float32. Returns: A _RealValuedColumn. Raises: TypeError: if dimension is not an int ValueError: if dimension is not a positive integer TypeError: if default_value is a list but its length is not equal to the value of `dimension`. TypeError: if default_value is not compatible with dtype. ValueError: if dtype is not convertable to tf.float32.
Creates a _RealValuedColumn.
[ "Creates", "a", "_RealValuedColumn", "." ]
def real_valued_column(column_name, dimension=1, default_value=None, dtype=dtypes.float32): """Creates a _RealValuedColumn. Args: column_name: A string defining real valued column name. dimension: An integer specifying dimension of the real valued column. The default is 1. The Tensor representing the _RealValuedColumn will have the shape of [batch_size, dimension]. default_value: A single value compatible with dtype or a list of values compatible with dtype which the column takes on if data is missing. If None, then tf.parse_example will fail if an example does not contain this column. If a single value is provided, the same value will be applied as the default value for every dimension. If a list of values is provided, the length of the list should be equal to the value of `dimension`. dtype: defines the type of values. Default value is tf.float32. Returns: A _RealValuedColumn. Raises: TypeError: if dimension is not an int ValueError: if dimension is not a positive integer TypeError: if default_value is a list but its length is not equal to the value of `dimension`. TypeError: if default_value is not compatible with dtype. ValueError: if dtype is not convertable to tf.float32. """ if not isinstance(dimension, int): raise TypeError("dimension must be an integer. " "dimension: {}, column_name: {}".format(dimension, column_name)) if dimension < 1: raise ValueError("dimension must be greater than 0. " "dimension: {}, column_name: {}".format(dimension, column_name)) if not (dtype.is_integer or dtype.is_floating): raise ValueError("dtype must be convertible to float. " "dtype: {}, column_name: {}".format(dtype, column_name)) if default_value is None: return _RealValuedColumn(column_name, dimension, default_value, dtype) if isinstance(default_value, int): if dtype.is_integer: default_value = [default_value for _ in range(dimension)] return _RealValuedColumn(column_name, dimension, default_value, dtype) if dtype.is_floating: default_value = float(default_value) default_value = [default_value for _ in range(dimension)] return _RealValuedColumn(column_name, dimension, default_value, dtype) if isinstance(default_value, float): if dtype.is_floating and (not dtype.is_integer): default_value = [default_value for _ in range(dimension)] return _RealValuedColumn(column_name, dimension, default_value, dtype) if isinstance(default_value, list): if len(default_value) != dimension: raise ValueError( "The length of default_value must be equal to dimension. " "default_value: {}, dimension: {}, column_name: {}".format( default_value, dimension, column_name)) # Check if the values in the list are all integers or are convertible to # floats. is_list_all_int = True is_list_all_float = True for v in default_value: if not isinstance(v, int): is_list_all_int = False if not (isinstance(v, float) or isinstance(v, int)): is_list_all_float = False if is_list_all_int: if dtype.is_integer: return _RealValuedColumn(column_name, dimension, default_value, dtype) elif dtype.is_floating: default_value = [float(v) for v in default_value] return _RealValuedColumn(column_name, dimension, default_value, dtype) if is_list_all_float: if dtype.is_floating and (not dtype.is_integer): default_value = [float(v) for v in default_value] return _RealValuedColumn(column_name, dimension, default_value, dtype) raise TypeError("default_value must be compatible with dtype. " "default_value: {}, dtype: {}, column_name: {}".format( default_value, dtype, column_name))
[ "def", "real_valued_column", "(", "column_name", ",", "dimension", "=", "1", ",", "default_value", "=", "None", ",", "dtype", "=", "dtypes", ".", "float32", ")", ":", "if", "not", "isinstance", "(", "dimension", ",", "int", ")", ":", "raise", "TypeError", "(", "\"dimension must be an integer. \"", "\"dimension: {}, column_name: {}\"", ".", "format", "(", "dimension", ",", "column_name", ")", ")", "if", "dimension", "<", "1", ":", "raise", "ValueError", "(", "\"dimension must be greater than 0. \"", "\"dimension: {}, column_name: {}\"", ".", "format", "(", "dimension", ",", "column_name", ")", ")", "if", "not", "(", "dtype", ".", "is_integer", "or", "dtype", ".", "is_floating", ")", ":", "raise", "ValueError", "(", "\"dtype must be convertible to float. \"", "\"dtype: {}, column_name: {}\"", ".", "format", "(", "dtype", ",", "column_name", ")", ")", "if", "default_value", "is", "None", ":", "return", "_RealValuedColumn", "(", "column_name", ",", "dimension", ",", "default_value", ",", "dtype", ")", "if", "isinstance", "(", "default_value", ",", "int", ")", ":", "if", "dtype", ".", "is_integer", ":", "default_value", "=", "[", "default_value", "for", "_", "in", "range", "(", "dimension", ")", "]", "return", "_RealValuedColumn", "(", "column_name", ",", "dimension", ",", "default_value", ",", "dtype", ")", "if", "dtype", ".", "is_floating", ":", "default_value", "=", "float", "(", "default_value", ")", "default_value", "=", "[", "default_value", "for", "_", "in", "range", "(", "dimension", ")", "]", "return", "_RealValuedColumn", "(", "column_name", ",", "dimension", ",", "default_value", ",", "dtype", ")", "if", "isinstance", "(", "default_value", ",", "float", ")", ":", "if", "dtype", ".", "is_floating", "and", "(", "not", "dtype", ".", "is_integer", ")", ":", "default_value", "=", "[", "default_value", "for", "_", "in", "range", "(", "dimension", ")", "]", "return", "_RealValuedColumn", "(", "column_name", ",", "dimension", ",", "default_value", ",", "dtype", ")", "if", "isinstance", "(", "default_value", ",", "list", ")", ":", "if", "len", "(", "default_value", ")", "!=", "dimension", ":", "raise", "ValueError", "(", "\"The length of default_value must be equal to dimension. \"", "\"default_value: {}, dimension: {}, column_name: {}\"", ".", "format", "(", "default_value", ",", "dimension", ",", "column_name", ")", ")", "# Check if the values in the list are all integers or are convertible to", "# floats.", "is_list_all_int", "=", "True", "is_list_all_float", "=", "True", "for", "v", "in", "default_value", ":", "if", "not", "isinstance", "(", "v", ",", "int", ")", ":", "is_list_all_int", "=", "False", "if", "not", "(", "isinstance", "(", "v", ",", "float", ")", "or", "isinstance", "(", "v", ",", "int", ")", ")", ":", "is_list_all_float", "=", "False", "if", "is_list_all_int", ":", "if", "dtype", ".", "is_integer", ":", "return", "_RealValuedColumn", "(", "column_name", ",", "dimension", ",", "default_value", ",", "dtype", ")", "elif", "dtype", ".", "is_floating", ":", "default_value", "=", "[", "float", "(", "v", ")", "for", "v", "in", "default_value", "]", "return", "_RealValuedColumn", "(", "column_name", ",", "dimension", ",", "default_value", ",", "dtype", ")", "if", "is_list_all_float", ":", "if", "dtype", ".", "is_floating", "and", "(", "not", "dtype", ".", "is_integer", ")", ":", "default_value", "=", "[", "float", "(", "v", ")", "for", "v", "in", "default_value", "]", "return", "_RealValuedColumn", "(", "column_name", ",", "dimension", ",", "default_value", ",", "dtype", ")", "raise", "TypeError", "(", "\"default_value must be compatible with dtype. \"", "\"default_value: {}, dtype: {}, column_name: {}\"", ".", "format", "(", "default_value", ",", "dtype", ",", "column_name", ")", ")" ]
https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/tensorflow/contrib/layers/python/layers/feature_column.py#L909-L998
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/msw/html.py
python
HtmlLinkEvent.__init__
(self, *args, **kwargs)
__init__(self, int id, HtmlLinkInfo linkinfo) -> HtmlLinkEvent
__init__(self, int id, HtmlLinkInfo linkinfo) -> HtmlLinkEvent
[ "__init__", "(", "self", "int", "id", "HtmlLinkInfo", "linkinfo", ")", "-", ">", "HtmlLinkEvent" ]
def __init__(self, *args, **kwargs): """__init__(self, int id, HtmlLinkInfo linkinfo) -> HtmlLinkEvent""" _html.HtmlLinkEvent_swiginit(self,_html.new_HtmlLinkEvent(*args, **kwargs))
[ "def", "__init__", "(", "self", ",", "*", "args", ",", "*", "*", "kwargs", ")", ":", "_html", ".", "HtmlLinkEvent_swiginit", "(", "self", ",", "_html", ".", "new_HtmlLinkEvent", "(", "*", "args", ",", "*", "*", "kwargs", ")", ")" ]
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/html.py#L1716-L1718
Tencent/CMONGO
c40380caa14e05509f46993aa8b8da966b09b0b5
src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Environment.py
python
Base.Detect
(self, progs)
return None
Return the first available program in progs.
Return the first available program in progs.
[ "Return", "the", "first", "available", "program", "in", "progs", "." ]
def Detect(self, progs): """Return the first available program in progs. """ if not SCons.Util.is_List(progs): progs = [ progs ] for prog in progs: path = self.WhereIs(prog) if path: return prog return None
[ "def", "Detect", "(", "self", ",", "progs", ")", ":", "if", "not", "SCons", ".", "Util", ".", "is_List", "(", "progs", ")", ":", "progs", "=", "[", "progs", "]", "for", "prog", "in", "progs", ":", "path", "=", "self", ".", "WhereIs", "(", "prog", ")", "if", "path", ":", "return", "prog", "return", "None" ]
https://github.com/Tencent/CMONGO/blob/c40380caa14e05509f46993aa8b8da966b09b0b5/src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Environment.py#L1486-L1494
wxWidgets/wxPython-Classic
19571e1ae65f1ac445f5491474121998c97a1bf0
src/gtk/_controls.py
python
PickerBase.IsTextCtrlGrowable
(*args, **kwargs)
return _controls_.PickerBase_IsTextCtrlGrowable(*args, **kwargs)
IsTextCtrlGrowable(self) -> bool
IsTextCtrlGrowable(self) -> bool
[ "IsTextCtrlGrowable", "(", "self", ")", "-", ">", "bool" ]
def IsTextCtrlGrowable(*args, **kwargs): """IsTextCtrlGrowable(self) -> bool""" return _controls_.PickerBase_IsTextCtrlGrowable(*args, **kwargs)
[ "def", "IsTextCtrlGrowable", "(", "*", "args", ",", "*", "*", "kwargs", ")", ":", "return", "_controls_", ".", "PickerBase_IsTextCtrlGrowable", "(", "*", "args", ",", "*", "*", "kwargs", ")" ]
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_controls.py#L6790-L6792