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openvinotoolkit/openvino
|
dedcbeafa8b84cccdc55ca64b8da516682b381c7
|
tools/mo/openvino/tools/mo/middle/passes/infer.py
|
python
|
override_batch
|
(graph: Graph, batch: int)
|
Overrides batch for nodes with 'op' param set to 'Parameter'
Parameters
----------
graph: graph to operate on
batch: user defined integer value to override batch
|
Overrides batch for nodes with 'op' param set to 'Parameter'
Parameters
----------
graph: graph to operate on
batch: user defined integer value to override batch
|
[
"Overrides",
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"operate",
"on",
"batch",
":",
"user",
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"integer",
"value",
"to",
"override",
"batch"
] |
def override_batch(graph: Graph, batch: int):
"""
Overrides batch for nodes with 'op' param set to 'Parameter'
Parameters
----------
graph: graph to operate on
batch: user defined integer value to override batch
"""
if batch is not None:
in_nodes = graph.get_op_nodes(op='Parameter')
for node in in_nodes:
if not node.soft_get('fixed_batch', False):
name = node.soft_get('name', node.id)
idx, has_layout = get_dim_from_layout(node, 'N')
if has_layout:
if idx is not None:
node['shape'][idx] = batch
else:
log.warning(
'Layout for input {} doesn\'t have batch dimension. Skipping this input.'.format(name))
else:
validate_batch_in_shape(node['shape'], name)
node['shape'][0] = batch
|
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https://github.com/openvinotoolkit/openvino/blob/dedcbeafa8b84cccdc55ca64b8da516682b381c7/tools/mo/openvino/tools/mo/middle/passes/infer.py#L216-L238
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/targets/arrayobj.py
|
python
|
_do_concatenate
|
(context, builder, axis,
arrtys, arrs, arr_shapes, arr_strides,
retty, ret_shapes)
|
return ret
|
Concatenate arrays along the given axis.
|
Concatenate arrays along the given axis.
|
[
"Concatenate",
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"along",
"the",
"given",
"axis",
"."
] |
def _do_concatenate(context, builder, axis,
arrtys, arrs, arr_shapes, arr_strides,
retty, ret_shapes):
"""
Concatenate arrays along the given axis.
"""
assert len(arrtys) == len(arrs) == len(arr_shapes) == len(arr_strides)
zero = cgutils.intp_t(0)
# Allocate return array
ret = _empty_nd_impl(context, builder, retty, ret_shapes)
ret_strides = cgutils.unpack_tuple(builder, ret.strides)
# Compute the offset by which to bump the destination pointer
# after copying each input array.
# Morally, we need to copy each input array at different start indices
# into the destination array; bumping the destination pointer
# is simply easier than offsetting all destination indices.
copy_offsets = []
for arr_sh in arr_shapes:
# offset = ret_strides[axis] * input_shape[axis]
offset = zero
for dim, (size, stride) in enumerate(zip(arr_sh, ret_strides)):
is_axis = builder.icmp_signed('==', axis.type(dim), axis)
addend = builder.mul(size, stride)
offset = builder.select(is_axis,
builder.add(offset, addend),
offset)
copy_offsets.append(offset)
# Copy input arrays into the return array
ret_data = ret.data
for arrty, arr, arr_sh, arr_st, offset in zip(arrtys, arrs, arr_shapes,
arr_strides, copy_offsets):
arr_data = arr.data
# Do the copy loop
# Note the loop nesting is optimized for the destination layout
loop_nest = cgutils.loop_nest(builder, arr_sh, cgutils.intp_t,
order=retty.layout)
with loop_nest as indices:
src_ptr = cgutils.get_item_pointer2(context, builder, arr_data,
arr_sh, arr_st,
arrty.layout, indices)
val = load_item(context, builder, arrty, src_ptr)
val = context.cast(builder, val, arrty.dtype, retty.dtype)
dest_ptr = cgutils.get_item_pointer2(context, builder, ret_data,
ret_shapes, ret_strides,
retty.layout, indices)
store_item(context, builder, retty, val, dest_ptr)
# Bump destination pointer
ret_data = cgutils.pointer_add(builder, ret_data, offset)
return ret
|
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] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/targets/arrayobj.py#L4519-L4577
|
|
apiaryio/snowcrash
|
b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3
|
tools/gyp/pylib/gyp/generator/analyzer.py
|
python
|
CalculateVariables
|
(default_variables, params)
|
Calculate additional variables for use in the build (called by gyp).
|
Calculate additional variables for use in the build (called by gyp).
|
[
"Calculate",
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"variables",
"for",
"use",
"in",
"the",
"build",
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"called",
"by",
"gyp",
")",
"."
] |
def CalculateVariables(default_variables, params):
"""Calculate additional variables for use in the build (called by gyp)."""
flavor = gyp.common.GetFlavor(params)
if flavor == 'mac':
default_variables.setdefault('OS', 'mac')
elif flavor == 'win':
default_variables.setdefault('OS', 'win')
# Copy additional generator configuration data from VS, which is shared
# by the Windows Ninja generator.
import gyp.generator.msvs as msvs_generator
generator_additional_non_configuration_keys = getattr(msvs_generator,
'generator_additional_non_configuration_keys', [])
generator_additional_path_sections = getattr(msvs_generator,
'generator_additional_path_sections', [])
gyp.msvs_emulation.CalculateCommonVariables(default_variables, params)
else:
operating_system = flavor
if flavor == 'android':
operating_system = 'linux' # Keep this legacy behavior for now.
default_variables.setdefault('OS', operating_system)
|
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https://github.com/apiaryio/snowcrash/blob/b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3/tools/gyp/pylib/gyp/generator/analyzer.py#L575-L595
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/_windows.py
|
python
|
PageSetupDialog.ShowModal
|
(*args, **kwargs)
|
return _windows_.PageSetupDialog_ShowModal(*args, **kwargs)
|
ShowModal(self) -> int
|
ShowModal(self) -> int
|
[
"ShowModal",
"(",
"self",
")",
"-",
">",
"int"
] |
def ShowModal(*args, **kwargs):
"""ShowModal(self) -> int"""
return _windows_.PageSetupDialog_ShowModal(*args, **kwargs)
|
[
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"PageSetupDialog_ShowModal",
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"*",
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",",
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] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/_windows.py#L5020-L5022
|
|
pmq20/node-packer
|
12c46c6e44fbc14d9ee645ebd17d5296b324f7e0
|
lts/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/msvs.py
|
python
|
_GenerateMSVSProject
|
(project, options, version, generator_flags)
|
return missing_sources
|
Generates a .vcproj file. It may create .rules and .user files too.
Arguments:
project: The project object we will generate the file for.
options: Global options passed to the generator.
version: The VisualStudioVersion object.
generator_flags: dict of generator-specific flags.
|
Generates a .vcproj file. It may create .rules and .user files too.
|
[
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"may",
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"files",
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"."
] |
def _GenerateMSVSProject(project, options, version, generator_flags):
"""Generates a .vcproj file. It may create .rules and .user files too.
Arguments:
project: The project object we will generate the file for.
options: Global options passed to the generator.
version: The VisualStudioVersion object.
generator_flags: dict of generator-specific flags.
"""
spec = project.spec
gyp.common.EnsureDirExists(project.path)
platforms = _GetUniquePlatforms(spec)
p = MSVSProject.Writer(project.path, version, spec['target_name'],
project.guid, platforms)
# Get directory project file is in.
project_dir = os.path.split(project.path)[0]
gyp_path = _NormalizedSource(project.build_file)
relative_path_of_gyp_file = gyp.common.RelativePath(gyp_path, project_dir)
config_type = _GetMSVSConfigurationType(spec, project.build_file)
for config_name, config in spec['configurations'].items():
_AddConfigurationToMSVSProject(p, spec, config_type, config_name, config)
# MSVC08 and prior version cannot handle duplicate basenames in the same
# target.
# TODO: Take excluded sources into consideration if possible.
_ValidateSourcesForMSVSProject(spec, version)
# Prepare list of sources and excluded sources.
gyp_file = os.path.split(project.build_file)[1]
sources, excluded_sources = _PrepareListOfSources(spec, generator_flags,
gyp_file)
# Add rules.
actions_to_add = {}
_GenerateRulesForMSVS(p, project_dir, options, spec,
sources, excluded_sources,
actions_to_add)
list_excluded = generator_flags.get('msvs_list_excluded_files', True)
sources, excluded_sources, excluded_idl = (
_AdjustSourcesAndConvertToFilterHierarchy(spec, options, project_dir,
sources, excluded_sources,
list_excluded, version))
# Add in files.
missing_sources = _VerifySourcesExist(sources, project_dir)
p.AddFiles(sources)
_AddToolFilesToMSVS(p, spec)
_HandlePreCompiledHeaders(p, sources, spec)
_AddActions(actions_to_add, spec, relative_path_of_gyp_file)
_AddCopies(actions_to_add, spec)
_WriteMSVSUserFile(project.path, version, spec)
# NOTE: this stanza must appear after all actions have been decided.
# Don't excluded sources with actions attached, or they won't run.
excluded_sources = _FilterActionsFromExcluded(
excluded_sources, actions_to_add)
_ExcludeFilesFromBeingBuilt(p, spec, excluded_sources, excluded_idl,
list_excluded)
_AddAccumulatedActionsToMSVS(p, spec, actions_to_add)
# Write it out.
p.WriteIfChanged()
return missing_sources
|
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"_HandlePreCompiledHeaders",
"(",
"p",
",",
"sources",
",",
"spec",
")",
"_AddActions",
"(",
"actions_to_add",
",",
"spec",
",",
"relative_path_of_gyp_file",
")",
"_AddCopies",
"(",
"actions_to_add",
",",
"spec",
")",
"_WriteMSVSUserFile",
"(",
"project",
".",
"path",
",",
"version",
",",
"spec",
")",
"# NOTE: this stanza must appear after all actions have been decided.",
"# Don't excluded sources with actions attached, or they won't run.",
"excluded_sources",
"=",
"_FilterActionsFromExcluded",
"(",
"excluded_sources",
",",
"actions_to_add",
")",
"_ExcludeFilesFromBeingBuilt",
"(",
"p",
",",
"spec",
",",
"excluded_sources",
",",
"excluded_idl",
",",
"list_excluded",
")",
"_AddAccumulatedActionsToMSVS",
"(",
"p",
",",
"spec",
",",
"actions_to_add",
")",
"# Write it out.",
"p",
".",
"WriteIfChanged",
"(",
")",
"return",
"missing_sources"
] |
https://github.com/pmq20/node-packer/blob/12c46c6e44fbc14d9ee645ebd17d5296b324f7e0/lts/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/msvs.py#L991-L1058
|
|
keyboardio/Kaleidoscope
|
d59604e98b2439d108647f15be52984a6837d360
|
bin/cpplint.py
|
python
|
_SetCountingStyle
|
(level)
|
Sets the module's counting options.
|
Sets the module's counting options.
|
[
"Sets",
"the",
"module",
"s",
"counting",
"options",
"."
] |
def _SetCountingStyle(level):
"""Sets the module's counting options."""
_cpplint_state.SetCountingStyle(level)
|
[
"def",
"_SetCountingStyle",
"(",
"level",
")",
":",
"_cpplint_state",
".",
"SetCountingStyle",
"(",
"level",
")"
] |
https://github.com/keyboardio/Kaleidoscope/blob/d59604e98b2439d108647f15be52984a6837d360/bin/cpplint.py#L1190-L1192
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/lib/masked/numctrl.py
|
python
|
NumCtrl.GetLimitOnFieldChange
|
(self)
|
return self.IsLimitedOnFieldChange()
|
(For regularization of property accessors)
|
(For regularization of property accessors)
|
[
"(",
"For",
"regularization",
"of",
"property",
"accessors",
")"
] |
def GetLimitOnFieldChange(self):
""" (For regularization of property accessors) """
return self.IsLimitedOnFieldChange()
|
[
"def",
"GetLimitOnFieldChange",
"(",
"self",
")",
":",
"return",
"self",
".",
"IsLimitedOnFieldChange",
"(",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/masked/numctrl.py#L1455-L1457
|
|
mindspore-ai/mindspore
|
fb8fd3338605bb34fa5cea054e535a8b1d753fab
|
mindspore/python/mindspore/train/model.py
|
python
|
Model.predict
|
(self, *predict_data)
|
return result
|
Generate output predictions for the input samples.
Args:
predict_data (Optional[Tensor, list[Tensor], tuple[Tensor]]): The predict data, can be a single tensor,
a list of tensor, or a tuple of tensor.
Returns:
Tensor, array(s) of predictions.
Examples:
>>> import mindspore as ms
>>> from mindspore import Model, Tensor
>>>
>>> input_data = Tensor(np.random.randint(0, 255, [1, 1, 32, 32]), ms.float32)
>>> model = Model(Net())
>>> result = model.predict(input_data)
|
Generate output predictions for the input samples.
|
[
"Generate",
"output",
"predictions",
"for",
"the",
"input",
"samples",
"."
] |
def predict(self, *predict_data):
"""
Generate output predictions for the input samples.
Args:
predict_data (Optional[Tensor, list[Tensor], tuple[Tensor]]): The predict data, can be a single tensor,
a list of tensor, or a tuple of tensor.
Returns:
Tensor, array(s) of predictions.
Examples:
>>> import mindspore as ms
>>> from mindspore import Model, Tensor
>>>
>>> input_data = Tensor(np.random.randint(0, 255, [1, 1, 32, 32]), ms.float32)
>>> model = Model(Net())
>>> result = model.predict(input_data)
"""
self._predict_network.set_train(False)
check_input_data(*predict_data, data_class=(int, float, str, None, Tensor))
_parallel_predict_check()
result = self._predict_network(*predict_data)
check_output_data(result)
return result
|
[
"def",
"predict",
"(",
"self",
",",
"*",
"predict_data",
")",
":",
"self",
".",
"_predict_network",
".",
"set_train",
"(",
"False",
")",
"check_input_data",
"(",
"*",
"predict_data",
",",
"data_class",
"=",
"(",
"int",
",",
"float",
",",
"str",
",",
"None",
",",
"Tensor",
")",
")",
"_parallel_predict_check",
"(",
")",
"result",
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"_predict_network",
"(",
"*",
"predict_data",
")",
"check_output_data",
"(",
"result",
")",
"return",
"result"
] |
https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/train/model.py#L987-L1012
|
|
hpi-xnor/BMXNet
|
ed0b201da6667887222b8e4b5f997c4f6b61943d
|
python/mxnet/ndarray/ndarray.py
|
python
|
NDArray.degrees
|
(self, *args, **kwargs)
|
return op.degrees(self, *args, **kwargs)
|
Convenience fluent method for :py:func:`degrees`.
The arguments are the same as for :py:func:`degrees`, with
this array as data.
|
Convenience fluent method for :py:func:`degrees`.
|
[
"Convenience",
"fluent",
"method",
"for",
":",
"py",
":",
"func",
":",
"degrees",
"."
] |
def degrees(self, *args, **kwargs):
"""Convenience fluent method for :py:func:`degrees`.
The arguments are the same as for :py:func:`degrees`, with
this array as data.
"""
return op.degrees(self, *args, **kwargs)
|
[
"def",
"degrees",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"op",
".",
"degrees",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/hpi-xnor/BMXNet/blob/ed0b201da6667887222b8e4b5f997c4f6b61943d/python/mxnet/ndarray/ndarray.py#L1356-L1362
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/stc.py
|
python
|
StyledTextCtrl.SetVScrollBar
|
(*args, **kwargs)
|
return _stc.StyledTextCtrl_SetVScrollBar(*args, **kwargs)
|
SetVScrollBar(self, ScrollBar bar)
Set the vertical scrollbar to use instead of the one that's built-in.
|
SetVScrollBar(self, ScrollBar bar)
|
[
"SetVScrollBar",
"(",
"self",
"ScrollBar",
"bar",
")"
] |
def SetVScrollBar(*args, **kwargs):
"""
SetVScrollBar(self, ScrollBar bar)
Set the vertical scrollbar to use instead of the one that's built-in.
"""
return _stc.StyledTextCtrl_SetVScrollBar(*args, **kwargs)
|
[
"def",
"SetVScrollBar",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_stc",
".",
"StyledTextCtrl_SetVScrollBar",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/stc.py#L6629-L6635
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_vendor/requests/_internal_utils.py
|
python
|
unicode_is_ascii
|
(u_string)
|
Determine if unicode string only contains ASCII characters.
:param str u_string: unicode string to check. Must be unicode
and not Python 2 `str`.
:rtype: bool
|
Determine if unicode string only contains ASCII characters.
|
[
"Determine",
"if",
"unicode",
"string",
"only",
"contains",
"ASCII",
"characters",
"."
] |
def unicode_is_ascii(u_string):
"""Determine if unicode string only contains ASCII characters.
:param str u_string: unicode string to check. Must be unicode
and not Python 2 `str`.
:rtype: bool
"""
assert isinstance(u_string, str)
try:
u_string.encode('ascii')
return True
except UnicodeEncodeError:
return False
|
[
"def",
"unicode_is_ascii",
"(",
"u_string",
")",
":",
"assert",
"isinstance",
"(",
"u_string",
",",
"str",
")",
"try",
":",
"u_string",
".",
"encode",
"(",
"'ascii'",
")",
"return",
"True",
"except",
"UnicodeEncodeError",
":",
"return",
"False"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_vendor/requests/_internal_utils.py#L30-L42
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/types/containers.py
|
python
|
UniTuple.unify
|
(self, typingctx, other)
|
Unify UniTuples with their dtype
|
Unify UniTuples with their dtype
|
[
"Unify",
"UniTuples",
"with",
"their",
"dtype"
] |
def unify(self, typingctx, other):
"""
Unify UniTuples with their dtype
"""
if isinstance(other, UniTuple) and len(self) == len(other):
dtype = typingctx.unify_pairs(self.dtype, other.dtype)
if dtype is not None:
return UniTuple(dtype=dtype, count=self.count)
|
[
"def",
"unify",
"(",
"self",
",",
"typingctx",
",",
"other",
")",
":",
"if",
"isinstance",
"(",
"other",
",",
"UniTuple",
")",
"and",
"len",
"(",
"self",
")",
"==",
"len",
"(",
"other",
")",
":",
"dtype",
"=",
"typingctx",
".",
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"(",
"self",
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"dtype",
",",
"other",
".",
"dtype",
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"if",
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"UniTuple",
"(",
"dtype",
"=",
"dtype",
",",
"count",
"=",
"self",
".",
"count",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/types/containers.py#L218-L225
|
||
freeorion/freeorion
|
c266a40eccd3a99a17de8fe57c36ef6ba3771665
|
default/python/AI/savegame_codec/_decoder.py
|
python
|
_replace_quote_placeholders
|
(s)
|
return s
|
Replace PLACEHOLDER with quotes if not nested within another encoded container.
To be able to use tuples as dictionary keys, to use standard json decoder,
the entire tuple with its content must be encoded as a single string.
The inner objects may no longer be quoted as that would prematurely terminate
the strings. Inner quotes are therefore replaced with the PLACEHOLDER char.
Example:
output = encode(tuple(["1", "string"]))
"__TUPLE__([$1$, $string$])"
To be able to decode the inner content, the PLACEHOLDER must be converted
to quotes again.
|
Replace PLACEHOLDER with quotes if not nested within another encoded container.
|
[
"Replace",
"PLACEHOLDER",
"with",
"quotes",
"if",
"not",
"nested",
"within",
"another",
"encoded",
"container",
"."
] |
def _replace_quote_placeholders(s):
"""Replace PLACEHOLDER with quotes if not nested within another encoded container.
To be able to use tuples as dictionary keys, to use standard json decoder,
the entire tuple with its content must be encoded as a single string.
The inner objects may no longer be quoted as that would prematurely terminate
the strings. Inner quotes are therefore replaced with the PLACEHOLDER char.
Example:
output = encode(tuple(["1", "string"]))
"__TUPLE__([$1$, $string$])"
To be able to decode the inner content, the PLACEHOLDER must be converted
to quotes again.
"""
n = 0 # counts nesting level (i.e. number of opened but not closed parentheses)
start = 0 # starting point for string replacement
for i in range(len(s)):
if s[i] == "(":
# if this is an outer opening parenthesis, then replace placeholder from last parenthesis to here
if n == 0:
s = s[:start] + s[start:i].replace(PLACEHOLDER, '"') + s[i:]
n += 1
elif s[i] == ")":
n -= 1
if n == 0:
start = i
s = s[:start] + s[start:].replace(PLACEHOLDER, '"')
return s
|
[
"def",
"_replace_quote_placeholders",
"(",
"s",
")",
":",
"n",
"=",
"0",
"# counts nesting level (i.e. number of opened but not closed parentheses)",
"start",
"=",
"0",
"# starting point for string replacement",
"for",
"i",
"in",
"range",
"(",
"len",
"(",
"s",
")",
")",
":",
"if",
"s",
"[",
"i",
"]",
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"# if this is an outer opening parenthesis, then replace placeholder from last parenthesis to here",
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"0",
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"s",
"=",
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"[",
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",",
"'\"'",
")",
"+",
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"[",
"i",
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"[",
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"[",
"start",
":",
"]",
".",
"replace",
"(",
"PLACEHOLDER",
",",
"'\"'",
")",
"return",
"s"
] |
https://github.com/freeorion/freeorion/blob/c266a40eccd3a99a17de8fe57c36ef6ba3771665/default/python/AI/savegame_codec/_decoder.py#L192-L220
|
|
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/checkpoint/python/python_state.py
|
python
|
NumpyState.__getattribute__
|
(self, name)
|
return value
|
Un-wrap `_NumpyWrapper` objects when accessing attributes.
|
Un-wrap `_NumpyWrapper` objects when accessing attributes.
|
[
"Un",
"-",
"wrap",
"_NumpyWrapper",
"objects",
"when",
"accessing",
"attributes",
"."
] |
def __getattribute__(self, name):
"""Un-wrap `_NumpyWrapper` objects when accessing attributes."""
value = super(NumpyState, self).__getattribute__(name)
if isinstance(value, _NumpyWrapper):
return value.array
return value
|
[
"def",
"__getattribute__",
"(",
"self",
",",
"name",
")",
":",
"value",
"=",
"super",
"(",
"NumpyState",
",",
"self",
")",
".",
"__getattribute__",
"(",
"name",
")",
"if",
"isinstance",
"(",
"value",
",",
"_NumpyWrapper",
")",
":",
"return",
"value",
".",
"array",
"return",
"value"
] |
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/checkpoint/python/python_state.py#L91-L96
|
|
ChromiumWebApps/chromium
|
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
|
remoting/tools/build/remoting_copy_locales.py
|
python
|
repack_locales
|
(locales)
|
Loop over and repack the given locales.
|
Loop over and repack the given locales.
|
[
"Loop",
"over",
"and",
"repack",
"the",
"given",
"locales",
"."
] |
def repack_locales(locales):
""" Loop over and repack the given locales."""
for locale in locales:
inputs = calc_inputs(locale)
output = calc_output(locale)
data_pack.DataPack.RePack(output, inputs)
|
[
"def",
"repack_locales",
"(",
"locales",
")",
":",
"for",
"locale",
"in",
"locales",
":",
"inputs",
"=",
"calc_inputs",
"(",
"locale",
")",
"output",
"=",
"calc_output",
"(",
"locale",
")",
"data_pack",
".",
"DataPack",
".",
"RePack",
"(",
"output",
",",
"inputs",
")"
] |
https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/remoting/tools/build/remoting_copy_locales.py#L90-L95
|
||
goldeneye-source/ges-code
|
2630cd8ef3d015af53c72ec2e19fc1f7e7fe8d9d
|
thirdparty/protobuf-2.3.0/python/google/protobuf/internal/containers.py
|
python
|
BaseContainer.__init__
|
(self, message_listener)
|
Args:
message_listener: A MessageListener implementation.
The RepeatedScalarFieldContainer will call this object's
Modified() method when it is modified.
|
Args:
message_listener: A MessageListener implementation.
The RepeatedScalarFieldContainer will call this object's
Modified() method when it is modified.
|
[
"Args",
":",
"message_listener",
":",
"A",
"MessageListener",
"implementation",
".",
"The",
"RepeatedScalarFieldContainer",
"will",
"call",
"this",
"object",
"s",
"Modified",
"()",
"method",
"when",
"it",
"is",
"modified",
"."
] |
def __init__(self, message_listener):
"""
Args:
message_listener: A MessageListener implementation.
The RepeatedScalarFieldContainer will call this object's
Modified() method when it is modified.
"""
self._message_listener = message_listener
self._values = []
|
[
"def",
"__init__",
"(",
"self",
",",
"message_listener",
")",
":",
"self",
".",
"_message_listener",
"=",
"message_listener",
"self",
".",
"_values",
"=",
"[",
"]"
] |
https://github.com/goldeneye-source/ges-code/blob/2630cd8ef3d015af53c72ec2e19fc1f7e7fe8d9d/thirdparty/protobuf-2.3.0/python/google/protobuf/internal/containers.py#L52-L60
|
||
gemrb/gemrb
|
730206eed8d1dd358ca5e69a62f9e099aa22ffc6
|
gemrb/GUIScripts/bg2/LUHLASelection.py
|
python
|
HLAMarkButton
|
(i, select)
|
return
|
Enables, disables, or highlights the given button.
If select is true, the button is highlighted.
|
Enables, disables, or highlights the given button.
|
[
"Enables",
"disables",
"or",
"highlights",
"the",
"given",
"button",
"."
] |
def HLAMarkButton (i, select):
"""Enables, disables, or highlights the given button.
If select is true, the button is highlighted."""
j = ( GemRB.GetVar("HLATopIndex") + 1 ) * 5 - 5
if select:
state = IE_GUI_BUTTON_SELECTED
else:
if HLAAbilities[i][1]:
state = IE_GUI_BUTTON_ENABLED
else: # can't learn
state = IE_GUI_BUTTON_LOCKED
# we have to use the index on the actual grid
SpellButton = HLAWindow.GetControl(i-j)
SpellButton.SetState(state)
return
|
[
"def",
"HLAMarkButton",
"(",
"i",
",",
"select",
")",
":",
"j",
"=",
"(",
"GemRB",
".",
"GetVar",
"(",
"\"HLATopIndex\"",
")",
"+",
"1",
")",
"*",
"5",
"-",
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"state",
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"IE_GUI_BUTTON_SELECTED",
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"HLAAbilities",
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"SpellButton",
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"(",
"i",
"-",
"j",
")",
"SpellButton",
".",
"SetState",
"(",
"state",
")",
"return"
] |
https://github.com/gemrb/gemrb/blob/730206eed8d1dd358ca5e69a62f9e099aa22ffc6/gemrb/GUIScripts/bg2/LUHLASelection.py#L270-L288
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/os.py
|
python
|
getenv
|
(key, default=None)
|
return environ.get(key, default)
|
Get an environment variable, return None if it doesn't exist.
The optional second argument can specify an alternate default.
key, default and the result are str.
|
Get an environment variable, return None if it doesn't exist.
The optional second argument can specify an alternate default.
key, default and the result are str.
|
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def getenv(key, default=None):
"""Get an environment variable, return None if it doesn't exist.
The optional second argument can specify an alternate default.
key, default and the result are str."""
return environ.get(key, default)
|
[
"def",
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"get",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/os.py#L772-L776
|
|
panda3d/panda3d
|
833ad89ebad58395d0af0b7ec08538e5e4308265
|
contrib/src/sceneeditor/seMopathRecorder.py
|
python
|
namePathPanel.onDestroy
|
(self, event)
|
If you have open any thing, please rewrite here!
|
If you have open any thing, please rewrite here!
|
[
"If",
"you",
"have",
"open",
"any",
"thing",
"please",
"rewrite",
"here!"
] |
def onDestroy(self, event):
'''
If you have open any thing, please rewrite here!
'''
pass
|
[
"def",
"onDestroy",
"(",
"self",
",",
"event",
")",
":",
"pass"
] |
https://github.com/panda3d/panda3d/blob/833ad89ebad58395d0af0b7ec08538e5e4308265/contrib/src/sceneeditor/seMopathRecorder.py#L2063-L2067
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/tools/Editra/src/extern/aui/auibook.py
|
python
|
AuiTabContainer.SetAGWFlags
|
(self, agwFlags)
|
Sets the tab art flags.
:param integer `agwFlags`: a combination of the following values:
==================================== ==================================
Flag name Description
==================================== ==================================
``AUI_NB_TOP`` With this style, tabs are drawn along the top of the notebook
``AUI_NB_LEFT`` With this style, tabs are drawn along the left of the notebook. Not implemented yet
``AUI_NB_RIGHT`` With this style, tabs are drawn along the right of the notebook. Not implemented yet
``AUI_NB_BOTTOM`` With this style, tabs are drawn along the bottom of the notebook
``AUI_NB_TAB_SPLIT`` Allows the tab control to be split by dragging a tab
``AUI_NB_TAB_MOVE`` Allows a tab to be moved horizontally by dragging
``AUI_NB_TAB_EXTERNAL_MOVE`` Allows a tab to be moved to another tab control
``AUI_NB_TAB_FIXED_WIDTH`` With this style, all tabs have the same width
``AUI_NB_SCROLL_BUTTONS`` With this style, left and right scroll buttons are displayed
``AUI_NB_WINDOWLIST_BUTTON`` With this style, a drop-down list of windows is available
``AUI_NB_CLOSE_BUTTON`` With this style, a close button is available on the tab bar
``AUI_NB_CLOSE_ON_ACTIVE_TAB`` With this style, a close button is available on the active tab
``AUI_NB_CLOSE_ON_ALL_TABS`` With this style, a close button is available on all tabs
``AUI_NB_MIDDLE_CLICK_CLOSE`` Allows to close :class:`AuiNotebook` tabs by mouse middle button click
``AUI_NB_SUB_NOTEBOOK`` This style is used by :class:`~lib.agw.aui.framemanager.AuiManager` to create automatic AuiNotebooks
``AUI_NB_HIDE_ON_SINGLE_TAB`` Hides the tab window if only one tab is present
``AUI_NB_SMART_TABS`` Use Smart Tabbing, like ``Alt`` + ``Tab`` on Windows
``AUI_NB_USE_IMAGES_DROPDOWN`` Uses images on dropdown window list menu instead of check items
``AUI_NB_CLOSE_ON_TAB_LEFT`` Draws the tab close button on the left instead of on the right (a la Camino browser)
``AUI_NB_TAB_FLOAT`` Allows the floating of single tabs. Known limitation: when the notebook is more or less full screen,
tabs cannot be dragged far enough outside of the notebook to become floating pages
``AUI_NB_DRAW_DND_TAB`` Draws an image representation of a tab while dragging (on by default)
``AUI_NB_ORDER_BY_ACCESS`` Tab navigation order by last access time for the tabs
``AUI_NB_NO_TAB_FOCUS`` Don't draw tab focus rectangle
==================================== ==================================
.. todo:: Implementation of flags ``AUI_NB_RIGHT`` and ``AUI_NB_LEFT``.
|
Sets the tab art flags.
|
[
"Sets",
"the",
"tab",
"art",
"flags",
"."
] |
def SetAGWFlags(self, agwFlags):
"""
Sets the tab art flags.
:param integer `agwFlags`: a combination of the following values:
==================================== ==================================
Flag name Description
==================================== ==================================
``AUI_NB_TOP`` With this style, tabs are drawn along the top of the notebook
``AUI_NB_LEFT`` With this style, tabs are drawn along the left of the notebook. Not implemented yet
``AUI_NB_RIGHT`` With this style, tabs are drawn along the right of the notebook. Not implemented yet
``AUI_NB_BOTTOM`` With this style, tabs are drawn along the bottom of the notebook
``AUI_NB_TAB_SPLIT`` Allows the tab control to be split by dragging a tab
``AUI_NB_TAB_MOVE`` Allows a tab to be moved horizontally by dragging
``AUI_NB_TAB_EXTERNAL_MOVE`` Allows a tab to be moved to another tab control
``AUI_NB_TAB_FIXED_WIDTH`` With this style, all tabs have the same width
``AUI_NB_SCROLL_BUTTONS`` With this style, left and right scroll buttons are displayed
``AUI_NB_WINDOWLIST_BUTTON`` With this style, a drop-down list of windows is available
``AUI_NB_CLOSE_BUTTON`` With this style, a close button is available on the tab bar
``AUI_NB_CLOSE_ON_ACTIVE_TAB`` With this style, a close button is available on the active tab
``AUI_NB_CLOSE_ON_ALL_TABS`` With this style, a close button is available on all tabs
``AUI_NB_MIDDLE_CLICK_CLOSE`` Allows to close :class:`AuiNotebook` tabs by mouse middle button click
``AUI_NB_SUB_NOTEBOOK`` This style is used by :class:`~lib.agw.aui.framemanager.AuiManager` to create automatic AuiNotebooks
``AUI_NB_HIDE_ON_SINGLE_TAB`` Hides the tab window if only one tab is present
``AUI_NB_SMART_TABS`` Use Smart Tabbing, like ``Alt`` + ``Tab`` on Windows
``AUI_NB_USE_IMAGES_DROPDOWN`` Uses images on dropdown window list menu instead of check items
``AUI_NB_CLOSE_ON_TAB_LEFT`` Draws the tab close button on the left instead of on the right (a la Camino browser)
``AUI_NB_TAB_FLOAT`` Allows the floating of single tabs. Known limitation: when the notebook is more or less full screen,
tabs cannot be dragged far enough outside of the notebook to become floating pages
``AUI_NB_DRAW_DND_TAB`` Draws an image representation of a tab while dragging (on by default)
``AUI_NB_ORDER_BY_ACCESS`` Tab navigation order by last access time for the tabs
``AUI_NB_NO_TAB_FOCUS`` Don't draw tab focus rectangle
==================================== ==================================
.. todo:: Implementation of flags ``AUI_NB_RIGHT`` and ``AUI_NB_LEFT``.
"""
self._agwFlags = agwFlags
# check for new close button settings
self.RemoveButton(AUI_BUTTON_LEFT)
self.RemoveButton(AUI_BUTTON_RIGHT)
self.RemoveButton(AUI_BUTTON_WINDOWLIST)
self.RemoveButton(AUI_BUTTON_CLOSE)
if agwFlags & AUI_NB_SCROLL_BUTTONS:
self.AddButton(AUI_BUTTON_LEFT, wx.LEFT)
self.AddButton(AUI_BUTTON_RIGHT, wx.RIGHT)
if agwFlags & AUI_NB_WINDOWLIST_BUTTON:
self.AddButton(AUI_BUTTON_WINDOWLIST, wx.RIGHT)
if agwFlags & AUI_NB_CLOSE_BUTTON:
self.AddButton(AUI_BUTTON_CLOSE, wx.RIGHT)
if self._art:
self._art.SetAGWFlags(self._agwFlags)
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/tools/Editra/src/extern/aui/auibook.py#L880-L938
|
||
apache/thrift
|
0b29261a4f3c6882ef3b09aae47914f0012b0472
|
lib/py/src/server/TNonblockingServer.py
|
python
|
Connection.fileno
|
(self)
|
return self.socket.fileno()
|
Returns the file descriptor of the associated socket.
|
Returns the file descriptor of the associated socket.
|
[
"Returns",
"the",
"file",
"descriptor",
"of",
"the",
"associated",
"socket",
"."
] |
def fileno(self):
"""Returns the file descriptor of the associated socket."""
return self.socket.fileno()
|
[
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"fileno",
"(",
"self",
")",
":",
"return",
"self",
".",
"socket",
".",
"fileno",
"(",
")"
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https://github.com/apache/thrift/blob/0b29261a4f3c6882ef3b09aae47914f0012b0472/lib/py/src/server/TNonblockingServer.py#L223-L225
|
|
ceph/ceph
|
959663007321a369c83218414a29bd9dbc8bda3a
|
src/pybind/mgr/dashboard/controllers/_permissions.py
|
python
|
CreatePermission
|
(func)
|
return func
|
:raises PermissionNotValid: If the permission is missing.
|
:raises PermissionNotValid: If the permission is missing.
|
[
":",
"raises",
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":",
"If",
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"permission",
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"missing",
"."
] |
def CreatePermission(func): # noqa: N802
"""
:raises PermissionNotValid: If the permission is missing.
"""
_set_func_permissions(func, Permission.CREATE)
return func
|
[
"def",
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"# noqa: N802",
"_set_func_permissions",
"(",
"func",
",",
"Permission",
".",
"CREATE",
")",
"return",
"func"
] |
https://github.com/ceph/ceph/blob/959663007321a369c83218414a29bd9dbc8bda3a/src/pybind/mgr/dashboard/controllers/_permissions.py#L39-L44
|
|
devsisters/libquic
|
8954789a056d8e7d5fcb6452fd1572ca57eb5c4e
|
src/third_party/protobuf/python/google/protobuf/internal/python_message.py
|
python
|
_AddHasExtensionMethod
|
(cls)
|
Helper for _AddMessageMethods().
|
Helper for _AddMessageMethods().
|
[
"Helper",
"for",
"_AddMessageMethods",
"()",
"."
] |
def _AddHasExtensionMethod(cls):
"""Helper for _AddMessageMethods()."""
def HasExtension(self, extension_handle):
_VerifyExtensionHandle(self, extension_handle)
if extension_handle.label == _FieldDescriptor.LABEL_REPEATED:
raise KeyError('"%s" is repeated.' % extension_handle.full_name)
if extension_handle.cpp_type == _FieldDescriptor.CPPTYPE_MESSAGE:
value = self._fields.get(extension_handle)
return value is not None and value._is_present_in_parent
else:
return extension_handle in self._fields
cls.HasExtension = HasExtension
|
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https://github.com/devsisters/libquic/blob/8954789a056d8e7d5fcb6452fd1572ca57eb5c4e/src/third_party/protobuf/python/google/protobuf/internal/python_message.py#L902-L914
|
||
hfinkel/llvm-project-cxxjit
|
91084ef018240bbb8e24235ff5cd8c355a9c1a1e
|
lldb/utils/lui/lldbutil.py
|
python
|
which
|
(program)
|
return None
|
Returns the full path to a program; None otherwise.
|
Returns the full path to a program; None otherwise.
|
[
"Returns",
"the",
"full",
"path",
"to",
"a",
"program",
";",
"None",
"otherwise",
"."
] |
def which(program):
"""Returns the full path to a program; None otherwise."""
fpath, fname = os.path.split(program)
if fpath:
if is_exe(program):
return program
else:
for path in os.environ["PATH"].split(os.pathsep):
exe_file = os.path.join(path, program)
if is_exe(exe_file):
return exe_file
return None
|
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https://github.com/hfinkel/llvm-project-cxxjit/blob/91084ef018240bbb8e24235ff5cd8c355a9c1a1e/lldb/utils/lui/lldbutil.py#L30-L41
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/cuda/api.py
|
python
|
event
|
(timing=True)
|
return evt
|
Create a CUDA event. Timing data is only recorded by the event if it is
created with ``timing=True``.
|
Create a CUDA event. Timing data is only recorded by the event if it is
created with ``timing=True``.
|
[
"Create",
"a",
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"event",
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"Timing",
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"True",
"."
] |
def event(timing=True):
"""
Create a CUDA event. Timing data is only recorded by the event if it is
created with ``timing=True``.
"""
evt = current_context().create_event(timing=timing)
return evt
|
[
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"(",
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")",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/cuda/api.py#L317-L323
|
|
Kitware/VTK
|
5b4df4d90a4f31194d97d3c639dd38ea8f81e8b8
|
Wrapping/Python/vtkmodules/tk/vtkTkRenderWidget.py
|
python
|
vtkTkRenderWidget.BindTkRenderWidget
|
(self)
|
Bind some default actions.
|
Bind some default actions.
|
[
"Bind",
"some",
"default",
"actions",
"."
] |
def BindTkRenderWidget(self):
"""
Bind some default actions.
"""
self.bind("<ButtonPress>",
lambda e,s=self: s.StartMotion(e.x,e.y))
self.bind("<ButtonRelease>",
lambda e,s=self: s.EndMotion(e.x,e.y))
self.bind("<B1-Motion>",
lambda e,s=self: s.Rotate(e.x,e.y))
self.bind("<B2-Motion>",
lambda e,s=self: s.Pan(e.x,e.y))
self.bind("<B3-Motion>",
lambda e,s=self: s.Zoom(e.x,e.y))
self.bind("<Shift-B1-Motion>",
lambda e,s=self: s.Pan(e.x,e.y))
self.bind("<KeyPress-r>",
lambda e,s=self: s.Reset(e.x,e.y))
self.bind("<KeyPress-u>",
lambda e,s=self: s.deiconify())
self.bind("<KeyPress-w>",
lambda e,s=self: s.Wireframe())
self.bind("<KeyPress-s>",
lambda e,s=self: s.Surface())
self.bind("<KeyPress-p>",
lambda e,s=self: s.PickActor(e.x,e.y))
if self._FocusOnEnter:
self.bind("<Enter>",
lambda e,s=self: s.Enter(e.x,e.y))
self.bind("<Leave>",
lambda e,s=self: s.Leave(e.x,e.y))
else:
self.bind("<ButtonPress>",
lambda e,s=self: s.Enter(e.x,e.y))
self.bind("<Expose>",
lambda e,s=self: s.Expose())
|
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https://github.com/Kitware/VTK/blob/5b4df4d90a4f31194d97d3c639dd38ea8f81e8b8/Wrapping/Python/vtkmodules/tk/vtkTkRenderWidget.py#L150-L185
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/_core.py
|
python
|
Window.GetScreenRect
|
(*args, **kwargs)
|
return _core_.Window_GetScreenRect(*args, **kwargs)
|
GetScreenRect(self) -> Rect
Returns the size and position of the window in screen coordinantes as
a `wx.Rect` object.
|
GetScreenRect(self) -> Rect
|
[
"GetScreenRect",
"(",
"self",
")",
"-",
">",
"Rect"
] |
def GetScreenRect(*args, **kwargs):
"""
GetScreenRect(self) -> Rect
Returns the size and position of the window in screen coordinantes as
a `wx.Rect` object.
"""
return _core_.Window_GetScreenRect(*args, **kwargs)
|
[
"def",
"GetScreenRect",
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"Window_GetScreenRect",
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"*",
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"*",
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_core.py#L9492-L9499
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/scipy/scipy/sparse/base.py
|
python
|
spmatrix.count_nonzero
|
(self)
|
Number of non-zero entries, equivalent to
np.count_nonzero(a.toarray())
Unlike getnnz() and the nnz property, which return the number of stored
entries (the length of the data attribute), this method counts the
actual number of non-zero entries in data.
|
Number of non-zero entries, equivalent to
|
[
"Number",
"of",
"non",
"-",
"zero",
"entries",
"equivalent",
"to"
] |
def count_nonzero(self):
"""Number of non-zero entries, equivalent to
np.count_nonzero(a.toarray())
Unlike getnnz() and the nnz property, which return the number of stored
entries (the length of the data attribute), this method counts the
actual number of non-zero entries in data.
"""
raise NotImplementedError("count_nonzero not implemented for %s." %
self.__class__.__name__)
|
[
"def",
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":",
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"(",
"\"count_nonzero not implemented for %s.\"",
"%",
"self",
".",
"__class__",
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"__name__",
")"
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https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/sparse/base.py#L153-L163
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/setuptools/monkey.py
|
python
|
_patch_distribution_metadata
|
()
|
Patch write_pkg_file and read_pkg_file for higher metadata standards
|
Patch write_pkg_file and read_pkg_file for higher metadata standards
|
[
"Patch",
"write_pkg_file",
"and",
"read_pkg_file",
"for",
"higher",
"metadata",
"standards"
] |
def _patch_distribution_metadata():
"""Patch write_pkg_file and read_pkg_file for higher metadata standards"""
for attr in ('write_pkg_file', 'read_pkg_file', 'get_metadata_version'):
new_val = getattr(setuptools.dist, attr)
setattr(distutils.dist.DistributionMetadata, attr, new_val)
|
[
"def",
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"'write_pkg_file'",
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".",
"DistributionMetadata",
",",
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",",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemFramework/v1/AWS/resource-manager-code/lib/setuptools/monkey.py#L104-L108
|
||
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/third_party/mox3/mox3/mox.py
|
python
|
MethodSignatureChecker.Check
|
(self, params, named_params)
|
Ensures that the parameters used while recording a call are valid.
Args:
# params: A list of positional parameters.
# named_params: A dict of named parameters.
params: list
named_params: dict
Raises:
AttributeError: the given parameters don't work with the given
method.
|
Ensures that the parameters used while recording a call are valid.
|
[
"Ensures",
"that",
"the",
"parameters",
"used",
"while",
"recording",
"a",
"call",
"are",
"valid",
"."
] |
def Check(self, params, named_params):
"""Ensures that the parameters used while recording a call are valid.
Args:
# params: A list of positional parameters.
# named_params: A dict of named parameters.
params: list
named_params: dict
Raises:
AttributeError: the given parameters don't work with the given
method.
"""
arg_status = dict((a, MethodSignatureChecker._NEEDED)
for a in self._required_args)
for arg in self._default_args:
arg_status[arg] = MethodSignatureChecker._DEFAULT
# WARNING: Suspect hack ahead.
#
# Check to see if this is an unbound method, where the instance
# should be bound as the first argument. We try to determine if
# the first argument (param[0]) is an instance of the class, or it
# is equivalent to the class (used to account for Comparators).
#
# NOTE: If a Func() comparator is used, and the signature is not
# correct, this will cause extra executions of the function.
if inspect.ismethod(self._method) or self._bounded_to:
# The extra param accounts for the bound instance.
if len(params) > len(self._required_args):
expected = self._bounded_to
# Check if the param is an instance of the expected class,
# or check equality (useful for checking Comparators).
# This is a hack to work around the fact that the first
# parameter can be a Comparator, and the comparison may raise
# an exception during this comparison, which is OK.
try:
param_equality = (params[0] == expected)
except Exception:
param_equality = False
if isinstance(params[0], expected) or param_equality:
params = params[1:]
# If the IsA() comparator is being used, we need to check the
# inverse of the usual case - that the given instance is a
# subclass of the expected class. For example, the code under
# test does late binding to a subclass.
elif (isinstance(params[0], IsA) and
params[0]._IsSubClass(expected)):
params = params[1:]
# Check that each positional param is valid.
for i in range(len(params)):
try:
arg_name = self._args[i]
except IndexError:
if not self._has_varargs:
raise AttributeError(
'%s does not take %d or more positional '
'arguments' % (self._method.__name__, i))
else:
self._RecordArgumentGiven(arg_name, arg_status)
# Check each keyword argument.
for arg_name in named_params:
if arg_name not in arg_status and not self._has_varkw:
raise AttributeError('%s is not expecting keyword argument %s'
% (self._method.__name__, arg_name))
self._RecordArgumentGiven(arg_name, arg_status)
# Ensure all the required arguments have been given.
still_needed = [k for k, v in arg_status.items()
if v == MethodSignatureChecker._NEEDED]
if still_needed:
raise AttributeError('No values given for arguments: %s'
% (' '.join(sorted(still_needed))))
|
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https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/mox3/mox3/mox.py#L952-L1029
|
||
kushview/Element
|
1cc16380caa2ab79461246ba758b9de1f46db2a5
|
waflib/Tools/suncc.py
|
python
|
find_scc
|
(conf)
|
Detects the Sun C compiler
|
Detects the Sun C compiler
|
[
"Detects",
"the",
"Sun",
"C",
"compiler"
] |
def find_scc(conf):
"""
Detects the Sun C compiler
"""
v = conf.env
cc = conf.find_program('cc', var='CC')
try:
conf.cmd_and_log(cc + ['-flags'])
except Errors.WafError:
conf.fatal('%r is not a Sun compiler' % cc)
v.CC_NAME = 'sun'
conf.get_suncc_version(cc)
|
[
"def",
"find_scc",
"(",
"conf",
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"=",
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".",
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",",
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"v",
".",
"CC_NAME",
"=",
"'sun'",
"conf",
".",
"get_suncc_version",
"(",
"cc",
")"
] |
https://github.com/kushview/Element/blob/1cc16380caa2ab79461246ba758b9de1f46db2a5/waflib/Tools/suncc.py#L11-L22
|
||
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/third_party/gsutil/third_party/boto/boto/glacier/layer1.py
|
python
|
Layer1.get_vault_notifications
|
(self, vault_name)
|
return self.make_request('GET', uri)
|
This operation retrieves the `notification-configuration`
subresource of the specified vault.
For information about setting a notification configuration on
a vault, see SetVaultNotifications. If a notification
configuration for a vault is not set, the operation returns a
`404 Not Found` error. For more information about vault
notifications, see `Configuring Vault Notifications in Amazon
Glacier`_.
An AWS account has full permission to perform all operations
(actions). However, AWS Identity and Access Management (IAM)
users don't have any permissions by default. You must grant
them explicit permission to perform specific actions. For more
information, see `Access Control Using AWS Identity and Access
Management (IAM)`_.
For conceptual information and underlying REST API, go to
`Configuring Vault Notifications in Amazon Glacier`_ and `Get
Vault Notification Configuration `_ in the Amazon Glacier
Developer Guide .
:type vault_name: string
:param vault_name: The name of the vault.
|
This operation retrieves the `notification-configuration`
subresource of the specified vault.
|
[
"This",
"operation",
"retrieves",
"the",
"notification",
"-",
"configuration",
"subresource",
"of",
"the",
"specified",
"vault",
"."
] |
def get_vault_notifications(self, vault_name):
"""
This operation retrieves the `notification-configuration`
subresource of the specified vault.
For information about setting a notification configuration on
a vault, see SetVaultNotifications. If a notification
configuration for a vault is not set, the operation returns a
`404 Not Found` error. For more information about vault
notifications, see `Configuring Vault Notifications in Amazon
Glacier`_.
An AWS account has full permission to perform all operations
(actions). However, AWS Identity and Access Management (IAM)
users don't have any permissions by default. You must grant
them explicit permission to perform specific actions. For more
information, see `Access Control Using AWS Identity and Access
Management (IAM)`_.
For conceptual information and underlying REST API, go to
`Configuring Vault Notifications in Amazon Glacier`_ and `Get
Vault Notification Configuration `_ in the Amazon Glacier
Developer Guide .
:type vault_name: string
:param vault_name: The name of the vault.
"""
uri = 'vaults/%s/notification-configuration' % vault_name
return self.make_request('GET', uri)
|
[
"def",
"get_vault_notifications",
"(",
"self",
",",
"vault_name",
")",
":",
"uri",
"=",
"'vaults/%s/notification-configuration'",
"%",
"vault_name",
"return",
"self",
".",
"make_request",
"(",
"'GET'",
",",
"uri",
")"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/third_party/boto/boto/glacier/layer1.py#L268-L296
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/pandas/py2/pandas/core/generic.py
|
python
|
NDFrame.get_dtype_counts
|
(self)
|
return Series(self._data.get_dtype_counts())
|
Return counts of unique dtypes in this object.
Returns
-------
dtype : Series
Series with the count of columns with each dtype.
See Also
--------
dtypes : Return the dtypes in this object.
Examples
--------
>>> a = [['a', 1, 1.0], ['b', 2, 2.0], ['c', 3, 3.0]]
>>> df = pd.DataFrame(a, columns=['str', 'int', 'float'])
>>> df
str int float
0 a 1 1.0
1 b 2 2.0
2 c 3 3.0
>>> df.get_dtype_counts()
float64 1
int64 1
object 1
dtype: int64
|
Return counts of unique dtypes in this object.
|
[
"Return",
"counts",
"of",
"unique",
"dtypes",
"in",
"this",
"object",
"."
] |
def get_dtype_counts(self):
"""
Return counts of unique dtypes in this object.
Returns
-------
dtype : Series
Series with the count of columns with each dtype.
See Also
--------
dtypes : Return the dtypes in this object.
Examples
--------
>>> a = [['a', 1, 1.0], ['b', 2, 2.0], ['c', 3, 3.0]]
>>> df = pd.DataFrame(a, columns=['str', 'int', 'float'])
>>> df
str int float
0 a 1 1.0
1 b 2 2.0
2 c 3 3.0
>>> df.get_dtype_counts()
float64 1
int64 1
object 1
dtype: int64
"""
from pandas import Series
return Series(self._data.get_dtype_counts())
|
[
"def",
"get_dtype_counts",
"(",
"self",
")",
":",
"from",
"pandas",
"import",
"Series",
"return",
"Series",
"(",
"self",
".",
"_data",
".",
"get_dtype_counts",
"(",
")",
")"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py2/pandas/core/generic.py#L5382-L5412
|
|
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/x86/toolchain/lib/python2.7/lib2to3/refactor.py
|
python
|
RefactoringTool.refactor_file
|
(self, filename, write=False, doctests_only=False)
|
Refactors a file.
|
Refactors a file.
|
[
"Refactors",
"a",
"file",
"."
] |
def refactor_file(self, filename, write=False, doctests_only=False):
"""Refactors a file."""
input, encoding = self._read_python_source(filename)
if input is None:
# Reading the file failed.
return
input += u"\n" # Silence certain parse errors
if doctests_only:
self.log_debug("Refactoring doctests in %s", filename)
output = self.refactor_docstring(input, filename)
if self.write_unchanged_files or output != input:
self.processed_file(output, filename, input, write, encoding)
else:
self.log_debug("No doctest changes in %s", filename)
else:
tree = self.refactor_string(input, filename)
if self.write_unchanged_files or (tree and tree.was_changed):
# The [:-1] is to take off the \n we added earlier
self.processed_file(unicode(tree)[:-1], filename,
write=write, encoding=encoding)
else:
self.log_debug("No changes in %s", filename)
|
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"log_debug",
"(",
"\"No changes in %s\"",
",",
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")"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/lib2to3/refactor.py#L339-L360
|
||
fastmachinelearning/hls4ml
|
58d761006250deed721d85fefea91201708f2165
|
hls4ml/model/profiling.py
|
python
|
compare
|
(keras_model, hls_model, X, plot_type = "dist_diff")
|
return f
|
Compare each layer's output in keras and hls model. Note that the hls_model should not be compiled before using this.
Parameters
----------
keras_model :
original keras model
hls_model :
converted ModelGraph, with "Trace:True" in the configuration file.
X : array-like
Input for the model.
plot_type : string
different methods to visualize the y_model and y_sim differences.
Possible options include:
- 'norm_diff' : square root of the sum of the squares of the differences
between each output vectors
- 'dist_diff' : The normalized distribution of the differences of the elements
between two output vectors
Returns
-------
matplotlib figure
plot object of the histogram depicting the difference in each layer's output
|
Compare each layer's output in keras and hls model. Note that the hls_model should not be compiled before using this.
|
[
"Compare",
"each",
"layer",
"s",
"output",
"in",
"keras",
"and",
"hls",
"model",
".",
"Note",
"that",
"the",
"hls_model",
"should",
"not",
"be",
"compiled",
"before",
"using",
"this",
"."
] |
def compare(keras_model, hls_model, X, plot_type = "dist_diff"):
"""
Compare each layer's output in keras and hls model. Note that the hls_model should not be compiled before using this.
Parameters
----------
keras_model :
original keras model
hls_model :
converted ModelGraph, with "Trace:True" in the configuration file.
X : array-like
Input for the model.
plot_type : string
different methods to visualize the y_model and y_sim differences.
Possible options include:
- 'norm_diff' : square root of the sum of the squares of the differences
between each output vectors
- 'dist_diff' : The normalized distribution of the differences of the elements
between two output vectors
Returns
-------
matplotlib figure
plot object of the histogram depicting the difference in each layer's output
"""
#Take in output from both models
#Note that each y is a dictionary with structure {"layer_name": flattened ouput array}
ymodel = get_ymodel_keras(keras_model, X)
_, ysim = hls_model.trace(X)
print("Plotting difference...")
f = plt.figure()
if plot_type == "norm_diff":
f = _norm_diff(ymodel, ysim)
elif plot_type == "dist_diff":
f = _dist_diff(ymodel, ysim)
return f
|
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"def",
"compare",
"(",
"keras_model",
",",
"hls_model",
",",
"X",
",",
"plot_type",
"=",
"\"dist_diff\"",
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"#Take in output from both models",
"#Note that each y is a dictionary with structure {\"layer_name\": flattened ouput array}",
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"=",
"_dist_diff",
"(",
"ymodel",
",",
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"return",
"f"
] |
https://github.com/fastmachinelearning/hls4ml/blob/58d761006250deed721d85fefea91201708f2165/hls4ml/model/profiling.py#L655-L694
|
|
tensorflow/tensorflow
|
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
|
tensorflow/python/keras/engine/training_v1.py
|
python
|
Model._handle_per_output_metrics
|
(self,
metrics_dict,
y_true,
y_pred,
mask,
weights=None)
|
return metric_results
|
Calls metric functions for a single output.
Args:
metrics_dict: A dict with metric names as keys and metric fns as values.
y_true: Target output.
y_pred: Predicted output.
mask: Computed mask value for the current output.
weights: Weights to be applied on the current output.
Returns:
A list of metric result tensors.
|
Calls metric functions for a single output.
|
[
"Calls",
"metric",
"functions",
"for",
"a",
"single",
"output",
"."
] |
def _handle_per_output_metrics(self,
metrics_dict,
y_true,
y_pred,
mask,
weights=None):
"""Calls metric functions for a single output.
Args:
metrics_dict: A dict with metric names as keys and metric fns as values.
y_true: Target output.
y_pred: Predicted output.
mask: Computed mask value for the current output.
weights: Weights to be applied on the current output.
Returns:
A list of metric result tensors.
"""
metric_results = []
for metric_name, metric_fn in metrics_dict.items():
with backend.name_scope(metric_name):
metric_result = training_utils_v1.call_metric_function(
metric_fn, y_true, y_pred, weights=weights, mask=mask)
metric_results.append(metric_result)
return metric_results
|
[
"def",
"_handle_per_output_metrics",
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",",
"metrics_dict",
",",
"y_true",
",",
"y_pred",
",",
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",",
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"None",
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"[",
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")",
"metric_results",
".",
"append",
"(",
"metric_result",
")",
"return",
"metric_results"
] |
https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/keras/engine/training_v1.py#L1901-L1925
|
|
rapidsai/cudf
|
d5b2448fc69f17509304d594f029d0df56984962
|
python/cudf/cudf/core/series.py
|
python
|
Series.nullmask
|
(self)
|
return cudf.Series(self._column.nullmask)
|
The gpu buffer for the null-mask
|
The gpu buffer for the null-mask
|
[
"The",
"gpu",
"buffer",
"for",
"the",
"null",
"-",
"mask"
] |
def nullmask(self):
"""The gpu buffer for the null-mask"""
return cudf.Series(self._column.nullmask)
|
[
"def",
"nullmask",
"(",
"self",
")",
":",
"return",
"cudf",
".",
"Series",
"(",
"self",
".",
"_column",
".",
"nullmask",
")"
] |
https://github.com/rapidsai/cudf/blob/d5b2448fc69f17509304d594f029d0df56984962/python/cudf/cudf/core/series.py#L1815-L1817
|
|
livecode/livecode
|
4606a10ea10b16d5071d0f9f263ccdd7ede8b31d
|
gyp/pylib/gyp/MSVSSettings.py
|
python
|
_Same
|
(tool, name, setting_type)
|
Defines a setting that has the same name in MSVS and MSBuild.
Args:
tool: a dictionary that gives the names of the tool for MSVS and MSBuild.
name: the name of the setting.
setting_type: the type of this setting.
|
Defines a setting that has the same name in MSVS and MSBuild.
|
[
"Defines",
"a",
"setting",
"that",
"has",
"the",
"same",
"name",
"in",
"MSVS",
"and",
"MSBuild",
"."
] |
def _Same(tool, name, setting_type):
"""Defines a setting that has the same name in MSVS and MSBuild.
Args:
tool: a dictionary that gives the names of the tool for MSVS and MSBuild.
name: the name of the setting.
setting_type: the type of this setting.
"""
_Renamed(tool, name, name, setting_type)
|
[
"def",
"_Same",
"(",
"tool",
",",
"name",
",",
"setting_type",
")",
":",
"_Renamed",
"(",
"tool",
",",
"name",
",",
"name",
",",
"setting_type",
")"
] |
https://github.com/livecode/livecode/blob/4606a10ea10b16d5071d0f9f263ccdd7ede8b31d/gyp/pylib/gyp/MSVSSettings.py#L233-L241
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/scipy/scipy/sparse/sputils.py
|
python
|
downcast_intp_index
|
(arr)
|
return arr
|
Down-cast index array to np.intp dtype if it is of a larger dtype.
Raise an error if the array contains a value that is too large for
intp.
|
Down-cast index array to np.intp dtype if it is of a larger dtype.
|
[
"Down",
"-",
"cast",
"index",
"array",
"to",
"np",
".",
"intp",
"dtype",
"if",
"it",
"is",
"of",
"a",
"larger",
"dtype",
"."
] |
def downcast_intp_index(arr):
"""
Down-cast index array to np.intp dtype if it is of a larger dtype.
Raise an error if the array contains a value that is too large for
intp.
"""
if arr.dtype.itemsize > np.dtype(np.intp).itemsize:
if arr.size == 0:
return arr.astype(np.intp)
maxval = arr.max()
minval = arr.min()
if maxval > np.iinfo(np.intp).max or minval < np.iinfo(np.intp).min:
raise ValueError("Cannot deal with arrays with indices larger "
"than the machine maximum address size "
"(e.g. 64-bit indices on 32-bit machine).")
return arr.astype(np.intp)
return arr
|
[
"def",
"downcast_intp_index",
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"arr",
")",
":",
"if",
"arr",
".",
"dtype",
".",
"itemsize",
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")",
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"arr",
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"astype",
"(",
"np",
".",
"intp",
")",
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"arr"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/sparse/sputils.py#L79-L96
|
|
cvxpy/cvxpy
|
5165b4fb750dfd237de8659383ef24b4b2e33aaf
|
cvxpy/constraints/exponential.py
|
python
|
ExpCone.size
|
(self)
|
return 3 * self.num_cones()
|
The number of entries in the combined cones.
|
The number of entries in the combined cones.
|
[
"The",
"number",
"of",
"entries",
"in",
"the",
"combined",
"cones",
"."
] |
def size(self) -> int:
"""The number of entries in the combined cones.
"""
return 3 * self.num_cones()
|
[
"def",
"size",
"(",
"self",
")",
"->",
"int",
":",
"return",
"3",
"*",
"self",
".",
"num_cones",
"(",
")"
] |
https://github.com/cvxpy/cvxpy/blob/5165b4fb750dfd237de8659383ef24b4b2e33aaf/cvxpy/constraints/exponential.py#L91-L94
|
|
microsoft/checkedc-clang
|
a173fefde5d7877b7750e7ce96dd08cf18baebf2
|
clang/tools/scan-build-py/libscanbuild/analyze.py
|
python
|
create_global_ctu_extdef_map
|
(extdef_map_lines)
|
return mangled_ast_pairs
|
Takes iterator of individual external definition maps and creates a
global map keeping only unique names. We leave conflicting names out of
CTU.
:param extdef_map_lines: Contains the id of a definition (mangled name) and
the originating source (the corresponding AST file) name.
:type extdef_map_lines: Iterator of str.
:returns: Mangled name - AST file pairs.
:rtype: List of (str, str) tuples.
|
Takes iterator of individual external definition maps and creates a
global map keeping only unique names. We leave conflicting names out of
CTU.
|
[
"Takes",
"iterator",
"of",
"individual",
"external",
"definition",
"maps",
"and",
"creates",
"a",
"global",
"map",
"keeping",
"only",
"unique",
"names",
".",
"We",
"leave",
"conflicting",
"names",
"out",
"of",
"CTU",
"."
] |
def create_global_ctu_extdef_map(extdef_map_lines):
""" Takes iterator of individual external definition maps and creates a
global map keeping only unique names. We leave conflicting names out of
CTU.
:param extdef_map_lines: Contains the id of a definition (mangled name) and
the originating source (the corresponding AST file) name.
:type extdef_map_lines: Iterator of str.
:returns: Mangled name - AST file pairs.
:rtype: List of (str, str) tuples.
"""
mangled_to_asts = defaultdict(set)
for line in extdef_map_lines:
mangled_name, ast_file = line.strip().split(' ', 1)
mangled_to_asts[mangled_name].add(ast_file)
mangled_ast_pairs = []
for mangled_name, ast_files in mangled_to_asts.items():
if len(ast_files) == 1:
mangled_ast_pairs.append((mangled_name, next(iter(ast_files))))
return mangled_ast_pairs
|
[
"def",
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":",
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"defaultdict",
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"(",
"iter",
"(",
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")",
")",
")",
")",
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] |
https://github.com/microsoft/checkedc-clang/blob/a173fefde5d7877b7750e7ce96dd08cf18baebf2/clang/tools/scan-build-py/libscanbuild/analyze.py#L136-L160
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/tools/Editra/src/ed_stc.py
|
python
|
EditraStc.SyntaxOnOff
|
(self, switch=None)
|
return 0
|
Turn Syntax Highlighting on and off
@keyword switch: force a particular setting
|
Turn Syntax Highlighting on and off
@keyword switch: force a particular setting
|
[
"Turn",
"Syntax",
"Highlighting",
"on",
"and",
"off",
"@keyword",
"switch",
":",
"force",
"a",
"particular",
"setting"
] |
def SyntaxOnOff(self, switch=None):
"""Turn Syntax Highlighting on and off
@keyword switch: force a particular setting
"""
if (switch is None and not self._config['highlight']) or switch:
self.LOG("[ed_stc][evt] Syntax Highlighting Turned On")
self._config['highlight'] = True
self.FindLexer()
else:
self.LOG("[ed_stc][evt] Syntax Highlighting Turned Off")
self._config['highlight'] = False
self.SetLexer(wx.stc.STC_LEX_NULL)
self.ClearDocumentStyle()
self.UpdateBaseStyles()
return 0
|
[
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"None",
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":",
"if",
"(",
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"ClearDocumentStyle",
"(",
")",
"self",
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"UpdateBaseStyles",
"(",
")",
"return",
"0"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/tools/Editra/src/ed_stc.py#L1606-L1621
|
|
openmm/openmm
|
cb293447c4fc8b03976dfe11399f107bab70f3d9
|
wrappers/python/openmm/unit/baseunit.py
|
python
|
BaseUnit.conversion_factor_to
|
(self, other)
|
return self._conversion_factor_to_by_name[other.name]
|
Returns a conversion factor from this BaseUnit to another BaseUnit.
It does not matter which existing BaseUnit you define the conversion factor to.
Conversions for all other known BaseUnits will be computed at the same time.
Raises TypeError if dimension does not match.
Raises LookupError if no conversion has been defined. (see define_conversion_factor_to).
|
Returns a conversion factor from this BaseUnit to another BaseUnit.
|
[
"Returns",
"a",
"conversion",
"factor",
"from",
"this",
"BaseUnit",
"to",
"another",
"BaseUnit",
"."
] |
def conversion_factor_to(self, other):
"""Returns a conversion factor from this BaseUnit to another BaseUnit.
It does not matter which existing BaseUnit you define the conversion factor to.
Conversions for all other known BaseUnits will be computed at the same time.
Raises TypeError if dimension does not match.
Raises LookupError if no conversion has been defined. (see define_conversion_factor_to).
"""
if self is other: return 1.0
if self.dimension != other.dimension:
raise TypeError('Cannot get conversion for BaseUnits with different dimensions.')
if not other.name in self._conversion_factor_to_by_name:
raise LookupError('No conversion defined from BaseUnit "%s" to "%s".' % (self, other))
return self._conversion_factor_to_by_name[other.name]
|
[
"def",
"conversion_factor_to",
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"return",
"self",
".",
"_conversion_factor_to_by_name",
"[",
"other",
".",
"name",
"]"
] |
https://github.com/openmm/openmm/blob/cb293447c4fc8b03976dfe11399f107bab70f3d9/wrappers/python/openmm/unit/baseunit.py#L149-L164
|
|
oracle/graaljs
|
36a56e8e993d45fc40939a3a4d9c0c24990720f1
|
graal-nodejs/deps/v8/third_party/jinja2/parser.py
|
python
|
Parser.parse_if
|
(self)
|
return result
|
Parse an if construct.
|
Parse an if construct.
|
[
"Parse",
"an",
"if",
"construct",
"."
] |
def parse_if(self):
"""Parse an if construct."""
node = result = nodes.If(lineno=self.stream.expect('name:if').lineno)
while 1:
node.test = self.parse_tuple(with_condexpr=False)
node.body = self.parse_statements(('name:elif', 'name:else',
'name:endif'))
node.elif_ = []
node.else_ = []
token = next(self.stream)
if token.test('name:elif'):
node = nodes.If(lineno=self.stream.current.lineno)
result.elif_.append(node)
continue
elif token.test('name:else'):
result.else_ = self.parse_statements(('name:endif',),
drop_needle=True)
break
return result
|
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https://github.com/oracle/graaljs/blob/36a56e8e993d45fc40939a3a4d9c0c24990720f1/graal-nodejs/deps/v8/third_party/jinja2/parser.py#L207-L225
|
|
gimli-org/gimli
|
17aa2160de9b15ababd9ef99e89b1bc3277bbb23
|
pygimli/meshtools/mesh.py
|
python
|
exportHDF5Mesh
|
(mesh, exportname, group='mesh', indices='cell_indices',
pos='coordinates', cells='topology', marker='values')
|
return True
|
Writes given :gimliapi:`GIMLI::Mesh` in a hdf5 format file.
3D tetrahedral meshes only! Boundary markers are ignored.
Keywords are explained in :py:mod:`pygimli.meshtools.readHDFS`
|
Writes given :gimliapi:`GIMLI::Mesh` in a hdf5 format file.
|
[
"Writes",
"given",
":",
"gimliapi",
":",
"GIMLI",
"::",
"Mesh",
"in",
"a",
"hdf5",
"format",
"file",
"."
] |
def exportHDF5Mesh(mesh, exportname, group='mesh', indices='cell_indices',
pos='coordinates', cells='topology', marker='values'):
"""Writes given :gimliapi:`GIMLI::Mesh` in a hdf5 format file.
3D tetrahedral meshes only! Boundary markers are ignored.
Keywords are explained in :py:mod:`pygimli.meshtools.readHDFS`
"""
h5py = pg.optImport('h5py',
requiredFor='export mesh in .h5 data format')
if not isinstance(mesh, pg.Mesh):
mesh = pg.Mesh(mesh)
# prepare output for writing in hdf data container
pg_pos = mesh.positions()
mesh_pos = np.array((np.array(pg.x(pg_pos)), np.array(pg.y(pg_pos)),
np.array(pg.z(pg_pos)))).T
mesh_cells = np.zeros((mesh.cellCount(), 4)) # hard coded for tetrahedrons
for i, cell in enumerate(mesh.cells()):
mesh_cells[i] = cell.ids()
mesh_indices = np.arange(0, mesh.cellCount() + 1, 1, dtype=np.int64)
mesh_markers = np.array(mesh.cellMarkers())
with h5py.File(exportname, 'w') as out:
for grp in np.atleast_1d(group): # can use more than one group
# writing indices
idx_name = '{}/{}'.format(grp, indices)
out.create_dataset(idx_name, data=mesh_indices, dtype=int)
# writing node positions
pos_name = '{}/{}'.format(grp, pos)
out.create_dataset(pos_name, data=mesh_pos, dtype=float)
# writing cells via indices
cells_name = '{}/{}'.format(grp, cells)
out.create_dataset(cells_name, data=mesh_cells, dtype=int)
# writing marker
marker_name = '{}/{}'.format(grp, marker)
out.create_dataset(marker_name, data=mesh_markers, dtype=int)
out[grp][cells].attrs['celltype'] = np.string_('tetrahedron')
out[grp][cells].attrs.create('partition', [0])
return True
|
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https://github.com/gimli-org/gimli/blob/17aa2160de9b15ababd9ef99e89b1bc3277bbb23/pygimli/meshtools/mesh.py#L1479-L1521
|
|
nyuwireless-unipd/ns3-mmwave
|
4ff9e87e8079764e04cbeccd8e85bff15ae16fb3
|
src/core/examples/sample-simulator.py
|
python
|
MyModel.Start
|
(self)
|
Start model execution by scheduling a HandleEvent.
|
Start model execution by scheduling a HandleEvent.
|
[
"Start",
"model",
"execution",
"by",
"scheduling",
"a",
"HandleEvent",
"."
] |
def Start(self):
"""Start model execution by scheduling a HandleEvent."""
ns.core.Simulator.Schedule(ns.core.Seconds(10.0), self.HandleEvent, ns.core.Simulator.Now().GetSeconds())
|
[
"def",
"Start",
"(",
"self",
")",
":",
"ns",
".",
"core",
".",
"Simulator",
".",
"Schedule",
"(",
"ns",
".",
"core",
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"Seconds",
"(",
"10.0",
")",
",",
"self",
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",",
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".",
"core",
".",
"Simulator",
".",
"Now",
"(",
")",
".",
"GetSeconds",
"(",
")",
")"
] |
https://github.com/nyuwireless-unipd/ns3-mmwave/blob/4ff9e87e8079764e04cbeccd8e85bff15ae16fb3/src/core/examples/sample-simulator.py#L35-L37
|
||
hfinkel/llvm-project-cxxjit
|
91084ef018240bbb8e24235ff5cd8c355a9c1a1e
|
llvm/bindings/python/llvm/object.py
|
python
|
ObjectFile.get_sections
|
(self, cache=False)
|
Obtain the sections in this object file.
This is a generator for llvm.object.Section instances.
Sections are exposed as limited-use objects. See the module's
documentation on iterators for more.
|
Obtain the sections in this object file.
|
[
"Obtain",
"the",
"sections",
"in",
"this",
"object",
"file",
"."
] |
def get_sections(self, cache=False):
"""Obtain the sections in this object file.
This is a generator for llvm.object.Section instances.
Sections are exposed as limited-use objects. See the module's
documentation on iterators for more.
"""
sections = lib.LLVMGetSections(self)
last = None
while True:
if lib.LLVMIsSectionIteratorAtEnd(self, sections):
break
last = Section(sections)
if cache:
last.cache()
yield last
lib.LLVMMoveToNextSection(sections)
last.expire()
if last is not None:
last.expire()
lib.LLVMDisposeSectionIterator(sections)
|
[
"def",
"get_sections",
"(",
"self",
",",
"cache",
"=",
"False",
")",
":",
"sections",
"=",
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"LLVMDisposeSectionIterator",
"(",
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")"
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https://github.com/hfinkel/llvm-project-cxxjit/blob/91084ef018240bbb8e24235ff5cd8c355a9c1a1e/llvm/bindings/python/llvm/object.py#L122-L148
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/scipy/py2/scipy/linalg/_interpolative_backend.py
|
python
|
idzr_svd
|
(A, k)
|
return U, V, S
|
Compute SVD of a complex matrix to a specified rank.
:param A:
Matrix.
:type A: :class:`numpy.ndarray`
:param k:
Rank of SVD.
:type k: int
:return:
Left singular vectors.
:rtype: :class:`numpy.ndarray`
:return:
Right singular vectors.
:rtype: :class:`numpy.ndarray`
:return:
Singular values.
:rtype: :class:`numpy.ndarray`
|
Compute SVD of a complex matrix to a specified rank.
|
[
"Compute",
"SVD",
"of",
"a",
"complex",
"matrix",
"to",
"a",
"specified",
"rank",
"."
] |
def idzr_svd(A, k):
"""
Compute SVD of a complex matrix to a specified rank.
:param A:
Matrix.
:type A: :class:`numpy.ndarray`
:param k:
Rank of SVD.
:type k: int
:return:
Left singular vectors.
:rtype: :class:`numpy.ndarray`
:return:
Right singular vectors.
:rtype: :class:`numpy.ndarray`
:return:
Singular values.
:rtype: :class:`numpy.ndarray`
"""
A = np.asfortranarray(A)
U, V, S, ier = _id.idzr_svd(A, k)
if ier:
raise _RETCODE_ERROR
return U, V, S
|
[
"def",
"idzr_svd",
"(",
"A",
",",
"k",
")",
":",
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"=",
"np",
".",
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")",
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":",
"raise",
"_RETCODE_ERROR",
"return",
"U",
",",
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",",
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] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/py2/scipy/linalg/_interpolative_backend.py#L1214-L1239
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/xrc.py
|
python
|
XmlResourceHandler.AddStyle
|
(*args, **kwargs)
|
return _xrc.XmlResourceHandler_AddStyle(*args, **kwargs)
|
AddStyle(self, String name, int value)
|
AddStyle(self, String name, int value)
|
[
"AddStyle",
"(",
"self",
"String",
"name",
"int",
"value",
")"
] |
def AddStyle(*args, **kwargs):
"""AddStyle(self, String name, int value)"""
return _xrc.XmlResourceHandler_AddStyle(*args, **kwargs)
|
[
"def",
"AddStyle",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_xrc",
".",
"XmlResourceHandler_AddStyle",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/xrc.py#L647-L649
|
|
natanielruiz/android-yolo
|
1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f
|
jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/estimator.py
|
python
|
BaseEstimator._get_feature_ops_from_example
|
(self, examples_batch)
|
return tensor_signature.create_example_parser_from_signatures(
self._features_info, examples_batch)
|
Returns feature parser for given example batch using features info.
This function requires `fit()` has been called.
Args:
examples_batch: batch of tf.Example
Returns:
features: `Tensor` or `dict` of `Tensor` objects.
Raises:
ValueError: If `_features_info` attribute is not available (usually
because `fit()` has not been called).
|
Returns feature parser for given example batch using features info.
|
[
"Returns",
"feature",
"parser",
"for",
"given",
"example",
"batch",
"using",
"features",
"info",
"."
] |
def _get_feature_ops_from_example(self, examples_batch):
"""Returns feature parser for given example batch using features info.
This function requires `fit()` has been called.
Args:
examples_batch: batch of tf.Example
Returns:
features: `Tensor` or `dict` of `Tensor` objects.
Raises:
ValueError: If `_features_info` attribute is not available (usually
because `fit()` has not been called).
"""
if self._features_info is None:
raise ValueError('Features information missing, was fit() ever called?')
return tensor_signature.create_example_parser_from_signatures(
self._features_info, examples_batch)
|
[
"def",
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"(",
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",",
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https://github.com/natanielruiz/android-yolo/blob/1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f/jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/estimator.py#L400-L418
|
|
nyuwireless-unipd/ns3-mmwave
|
4ff9e87e8079764e04cbeccd8e85bff15ae16fb3
|
src/visualizer/visualizer/core.py
|
python
|
SimulationThread.set_nodes_of_interest
|
(self, nodes)
|
!
Set nodes of interest function.
@param self: class object.
@param nodes: class object.
@return
|
!
Set nodes of interest function.
|
[
"!",
"Set",
"nodes",
"of",
"interest",
"function",
"."
] |
def set_nodes_of_interest(self, nodes):
"""!
Set nodes of interest function.
@param self: class object.
@param nodes: class object.
@return
"""
self.lock.acquire()
try:
self.sim_helper.SetNodesOfInterest(nodes)
finally:
self.lock.release()
|
[
"def",
"set_nodes_of_interest",
"(",
"self",
",",
"nodes",
")",
":",
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".",
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"(",
"nodes",
")",
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":",
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"lock",
".",
"release",
"(",
")"
] |
https://github.com/nyuwireless-unipd/ns3-mmwave/blob/4ff9e87e8079764e04cbeccd8e85bff15ae16fb3/src/visualizer/visualizer/core.py#L637-L649
|
||
Alexhuszagh/rust-lexical
|
01fcdcf8efc8850edb35d8fc65fd5f31bd0981a0
|
lexical-util/etc/div128.py
|
python
|
is_valid
|
(x)
|
return (
x <= u64_max
and (u128_max / (x**2)) < x
)
|
Determine if the power is valid.
|
Determine if the power is valid.
|
[
"Determine",
"if",
"the",
"power",
"is",
"valid",
"."
] |
def is_valid(x):
'''Determine if the power is valid.'''
return (
x <= u64_max
and (u128_max / (x**2)) < x
)
|
[
"def",
"is_valid",
"(",
"x",
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":",
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"(",
"x",
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"u64_max",
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"(",
"u128_max",
"/",
"(",
"x",
"**",
"2",
")",
")",
"<",
"x",
")"
] |
https://github.com/Alexhuszagh/rust-lexical/blob/01fcdcf8efc8850edb35d8fc65fd5f31bd0981a0/lexical-util/etc/div128.py#L21-L26
|
|
mongodb/mongo
|
d8ff665343ad29cf286ee2cf4a1960d29371937b
|
src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Tool/icc.py
|
python
|
generate
|
(env)
|
Add Builders and construction variables for the OS/2 to an Environment.
|
Add Builders and construction variables for the OS/2 to an Environment.
|
[
"Add",
"Builders",
"and",
"construction",
"variables",
"for",
"the",
"OS",
"/",
"2",
"to",
"an",
"Environment",
"."
] |
def generate(env):
"""Add Builders and construction variables for the OS/2 to an Environment."""
cc.generate(env)
env['CC'] = 'icc'
env['CCCOM'] = '$CC $CFLAGS $CCFLAGS $CPPFLAGS $_CPPDEFFLAGS $_CPPINCFLAGS /c $SOURCES /Fo$TARGET'
env['CXXCOM'] = '$CXX $CXXFLAGS $CPPFLAGS $_CPPDEFFLAGS $_CPPINCFLAGS /c $SOURCES /Fo$TARGET'
env['CPPDEFPREFIX'] = '/D'
env['CPPDEFSUFFIX'] = ''
env['INCPREFIX'] = '/I'
env['INCSUFFIX'] = ''
env['CFILESUFFIX'] = '.c'
env['CXXFILESUFFIX'] = '.cc'
|
[
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"'.cc'"
] |
https://github.com/mongodb/mongo/blob/d8ff665343ad29cf286ee2cf4a1960d29371937b/src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Tool/icc.py#L38-L50
|
||
freeorion/freeorion
|
c266a40eccd3a99a17de8fe57c36ef6ba3771665
|
default/python/universe_generation/galaxy.py
|
python
|
recalc_universe_width
|
(positions)
|
return actual_width, new_positions
|
Recalculates the universe width. This is done by shifting all positions by a delta so too much "extra space"
beyond the uppermost, lowermost, leftmost and rightmost positions is cropped, and adjust the universe width
accordingly.
Returns the new universe width and the recalculated positions.
|
Recalculates the universe width. This is done by shifting all positions by a delta so too much "extra space"
beyond the uppermost, lowermost, leftmost and rightmost positions is cropped, and adjust the universe width
accordingly.
|
[
"Recalculates",
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"universe",
"width",
".",
"This",
"is",
"done",
"by",
"shifting",
"all",
"positions",
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"a",
"delta",
"so",
"too",
"much",
"extra",
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"and",
"rightmost",
"positions",
"is",
"cropped",
"and",
"adjust",
"the",
"universe",
"width",
"accordingly",
"."
] |
def recalc_universe_width(positions):
"""
Recalculates the universe width. This is done by shifting all positions by a delta so too much "extra space"
beyond the uppermost, lowermost, leftmost and rightmost positions is cropped, and adjust the universe width
accordingly.
Returns the new universe width and the recalculated positions.
"""
print("Recalculating universe width...")
# first, get the uppermost, lowermost, leftmost and rightmost positions
# (these are those with their x or y coordinate closest to or farthest away from the x or y axis)
min_x = min(positions, key=lambda p: p[0])[0]
min_y = min(positions, key=lambda p: p[1])[1]
max_x = max(positions, key=lambda p: p[0])[0]
max_y = max(positions, key=lambda p: p[1])[1]
print("...the leftmost system position is at x coordinate {}".format(min_x))
print("...the uppermost system position is at y coordinate {}".format(min_y))
print("...the rightmost system position is at x coordinate {}".format(max_x))
print("...the lowermost system position is at y coordinate {}".format(max_y))
# calculate the actual universe width by determining the width and height of an rectangle that encompasses all
# positions, and take the greater of the two as the new actual width for the universe
# also add a constant value to the width so we have some small space around
width = max_x - min_x
height = max_y - min_y
actual_width = max(width, height) + 20.0
print("...recalculated universe width: {}".format(actual_width))
# shift all positions so the entire map is centered in a quadratic box of the width we just calculated
# this box defines the extends of our universe
delta_x = ((actual_width - width) / 2) - min_x
delta_y = ((actual_width - height) / 2) - min_y
print("...shifting all system positions by {}/{}".format(delta_x, delta_y))
new_positions = [(p[0] + delta_x, p[1] + delta_y) for p in positions]
print("...the leftmost system position is now at x coordinate {}".format(min(new_positions, key=lambda p: p[0])[0]))
print(
"...the uppermost system position is now at y coordinate {}".format(min(new_positions, key=lambda p: p[1])[1])
)
print(
"...the rightmost system position is now at x coordinate {}".format(max(new_positions, key=lambda p: p[0])[0])
)
print(
"...the lowermost system position is now at y coordinate {}".format(max(new_positions, key=lambda p: p[1])[1])
)
return actual_width, new_positions
|
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] |
https://github.com/freeorion/freeorion/blob/c266a40eccd3a99a17de8fe57c36ef6ba3771665/default/python/universe_generation/galaxy.py#L738-L784
|
|
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/ntpath.py
|
python
|
islink
|
(path)
|
return False
|
Test for symbolic link.
On WindowsNT/95 and OS/2 always returns false
|
Test for symbolic link.
On WindowsNT/95 and OS/2 always returns false
|
[
"Test",
"for",
"symbolic",
"link",
".",
"On",
"WindowsNT",
"/",
"95",
"and",
"OS",
"/",
"2",
"always",
"returns",
"false"
] |
def islink(path):
"""Test for symbolic link.
On WindowsNT/95 and OS/2 always returns false
"""
return False
|
[
"def",
"islink",
"(",
"path",
")",
":",
"return",
"False"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/ntpath.py#L210-L214
|
|
weolar/miniblink49
|
1c4678db0594a4abde23d3ebbcc7cd13c3170777
|
third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/mod_pywebsocket/_stream_hybi.py
|
python
|
create_length_header
|
(length, mask)
|
Creates a length header.
Args:
length: Frame length. Must be less than 2^63.
mask: Mask bit. Must be boolean.
Raises:
ValueError: when bad data is given.
|
Creates a length header.
|
[
"Creates",
"a",
"length",
"header",
"."
] |
def create_length_header(length, mask):
"""Creates a length header.
Args:
length: Frame length. Must be less than 2^63.
mask: Mask bit. Must be boolean.
Raises:
ValueError: when bad data is given.
"""
if mask:
mask_bit = 1 << 7
else:
mask_bit = 0
if length < 0:
raise ValueError('length must be non negative integer')
elif length <= 125:
return chr(mask_bit | length)
elif length < (1 << 16):
return chr(mask_bit | 126) + struct.pack('!H', length)
elif length < (1 << 63):
return chr(mask_bit | 127) + struct.pack('!Q', length)
else:
raise ValueError('Payload is too big for one frame')
|
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https://github.com/weolar/miniblink49/blob/1c4678db0594a4abde23d3ebbcc7cd13c3170777/third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/mod_pywebsocket/_stream_hybi.py#L74-L99
|
||
microsoft/CNTK
|
e9396480025b9ca457d26b6f33dd07c474c6aa04
|
bindings/python/cntk/ops/__init__.py
|
python
|
reduce_max
|
(x, axis=None, keepdims=True, name='')
|
return reduce_max(x, axis, keepdims, name)
|
Computes the max of the input tensor's elements across a specified axis or a list of specified axes.
Example:
>>> # create 3x2x2 matrix in a sequence of length 1 in a batch of one sample
>>> data = np.array([[[5,1], [20,2]],[[30,1], [40,2]],[[55,1], [60,2]]], dtype=np.float32)
>>> C.reduce_max(data, 0).eval().round(4)
array([[[ 55., 1.],
[ 60., 2.]]], dtype=float32)
>>> C.reduce_max(data, 1).eval().round(4)
array([[[ 20., 2.]],
<BLANKLINE>
[[ 40., 2.]],
<BLANKLINE>
[[ 60., 2.]]], dtype=float32)
>>> C.reduce_max(data, (0,2)).eval().round(4)
array([[[ 55.],
[ 60.]]], dtype=float32)
>>> x = C.input_variable((2,2))
>>> C.reduce_max( x * 1.0, (C.Axis.default_batch_axis(), 1)).eval({x: data}).round(4)
array([[ 55.],
[ 60.]], dtype=float32)
Args:
x: input tensor
axis (int or :class:`~cntk.axis.Axis` or a :obj:`list` or :obj:`tuple` of int or :class:`~cntk.axis.Axis`): axis along which the reduction will be performed
keepdims (boolean): Keep the reduced dimension or not, default True mean keep reduced dimension
name (str): the name of the Function instance in the network
Returns:
:class:`~cntk.ops.functions.Function`
Note that CNTK keeps the shape of the resulting tensors when reducing over multiple static axes.
|
Computes the max of the input tensor's elements across a specified axis or a list of specified axes.
|
[
"Computes",
"the",
"max",
"of",
"the",
"input",
"tensor",
"s",
"elements",
"across",
"a",
"specified",
"axis",
"or",
"a",
"list",
"of",
"specified",
"axes",
"."
] |
def reduce_max(x, axis=None, keepdims=True, name=''):
'''
Computes the max of the input tensor's elements across a specified axis or a list of specified axes.
Example:
>>> # create 3x2x2 matrix in a sequence of length 1 in a batch of one sample
>>> data = np.array([[[5,1], [20,2]],[[30,1], [40,2]],[[55,1], [60,2]]], dtype=np.float32)
>>> C.reduce_max(data, 0).eval().round(4)
array([[[ 55., 1.],
[ 60., 2.]]], dtype=float32)
>>> C.reduce_max(data, 1).eval().round(4)
array([[[ 20., 2.]],
<BLANKLINE>
[[ 40., 2.]],
<BLANKLINE>
[[ 60., 2.]]], dtype=float32)
>>> C.reduce_max(data, (0,2)).eval().round(4)
array([[[ 55.],
[ 60.]]], dtype=float32)
>>> x = C.input_variable((2,2))
>>> C.reduce_max( x * 1.0, (C.Axis.default_batch_axis(), 1)).eval({x: data}).round(4)
array([[ 55.],
[ 60.]], dtype=float32)
Args:
x: input tensor
axis (int or :class:`~cntk.axis.Axis` or a :obj:`list` or :obj:`tuple` of int or :class:`~cntk.axis.Axis`): axis along which the reduction will be performed
keepdims (boolean): Keep the reduced dimension or not, default True mean keep reduced dimension
name (str): the name of the Function instance in the network
Returns:
:class:`~cntk.ops.functions.Function`
Note that CNTK keeps the shape of the resulting tensors when reducing over multiple static axes.
'''
from cntk.cntk_py import reduce_max
x = sanitize_input(x)
axis = sanitize_multi_axis_reduction_list(axis)
return reduce_max(x, axis, keepdims, name)
|
[
"def",
"reduce_max",
"(",
"x",
",",
"axis",
"=",
"None",
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"keepdims",
"=",
"True",
",",
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"=",
"''",
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"reduce_max",
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",",
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",",
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",",
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")"
] |
https://github.com/microsoft/CNTK/blob/e9396480025b9ca457d26b6f33dd07c474c6aa04/bindings/python/cntk/ops/__init__.py#L3106-L3146
|
|
pristineio/webrtc-mirror
|
7a5bcdffaab90a05bc1146b2b1ea71c004e54d71
|
tools_webrtc/sslroots/generate_sslroots.py
|
python
|
main
|
()
|
The main entrypoint.
|
The main entrypoint.
|
[
"The",
"main",
"entrypoint",
"."
] |
def main():
"""The main entrypoint."""
parser = OptionParser('usage %prog FILE')
parser.add_option('-v', '--verbose', dest='verbose', action='store_true')
parser.add_option('-f', '--full_cert', dest='full_cert', action='store_true')
options, args = parser.parse_args()
if len(args) < 1:
parser.error('No crt file specified.')
return
root_dir = _SplitCrt(args[0], options)
_GenCFiles(root_dir, options)
_Cleanup(root_dir)
|
[
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"main",
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] |
https://github.com/pristineio/webrtc-mirror/blob/7a5bcdffaab90a05bc1146b2b1ea71c004e54d71/tools_webrtc/sslroots/generate_sslroots.py#L43-L54
|
||
miyosuda/TensorFlowAndroidMNIST
|
7b5a4603d2780a8a2834575706e9001977524007
|
jni-build/jni/include/tensorflow/contrib/slim/python/slim/nets/alexnet.py
|
python
|
alexnet_v2
|
(inputs,
num_classes=1000,
dropout_keep_prob=0.5,
is_training=True,
spatial_squeeze=True,
scope='alexnet_v2')
|
AlexNet version 2.
Described in: http://arxiv.org/pdf/1404.5997v2.pdf
Parameters from:
github.com/akrizhevsky/cuda-convnet2/blob/master/layers/
layers-imagenet-1gpu.cfg
Note: All the fully_connected layers have been transformed to conv2d layers.
To use in classification mode, resize input to 224x224. To use in fully
convolutional mode, set spatial_squeeze to false.
The LRN layers have been removed and change the initializers from
random_normal_initializer to xavier_initializer.
Args:
inputs: a tensor of size [batch_size, height, width, channels].
num_classes: number of predicted classes.
dropout_keep_prob: the probability that activations are kept in the dropout
layers during training.
is_training: whether or not the model is being trained.
spatial_squeeze: whether or not should squeeze the spatial dimensions of the
outputs. Useful to remove unnecessary dimensions for classification.
scope: Optional scope for the variables.
Returns:
the last op containing the log predictions and end_points dict.
|
AlexNet version 2.
|
[
"AlexNet",
"version",
"2",
"."
] |
def alexnet_v2(inputs,
num_classes=1000,
dropout_keep_prob=0.5,
is_training=True,
spatial_squeeze=True,
scope='alexnet_v2'):
"""AlexNet version 2.
Described in: http://arxiv.org/pdf/1404.5997v2.pdf
Parameters from:
github.com/akrizhevsky/cuda-convnet2/blob/master/layers/
layers-imagenet-1gpu.cfg
Note: All the fully_connected layers have been transformed to conv2d layers.
To use in classification mode, resize input to 224x224. To use in fully
convolutional mode, set spatial_squeeze to false.
The LRN layers have been removed and change the initializers from
random_normal_initializer to xavier_initializer.
Args:
inputs: a tensor of size [batch_size, height, width, channels].
num_classes: number of predicted classes.
dropout_keep_prob: the probability that activations are kept in the dropout
layers during training.
is_training: whether or not the model is being trained.
spatial_squeeze: whether or not should squeeze the spatial dimensions of the
outputs. Useful to remove unnecessary dimensions for classification.
scope: Optional scope for the variables.
Returns:
the last op containing the log predictions and end_points dict.
"""
with tf.variable_op_scope([inputs], scope, 'alexnet_v2') as sc:
end_points_collection = sc.name + '_end_points'
# Collect outputs for conv2d, fully_connected and max_pool2d.
with slim.arg_scope([slim.conv2d, slim.fully_connected, slim.max_pool2d],
outputs_collections=[end_points_collection]):
net = slim.conv2d(inputs, 64, [11, 11], 4, padding='VALID',
scope='conv1')
net = slim.max_pool2d(net, [3, 3], 2, scope='pool1')
net = slim.conv2d(net, 192, [5, 5], scope='conv2')
net = slim.max_pool2d(net, [3, 3], 2, scope='pool2')
net = slim.conv2d(net, 384, [3, 3], scope='conv3')
net = slim.conv2d(net, 384, [3, 3], scope='conv4')
net = slim.conv2d(net, 256, [3, 3], scope='conv5')
net = slim.max_pool2d(net, [3, 3], 2, scope='pool5')
# Use conv2d instead of fully_connected layers.
with slim.arg_scope([slim.conv2d],
weights_initializer=trunc_normal(0.005),
biases_initializer=tf.constant_initializer(0.1)):
net = slim.conv2d(net, 4096, [5, 5], padding='VALID',
scope='fc6')
net = slim.dropout(net, dropout_keep_prob, is_training=is_training,
scope='dropout6')
net = slim.conv2d(net, 4096, [1, 1], scope='fc7')
net = slim.dropout(net, dropout_keep_prob, is_training=is_training,
scope='dropout7')
net = slim.conv2d(net, num_classes, [1, 1],
activation_fn=None,
normalizer_fn=None,
biases_initializer=tf.zeros_initializer,
scope='fc8')
# Convert end_points_collection into a end_point dict.
end_points = dict(tf.get_collection(end_points_collection))
if spatial_squeeze:
net = tf.squeeze(net, [1, 2], name='fc8/squeezed')
end_points[sc.name + '/fc8'] = net
return net, end_points
|
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"+",
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"]",
"=",
"net",
"return",
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",",
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] |
https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/tensorflow/contrib/slim/python/slim/nets/alexnet.py#L51-L120
|
||
Kitware/ParaView
|
f760af9124ff4634b23ebbeab95a4f56e0261955
|
ThirdParty/cinema/paraview/tpl/cinema_python/database/file_store.py
|
python
|
FileStore.load
|
(self)
|
loads an existing filestore
|
loads an existing filestore
|
[
"loads",
"an",
"existing",
"filestore"
] |
def load(self):
"""loads an existing filestore"""
super(FileStore, self).load()
with open(self.__dbfilename, mode="r") as file:
info_json = json.load(file)
if 'arguments' in info_json:
self._set_parameter_list(info_json['arguments'])
elif 'parameter_list' in info_json:
self._set_parameter_list(info_json['parameter_list'])
else:
print("Error I can't read that file")
exit()
self.metadata = info_json['metadata']
self.filename_pattern = info_json['name_pattern']
a = {}
if 'associations' in info_json:
a = info_json['associations']
elif 'constraints' in info_json:
a = info_json['constraints']
self._set_parameter_associations(a)
|
[
"def",
"load",
"(",
"self",
")",
":",
"super",
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"FileStore",
",",
"self",
")",
".",
"load",
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")",
"with",
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"}",
"if",
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"a",
"=",
"info_json",
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"'associations'",
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"elif",
"'constraints'",
"in",
"info_json",
":",
"a",
"=",
"info_json",
"[",
"'constraints'",
"]",
"self",
".",
"_set_parameter_associations",
"(",
"a",
")"
] |
https://github.com/Kitware/ParaView/blob/f760af9124ff4634b23ebbeab95a4f56e0261955/ThirdParty/cinema/paraview/tpl/cinema_python/database/file_store.py#L45-L64
|
||
SequoiaDB/SequoiaDB
|
2894ed7e5bd6fe57330afc900cf76d0ff0df9f64
|
tools/server/php_linux/libxml2/lib/python2.4/site-packages/libxml2.py
|
python
|
xmlNode.freeNodeList
|
(self)
|
Free a node and all its siblings, this is a recursive
behaviour, all the children are freed too.
|
Free a node and all its siblings, this is a recursive
behaviour, all the children are freed too.
|
[
"Free",
"a",
"node",
"and",
"all",
"its",
"siblings",
"this",
"is",
"a",
"recursive",
"behaviour",
"all",
"the",
"children",
"are",
"freed",
"too",
"."
] |
def freeNodeList(self):
"""Free a node and all its siblings, this is a recursive
behaviour, all the children are freed too. """
libxml2mod.xmlFreeNodeList(self._o)
|
[
"def",
"freeNodeList",
"(",
"self",
")",
":",
"libxml2mod",
".",
"xmlFreeNodeList",
"(",
"self",
".",
"_o",
")"
] |
https://github.com/SequoiaDB/SequoiaDB/blob/2894ed7e5bd6fe57330afc900cf76d0ff0df9f64/tools/server/php_linux/libxml2/lib/python2.4/site-packages/libxml2.py#L3184-L3187
|
||
mongodb/mongo
|
d8ff665343ad29cf286ee2cf4a1960d29371937b
|
src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Environment.py
|
python
|
Base._update
|
(self, dict)
|
Update an environment's values directly, bypassing the normal
checks that occur when users try to set items.
|
Update an environment's values directly, bypassing the normal
checks that occur when users try to set items.
|
[
"Update",
"an",
"environment",
"s",
"values",
"directly",
"bypassing",
"the",
"normal",
"checks",
"that",
"occur",
"when",
"users",
"try",
"to",
"set",
"items",
"."
] |
def _update(self, dict):
"""Update an environment's values directly, bypassing the normal
checks that occur when users try to set items.
"""
self._dict.update(dict)
|
[
"def",
"_update",
"(",
"self",
",",
"dict",
")",
":",
"self",
".",
"_dict",
".",
"update",
"(",
"dict",
")"
] |
https://github.com/mongodb/mongo/blob/d8ff665343ad29cf286ee2cf4a1960d29371937b/src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Environment.py#L1127-L1131
|
||
baidu-research/tensorflow-allreduce
|
66d5b855e90b0949e9fa5cca5599fd729a70e874
|
tensorflow/contrib/layers/python/layers/regularizers.py
|
python
|
l1_l2_regularizer
|
(scale_l1=1.0, scale_l2=1.0, scope=None)
|
return sum_regularizer([l1_regularizer(scale_l1),
l2_regularizer(scale_l2)],
scope=scope)
|
Returns a function that can be used to apply L1 L2 regularizations.
Args:
scale_l1: A scalar multiplier `Tensor` for L1 regularization.
scale_l2: A scalar multiplier `Tensor` for L2 regularization.
scope: An optional scope name.
Returns:
A function with signature `l1_l2(weights)` that applies a weighted sum of
L1 L2 regularization.
Raises:
ValueError: If scale is negative or if scale is not a float.
|
Returns a function that can be used to apply L1 L2 regularizations.
|
[
"Returns",
"a",
"function",
"that",
"can",
"be",
"used",
"to",
"apply",
"L1",
"L2",
"regularizations",
"."
] |
def l1_l2_regularizer(scale_l1=1.0, scale_l2=1.0, scope=None):
"""Returns a function that can be used to apply L1 L2 regularizations.
Args:
scale_l1: A scalar multiplier `Tensor` for L1 regularization.
scale_l2: A scalar multiplier `Tensor` for L2 regularization.
scope: An optional scope name.
Returns:
A function with signature `l1_l2(weights)` that applies a weighted sum of
L1 L2 regularization.
Raises:
ValueError: If scale is negative or if scale is not a float.
"""
if isinstance(scale_l1, numbers.Integral):
raise ValueError('scale_l1 cannot be an integer: %s' % (scale_l1,))
if isinstance(scale_l2, numbers.Integral):
raise ValueError('scale_l2 cannot be an integer: %s' % (scale_l2,))
scope = scope or 'l1_l2_regularizer'
if scale_l1 == 0.:
return l2_regularizer(scale_l2, scope)
if scale_l2 == 0.:
return l1_regularizer(scale_l1, scope)
return sum_regularizer([l1_regularizer(scale_l1),
l2_regularizer(scale_l2)],
scope=scope)
|
[
"def",
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"scale_l1",
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"1.0",
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"]",
",",
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"=",
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")"
] |
https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/contrib/layers/python/layers/regularizers.py#L112-L138
|
|
Komnomnomnom/swigibpy
|
cfd307fdbfaffabc69a2dc037538d7e34a8b8daf
|
swigibpy.py
|
python
|
SwigPyIterator.advance
|
(self, n)
|
return _swigibpy.SwigPyIterator_advance(self, n)
|
advance(SwigPyIterator self, ptrdiff_t n) -> SwigPyIterator
|
advance(SwigPyIterator self, ptrdiff_t n) -> SwigPyIterator
|
[
"advance",
"(",
"SwigPyIterator",
"self",
"ptrdiff_t",
"n",
")",
"-",
">",
"SwigPyIterator"
] |
def advance(self, n):
"""advance(SwigPyIterator self, ptrdiff_t n) -> SwigPyIterator"""
return _swigibpy.SwigPyIterator_advance(self, n)
|
[
"def",
"advance",
"(",
"self",
",",
"n",
")",
":",
"return",
"_swigibpy",
".",
"SwigPyIterator_advance",
"(",
"self",
",",
"n",
")"
] |
https://github.com/Komnomnomnom/swigibpy/blob/cfd307fdbfaffabc69a2dc037538d7e34a8b8daf/swigibpy.py#L178-L180
|
|
Polidea/SiriusObfuscator
|
b0e590d8130e97856afe578869b83a209e2b19be
|
SymbolExtractorAndRenamer/compiler-rt/lib/sanitizer_common/scripts/cpplint.py
|
python
|
_CppLintState.SetCountingStyle
|
(self, counting_style)
|
Sets the module's counting options.
|
Sets the module's counting options.
|
[
"Sets",
"the",
"module",
"s",
"counting",
"options",
"."
] |
def SetCountingStyle(self, counting_style):
"""Sets the module's counting options."""
self.counting = counting_style
|
[
"def",
"SetCountingStyle",
"(",
"self",
",",
"counting_style",
")",
":",
"self",
".",
"counting",
"=",
"counting_style"
] |
https://github.com/Polidea/SiriusObfuscator/blob/b0e590d8130e97856afe578869b83a209e2b19be/SymbolExtractorAndRenamer/compiler-rt/lib/sanitizer_common/scripts/cpplint.py#L577-L579
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/scipy/scipy/signal/windows.py
|
python
|
bohman
|
(M, sym=True)
|
return _truncate(w, needs_trunc)
|
Return a Bohman window.
Parameters
----------
M : int
Number of points in the output window. If zero or less, an empty
array is returned.
sym : bool, optional
When True (default), generates a symmetric window, for use in filter
design.
When False, generates a periodic window, for use in spectral analysis.
Returns
-------
w : ndarray
The window, with the maximum value normalized to 1 (though the value 1
does not appear if `M` is even and `sym` is True).
Examples
--------
Plot the window and its frequency response:
>>> from scipy import signal
>>> from scipy.fftpack import fft, fftshift
>>> import matplotlib.pyplot as plt
>>> window = signal.bohman(51)
>>> plt.plot(window)
>>> plt.title("Bohman window")
>>> plt.ylabel("Amplitude")
>>> plt.xlabel("Sample")
>>> plt.figure()
>>> A = fft(window, 2048) / (len(window)/2.0)
>>> freq = np.linspace(-0.5, 0.5, len(A))
>>> response = 20 * np.log10(np.abs(fftshift(A / abs(A).max())))
>>> plt.plot(freq, response)
>>> plt.axis([-0.5, 0.5, -120, 0])
>>> plt.title("Frequency response of the Bohman window")
>>> plt.ylabel("Normalized magnitude [dB]")
>>> plt.xlabel("Normalized frequency [cycles per sample]")
|
Return a Bohman window.
|
[
"Return",
"a",
"Bohman",
"window",
"."
] |
def bohman(M, sym=True):
"""Return a Bohman window.
Parameters
----------
M : int
Number of points in the output window. If zero or less, an empty
array is returned.
sym : bool, optional
When True (default), generates a symmetric window, for use in filter
design.
When False, generates a periodic window, for use in spectral analysis.
Returns
-------
w : ndarray
The window, with the maximum value normalized to 1 (though the value 1
does not appear if `M` is even and `sym` is True).
Examples
--------
Plot the window and its frequency response:
>>> from scipy import signal
>>> from scipy.fftpack import fft, fftshift
>>> import matplotlib.pyplot as plt
>>> window = signal.bohman(51)
>>> plt.plot(window)
>>> plt.title("Bohman window")
>>> plt.ylabel("Amplitude")
>>> plt.xlabel("Sample")
>>> plt.figure()
>>> A = fft(window, 2048) / (len(window)/2.0)
>>> freq = np.linspace(-0.5, 0.5, len(A))
>>> response = 20 * np.log10(np.abs(fftshift(A / abs(A).max())))
>>> plt.plot(freq, response)
>>> plt.axis([-0.5, 0.5, -120, 0])
>>> plt.title("Frequency response of the Bohman window")
>>> plt.ylabel("Normalized magnitude [dB]")
>>> plt.xlabel("Normalized frequency [cycles per sample]")
"""
if _len_guards(M):
return np.ones(M)
M, needs_trunc = _extend(M, sym)
fac = np.abs(np.linspace(-1, 1, M)[1:-1])
w = (1 - fac) * np.cos(np.pi * fac) + 1.0 / np.pi * np.sin(np.pi * fac)
w = np.r_[0, w, 0]
return _truncate(w, needs_trunc)
|
[
"def",
"bohman",
"(",
"M",
",",
"sym",
"=",
"True",
")",
":",
"if",
"_len_guards",
"(",
"M",
")",
":",
"return",
"np",
".",
"ones",
"(",
"M",
")",
"M",
",",
"needs_trunc",
"=",
"_extend",
"(",
"M",
",",
"sym",
")",
"fac",
"=",
"np",
".",
"abs",
"(",
"np",
".",
"linspace",
"(",
"-",
"1",
",",
"1",
",",
"M",
")",
"[",
"1",
":",
"-",
"1",
"]",
")",
"w",
"=",
"(",
"1",
"-",
"fac",
")",
"*",
"np",
".",
"cos",
"(",
"np",
".",
"pi",
"*",
"fac",
")",
"+",
"1.0",
"/",
"np",
".",
"pi",
"*",
"np",
".",
"sin",
"(",
"np",
".",
"pi",
"*",
"fac",
")",
"w",
"=",
"np",
".",
"r_",
"[",
"0",
",",
"w",
",",
"0",
"]",
"return",
"_truncate",
"(",
"w",
",",
"needs_trunc",
")"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/scipy/scipy/signal/windows.py#L301-L353
|
|
quarkslab/arybo
|
89d9a4266fa51c1a560f6c4a66f65d1ffde5f093
|
arybo/lib/mba_if.py
|
python
|
simplify
|
(e)
|
return __call_impl_func(simplify_vec, e)
|
Simplify the expression or variable e.
|
Simplify the expression or variable e.
|
[
"Simplify",
"the",
"expression",
"or",
"variable",
"e",
"."
] |
def simplify(e):
''' Simplify the expression or variable e. '''
return __call_impl_func(simplify_vec, e)
|
[
"def",
"simplify",
"(",
"e",
")",
":",
"return",
"__call_impl_func",
"(",
"simplify_vec",
",",
"e",
")"
] |
https://github.com/quarkslab/arybo/blob/89d9a4266fa51c1a560f6c4a66f65d1ffde5f093/arybo/lib/mba_if.py#L60-L62
|
|
Polidea/SiriusObfuscator
|
b0e590d8130e97856afe578869b83a209e2b19be
|
SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py
|
python
|
SBSourceManager.__init__
|
(self, *args)
|
__init__(self, SBSourceManager rhs) -> SBSourceManager
|
__init__(self, SBSourceManager rhs) -> SBSourceManager
|
[
"__init__",
"(",
"self",
"SBSourceManager",
"rhs",
")",
"-",
">",
"SBSourceManager"
] |
def __init__(self, *args):
"""__init__(self, SBSourceManager rhs) -> SBSourceManager"""
this = _lldb.new_SBSourceManager(*args)
try: self.this.append(this)
except: self.this = this
|
[
"def",
"__init__",
"(",
"self",
",",
"*",
"args",
")",
":",
"this",
"=",
"_lldb",
".",
"new_SBSourceManager",
"(",
"*",
"args",
")",
"try",
":",
"self",
".",
"this",
".",
"append",
"(",
"this",
")",
"except",
":",
"self",
".",
"this",
"=",
"this"
] |
https://github.com/Polidea/SiriusObfuscator/blob/b0e590d8130e97856afe578869b83a209e2b19be/SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py#L7848-L7852
|
||
deepmodeling/deepmd-kit
|
159e45d248b0429844fb6a8cb3b3a201987c8d79
|
deepmd/env.py
|
python
|
get_tf_default_nthreads
|
()
|
return int(os.environ.get("TF_INTRA_OP_PARALLELISM_THREADS", "0")), int(
os.environ.get("TF_INTER_OP_PARALLELISM_THREADS", "0")
)
|
Get TF paralellism settings.
Returns
-------
Tuple[int, int]
number of `TF_INTRA_OP_PARALLELISM_THREADS` and
`TF_INTER_OP_PARALLELISM_THREADS`
|
Get TF paralellism settings.
|
[
"Get",
"TF",
"paralellism",
"settings",
"."
] |
def get_tf_default_nthreads() -> Tuple[int, int]:
"""Get TF paralellism settings.
Returns
-------
Tuple[int, int]
number of `TF_INTRA_OP_PARALLELISM_THREADS` and
`TF_INTER_OP_PARALLELISM_THREADS`
"""
return int(os.environ.get("TF_INTRA_OP_PARALLELISM_THREADS", "0")), int(
os.environ.get("TF_INTER_OP_PARALLELISM_THREADS", "0")
)
|
[
"def",
"get_tf_default_nthreads",
"(",
")",
"->",
"Tuple",
"[",
"int",
",",
"int",
"]",
":",
"return",
"int",
"(",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_INTRA_OP_PARALLELISM_THREADS\"",
",",
"\"0\"",
")",
")",
",",
"int",
"(",
"os",
".",
"environ",
".",
"get",
"(",
"\"TF_INTER_OP_PARALLELISM_THREADS\"",
",",
"\"0\"",
")",
")"
] |
https://github.com/deepmodeling/deepmd-kit/blob/159e45d248b0429844fb6a8cb3b3a201987c8d79/deepmd/env.py#L97-L108
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/setuptools/_vendor/pyparsing.py
|
python
|
withClass
|
(classname, namespace='')
|
return withAttribute(**{classattr : classname})
|
Simplified version of C{L{withAttribute}} when matching on a div class - made
difficult because C{class} is a reserved word in Python.
Example::
html = '''
<div>
Some text
<div class="grid">1 4 0 1 0</div>
<div class="graph">1,3 2,3 1,1</div>
<div>this <div> has no class</div>
</div>
'''
div,div_end = makeHTMLTags("div")
div_grid = div().setParseAction(withClass("grid"))
grid_expr = div_grid + SkipTo(div | div_end)("body")
for grid_header in grid_expr.searchString(html):
print(grid_header.body)
div_any_type = div().setParseAction(withClass(withAttribute.ANY_VALUE))
div_expr = div_any_type + SkipTo(div | div_end)("body")
for div_header in div_expr.searchString(html):
print(div_header.body)
prints::
1 4 0 1 0
1 4 0 1 0
1,3 2,3 1,1
|
Simplified version of C{L{withAttribute}} when matching on a div class - made
difficult because C{class} is a reserved word in Python.
|
[
"Simplified",
"version",
"of",
"C",
"{",
"L",
"{",
"withAttribute",
"}}",
"when",
"matching",
"on",
"a",
"div",
"class",
"-",
"made",
"difficult",
"because",
"C",
"{",
"class",
"}",
"is",
"a",
"reserved",
"word",
"in",
"Python",
"."
] |
def withClass(classname, namespace=''):
"""
Simplified version of C{L{withAttribute}} when matching on a div class - made
difficult because C{class} is a reserved word in Python.
Example::
html = '''
<div>
Some text
<div class="grid">1 4 0 1 0</div>
<div class="graph">1,3 2,3 1,1</div>
<div>this <div> has no class</div>
</div>
'''
div,div_end = makeHTMLTags("div")
div_grid = div().setParseAction(withClass("grid"))
grid_expr = div_grid + SkipTo(div | div_end)("body")
for grid_header in grid_expr.searchString(html):
print(grid_header.body)
div_any_type = div().setParseAction(withClass(withAttribute.ANY_VALUE))
div_expr = div_any_type + SkipTo(div | div_end)("body")
for div_header in div_expr.searchString(html):
print(div_header.body)
prints::
1 4 0 1 0
1 4 0 1 0
1,3 2,3 1,1
"""
classattr = "%s:class" % namespace if namespace else "class"
return withAttribute(**{classattr : classname})
|
[
"def",
"withClass",
"(",
"classname",
",",
"namespace",
"=",
"''",
")",
":",
"classattr",
"=",
"\"%s:class\"",
"%",
"namespace",
"if",
"namespace",
"else",
"\"class\"",
"return",
"withAttribute",
"(",
"*",
"*",
"{",
"classattr",
":",
"classname",
"}",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/setuptools/_vendor/pyparsing.py#L4997-L5030
|
|
thalium/icebox
|
99d147d5b9269222225443ce171b4fd46d8985d4
|
third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2.py
|
python
|
readerForDoc
|
(cur, URL, encoding, options)
|
return xmlTextReader(_obj=ret)
|
Create an xmltextReader for an XML in-memory document. The
parsing flags @options are a combination of xmlParserOption.
|
Create an xmltextReader for an XML in-memory document. The
parsing flags
|
[
"Create",
"an",
"xmltextReader",
"for",
"an",
"XML",
"in",
"-",
"memory",
"document",
".",
"The",
"parsing",
"flags"
] |
def readerForDoc(cur, URL, encoding, options):
"""Create an xmltextReader for an XML in-memory document. The
parsing flags @options are a combination of xmlParserOption. """
ret = libxml2mod.xmlReaderForDoc(cur, URL, encoding, options)
if ret is None:raise treeError('xmlReaderForDoc() failed')
return xmlTextReader(_obj=ret)
|
[
"def",
"readerForDoc",
"(",
"cur",
",",
"URL",
",",
"encoding",
",",
"options",
")",
":",
"ret",
"=",
"libxml2mod",
".",
"xmlReaderForDoc",
"(",
"cur",
",",
"URL",
",",
"encoding",
",",
"options",
")",
"if",
"ret",
"is",
"None",
":",
"raise",
"treeError",
"(",
"'xmlReaderForDoc() failed'",
")",
"return",
"xmlTextReader",
"(",
"_obj",
"=",
"ret",
")"
] |
https://github.com/thalium/icebox/blob/99d147d5b9269222225443ce171b4fd46d8985d4/third_party/virtualbox/src/libs/libxml2-2.9.4/python/libxml2.py#L1950-L1955
|
|
generalized-intelligence/GAAS
|
29ab17d3e8a4ba18edef3a57c36d8db6329fac73
|
deprecated/algorithms/sfm/OpenSfM/opensfm/io.py
|
python
|
point_to_json
|
(point)
|
return {
'color': list(point.color),
'coordinates': list(point.coordinates),
'reprojection_error': point.reprojection_error
}
|
Write a point to a json object
|
Write a point to a json object
|
[
"Write",
"a",
"point",
"to",
"a",
"json",
"object"
] |
def point_to_json(point):
"""
Write a point to a json object
"""
return {
'color': list(point.color),
'coordinates': list(point.coordinates),
'reprojection_error': point.reprojection_error
}
|
[
"def",
"point_to_json",
"(",
"point",
")",
":",
"return",
"{",
"'color'",
":",
"list",
"(",
"point",
".",
"color",
")",
",",
"'coordinates'",
":",
"list",
"(",
"point",
".",
"coordinates",
")",
",",
"'reprojection_error'",
":",
"point",
".",
"reprojection_error",
"}"
] |
https://github.com/generalized-intelligence/GAAS/blob/29ab17d3e8a4ba18edef3a57c36d8db6329fac73/deprecated/algorithms/sfm/OpenSfM/opensfm/io.py#L297-L305
|
|
apiaryio/snowcrash
|
b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3
|
tools/gyp/tools/pretty_gyp.py
|
python
|
split_double_braces
|
(input)
|
return output
|
Masks out the quotes and comments, and then splits appropriate
lines (lines that matche the double_*_brace re's above) before
indenting them below.
These are used to split lines which have multiple braces on them, so
that the indentation looks prettier when all laid out (e.g. closing
braces make a nice diagonal line).
|
Masks out the quotes and comments, and then splits appropriate
lines (lines that matche the double_*_brace re's above) before
indenting them below.
|
[
"Masks",
"out",
"the",
"quotes",
"and",
"comments",
"and",
"then",
"splits",
"appropriate",
"lines",
"(",
"lines",
"that",
"matche",
"the",
"double_",
"*",
"_brace",
"re",
"s",
"above",
")",
"before",
"indenting",
"them",
"below",
"."
] |
def split_double_braces(input):
"""Masks out the quotes and comments, and then splits appropriate
lines (lines that matche the double_*_brace re's above) before
indenting them below.
These are used to split lines which have multiple braces on them, so
that the indentation looks prettier when all laid out (e.g. closing
braces make a nice diagonal line).
"""
double_open_brace_re = re.compile(r'(.*?[\[\{\(,])(\s*)([\[\{\(])')
double_close_brace_re = re.compile(r'(.*?[\]\}\)],?)(\s*)([\]\}\)])')
masked_input = mask_quotes(input)
masked_input = mask_comments(masked_input)
(output, mask_output) = do_split(input, masked_input, double_open_brace_re)
(output, mask_output) = do_split(output, mask_output, double_close_brace_re)
return output
|
[
"def",
"split_double_braces",
"(",
"input",
")",
":",
"double_open_brace_re",
"=",
"re",
".",
"compile",
"(",
"r'(.*?[\\[\\{\\(,])(\\s*)([\\[\\{\\(])'",
")",
"double_close_brace_re",
"=",
"re",
".",
"compile",
"(",
"r'(.*?[\\]\\}\\)],?)(\\s*)([\\]\\}\\)])'",
")",
"masked_input",
"=",
"mask_quotes",
"(",
"input",
")",
"masked_input",
"=",
"mask_comments",
"(",
"masked_input",
")",
"(",
"output",
",",
"mask_output",
")",
"=",
"do_split",
"(",
"input",
",",
"masked_input",
",",
"double_open_brace_re",
")",
"(",
"output",
",",
"mask_output",
")",
"=",
"do_split",
"(",
"output",
",",
"mask_output",
",",
"double_close_brace_re",
")",
"return",
"output"
] |
https://github.com/apiaryio/snowcrash/blob/b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3/tools/gyp/tools/pretty_gyp.py#L62-L80
|
|
epam/Indigo
|
30e40b4b1eb9bae0207435a26cfcb81ddcc42be1
|
api/python/indigo/__init__.py
|
python
|
IndigoObject.iterateMatches
|
(self, query)
|
return self.dispatcher.IndigoObject(
self.dispatcher,
self.dispatcher._checkResult(
Indigo._lib.indigoIterateMatches(self.id, query.id)
),
)
|
Matcher method returns matches iterator
Args:
query (IndigoObject): query structure
Returns:
IndigoObject: matches iterator
|
Matcher method returns matches iterator
|
[
"Matcher",
"method",
"returns",
"matches",
"iterator"
] |
def iterateMatches(self, query):
"""Matcher method returns matches iterator
Args:
query (IndigoObject): query structure
Returns:
IndigoObject: matches iterator
"""
self.dispatcher._setSessionId()
return self.dispatcher.IndigoObject(
self.dispatcher,
self.dispatcher._checkResult(
Indigo._lib.indigoIterateMatches(self.id, query.id)
),
)
|
[
"def",
"iterateMatches",
"(",
"self",
",",
"query",
")",
":",
"self",
".",
"dispatcher",
".",
"_setSessionId",
"(",
")",
"return",
"self",
".",
"dispatcher",
".",
"IndigoObject",
"(",
"self",
".",
"dispatcher",
",",
"self",
".",
"dispatcher",
".",
"_checkResult",
"(",
"Indigo",
".",
"_lib",
".",
"indigoIterateMatches",
"(",
"self",
".",
"id",
",",
"query",
".",
"id",
")",
")",
",",
")"
] |
https://github.com/epam/Indigo/blob/30e40b4b1eb9bae0207435a26cfcb81ddcc42be1/api/python/indigo/__init__.py#L3896-L3911
|
|
cocos-creator/engine-native
|
984c4c9f5838253313b44ccd429bd8fac4ec8a6a
|
tools/bindings-generator/clang/cindex.py
|
python
|
CursorKind.is_unexposed
|
(self)
|
return conf.lib.clang_isUnexposed(self)
|
Test if this is an unexposed kind.
|
Test if this is an unexposed kind.
|
[
"Test",
"if",
"this",
"is",
"an",
"unexposed",
"kind",
"."
] |
def is_unexposed(self):
"""Test if this is an unexposed kind."""
return conf.lib.clang_isUnexposed(self)
|
[
"def",
"is_unexposed",
"(",
"self",
")",
":",
"return",
"conf",
".",
"lib",
".",
"clang_isUnexposed",
"(",
"self",
")"
] |
https://github.com/cocos-creator/engine-native/blob/984c4c9f5838253313b44ccd429bd8fac4ec8a6a/tools/bindings-generator/clang/cindex.py#L703-L705
|
|
okex/V3-Open-API-SDK
|
c5abb0db7e2287718e0055e17e57672ce0ec7fd9
|
okex-python-sdk-api/venv/Lib/site-packages/pip-19.0.3-py3.8.egg/pip/_internal/vcs/subversion.py
|
python
|
Subversion.export
|
(self, location)
|
Export the svn repository at the url to the destination location
|
Export the svn repository at the url to the destination location
|
[
"Export",
"the",
"svn",
"repository",
"at",
"the",
"url",
"to",
"the",
"destination",
"location"
] |
def export(self, location):
"""Export the svn repository at the url to the destination location"""
url, rev_options = self.get_url_rev_options(self.url)
logger.info('Exporting svn repository %s to %s', url, location)
with indent_log():
if os.path.exists(location):
# Subversion doesn't like to check out over an existing
# directory --force fixes this, but was only added in svn 1.5
rmtree(location)
cmd_args = ['export'] + rev_options.to_args() + [url, location]
self.run_command(cmd_args, show_stdout=False)
|
[
"def",
"export",
"(",
"self",
",",
"location",
")",
":",
"url",
",",
"rev_options",
"=",
"self",
".",
"get_url_rev_options",
"(",
"self",
".",
"url",
")",
"logger",
".",
"info",
"(",
"'Exporting svn repository %s to %s'",
",",
"url",
",",
"location",
")",
"with",
"indent_log",
"(",
")",
":",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"location",
")",
":",
"# Subversion doesn't like to check out over an existing",
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".",
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"(",
"cmd_args",
",",
"show_stdout",
"=",
"False",
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https://github.com/okex/V3-Open-API-SDK/blob/c5abb0db7e2287718e0055e17e57672ce0ec7fd9/okex-python-sdk-api/venv/Lib/site-packages/pip-19.0.3-py3.8.egg/pip/_internal/vcs/subversion.py#L31-L42
|
||
apple/turicreate
|
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
|
src/external/boost/boost_1_68_0/tools/build/src/build/targets.py
|
python
|
BasicTarget.construct
|
(self, name, source_targets, properties)
|
Constructs the virtual targets for this abstract targets and
the dependecy graph. Returns a tuple consisting of the properties and the list of virtual targets.
Should be overrided in derived classes.
|
Constructs the virtual targets for this abstract targets and
the dependecy graph. Returns a tuple consisting of the properties and the list of virtual targets.
Should be overrided in derived classes.
|
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"Constructs",
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] |
def construct (self, name, source_targets, properties):
""" Constructs the virtual targets for this abstract targets and
the dependecy graph. Returns a tuple consisting of the properties and the list of virtual targets.
Should be overrided in derived classes.
"""
raise BaseException ("method should be defined in derived classes")
|
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https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/src/external/boost/boost_1_68_0/tools/build/src/build/targets.py#L1372-L1377
|
||
francinexue/xuefu
|
b6ff79747a42e020588c0c0a921048e08fe4680c
|
api/ctpx/ctptd.py
|
python
|
CtpTd.onRtnFromBankToFutureByFuture
|
(self, RspTransferField)
|
期货发起银行资金转期货通知
|
期货发起银行资金转期货通知
|
[
"期货发起银行资金转期货通知"
] |
def onRtnFromBankToFutureByFuture(self, RspTransferField):
"""期货发起银行资金转期货通知"""
pass
|
[
"def",
"onRtnFromBankToFutureByFuture",
"(",
"self",
",",
"RspTransferField",
")",
":",
"pass"
] |
https://github.com/francinexue/xuefu/blob/b6ff79747a42e020588c0c0a921048e08fe4680c/api/ctpx/ctptd.py#L475-L477
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/_core.py
|
python
|
PyApp.GetTraitsIfExists
|
(*args, **kwargs)
|
return _core_.PyApp_GetTraitsIfExists(*args, **kwargs)
|
GetTraitsIfExists() -> wxAppTraits
This function provides safer access to traits object than
wx.GetApp().GetTraits() during startup or termination when the global
application object itself may be unavailable.
|
GetTraitsIfExists() -> wxAppTraits
|
[
"GetTraitsIfExists",
"()",
"-",
">",
"wxAppTraits"
] |
def GetTraitsIfExists(*args, **kwargs):
"""
GetTraitsIfExists() -> wxAppTraits
This function provides safer access to traits object than
wx.GetApp().GetTraits() during startup or termination when the global
application object itself may be unavailable.
"""
return _core_.PyApp_GetTraitsIfExists(*args, **kwargs)
|
[
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"PyApp_GetTraitsIfExists",
"(",
"*",
"args",
",",
"*",
"*",
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")"
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_core.py#L7819-L7827
|
|
ChromiumWebApps/chromium
|
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
|
third_party/google_appengine_cloudstorage/cloudstorage/storage_api.py
|
python
|
StreamingBuffer.write
|
(self, data)
|
Write some bytes.
Args:
data: data to write. str.
Raises:
TypeError: if data is not of type str.
|
Write some bytes.
|
[
"Write",
"some",
"bytes",
"."
] |
def write(self, data):
"""Write some bytes.
Args:
data: data to write. str.
Raises:
TypeError: if data is not of type str.
"""
self._check_open()
if not isinstance(data, str):
raise TypeError('Expected str but got %s.' % type(data))
if not data:
return
self._buffer.append(data)
self._buffered += len(data)
self._offset += len(data)
if self._buffered >= self._blocksize:
self._flush()
|
[
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/third_party/google_appengine_cloudstorage/cloudstorage/storage_api.py#L683-L701
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/msw/grid.py
|
python
|
GridCellBoolEditor_IsTrueValue
|
(*args, **kwargs)
|
return _grid.GridCellBoolEditor_IsTrueValue(*args, **kwargs)
|
GridCellBoolEditor_IsTrueValue(String value) -> bool
|
GridCellBoolEditor_IsTrueValue(String value) -> bool
|
[
"GridCellBoolEditor_IsTrueValue",
"(",
"String",
"value",
")",
"-",
">",
"bool"
] |
def GridCellBoolEditor_IsTrueValue(*args, **kwargs):
"""GridCellBoolEditor_IsTrueValue(String value) -> bool"""
return _grid.GridCellBoolEditor_IsTrueValue(*args, **kwargs)
|
[
"def",
"GridCellBoolEditor_IsTrueValue",
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",",
"*",
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"GridCellBoolEditor_IsTrueValue",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/grid.py#L477-L479
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/_core.py
|
python
|
CloseEvent.SetCanVeto
|
(*args, **kwargs)
|
return _core_.CloseEvent_SetCanVeto(*args, **kwargs)
|
SetCanVeto(self, bool canVeto)
Sets the 'can veto' flag.
|
SetCanVeto(self, bool canVeto)
|
[
"SetCanVeto",
"(",
"self",
"bool",
"canVeto",
")"
] |
def SetCanVeto(*args, **kwargs):
"""
SetCanVeto(self, bool canVeto)
Sets the 'can veto' flag.
"""
return _core_.CloseEvent_SetCanVeto(*args, **kwargs)
|
[
"def",
"SetCanVeto",
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"*",
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"CloseEvent_SetCanVeto",
"(",
"*",
"args",
",",
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"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_core.py#L6542-L6548
|
|
yyzybb537/libgo
|
4af17b7c67643c4d54aa354dcc77963ea07847d0
|
third_party/boost.context/tools/build/src/build/type.py
|
python
|
all_derived
|
(type)
|
return result
|
Returns type and all classes that derive from it, in the order of their distance from type.
|
Returns type and all classes that derive from it, in the order of their distance from type.
|
[
"Returns",
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"and",
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"that",
"derive",
"from",
"it",
"in",
"the",
"order",
"of",
"their",
"distance",
"from",
"type",
"."
] |
def all_derived (type):
""" Returns type and all classes that derive from it, in the order of their distance from type.
"""
assert isinstance(type, basestring)
result = [type]
for d in __types [type]['derived']:
result.extend (all_derived (d))
return result
|
[
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"all_derived",
"(",
"d",
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")",
"return",
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] |
https://github.com/yyzybb537/libgo/blob/4af17b7c67643c4d54aa354dcc77963ea07847d0/third_party/boost.context/tools/build/src/build/type.py#L187-L195
|
|
miyosuda/TensorFlowAndroidMNIST
|
7b5a4603d2780a8a2834575706e9001977524007
|
jni-build/jni/include/external/bazel_tools/third_party/py/concurrent/futures/_base.py
|
python
|
Future.exception
|
(self, timeout=None)
|
Return the exception raised by the call that the future represents.
Args:
timeout: The number of seconds to wait for the exception if the
future isn't done. If None, then there is no limit on the wait
time.
Returns:
The exception raised by the call that the future represents or None
if the call completed without raising.
Raises:
CancelledError: If the future was cancelled.
TimeoutError: If the future didn't finish executing before the given
timeout.
|
Return the exception raised by the call that the future represents.
|
[
"Return",
"the",
"exception",
"raised",
"by",
"the",
"call",
"that",
"the",
"future",
"represents",
"."
] |
def exception(self, timeout=None):
"""Return the exception raised by the call that the future represents.
Args:
timeout: The number of seconds to wait for the exception if the
future isn't done. If None, then there is no limit on the wait
time.
Returns:
The exception raised by the call that the future represents or None
if the call completed without raising.
Raises:
CancelledError: If the future was cancelled.
TimeoutError: If the future didn't finish executing before the given
timeout.
"""
with self._condition:
if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:
raise CancelledError()
elif self._state == FINISHED:
return self._exception
self._condition.wait(timeout)
if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:
raise CancelledError()
elif self._state == FINISHED:
return self._exception
else:
raise TimeoutError()
|
[
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https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/external/bazel_tools/third_party/py/concurrent/futures/_base.py#L409-L440
|
||
tensorflow/tensorflow
|
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
|
tensorflow/python/client/session.py
|
python
|
BaseSession._make_callable_from_options
|
(self, callable_options)
|
return BaseSession._Callable(self, callable_options)
|
Returns a handle to a "callable" with the given options.
Args:
callable_options: A `CallableOptions` protocol buffer message describing
the computation that will be performed by the callable.
Returns:
A handle to the new callable.
|
Returns a handle to a "callable" with the given options.
|
[
"Returns",
"a",
"handle",
"to",
"a",
"callable",
"with",
"the",
"given",
"options",
"."
] |
def _make_callable_from_options(self, callable_options):
"""Returns a handle to a "callable" with the given options.
Args:
callable_options: A `CallableOptions` protocol buffer message describing
the computation that will be performed by the callable.
Returns:
A handle to the new callable.
"""
self._extend_graph()
return BaseSession._Callable(self, callable_options)
|
[
"def",
"_make_callable_from_options",
"(",
"self",
",",
"callable_options",
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":",
"self",
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"_extend_graph",
"(",
")",
"return",
"BaseSession",
".",
"_Callable",
"(",
"self",
",",
"callable_options",
")"
] |
https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/client/session.py#L1502-L1513
|
|
mantidproject/mantid
|
03deeb89254ec4289edb8771e0188c2090a02f32
|
qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/generalplotview.py
|
python
|
GeneralPlotWindow.do_export_plot
|
(self)
|
export plot
:return:
|
export plot
:return:
|
[
"export",
"plot",
":",
"return",
":"
] |
def do_export_plot(self):
"""
export plot
:return:
"""
# get directory
file_name = QFileDialog.getSaveFileName(self, caption='File to save the plot',
directory=self._work_dir,
filter='Data File(*.dat);;All Files(*.*')
if not file_name:
return
if isinstance(file_name, tuple):
file_name = file_name[0]
self.ui.graphicsView_plotView.save_current_plot(None, file_name)
|
[
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"(",
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https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/generalplotview.py#L51-L65
|
||
oracle/graaljs
|
36a56e8e993d45fc40939a3a4d9c0c24990720f1
|
graal-nodejs/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/eclipse.py
|
python
|
GetJavaJars
|
(target_list, target_dicts, toplevel_dir)
|
Generates a sequence of all .jars used as inputs.
|
Generates a sequence of all .jars used as inputs.
|
[
"Generates",
"a",
"sequence",
"of",
"all",
".",
"jars",
"used",
"as",
"inputs",
"."
] |
def GetJavaJars(target_list, target_dicts, toplevel_dir):
"""Generates a sequence of all .jars used as inputs."""
for target_name in target_list:
target = target_dicts[target_name]
for action in target.get("actions", []):
for input_ in action["inputs"]:
if os.path.splitext(input_)[1] == ".jar" and not input_.startswith("$"):
if os.path.isabs(input_):
yield input_
else:
yield os.path.join(os.path.dirname(target_name), input_)
|
[
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https://github.com/oracle/graaljs/blob/36a56e8e993d45fc40939a3a4d9c0c24990720f1/graal-nodejs/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/eclipse.py#L409-L419
|
||
fifengine/fifengine
|
4b62c42e85bec19893cef8e63e6855927cff2c47
|
engine/python/fife/extensions/pychan/__init__.py
|
python
|
setupModalExecution
|
(mainLoop,breakFromMainLoop)
|
Setup the synchronous dialog execution feature.
You can enable synchronous dialog execution by
passing to functions to this function.
@param mainLoop: Function - This is regarded as the applications
main loop, which should be able to be called recursively.
It should not take no arguments and return the argument
passed to the second function (breakFromMainLoop).
@param breakFromMainLoop: Function -This function should cause the
first function to finish and return the passed argument.
With these to functions dialogs can be executed synchronously.
See L{widgets.Widget.execute}.
|
Setup the synchronous dialog execution feature.
|
[
"Setup",
"the",
"synchronous",
"dialog",
"execution",
"feature",
"."
] |
def setupModalExecution(mainLoop,breakFromMainLoop):
"""
Setup the synchronous dialog execution feature.
You can enable synchronous dialog execution by
passing to functions to this function.
@param mainLoop: Function - This is regarded as the applications
main loop, which should be able to be called recursively.
It should not take no arguments and return the argument
passed to the second function (breakFromMainLoop).
@param breakFromMainLoop: Function -This function should cause the
first function to finish and return the passed argument.
With these to functions dialogs can be executed synchronously.
See L{widgets.Widget.execute}.
"""
if not manager:
raise InitializationError("PyChan is not initialized yet.")
manager.setupModalExecution(mainLoop,breakFromMainLoop)
|
[
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"setupModalExecution",
"(",
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",",
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"\"PyChan is not initialized yet.\"",
")",
"manager",
".",
"setupModalExecution",
"(",
"mainLoop",
",",
"breakFromMainLoop",
")"
] |
https://github.com/fifengine/fifengine/blob/4b62c42e85bec19893cef8e63e6855927cff2c47/engine/python/fife/extensions/pychan/__init__.py#L405-L425
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/xrc.py
|
python
|
XmlResourceHandler.GetDimension
|
(*args, **kwargs)
|
return _xrc.XmlResourceHandler_GetDimension(*args, **kwargs)
|
GetDimension(self, String param, int defaultv=0) -> int
|
GetDimension(self, String param, int defaultv=0) -> int
|
[
"GetDimension",
"(",
"self",
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"0",
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def GetDimension(*args, **kwargs):
"""GetDimension(self, String param, int defaultv=0) -> int"""
return _xrc.XmlResourceHandler_GetDimension(*args, **kwargs)
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/xrc.py#L691-L693
|
|
gromacs/gromacs
|
7dec3a3f99993cf5687a122de3e12de31c21c399
|
docs/doxygen/gmxtree.py
|
python
|
File.get_used_define_files
|
(self)
|
return set(self._used_defines.keys())
|
Return files like config.h whose defines are used in this file.
The return value is empty if find_define_file_uses() has not been called,
as well as for headers that declare these defines.
|
Return files like config.h whose defines are used in this file.
|
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".",
"h",
"whose",
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"are",
"used",
"in",
"this",
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"."
] |
def get_used_define_files(self):
"""Return files like config.h whose defines are used in this file.
The return value is empty if find_define_file_uses() has not been called,
as well as for headers that declare these defines."""
return set(self._used_defines.keys())
|
[
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"(",
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https://github.com/gromacs/gromacs/blob/7dec3a3f99993cf5687a122de3e12de31c21c399/docs/doxygen/gmxtree.py#L353-L358
|
|
baidu/lac
|
3e10dbed9bfd87bea927c84a6627a167c17b5617
|
python/LAC/ahocorasick.py
|
python
|
Ahocorasick.__init__
|
(self)
|
初始化Ahocorasick的根节点__root
|
初始化Ahocorasick的根节点__root
|
[
"初始化Ahocorasick的根节点__root"
] |
def __init__(self):
"""初始化Ahocorasick的根节点__root"""
self.__root = Node()
|
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"(",
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")",
":",
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"__root",
"=",
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")"
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https://github.com/baidu/lac/blob/3e10dbed9bfd87bea927c84a6627a167c17b5617/python/LAC/ahocorasick.py#L50-L52
|
||
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/linear_optimizer/python/sdca_estimator.py
|
python
|
SDCALinearRegressor.__init__
|
(self,
example_id_column,
feature_columns,
weight_column_name=None,
model_dir=None,
l1_regularization=0.0,
l2_regularization=1.0,
num_loss_partitions=None,
config=None,
feature_engineering_fn=None,
partitioner=None)
|
Construct a `SDCALinearRegressor` estimator object.
Args:
example_id_column: A string defining the feature column name representing
example ids. Used to initialize the underlying SDCA optimizer.
feature_columns: An iterable containing all the feature columns used by
the model. All items in the iterable should derive from `FeatureColumn`.
Note that the order of the items is ignored at model construction time.
weight_column_name: A string defining feature column name representing
weights. It is used to down weight or boost examples during training. It
will be multiplied by the loss of the example.
model_dir: Directory to save model parameters, graph etc. This can also be
used to load checkpoints from the directory into an estimator to
continue training a previously saved model.
l1_regularization: L1-regularization parameter. Refers to global L1
regularization (across all examples).
l2_regularization: L2-regularization parameter. Refers to global L2
regularization (across all examples).
num_loss_partitions: number of partitions of the (global) loss function
optimized by the underlying optimizer (SDCAOptimizer).
config: `RunConfig` object to configure the runtime settings.
feature_engineering_fn: Feature engineering function. Takes features and
labels which are the output of `input_fn` and returns features and
labels which will be fed into the model.
partitioner: Variable partitioner for the primal weights (`div`
partitioning strategy will be used).
Returns:
A `SDCALinearRegressor` estimator.
|
Construct a `SDCALinearRegressor` estimator object.
|
[
"Construct",
"a",
"SDCALinearRegressor",
"estimator",
"object",
"."
] |
def __init__(self,
example_id_column,
feature_columns,
weight_column_name=None,
model_dir=None,
l1_regularization=0.0,
l2_regularization=1.0,
num_loss_partitions=None,
config=None,
feature_engineering_fn=None,
partitioner=None):
"""Construct a `SDCALinearRegressor` estimator object.
Args:
example_id_column: A string defining the feature column name representing
example ids. Used to initialize the underlying SDCA optimizer.
feature_columns: An iterable containing all the feature columns used by
the model. All items in the iterable should derive from `FeatureColumn`.
Note that the order of the items is ignored at model construction time.
weight_column_name: A string defining feature column name representing
weights. It is used to down weight or boost examples during training. It
will be multiplied by the loss of the example.
model_dir: Directory to save model parameters, graph etc. This can also be
used to load checkpoints from the directory into an estimator to
continue training a previously saved model.
l1_regularization: L1-regularization parameter. Refers to global L1
regularization (across all examples).
l2_regularization: L2-regularization parameter. Refers to global L2
regularization (across all examples).
num_loss_partitions: number of partitions of the (global) loss function
optimized by the underlying optimizer (SDCAOptimizer).
config: `RunConfig` object to configure the runtime settings.
feature_engineering_fn: Feature engineering function. Takes features and
labels which are the output of `input_fn` and returns features and
labels which will be fed into the model.
partitioner: Variable partitioner for the primal weights (`div`
partitioning strategy will be used).
Returns:
A `SDCALinearRegressor` estimator.
"""
super(SDCALinearRegressor, self).__init__(
example_id_column=example_id_column,
feature_columns=feature_columns,
weight_column_name=weight_column_name,
model_dir=model_dir,
head=head_lib.regression_head(weight_column_name=weight_column_name),
l1_regularization=l1_regularization,
l2_regularization=l2_regularization,
num_loss_partitions=num_loss_partitions,
config=config,
feature_engineering_fn=None,
partitioner=partitioner)
|
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/linear_optimizer/python/sdca_estimator.py#L468-L521
|
||
natanielruiz/android-yolo
|
1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f
|
jni-build/jni/include/tensorflow/python/ops/linalg_ops.py
|
python
|
batch_svd
|
(tensor, compute_uv=True, full_matrices=False, name=None)
|
Computes the singular value decompositions of a batch of matrices.
Computes the SVD of each inner matrix in `tensor` such that
`tensor[..., :, :] = u[..., :, :] * diag(s[..., :, :]) * transpose(v[..., :,
:])`
```prettyprint
# a is a tensor.
# s is a tensor of singular values.
# u is a tensor of left singular vectors.
# v is a tensor of right singular vectors.
s, u, v = batch_svd(a)
s = batch_svd(a, compute_uv=False)
```
Args:
matrix: `Tensor` of shape `[..., M, N]`. Let `P` be the minimum of `M` and
`N`.
compute_uv: If `True` then left and right singular vectors will be
computed and returned in `u` and `v`, respectively. Otherwise, only the
singular values will be computed, which can be significantly faster.
full_matrices: If true, compute full-sized `u` and `v`. If false
(the default), compute only the leading `P` singular vectors.
Ignored if `compute_uv` is `False`.
name: string, optional name of the operation.
Returns:
s: Singular values. Shape is `[..., P]`.
u: Right singular vectors. If `full_matrices` is `False` (default) then
shape is `[..., M, P]`; if `full_matrices` is `True` then shape is
`[..., M, M]`. Not returned if `compute_uv` is `False`.
v: Left singular vectors. If `full_matrices` is `False` (default) then
shape is `[..., N, P]`. If `full_matrices` is `True` then shape is
`[..., N, N]`. Not returned if `compute_uv` is `False`.
|
Computes the singular value decompositions of a batch of matrices.
|
[
"Computes",
"the",
"singular",
"value",
"decompositions",
"of",
"a",
"batch",
"of",
"matrices",
"."
] |
def batch_svd(tensor, compute_uv=True, full_matrices=False, name=None):
"""Computes the singular value decompositions of a batch of matrices.
Computes the SVD of each inner matrix in `tensor` such that
`tensor[..., :, :] = u[..., :, :] * diag(s[..., :, :]) * transpose(v[..., :,
:])`
```prettyprint
# a is a tensor.
# s is a tensor of singular values.
# u is a tensor of left singular vectors.
# v is a tensor of right singular vectors.
s, u, v = batch_svd(a)
s = batch_svd(a, compute_uv=False)
```
Args:
matrix: `Tensor` of shape `[..., M, N]`. Let `P` be the minimum of `M` and
`N`.
compute_uv: If `True` then left and right singular vectors will be
computed and returned in `u` and `v`, respectively. Otherwise, only the
singular values will be computed, which can be significantly faster.
full_matrices: If true, compute full-sized `u` and `v`. If false
(the default), compute only the leading `P` singular vectors.
Ignored if `compute_uv` is `False`.
name: string, optional name of the operation.
Returns:
s: Singular values. Shape is `[..., P]`.
u: Right singular vectors. If `full_matrices` is `False` (default) then
shape is `[..., M, P]`; if `full_matrices` is `True` then shape is
`[..., M, M]`. Not returned if `compute_uv` is `False`.
v: Left singular vectors. If `full_matrices` is `False` (default) then
shape is `[..., N, P]`. If `full_matrices` is `True` then shape is
`[..., N, N]`. Not returned if `compute_uv` is `False`.
"""
s, u, v = gen_linalg_ops.batch_svd(
tensor, compute_uv=compute_uv, full_matrices=full_matrices)
if compute_uv:
return s, u, v
else:
return s
|
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https://github.com/natanielruiz/android-yolo/blob/1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f/jni-build/jni/include/tensorflow/python/ops/linalg_ops.py#L522-L563
|
||
larroy/clearskies_core
|
3574ddf0edc8555454c7044126e786a6c29444dc
|
tools/gyp/pylib/gyp/generator/ninja.py
|
python
|
NinjaWriter.__init__
|
(self, qualified_target, target_outputs, base_dir, build_dir,
output_file, toplevel_build, output_file_name, flavor,
toplevel_dir=None)
|
base_dir: path from source root to directory containing this gyp file,
by gyp semantics, all input paths are relative to this
build_dir: path from source root to build output
toplevel_dir: path to the toplevel directory
|
base_dir: path from source root to directory containing this gyp file,
by gyp semantics, all input paths are relative to this
build_dir: path from source root to build output
toplevel_dir: path to the toplevel directory
|
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"output",
"toplevel_dir",
":",
"path",
"to",
"the",
"toplevel",
"directory"
] |
def __init__(self, qualified_target, target_outputs, base_dir, build_dir,
output_file, toplevel_build, output_file_name, flavor,
toplevel_dir=None):
"""
base_dir: path from source root to directory containing this gyp file,
by gyp semantics, all input paths are relative to this
build_dir: path from source root to build output
toplevel_dir: path to the toplevel directory
"""
self.qualified_target = qualified_target
self.target_outputs = target_outputs
self.base_dir = base_dir
self.build_dir = build_dir
self.ninja = ninja_syntax.Writer(output_file)
self.toplevel_build = toplevel_build
self.output_file_name = output_file_name
self.flavor = flavor
self.abs_build_dir = None
if toplevel_dir is not None:
self.abs_build_dir = os.path.abspath(os.path.join(toplevel_dir,
build_dir))
self.obj_ext = '.obj' if flavor == 'win' else '.o'
if flavor == 'win':
# See docstring of msvs_emulation.GenerateEnvironmentFiles().
self.win_env = {}
for arch in ('x86', 'x64'):
self.win_env[arch] = 'environment.' + arch
# Relative path from build output dir to base dir.
build_to_top = gyp.common.InvertRelativePath(build_dir, toplevel_dir)
self.build_to_base = os.path.join(build_to_top, base_dir)
# Relative path from base dir to build dir.
base_to_top = gyp.common.InvertRelativePath(base_dir, toplevel_dir)
self.base_to_build = os.path.join(base_to_top, build_dir)
|
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https://github.com/larroy/clearskies_core/blob/3574ddf0edc8555454c7044126e786a6c29444dc/tools/gyp/pylib/gyp/generator/ninja.py#L215-L250
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/animate.py
|
python
|
Animation.GetFramePosition
|
(*args, **kwargs)
|
return _animate.Animation_GetFramePosition(*args, **kwargs)
|
GetFramePosition(self, int frame) -> Point
|
GetFramePosition(self, int frame) -> Point
|
[
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"(",
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"int",
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")",
"-",
">",
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] |
def GetFramePosition(*args, **kwargs):
"""GetFramePosition(self, int frame) -> Point"""
return _animate.Animation_GetFramePosition(*args, **kwargs)
|
[
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/animate.py#L122-L124
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/dataflow.py
|
python
|
DataFlowAnalysis.op_SLICE_2
|
(self, info, inst)
|
TOS = TOS1[:TOS]
|
TOS = TOS1[:TOS]
|
[
"TOS",
"=",
"TOS1",
"[",
":",
"TOS",
"]"
] |
def op_SLICE_2(self, info, inst):
"""
TOS = TOS1[:TOS]
"""
tos = info.pop()
tos1 = info.pop()
res = info.make_temp()
slicevar = info.make_temp()
indexvar = info.make_temp()
nonevar = info.make_temp()
info.append(inst, base=tos1, stop=tos, res=res, slicevar=slicevar,
indexvar=indexvar, nonevar=nonevar)
info.push(res)
|
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|
||
fredakilla/GPlayEngine
|
ae6b45f4c68f696fcd171ce6996a5a4e80aee09e
|
thirdparty/freetype/src/tools/docmaker/content.py
|
python
|
ContentProcessor.reset
|
( self )
|
Reset the content processor for a new block.
|
Reset the content processor for a new block.
|
[
"Reset",
"the",
"content",
"processor",
"for",
"a",
"new",
"block",
"."
] |
def reset( self ):
"""Reset the content processor for a new block."""
self.markups = []
self.markup = None
self.markup_lines = []
|
[
"def",
"reset",
"(",
"self",
")",
":",
"self",
".",
"markups",
"=",
"[",
"]",
"self",
".",
"markup",
"=",
"None",
"self",
".",
"markup_lines",
"=",
"[",
"]"
] |
https://github.com/fredakilla/GPlayEngine/blob/ae6b45f4c68f696fcd171ce6996a5a4e80aee09e/thirdparty/freetype/src/tools/docmaker/content.py#L427-L431
|
||
brave/brave-core
|
ceaa3de4735789d355b6fa80c21d4709e2c1d0e8
|
script/lib/transifex.py
|
python
|
clean_triple_quoted_string
|
(val)
|
return val.strip()
|
Grit parses out first 3 and last 3 isngle quote chars if they exist.
|
Grit parses out first 3 and last 3 isngle quote chars if they exist.
|
[
"Grit",
"parses",
"out",
"first",
"3",
"and",
"last",
"3",
"isngle",
"quote",
"chars",
"if",
"they",
"exist",
"."
] |
def clean_triple_quoted_string(val):
"""Grit parses out first 3 and last 3 isngle quote chars if they exist."""
val = val.strip()
if val.startswith("'''"):
val = val[3:]
if val.endswith("'''"):
val = val[:-3]
return val.strip()
|
[
"def",
"clean_triple_quoted_string",
"(",
"val",
")",
":",
"val",
"=",
"val",
".",
"strip",
"(",
")",
"if",
"val",
".",
"startswith",
"(",
"\"'''\"",
")",
":",
"val",
"=",
"val",
"[",
"3",
":",
"]",
"if",
"val",
".",
"endswith",
"(",
"\"'''\"",
")",
":",
"val",
"=",
"val",
"[",
":",
"-",
"3",
"]",
"return",
"val",
".",
"strip",
"(",
")"
] |
https://github.com/brave/brave-core/blob/ceaa3de4735789d355b6fa80c21d4709e2c1d0e8/script/lib/transifex.py#L321-L328
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_internal/vcs/git.py
|
python
|
Git.get_url_rev_and_auth
|
(cls, url)
|
return url, rev, user_pass
|
Prefixes stub URLs like 'user@hostname:user/repo.git' with 'ssh://'.
That's required because although they use SSH they sometimes don't
work with a ssh:// scheme (e.g. GitHub). But we need a scheme for
parsing. Hence we remove it again afterwards and return it as a stub.
|
[] |
def get_url_rev_and_auth(cls, url):
# type: (str) -> Tuple[str, Optional[str], AuthInfo]
"""
Prefixes stub URLs like 'user@hostname:user/repo.git' with 'ssh://'.
That's required because although they use SSH they sometimes don't
work with a ssh:// scheme (e.g. GitHub). But we need a scheme for
parsing. Hence we remove it again afterwards and return it as a stub.
"""
# Works around an apparent Git bug
# (see https://article.gmane.org/gmane.comp.version-control.git/146500)
scheme, netloc, path, query, fragment = urlsplit(url)
if scheme.endswith('file'):
initial_slashes = path[:-len(path.lstrip('/'))]
newpath = (
initial_slashes +
urllib.request.url2pathname(path)
.replace('\\', '/').lstrip('/')
)
after_plus = scheme.find('+') + 1
url = scheme[:after_plus] + urlunsplit(
(scheme[after_plus:], netloc, newpath, query, fragment),
)
if '://' not in url:
assert 'file:' not in url
url = url.replace('git+', 'git+ssh://')
url, rev, user_pass = super().get_url_rev_and_auth(url)
url = url.replace('ssh://', '')
else:
url, rev, user_pass = super().get_url_rev_and_auth(url)
return url, rev, user_pass
|
[
"def",
"get_url_rev_and_auth",
"(",
"cls",
",",
"url",
")",
":",
"# type: (str) -> Tuple[str, Optional[str], AuthInfo]",
"# Works around an apparent Git bug",
"# (see https://article.gmane.org/gmane.comp.version-control.git/146500)",
"scheme",
",",
"netloc",
",",
"path",
",",
"query",
",",
"fragment",
"=",
"urlsplit",
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"url",
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"'file'",
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":",
"initial_slashes",
"=",
"path",
"[",
":",
"-",
"len",
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"path",
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"lstrip",
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"'/'",
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")",
"]",
"newpath",
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"(",
"initial_slashes",
"+",
"urllib",
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".",
"url2pathname",
"(",
"path",
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".",
"replace",
"(",
"'\\\\'",
",",
"'/'",
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".",
"lstrip",
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"'/'",
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"=",
"scheme",
".",
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"'+'",
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"+",
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"=",
"scheme",
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"+",
"urlunsplit",
"(",
"(",
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"]",
",",
"netloc",
",",
"newpath",
",",
"query",
",",
"fragment",
")",
",",
")",
"if",
"'://'",
"not",
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"url",
":",
"assert",
"'file:'",
"not",
"in",
"url",
"url",
"=",
"url",
".",
"replace",
"(",
"'git+'",
",",
"'git+ssh://'",
")",
"url",
",",
"rev",
",",
"user_pass",
"=",
"super",
"(",
")",
".",
"get_url_rev_and_auth",
"(",
"url",
")",
"url",
"=",
"url",
".",
"replace",
"(",
"'ssh://'",
",",
"''",
")",
"else",
":",
"url",
",",
"rev",
",",
"user_pass",
"=",
"super",
"(",
")",
".",
"get_url_rev_and_auth",
"(",
"url",
")",
"return",
"url",
",",
"rev",
",",
"user_pass"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_internal/vcs/git.py#L777-L839
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unicode.py
|
python
|
_slice_span
|
(typingctx, sliceobj)
|
return sig, codegen
|
Compute the span from the given slice object.
|
Compute the span from the given slice object.
|
[
"Compute",
"the",
"span",
"from",
"the",
"given",
"slice",
"object",
"."
] |
def _slice_span(typingctx, sliceobj):
"""Compute the span from the given slice object.
"""
sig = types.intp(sliceobj)
def codegen(context, builder, sig, args):
[slicetype] = sig.args
[sliceobj] = args
slice = context.make_helper(builder, slicetype, sliceobj)
result_size = slicing.get_slice_length(builder, slice)
return result_size
return sig, codegen
|
[
"def",
"_slice_span",
"(",
"typingctx",
",",
"sliceobj",
")",
":",
"sig",
"=",
"types",
".",
"intp",
"(",
"sliceobj",
")",
"def",
"codegen",
"(",
"context",
",",
"builder",
",",
"sig",
",",
"args",
")",
":",
"[",
"slicetype",
"]",
"=",
"sig",
".",
"args",
"[",
"sliceobj",
"]",
"=",
"args",
"slice",
"=",
"context",
".",
"make_helper",
"(",
"builder",
",",
"slicetype",
",",
"sliceobj",
")",
"result_size",
"=",
"slicing",
".",
"get_slice_length",
"(",
"builder",
",",
"slice",
")",
"return",
"result_size",
"return",
"sig",
",",
"codegen"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unicode.py#L1537-L1549
|
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