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CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Tools/CryVersionSelector/cryselect.py | python | cmd_run_project | (args, sys_argv=sys.argv[1:]) | Runs the command on the project, by invoking it on the cryrun.exe
that is used by the engine the project is registered to. | Runs the command on the project, by invoking it on the cryrun.exe
that is used by the engine the project is registered to. | [
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] | def cmd_run_project(args, sys_argv=sys.argv[1:]):
"""
Runs the command on the project, by invoking it on the cryrun.exe
that is used by the engine the project is registered to.
"""
if not os.path.isfile(args.project_file):
error_project_not_found(args)
project = cryproject.CryProject()
try:
project.load(args.project_file)
except Exception:
error_project_json_decode(args)
engine_id = project.engine_id()
engine_path = ""
# Start by checking for the ability to specifying use of the local engine
if engine_id is '.':
engine_path = os.path.dirname(args.project_file)
else:
# Now check the registry
engine_registry = cryregistry.load_engines()
engine_path = cryregistry.engine_path(engine_registry, engine_id)
if engine_path is None:
error_engine_path_not_found(args, engine_id)
if getattr(sys, 'frozen', False):
subcmd = [get_cryrun_path(engine_path)]
else:
subcmd = [
get_python_path(),
get_cryrun_path(engine_path)
]
if not os.path.isfile(subcmd[-1]):
error_engine_tool_not_found(args, subcmd[-1])
subcmd.extend(sys_argv)
print_subprocess(subcmd)
try:
subprocess.run(subcmd, stdout=None,
stderr=None, check=True,
universal_newlines=True)
except subprocess.CalledProcessError as e:
error_subprocess_error(
args, "Encountered an error while running command '{}'!".format(e.cmd), e.returncode) | [
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hydrogen-music/hydrogen | 8a4eff74f9706922bd3a649a17cb18f4f5849cc1 | windows/ci/copy_thirdparty_dlls.py | python | LibraryResolver.scan_dependencies | (file_name: str) | return [entry.dll.decode("utf-8") for entry in pe.DIRECTORY_ENTRY_IMPORT] | Find libraries that given file depends on. | Find libraries that given file depends on. | [
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] | def scan_dependencies(file_name: str) -> List[str]:
"""
Find libraries that given file depends on.
"""
pe = pefile.PE(file_name)
return [entry.dll.decode("utf-8") for entry in pe.DIRECTORY_ENTRY_IMPORT] | [
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... | https://github.com/hydrogen-music/hydrogen/blob/8a4eff74f9706922bd3a649a17cb18f4f5849cc1/windows/ci/copy_thirdparty_dlls.py#L136-L141 | |
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/framework/ops.py | python | get_all_collection_keys | () | return get_default_graph().get_all_collection_keys() | Returns a list of collections used in the default graph. | Returns a list of collections used in the default graph. | [
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] | def get_all_collection_keys():
"""Returns a list of collections used in the default graph."""
return get_default_graph().get_all_collection_keys() | [
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] | https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/framework/ops.py#L6690-L6692 | |
tensor-compiler/taco | d0654a84137169883973c40a951dfdb89883fd9c | python_bindings/pytaco/pytensor/taco_tensor.py | python | tensor.copy | (self) | return new_t | Returns a deep copy of a tensor. | Returns a deep copy of a tensor. | [
"Returns",
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"of",
"a",
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"."
] | def copy(self):
"""
Returns a deep copy of a tensor.
"""
new_t = tensor(self.shape, self.format, dtype=self.dtype)
idx_vars = _cm.get_index_vars(self.order)
new_t[idx_vars] = self[idx_vars]
return new_t | [
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greenheartgames/greenworks | 3ea4ab490b56676de3f0a237c74bcfdb17323e60 | deps/cpplint/cpplint.py | python | _ShouldPrintError | (category, confidence, linenum) | return True | If confidence >= verbose, category passes filter and is not suppressed. | If confidence >= verbose, category passes filter and is not suppressed. | [
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] | def _ShouldPrintError(category, confidence, linenum):
"""If confidence >= verbose, category passes filter and is not suppressed."""
# There are three ways we might decide not to print an error message:
# a "NOLINT(category)" comment appears in the source,
# the verbosity level isn't high enough, or the filters filter it out.
if IsErrorSuppressedByNolint(category, linenum):
return False
if confidence < _cpplint_state.verbose_level:
return False
is_filtered = False
for one_filter in _Filters():
if one_filter.startswith('-'):
if category.startswith(one_filter[1:]):
is_filtered = True
elif one_filter.startswith('+'):
if category.startswith(one_filter[1:]):
is_filtered = False
else:
assert False # should have been checked for in SetFilter.
if is_filtered:
return False
return True | [
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stellar-deprecated/stellard | 67eabb2217bdfa9a6ea317f62338fb6bca458c90 | src/protobuf/python/google/protobuf/text_format.py | python | _Tokenizer._ParseError | (self, message) | return ParseError('%d:%d : %s' % (
self._line + 1, self._column + 1, message)) | Creates and *returns* a ParseError for the current token. | Creates and *returns* a ParseError for the current token. | [
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] | def _ParseError(self, message):
"""Creates and *returns* a ParseError for the current token."""
return ParseError('%d:%d : %s' % (
self._line + 1, self._column + 1, message)) | [
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FEniCS/dolfinx | 3dfdf038cccdb70962865b58a63bf29c2e55ec6e | utils/pylit/pylit.py | python | TextCodeConverter.convert | (self, lines) | Iterate over lines of a program document and convert
between "text" and "code" format | Iterate over lines of a program document and convert
between "text" and "code" format | [
"Iterate",
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"lines",
"of",
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"program",
"document",
"and",
"convert",
"between",
"text",
"and",
"code",
"format"
] | def convert(self, lines):
"""Iterate over lines of a program document and convert
between "text" and "code" format
"""
# Initialise internal data arguments. (Done here, so that every new iteration
# re-initialises them.)
#
# `state`
# the "type" of the currently processed block of lines. One of
#
# :"": initial state: check for header,
# :"header": leading code block: strip `header_string`,
# :"documentation": documentation part: comment out,
# :"code_block": literal blocks containing source code: unindent.
#
# ::
self.state = ""
# `_codeindent`
# * Do not confuse the internal attribute `_codeindent` with the configurable
# `codeindent` (without the leading underscore).
# * `_codeindent` is set in `Text2Code.code_block_handler`_ to the indent of
# first non-blank "code_block" line and stripped from all "code_block" lines
# in the text-to-code conversion,
# * `codeindent` is set in `__init__` to `defaults.codeindent`_ and added to
# "code_block" lines in the code-to-text conversion.
#
# ::
self._codeindent = 0
# `_textindent`
# * set by `Text2Code.documentation_handler`_ to the minimal indent of a
# documentation block,
# * used in `Text2Code.set_state`_ to find the end of a code block.
#
# ::
self._textindent = 0
# `_add_code_block_marker`
# If the last paragraph of a documentation block does not end with a
# code_block_marker_, it should be added (otherwise, the back-conversion
# fails.).
#
# `_add_code_block_marker` is set by `Code2Text.documentation_handler`_
# and evaluated by `Code2Text.code_block_handler`_, because the
# documentation_handler does not know whether the next block will be
# documentation (with no need for a code_block_marker) or a code block.
#
# ::
self._add_code_block_marker = False
# Determine the state of the block and convert with the matching "handler"::
for block in collect_blocks(expandtabs_filter(lines)):
self.set_state(block)
for line in getattr(self, self.state+"_handler")(block):
yield line | [
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"# :\"\": initial... | https://github.com/FEniCS/dolfinx/blob/3dfdf038cccdb70962865b58a63bf29c2e55ec6e/utils/pylit/pylit.py#L547-L610 | ||
krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/math/symbolic.py | python | Type.info | (self) | Returns a verbose, human readable string representation of this type | Returns a verbose, human readable string representation of this type | [
"Returns",
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"human",
"readable",
"string",
"representation",
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] | def info(self):
"""Returns a verbose, human readable string representation of this type"""
if self.char is None:
return 'unknown'
typedesc = "%s (%s)"%(self._TYPE_DESCRIPTIONS[self.char],self.char)
if self.size is not None:
if isinstance(self.size,(list,tuple)):
sizedesc = 'x'.join(str(v) for v in self.size)
typedesc = sizedesc + ' ' + typedesc
else:
sizedesc = str(self.size)
typedesc = sizedesc + '-' + typedesc
if self.subtype is None:
return typedesc
else:
if self.char == 'U':
return '%s of type %s'%(typedesc,self.subtype)
if isinstance(self.subtype,list):
return '%s of subtypes [%s]'%(typedesc,','.join(str(s) for s in self.subtype))
else:
return '%s of subtype (%s)'%(typedesc,self.subtype.info()) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/setuptools/py2/pkg_resources/_vendor/pyparsing.py | python | ParserElement.__call__ | (self, name=None) | Shortcut for C{L{setResultsName}}, with C{listAllMatches=False}.
If C{name} is given with a trailing C{'*'} character, then C{listAllMatches} will be
passed as C{True}.
If C{name} is omitted, same as calling C{L{copy}}.
Example::
# these are equivalent
userdata = Word(alphas).setResultsName("name") + Word(nums+"-").setResultsName("socsecno")
userdata = Word(alphas)("name") + Word(nums+"-")("socsecno") | Shortcut for C{L{setResultsName}}, with C{listAllMatches=False}.
If C{name} is given with a trailing C{'*'} character, then C{listAllMatches} will be
passed as C{True}.
If C{name} is omitted, same as calling C{L{copy}}. | [
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"""
Shortcut for C{L{setResultsName}}, with C{listAllMatches=False}.
If C{name} is given with a trailing C{'*'} character, then C{listAllMatches} will be
passed as C{True}.
If C{name} is omitted, same as calling C{L{copy}}.
Example::
# these are equivalent
userdata = Word(alphas).setResultsName("name") + Word(nums+"-").setResultsName("socsecno")
userdata = Word(alphas)("name") + Word(nums+"-")("socsecno")
"""
if name is not None:
return self.setResultsName(name)
else:
return self.copy() | [
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google/llvm-propeller | 45c226984fe8377ebfb2ad7713c680d652ba678d | mlir/utils/spirv/gen_spirv_dialect.py | python | get_description | (text, appendix) | return fmt_str.format(text=text, appendix=appendix) | Generates the description for the given SPIR-V instruction.
Arguments:
- text: Textual description of the operation as string.
- appendix: Additional contents to attach in description as string,
includking IR examples, and others.
Returns:
- A string that corresponds to the description of the Tablegen op. | Generates the description for the given SPIR-V instruction. | [
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"given",
"SPIR",
"-",
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"instruction",
"."
] | def get_description(text, appendix):
"""Generates the description for the given SPIR-V instruction.
Arguments:
- text: Textual description of the operation as string.
- appendix: Additional contents to attach in description as string,
includking IR examples, and others.
Returns:
- A string that corresponds to the description of the Tablegen op.
"""
fmt_str = '{text}\n\n <!-- End of AutoGen section -->\n{appendix}\n '
return fmt_str.format(text=text, appendix=appendix) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_windows.py | python | PreviewControlBar.GetPrintPreview | (*args, **kwargs) | return _windows_.PreviewControlBar_GetPrintPreview(*args, **kwargs) | GetPrintPreview(self) -> PrintPreview | GetPrintPreview(self) -> PrintPreview | [
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")",
"-",
">",
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] | def GetPrintPreview(*args, **kwargs):
"""GetPrintPreview(self) -> PrintPreview"""
return _windows_.PreviewControlBar_GetPrintPreview(*args, **kwargs) | [
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apple/swift-lldb | d74be846ef3e62de946df343e8c234bde93a8912 | scripts/Python/static-binding/lldb.py | python | SBProcess.GetAddressByteSize | (self) | return _lldb.SBProcess_GetAddressByteSize(self) | GetAddressByteSize(SBProcess self) -> uint32_t | GetAddressByteSize(SBProcess self) -> uint32_t | [
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"""GetAddressByteSize(SBProcess self) -> uint32_t"""
return _lldb.SBProcess_GetAddressByteSize(self) | [
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/train/callback/_summary_collector.py | python | SummaryCollector._collect_dataset_graph | (self, cb_params) | Only collect train dataset graph. | Only collect train dataset graph. | [
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"train",
"dataset",
"graph",
"."
] | def _collect_dataset_graph(self, cb_params):
"""Only collect train dataset graph."""
if not self._collect_specified_data.get('collect_dataset_graph'):
return
# After analysis, we think that the validated dataset graph and the training dataset graph
# should be consistent under normal scenarios, so only the training dataset graph is collected.
if cb_params.mode == ModeEnum.TRAIN.value:
train_dataset = cb_params.train_dataset
dataset_graph = DatasetGraph()
graph_bytes = dataset_graph.package_dataset_graph(train_dataset)
if graph_bytes is None:
return
self._record.add_value('dataset_graph', 'train_dataset', graph_bytes) | [
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PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/tensor/linalg.py | python | eigvalsh | (x, UPLO='L', name=None) | return out_value | Computes the eigenvalues of a
complex Hermitian (conjugate symmetric) or a real symmetric matrix.
Args:
x (Tensor): A tensor with shape :math:`[_, M, M]` , The data type of the input Tensor x
should be one of float32, float64, complex64, complex128.
UPLO(str, optional): Lower triangular part of a (‘L’, default) or the upper triangular part (‘U’).
name(str, optional): The default value is None. Normally there is no need for user to set this
property. For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor: The tensor eigenvalues in ascending order.
Examples:
.. code-block:: python
import numpy as np
import paddle
x_data = np.array([[1, -2j], [2j, 5]])
x = paddle.to_tensor(x_data)
out_value = paddle.eigvalsh(x, UPLO='L')
print(out_value)
#[0.17157288, 5.82842712] | Computes the eigenvalues of a
complex Hermitian (conjugate symmetric) or a real symmetric matrix. | [
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] | def eigvalsh(x, UPLO='L', name=None):
"""
Computes the eigenvalues of a
complex Hermitian (conjugate symmetric) or a real symmetric matrix.
Args:
x (Tensor): A tensor with shape :math:`[_, M, M]` , The data type of the input Tensor x
should be one of float32, float64, complex64, complex128.
UPLO(str, optional): Lower triangular part of a (‘L’, default) or the upper triangular part (‘U’).
name(str, optional): The default value is None. Normally there is no need for user to set this
property. For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor: The tensor eigenvalues in ascending order.
Examples:
.. code-block:: python
import numpy as np
import paddle
x_data = np.array([[1, -2j], [2j, 5]])
x = paddle.to_tensor(x_data)
out_value = paddle.eigvalsh(x, UPLO='L')
print(out_value)
#[0.17157288, 5.82842712]
"""
if in_dygraph_mode():
is_test = x.stop_gradient
values, _ = _C_ops.eigvalsh(x, 'UPLO', UPLO, 'is_test', is_test)
return values
def __check_input(x, UPLO):
x_shape = list(x.shape)
if len(x.shape) < 2:
raise ValueError(
"Input(input) only support >=2 tensor, but received "
"length of Input(input) is %s." % len(x.shape))
if x_shape[-1] != x_shape[-2]:
raise ValueError(
"The input matrix must be batches of square matrices. But received x's dimention: {}".
format(x_shape))
if UPLO is not 'L' and UPLO is not 'U':
raise ValueError(
"UPLO must be L or U. But received UPLO is: {}".format(UPLO))
__check_input(x, UPLO)
helper = LayerHelper('eigvalsh', **locals())
check_variable_and_dtype(x, 'dtype',
['float32', 'float64', 'complex64', 'complex128'],
'eigvalsh')
out_value = helper.create_variable_for_type_inference(dtype=x.dtype)
out_vector = helper.create_variable_for_type_inference(dtype=x.dtype)
is_test = x.stop_gradient
helper.append_op(
type='eigvalsh',
inputs={'X': x},
outputs={'Eigenvalues': out_value,
'Eigenvectors': out_vector},
attrs={'UPLO': UPLO,
'is_test': is_test})
return out_value | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemFramework/v1/AWS/lambda-code/ServiceLambda/resource_types/Custom_AccessControl.py | python | _get_permission_list | (resource_name, logical_resource_id, permission_metadata_list, problems) | return permission_list | Constructs a list of permissions from resource metadata.
Args:
resource_name - the name of the resource or resource group that defines the resource with the permission
logical_resource_id - the logical id of the resource with the permission
permission_metadata_list - The permission metadata from the resource.
[ # optional list or a single object
{
"AbstractRole": [ "<abstract-role-name>", ... ], # required list or single string
"Action": [ "<allowed-action>", ... ] # required list or single string
"ResourceSuffix": [ "<resource-suffix>", ... ] # required list or single string
},
...
]
problems - A ProblemList object used to report problems
Returns:
A list constructed from the provided metadata:
[
{
"AbstractRole": [ ["<resource-group-name>", "<abstract-role-name>"], ... ],
"Action": [ "<allowed-action>", ... ],
"ResourceSuffix": [ "<resource-suffix>", ... ],
"LogicalResourceId": "<logical-resource-id>"
},
...
] | Constructs a list of permissions from resource metadata. | [
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] | def _get_permission_list(resource_name, logical_resource_id, permission_metadata_list, problems):
"""Constructs a list of permissions from resource metadata.
Args:
resource_name - the name of the resource or resource group that defines the resource with the permission
logical_resource_id - the logical id of the resource with the permission
permission_metadata_list - The permission metadata from the resource.
[ # optional list or a single object
{
"AbstractRole": [ "<abstract-role-name>", ... ], # required list or single string
"Action": [ "<allowed-action>", ... ] # required list or single string
"ResourceSuffix": [ "<resource-suffix>", ... ] # required list or single string
},
...
]
problems - A ProblemList object used to report problems
Returns:
A list constructed from the provided metadata:
[
{
"AbstractRole": [ ["<resource-group-name>", "<abstract-role-name>"], ... ],
"Action": [ "<allowed-action>", ... ],
"ResourceSuffix": [ "<resource-suffix>", ... ],
"LogicalResourceId": "<logical-resource-id>"
},
...
]
"""
permission_list = []
if not isinstance(permission_metadata_list, list):
permission_metadata_list = [permission_metadata_list]
for permission_metadata in permission_metadata_list:
permission = _get_permission(resource_name, logical_resource_id, permission_metadata, problems)
if permission is not None:
permission_list.append(permission)
return permission_list | [
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facebook/watchman | 0917460c71b000b96be9b9575d77f06f2f6053bb | watchman/python/pywatchman_aio/__init__.py | python | AsyncCodec.send | (self, *args) | Send the given message via the underlying transport. | Send the given message via the underlying transport. | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/arrays/numpy_.py | python | PandasDtype.construct_array_type | (cls) | return PandasArray | Return the array type associated with this dtype.
Returns
-------
type | Return the array type associated with this dtype. | [
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"""
Return the array type associated with this dtype.
Returns
-------
type
"""
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hpi-xnor/BMXNet-v2 | af2b1859eafc5c721b1397cef02f946aaf2ce20d | python/mxnet/symbol/symbol.py | python | Symbol.nansum | (self, *args, **kwargs) | return op.nansum(self, *args, **kwargs) | Convenience fluent method for :py:func:`nansum`.
The arguments are the same as for :py:func:`nansum`, with
this array as data. | Convenience fluent method for :py:func:`nansum`. | [
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] | def nansum(self, *args, **kwargs):
"""Convenience fluent method for :py:func:`nansum`.
The arguments are the same as for :py:func:`nansum`, with
this array as data.
"""
return op.nansum(self, *args, **kwargs) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/core/arrays/datetimes.py | python | _maybe_localize_point | (ts, is_none, is_not_none, freq, tz) | return ts | Localize a start or end Timestamp to the timezone of the corresponding
start or end Timestamp
Parameters
----------
ts : start or end Timestamp to potentially localize
is_none : argument that should be None
is_not_none : argument that should not be None
freq : Tick, DateOffset, or None
tz : str, timezone object or None
Returns
-------
ts : Timestamp | Localize a start or end Timestamp to the timezone of the corresponding
start or end Timestamp | [
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] | def _maybe_localize_point(ts, is_none, is_not_none, freq, tz):
"""
Localize a start or end Timestamp to the timezone of the corresponding
start or end Timestamp
Parameters
----------
ts : start or end Timestamp to potentially localize
is_none : argument that should be None
is_not_none : argument that should not be None
freq : Tick, DateOffset, or None
tz : str, timezone object or None
Returns
-------
ts : Timestamp
"""
# Make sure start and end are timezone localized if:
# 1) freq = a Timedelta-like frequency (Tick)
# 2) freq = None i.e. generating a linspaced range
if isinstance(freq, Tick) or freq is None:
localize_args = {'tz': tz, 'ambiguous': False}
else:
localize_args = {'tz': None}
if is_none is None and is_not_none is not None:
ts = ts.tz_localize(**localize_args)
return ts | [
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/contrib/framework/python/ops/sampling_ops.py | python | _get_stratified_batch_from_tensors | (val_list, label, accept_probs,
batch_size, queue_threads=3) | return final_q.dequeue_many(batch_size) | Accepts examples one-at-a-time based on class. | Accepts examples one-at-a-time based on class. | [
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] | def _get_stratified_batch_from_tensors(val_list, label, accept_probs,
batch_size, queue_threads=3):
"""Accepts examples one-at-a-time based on class."""
# Make queue that will have proper class proportions. Contains exactly one
# batch at a time.
vals_shapes = [val.get_shape() for val in val_list]
vals_dtypes = [val.dtype for val in val_list]
label_shape = label.get_shape()
final_q = data_flow_ops.FIFOQueue(capacity=batch_size,
shapes=vals_shapes + [label_shape],
dtypes=vals_dtypes + [label.dtype],
name='batched_queue')
# Conditionally enqueue.
tensors_to_enqueue = val_list + [label]
eq_tf = array_ops.reshape(math_ops.less(
random_ops.random_uniform([1]),
array_ops.slice(accept_probs, [label], [1])),
[])
conditional_enqueue = control_flow_ops.cond(
eq_tf,
lambda: final_q.enqueue(tensors_to_enqueue),
control_flow_ops.no_op)
queue_runner.add_queue_runner(queue_runner.QueueRunner(
final_q, [conditional_enqueue] * queue_threads))
return final_q.dequeue_many(batch_size) | [
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/utils/data/_utils/worker.py | python | get_worker_info | () | return _worker_info | r"""Returns the information about the current
:class:`~torch.utils.data.DataLoader` iterator worker process.
When called in a worker, this returns an object guaranteed to have the
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* :attr:`id`: the current worker id.
* :attr:`num_workers`: the total number of workers.
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* :attr:`dataset`: the copy of the dataset object in **this** process. Note
that this will be a different object in a different process than the one
in the main process.
When called in the main process, this returns ``None``.
.. note::
When used in a :attr:`worker_init_fn` passed over to
:class:`~torch.utils.data.DataLoader`, this method can be useful to
set up each worker process differently, for instance, using ``worker_id``
to configure the ``dataset`` object to only read a specific fraction of a
sharded dataset, or use ``seed`` to seed other libraries used in dataset
code. | r"""Returns the information about the current
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r"""Returns the information about the current
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When called in a worker, this returns an object guaranteed to have the
following attributes:
* :attr:`id`: the current worker id.
* :attr:`num_workers`: the total number of workers.
* :attr:`seed`: the random seed set for the current worker. This value is
determined by main process RNG and the worker id. See
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* :attr:`dataset`: the copy of the dataset object in **this** process. Note
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"""
return _worker_info | [
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Tencent/Pebble | 68315f176d9e328a233ace29b7579a829f89879f | tools/blade/src/blade/cc_targets.py | python | cc_binary | (name,
srcs=[],
deps=[],
warning='yes',
defs=[],
incs=[],
optimize=[],
dynamic_link=False,
extra_cppflags=[],
extra_linkflags=[],
export_dynamic=False,
**kwargs) | cc_binary target. | cc_binary target. | [
"cc_binary",
"target",
"."
] | def cc_binary(name,
srcs=[],
deps=[],
warning='yes',
defs=[],
incs=[],
optimize=[],
dynamic_link=False,
extra_cppflags=[],
extra_linkflags=[],
export_dynamic=False,
**kwargs):
"""cc_binary target. """
cc_binary_target = CcBinary(name,
srcs,
deps,
warning,
defs,
incs,
optimize,
dynamic_link,
extra_cppflags,
extra_linkflags,
export_dynamic,
blade.blade,
kwargs)
blade.blade.register_target(cc_binary_target) | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/external/bazel_tools/third_party/py/gflags/__init__.py | python | FlagValues.KeyFlagsByModuleDict | (self) | return self.__dict__['__key_flags_by_module'] | Returns the dictionary of module_name -> list of key flags.
Returns:
A dictionary. Its keys are module names (strings). Its values
are lists of Flag objects. | Returns the dictionary of module_name -> list of key flags. | [
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"""Returns the dictionary of module_name -> list of key flags.
Returns:
A dictionary. Its keys are module names (strings). Its values
are lists of Flag objects.
"""
return self.__dict__['__key_flags_by_module'] | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/logging/handlers.py | python | SocketHandler.makeSocket | (self, timeout=1) | return result | A factory method which allows subclasses to define the precise
type of socket they want. | A factory method which allows subclasses to define the precise
type of socket they want. | [
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"""
A factory method which allows subclasses to define the precise
type of socket they want.
"""
if self.port is not None:
result = socket.create_connection(self.address, timeout=timeout)
else:
result = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
result.settimeout(timeout)
try:
result.connect(self.address)
except OSError:
result.close() # Issue 19182
raise
return result | [
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netease-youdao/hex | d7b8773dae8dde63f3807cef1d48c017077db727 | tools/file_util.py | python | remove_dir | (name, quiet = True) | Remove the specified directory. | Remove the specified directory. | [
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""" Remove the specified directory. """
try:
if path_exists(name):
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if not quiet:
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/indexes/base.py | python | Index._set_names | (self, values, level=None) | Set new names on index. Each name has to be a hashable type.
Parameters
----------
values : str or sequence
name(s) to set
level : int, level name, or sequence of int/level names (default None)
If the index is a MultiIndex (hierarchical), level(s) to set (None
for all levels). Otherwise level must be None
Raises
------
TypeError if each name is not hashable. | Set new names on index. Each name has to be a hashable type. | [
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"""
Set new names on index. Each name has to be a hashable type.
Parameters
----------
values : str or sequence
name(s) to set
level : int, level name, or sequence of int/level names (default None)
If the index is a MultiIndex (hierarchical), level(s) to set (None
for all levels). Otherwise level must be None
Raises
------
TypeError if each name is not hashable.
"""
if not is_list_like(values):
raise ValueError("Names must be a list-like")
if len(values) != 1:
raise ValueError(f"Length of new names must be 1, got {len(values)}")
# GH 20527
# All items in 'name' need to be hashable:
validate_all_hashable(*values, error_name=f"{type(self).__name__}.name")
self._name = values[0] | [
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baidu/tera | dbcd28af792d879d961bf9fc7eb60de81b437646 | src/sdk/python/TeraSdk.py | python | RowReader.SetTimeRange | (self, start, end) | set time range | set time range | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/ma/core.py | python | MaskedArray.harden_mask | (self) | return self | Force the mask to hard.
Whether the mask of a masked array is hard or soft is determined by
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See Also
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hardmask | Force the mask to hard. | [
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"""
Force the mask to hard.
Whether the mask of a masked array is hard or soft is determined by
its `hardmask` property. `harden_mask` sets `hardmask` to True.
See Also
--------
hardmask
"""
self._hardmask = True
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htcondor/htcondor | 4829724575176d1d6c936e4693dfd78a728569b0 | src/condor_contrib/campus_factory/python-lib/campus_factory/ClusterStatus.py | python | CondorConfig.get | (self, key) | @param key: string key
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@param key: string key
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logging.warning("Stderr: %s" % stderr)
self.config_dict[key] = stdout.strip()
return stdout.strip() | [
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Node/__init__.py | python | Node.get_build_scanner_path | (self, scanner) | return self.get_executor().get_build_scanner_path(scanner) | Fetch the appropriate scanner path for this node. | Fetch the appropriate scanner path for this node. | [
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return self.get_executor().get_build_scanner_path(scanner) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/tarfile.py | python | TarFile.getnames | (self) | return [tarinfo.name for tarinfo in self.getmembers()] | Return the members of the archive as a list of their names. It has
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"""Return the members of the archive as a list of their names. It has
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"""
return [tarinfo.name for tarinfo in self.getmembers()] | [
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francinexue/xuefu | b6ff79747a42e020588c0c0a921048e08fe4680c | api/ctpx/ctptd.py | python | CtpTd.onRtnFromFutureToBankByFuture | (self, RspTransferField) | 期货发起期货资金转银行通知 | 期货发起期货资金转银行通知 | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/multiprocessing/__init__.py | python | Pool | (processes=None, initializer=None, initargs=(), maxtasksperchild=None) | return Pool(processes, initializer, initargs, maxtasksperchild) | Returns a process pool object | Returns a process pool object | [
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'''
Returns a process pool object
'''
from multiprocessing.pool import Pool
return Pool(processes, initializer, initargs, maxtasksperchild) | [
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NVIDIA/MDL-SDK | aa9642b2546ad7b6236b5627385d882c2ed83c5d | src/mdl/jit/generator_jit/gen_intrinsic_func.py | python | SignatureParser.create_lazy_ir_construction | (self, f, intrinsic, signature) | Create a lazy IR construction call for a given intrinsic, signature pair. | Create a lazy IR construction call for a given intrinsic, signature pair. | [
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"""Create a lazy IR construction call for a given intrinsic, signature pair."""
ret_type, params = self.split_signature(signature)
mode = self.intrinsic_modes.get(intrinsic + signature)
func_index = self.get_function_index((intrinsic, signature))
self.write(f, "if (llvm::Function *func = m_intrinsics[%d * 2 + return_derivs])\n" %
func_index)
self.indent += 1
self.write(f, "return func;\n")
self.indent -= 1
mod_name = self.m_intrinsic_mods[intrinsic]
if mod_name == "state":
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self.indent += 1;
self.write(f, "llvm::Function *func;\n")
self.write(f, "if (m_code_gen.m_state_mode & Type_mapper::SSM_CORE)\n")
self.indent += 1
self.write(f, "func = m_code_gen.get_llvm_module()->getFunction(\"%s\");\n"
% self.get_mangled_state_func_name(intrinsic, "State_core"))
self.indent -= 1
self.write(f, "else\n")
self.indent += 1
self.write(f, "func = m_code_gen.get_llvm_module()->getFunction(\"%s\");\n"
% self.get_mangled_state_func_name(intrinsic, "State_environment"))
self.indent -= 1
self.write(f, "if (func != NULL) {\n")
self.indent += 1
self.write(f, "m_code_gen.create_context_data(func_def, return_derivs, func);\n")
self.write(f, "return m_intrinsics[%d * 2 + return_derivs] = func;\n" % func_index)
self.indent -= 1
self.write(f, "}\n")
self.indent -= 1
self.write(f, "}\n")
suffix = signature
if suffix[-1] == '_':
# no parameters
suffix = suffix[:-1]
self.write(f, "return m_intrinsics[%d * 2 + return_derivs] = create_%s_%s_%s(func_def, return_derivs);\n" %
(func_index, mod_name, intrinsic, suffix)) | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | native_client_sdk/src/build_tools/sdk_tools/third_party/fancy_urllib/__init__.py | python | can_validate_certs | () | Return True if we have the SSL package and can validate certificates. | Return True if we have the SSL package and can validate certificates. | [
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except ImportError:
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_controls.py | python | ListCtrl.SetColumn | (*args, **kwargs) | return _controls_.ListCtrl_SetColumn(*args, **kwargs) | SetColumn(self, int col, ListItem item) -> bool | SetColumn(self, int col, ListItem item) -> bool | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/applications/workbench/workbench/plotting/plotscriptgenerator/__init__.py | python | get_tick_commands | (ax, ax_object_var) | return ["{ax_obj}.{cmd}".format(ax_obj=ax_object_var, cmd=cmd) for cmd in tick_commands] | Get ax.tick_params commands for setting properties of tick marks and grid lines. | Get ax.tick_params commands for setting properties of tick marks and grid lines. | [
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tick_commands = generate_tick_commands(ax)
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tpfister/caffe-heatmap | 4db69ef53e6b8a0b3b4ebb29328b0ab3dbf67c4e | python/caffe/pycaffe.py | python | _Net_backward | (self, diffs=None, start=None, end=None, **kwargs) | return {out: self.blobs[out].diff for out in outputs} | Backward pass: prepare diffs and run the net backward.
Parameters
----------
diffs : list of diffs to return in addition to bottom diffs.
kwargs : Keys are output blob names and values are diff ndarrays.
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start : optional name of layer at which to begin the backward pass
end : optional name of layer at which to finish the backward pass
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Returns
-------
outs: {blob name: diff ndarray} dict. | Backward pass: prepare diffs and run the net backward. | [
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"""
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Parameters
----------
diffs : list of diffs to return in addition to bottom diffs.
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end : optional name of layer at which to finish the backward pass
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if diffs is None:
diffs = []
if start is not None:
start_ind = list(self._layer_names).index(start)
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start_ind = len(self.layers) - 1
if end is not None:
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outputs = set([end] + diffs)
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outputs = set(self.inputs + diffs)
if kwargs:
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for top, diff in kwargs.iteritems():
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raise Exception('{} diff is not 4-d'.format(top))
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raise Exception('Diff is not batch sized')
self.blobs[top].diff[...] = diff
self._backward(start_ind, end_ind)
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return {out: self.blobs[out].diff for out in outputs} | [
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/boost_1_66_0/tools/build/src/build/property_set.py | python | PropertySet.get_properties | (self, feature) | return result | Returns all contained properties associated with 'feature | Returns all contained properties associated with 'feature | [
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stepcode/stepcode | 2a50010e6f6b8bd4843561e48fdb0fd4e8b87f39 | src/exp2python/python/SCL/ConstructedDataTypes.py | python | SELECT.get_allowed_basic_types | (self) | return b | if a select contains some subselect, goes down through the different
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/polynomial/hermite_e.py | python | hermevander2d | (x, y, deg) | return pu._vander_nd_flat((hermevander, hermevander), (x, y), deg) | Pseudo-Vandermonde matrix of given degrees.
Returns the pseudo-Vandermonde matrix of degrees `deg` and sample
points `(x, y)`. The pseudo-Vandermonde matrix is defined by
.. math:: V[..., (deg[1] + 1)*i + j] = He_i(x) * He_j(y),
where `0 <= i <= deg[0]` and `0 <= j <= deg[1]`. The leading indices of
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(xdeg + 1, ydeg + 1) in the order
.. math:: c_{00}, c_{01}, c_{02} ... , c_{10}, c_{11}, c_{12} ...
and ``np.dot(V, c.flat)`` and ``hermeval2d(x, y, c)`` will be the same
up to roundoff. This equivalence is useful both for least squares
fitting and for the evaluation of a large number of 2-D HermiteE
series of the same degrees and sample points.
Parameters
----------
x, y : array_like
Arrays of point coordinates, all of the same shape. The dtypes
will be converted to either float64 or complex128 depending on
whether any of the elements are complex. Scalars are converted to
1-D arrays.
deg : list of ints
List of maximum degrees of the form [x_deg, y_deg].
Returns
-------
vander2d : ndarray
The shape of the returned matrix is ``x.shape + (order,)``, where
:math:`order = (deg[0]+1)*(deg([1]+1)`. The dtype will be the same
as the converted `x` and `y`.
See Also
--------
hermevander, hermevander3d, hermeval2d, hermeval3d
Notes
-----
.. versionadded:: 1.7.0 | Pseudo-Vandermonde matrix of given degrees. | [
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"""Pseudo-Vandermonde matrix of given degrees.
Returns the pseudo-Vandermonde matrix of degrees `deg` and sample
points `(x, y)`. The pseudo-Vandermonde matrix is defined by
.. math:: V[..., (deg[1] + 1)*i + j] = He_i(x) * He_j(y),
where `0 <= i <= deg[0]` and `0 <= j <= deg[1]`. The leading indices of
`V` index the points `(x, y)` and the last index encodes the degrees of
the HermiteE polynomials.
If ``V = hermevander2d(x, y, [xdeg, ydeg])``, then the columns of `V`
correspond to the elements of a 2-D coefficient array `c` of shape
(xdeg + 1, ydeg + 1) in the order
.. math:: c_{00}, c_{01}, c_{02} ... , c_{10}, c_{11}, c_{12} ...
and ``np.dot(V, c.flat)`` and ``hermeval2d(x, y, c)`` will be the same
up to roundoff. This equivalence is useful both for least squares
fitting and for the evaluation of a large number of 2-D HermiteE
series of the same degrees and sample points.
Parameters
----------
x, y : array_like
Arrays of point coordinates, all of the same shape. The dtypes
will be converted to either float64 or complex128 depending on
whether any of the elements are complex. Scalars are converted to
1-D arrays.
deg : list of ints
List of maximum degrees of the form [x_deg, y_deg].
Returns
-------
vander2d : ndarray
The shape of the returned matrix is ``x.shape + (order,)``, where
:math:`order = (deg[0]+1)*(deg([1]+1)`. The dtype will be the same
as the converted `x` and `y`.
See Also
--------
hermevander, hermevander3d, hermeval2d, hermeval3d
Notes
-----
.. versionadded:: 1.7.0
"""
return pu._vander_nd_flat((hermevander, hermevander), (x, y), deg) | [
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | toolkit/components/telemetry/histogram_tools.py | python | Histogram.keyed | (self) | return self._keyed | Returns True if this a keyed histogram, false otherwise. | Returns True if this a keyed histogram, false otherwise. | [
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/draftguitools/gui_trackers.py | python | rectangleTracker.p2 | (self) | return Vector(self.coords.point.getValues()[3].getValue()) | Get the second point (on u axis) of the rectangle. | Get the second point (on u axis) of the rectangle. | [
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alexgkendall/caffe-segnet | 344c113bf1832886f1cbe9f33ffe28a3beeaf412 | scripts/cpp_lint.py | python | _BlockInfo.CheckEnd | (self, filename, clean_lines, linenum, error) | Run checks that applies to text after the closing brace.
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/s3/bucket.py | python | Bucket.configure_lifecycle | (self, lifecycle_config, headers=None) | Configure lifecycle for this bucket.
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/contrib/distributions/python/ops/bernoulli.py | python | Bernoulli.q | (self) | return self._q | 1-p. | 1-p. | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | build/plugins/_xsyn_includes.py | python | get_include_callback | () | return get_include | .. function: get_include_callback returns function that processes each DOM element to get xsyn include from it, and it's aware of directory with all the xsyns.
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.. function: get_include_callback returns function that processes each DOM element to get xsyn include from it, and it's aware of directory with all the xsyns.
:param xsyn_dir directory with xsyns.
"""
def get_include(element):
"""
.. function: get_include returns list of includes from this DOM element.
:param element DOM element.
"""
res = []
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attrs = element.attributes
for i in xrange(attrs.length):
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/python/ops/array_ops.py | python | pack | (values, axis=0, name="pack") | return gen_array_ops._pack(values, axis=axis, name=name) | Packs a list of rank-`R` tensors into one rank-`(R+1)` tensor.
Packs the list of tensors in `values` into a tensor with rank one higher than
each tensor in `values`, by packing them along the `axis` dimension.
Given a list of length `N` of tensors of shape `(A, B, C)`;
if `axis == 0` then the `output` tensor will have the shape `(N, A, B, C)`.
if `axis == 1` then the `output` tensor will have the shape `(A, N, B, C)`.
Etc.
For example:
```prettyprint
# 'x' is [1, 4]
# 'y' is [2, 5]
# 'z' is [3, 6]
pack([x, y, z]) => [[1, 4], [2, 5], [3, 6]] # Pack along first dim.
pack([x, y, z], axis=1) => [[1, 2, 3], [4, 5, 6]]
```
This is the opposite of unpack. The numpy equivalent is
tf.pack([x, y, z]) = np.asarray([x, y, z])
Args:
values: A list of `Tensor` objects with the same shape and type.
axis: An `int`. The axis to pack along. Defaults to the first dimension.
Supports negative indexes.
name: A name for this operation (optional).
Returns:
output: A packed `Tensor` with the same type as `values`.
Raises:
ValueError: If `axis` is out of the range [-(R+1), R+1). | Packs a list of rank-`R` tensors into one rank-`(R+1)` tensor. | [
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if axis == 0:
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if value_shape.ndims is not None:
expanded_num_dims = value_shape.ndims + 1
if axis < -expanded_num_dims or axis >= expanded_num_dims:
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return gen_array_ops._pack(values, axis=axis, name=name) | [
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protocolbuffers/protobuf | b5ab0b7a18b7336c60130f4ddb2d97c51792f896 | python/google/protobuf/descriptor.py | python | FieldDescriptor.ProtoTypeToCppProtoType | (proto_type) | Converts from a Python proto type to a C++ Proto Type.
The Python ProtocolBuffer classes specify both the 'Python' datatype and the
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_core.py | python | BookCtrlBase.IsVertical | (*args, **kwargs) | return _core_.BookCtrlBase_IsVertical(*args, **kwargs) | IsVertical(self) -> bool | IsVertical(self) -> bool | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/src/robotsim.py | python | AABBPoser.__init__ | (self) | r"""
__init__(AABBPoser self) -> AABBPoser | r"""
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/propgrid.py | python | PropertyGrid.SetSortFunction | (*args, **kwargs) | return _propgrid.PropertyGrid_SetSortFunction(*args, **kwargs) | SetSortFunction(self, PGSortCallback sortFunction) | SetSortFunction(self, PGSortCallback sortFunction) | [
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SpenceKonde/megaTinyCore | 1c4a70b18a149fe6bcb551dfa6db11ca50b8997b | megaavr/tools/libs/pymcuprog/nvmpic.py | python | NvmAccessProviderCmsisDapPic.read | (self, memory_info, offset, numbytes) | return [] | Read the memory
:param memory_info: dictionary for the memory as provided by the DeviceMemoryInfo class
:param offset: relative offset in the memory type
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:param numbytes: number of bytes to read
:return: array of bytes read
"""
mem_name = memory_info[DeviceInfoKeys.NAME]
offset += memory_info[DeviceMemoryInfoKeys.ADDRESS]
if mem_name in [MemoryNames.FLASH, MemoryNames.USER_ID, MemoryNames.ICD]:
mem = self.pic.read_flash_memory(offset, numbytes)
return mem
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mem = self.pic.read_config_memory(offset, numbytes)
return mem
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/nn/layer/quant.py | python | DenseQuant.extend_repr | (self) | return s | A pretty print for Dense layer. | A pretty print for Dense layer. | [
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self.in_channels, self.out_channels, self.weight, self.has_bias)
if self.has_bias:
s += ', bias={}'.format(self.bias)
if self.activation_flag:
s += ', activation={}'.format(self.activation)
return s | [
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google/or-tools | 2cb85b4eead4c38e1c54b48044f92087cf165bce | ortools/constraint_solver/samples/tsp_cities.py | python | main | () | Entry point of the program. | Entry point of the program. | [
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"""Entry point of the program."""
# Instantiate the data problem.
# [START data]
data = create_data_model()
# [END data]
# Create the routing index manager.
# [START index_manager]
manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),
data['num_vehicles'], data['depot'])
# [END index_manager]
# Create Routing Model.
# [START routing_model]
routing = pywrapcp.RoutingModel(manager)
# [END routing_model]
# [START transit_callback]
def distance_callback(from_index, to_index):
"""Returns the distance between the two nodes."""
# Convert from routing variable Index to distance matrix NodeIndex.
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
return data['distance_matrix'][from_node][to_node]
transit_callback_index = routing.RegisterTransitCallback(distance_callback)
# [END transit_callback]
# Define cost of each arc.
# [START arc_cost]
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
# [END arc_cost]
# Setting first solution heuristic.
# [START parameters]
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.first_solution_strategy = (
routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
# [END parameters]
# Solve the problem.
# [START solve]
solution = routing.SolveWithParameters(search_parameters)
# [END solve]
# Print solution on console.
# [START print_solution]
if solution:
print_solution(manager, routing, solution) | [
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/boost_1_66_0/tools/build/src/build/type.py | python | register | (type, suffixes = [], base_type = None) | Registers a target type, possibly derived from a 'base-type'.
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type: a string
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Also, the first element gives the suffix to be used when constructing and object of
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type: a string
suffixes: None or a sequence of strings
base_type: None or a string
"""
# Type names cannot contain hyphens, because when used as
# feature-values they will be interpreted as composite features
# which need to be decomposed.
if __re_hyphen.search (type):
raise BaseException ('type name "%s" contains a hyphen' % type)
# it's possible for a type to be registered with a
# base type that hasn't been registered yet. in the
# check for base_type below and the following calls to setdefault()
# the key `type` will be added to __types. When the base type
# actually gets registered, it would fail after the simple check
# of "type in __types"; thus the check for "'base' in __types[type]"
if type in __types and 'base' in __types[type]:
raise BaseException ('Type "%s" is already registered.' % type)
entry = __types.setdefault(type, {})
entry['base'] = base_type
entry.setdefault('derived', [])
entry.setdefault('scanner', None)
if base_type:
__types.setdefault(base_type, {}).setdefault('derived', []).append(type)
if len (suffixes) > 0:
# Generated targets of 'type' will use the first of 'suffixes'
# (this may be overriden)
set_generated_target_suffix (type, [], suffixes [0])
# Specify mapping from suffixes to type
register_suffixes (suffixes, type)
feature.extend('target-type', [type])
feature.extend('main-target-type', [type])
feature.extend('base-target-type', [type])
if base_type:
feature.compose ('<target-type>' + type, [replace_grist (base_type, '<base-target-type>')])
feature.compose ('<base-target-type>' + type, ['<base-target-type>' + base_type])
import b2.build.generators as generators
# Adding a new derived type affects generator selection so we need to
# make the generator selection module update any of its cached
# information related to a new derived type being defined.
generators.update_cached_information_with_a_new_type(type)
# FIXME: resolving recursive dependency.
from b2.manager import get_manager
get_manager().projects().project_rules().add_rule_for_type(type) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/html.py | python | HtmlWinParser.GetContainer | (*args, **kwargs) | return _html.HtmlWinParser_GetContainer(*args, **kwargs) | GetContainer(self) -> HtmlContainerCell | GetContainer(self) -> HtmlContainerCell | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/core/arrays/categorical.py | python | Categorical.T | (self) | return self | Return transposed numpy array. | Return transposed numpy array. | [
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Return transposed numpy array.
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/protobuf/py2/google/protobuf/descriptor.py | python | _NestedDescriptorBase.CopyToProto | (self, proto) | Copies this to the matching proto in descriptor_pb2.
Args:
proto: An empty proto instance from descriptor_pb2.
Raises:
Error: If self couldn't be serialized, due to to few constructor
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"""Copies this to the matching proto in descriptor_pb2.
Args:
proto: An empty proto instance from descriptor_pb2.
Raises:
Error: If self couldn't be serialized, due to to few constructor
arguments.
"""
if (self.file is not None and
self._serialized_start is not None and
self._serialized_end is not None):
proto.ParseFromString(self.file.serialized_pb[
self._serialized_start:self._serialized_end])
else:
raise Error('Descriptor does not contain serialization.') | [
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Z3Prover/z3 | d745d03afdfdf638d66093e2bfbacaf87187f35b | src/api/python/z3/z3.py | python | Solver.add | (self, *args) | Assert constraints into the solver.
>>> x = Int('x')
>>> s = Solver()
>>> s.add(x > 0, x < 2)
>>> s
[x > 0, x < 2] | Assert constraints into the solver. | [
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"""Assert constraints into the solver.
>>> x = Int('x')
>>> s = Solver()
>>> s.add(x > 0, x < 2)
>>> s
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/buttonpanel.py | python | ButtonPanel.SetUseHelp | (self, useHelp=True) | Sets whether or not short and long help strings should be displayed as tooltips
and :class:`StatusBar` items respectively.
:param bool `useHelp`: ``True`` to display short and long help strings as tooltips
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Sets whether or not short and long help strings should be displayed as tooltips
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:param bool `useHelp`: ``True`` to display short and long help strings as tooltips
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macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/v8/tools/release/releases.py | python | BuildRevisionRanges | (cr_releases) | return dict((hsh, ", ".join(ran)) for hsh, ran in range_lists.iteritems()) | Returns a mapping of v8 revision -> chromium ranges.
The ranges are comma-separated, each range has the form R1:R2. The newest
entry is the only one of the form R1, as there is no end range.
cr_releases is a list of [cr_rev, v8_hsh] reverse-sorted by cr_rev.
cr_rev either refers to a chromium commit position or a chromium branch
number. | Returns a mapping of v8 revision -> chromium ranges.
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"""Returns a mapping of v8 revision -> chromium ranges.
The ranges are comma-separated, each range has the form R1:R2. The newest
entry is the only one of the form R1, as there is no end range.
cr_releases is a list of [cr_rev, v8_hsh] reverse-sorted by cr_rev.
cr_rev either refers to a chromium commit position or a chromium branch
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"""
range_lists = {}
cr_releases = FilterDuplicatesAndReverse(cr_releases)
# Visit pairs of cr releases from oldest to newest.
for cr_from, cr_to in itertools.izip(
cr_releases, itertools.islice(cr_releases, 1, None)):
# Assume the chromium revisions are all different.
assert cr_from[0] != cr_to[0]
ran = "%s:%d" % (cr_from[0], int(cr_to[0]) - 1)
# Collect the ranges in lists per revision.
range_lists.setdefault(cr_from[1], []).append(ran)
# Add the newest revision.
if cr_releases:
range_lists.setdefault(cr_releases[-1][1], []).append(cr_releases[-1][0])
# Stringify and comma-separate the range lists.
return dict((hsh, ", ".join(ran)) for hsh, ran in range_lists.iteritems()) | [
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/external/bazel_tools/tools/android/merge_manifests.py | python | MergeManifests._IsDuplicate | (self, node_to_copy, node) | return False | Is element a duplicate? | Is element a duplicate? | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/linalg_ops_impl.py | python | eye | (num_rows,
num_columns=None,
batch_shape=None,
dtype=dtypes.float32,
name=None) | Construct an identity matrix, or a batch of matrices.
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batch_shape=None,
dtype=dtypes.float32,
name=None):
"""Construct an identity matrix, or a batch of matrices.
See `linalg_ops.eye`.
"""
with ops.name_scope(
name, default_name='eye', values=[num_rows, num_columns, batch_shape]):
is_square = num_columns is None
batch_shape = [] if batch_shape is None else batch_shape
num_columns = num_rows if num_columns is None else num_columns
# We cannot statically infer what the diagonal size should be:
if (isinstance(num_rows, ops.Tensor) or
isinstance(num_columns, ops.Tensor)):
diag_size = math_ops.minimum(num_rows, num_columns)
else:
# We can statically infer the diagonal size, and whether it is square.
if not isinstance(num_rows, compat.integral_types) or not isinstance(
num_columns, compat.integral_types):
raise TypeError(
'Arguments `num_rows` and `num_columns` must be positive integer '
f'values. Received: num_rows={num_rows}, num_columns={num_columns}')
is_square = num_rows == num_columns
diag_size = np.minimum(num_rows, num_columns)
# We can not statically infer the shape of the tensor.
if isinstance(batch_shape, ops.Tensor) or isinstance(diag_size, ops.Tensor):
batch_shape = ops.convert_to_tensor(
batch_shape, name='shape', dtype=dtypes.int32)
diag_shape = array_ops.concat((batch_shape, [diag_size]), axis=0)
if not is_square:
shape = array_ops.concat((batch_shape, [num_rows, num_columns]), axis=0)
# We can statically infer everything.
else:
batch_shape = list(batch_shape)
diag_shape = batch_shape + [diag_size]
if not is_square:
shape = batch_shape + [num_rows, num_columns]
diag_ones = array_ops.ones(diag_shape, dtype=dtype)
if is_square:
return array_ops.matrix_diag(diag_ones)
else:
zero_matrix = array_ops.zeros(shape, dtype=dtype)
return array_ops.matrix_set_diag(zero_matrix, diag_ones) | [
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apple/swift-lldb | d74be846ef3e62de946df343e8c234bde93a8912 | scripts/Python/static-binding/lldb.py | python | SBPlatform.Run | (self, shell_command) | return _lldb.SBPlatform_Run(self, shell_command) | Run(SBPlatform self, SBPlatformShellCommand shell_command) -> SBError | Run(SBPlatform self, SBPlatformShellCommand shell_command) -> SBError | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/optimize/optimize.py | python | _minimize_scalar_bounded | (func, bounds, args=(),
xatol=1e-5, maxiter=500, disp=0,
**unknown_options) | return result | Options
-------
maxiter : int
Maximum number of iterations to perform.
disp: int, optional
If non-zero, print messages.
0 : no message printing.
1 : non-convergence notification messages only.
2 : print a message on convergence too.
3 : print iteration results.
xatol : float
Absolute error in solution `xopt` acceptable for convergence. | Options
-------
maxiter : int
Maximum number of iterations to perform.
disp: int, optional
If non-zero, print messages.
0 : no message printing.
1 : non-convergence notification messages only.
2 : print a message on convergence too.
3 : print iteration results.
xatol : float
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**unknown_options):
"""
Options
-------
maxiter : int
Maximum number of iterations to perform.
disp: int, optional
If non-zero, print messages.
0 : no message printing.
1 : non-convergence notification messages only.
2 : print a message on convergence too.
3 : print iteration results.
xatol : float
Absolute error in solution `xopt` acceptable for convergence.
"""
_check_unknown_options(unknown_options)
maxfun = maxiter
# Test bounds are of correct form
if len(bounds) != 2:
raise ValueError('bounds must have two elements.')
x1, x2 = bounds
if not (is_array_scalar(x1) and is_array_scalar(x2)):
raise ValueError("Optimisation bounds must be scalars"
" or array scalars.")
if x1 > x2:
raise ValueError("The lower bound exceeds the upper bound.")
flag = 0
header = ' Func-count x f(x) Procedure'
step = ' initial'
sqrt_eps = sqrt(2.2e-16)
golden_mean = 0.5 * (3.0 - sqrt(5.0))
a, b = x1, x2
fulc = a + golden_mean * (b - a)
nfc, xf = fulc, fulc
rat = e = 0.0
x = xf
fx = func(x, *args)
num = 1
fmin_data = (1, xf, fx)
ffulc = fnfc = fx
xm = 0.5 * (a + b)
tol1 = sqrt_eps * numpy.abs(xf) + xatol / 3.0
tol2 = 2.0 * tol1
if disp > 2:
print(" ")
print(header)
print("%5.0f %12.6g %12.6g %s" % (fmin_data + (step,)))
while (numpy.abs(xf - xm) > (tol2 - 0.5 * (b - a))):
golden = 1
# Check for parabolic fit
if numpy.abs(e) > tol1:
golden = 0
r = (xf - nfc) * (fx - ffulc)
q = (xf - fulc) * (fx - fnfc)
p = (xf - fulc) * q - (xf - nfc) * r
q = 2.0 * (q - r)
if q > 0.0:
p = -p
q = numpy.abs(q)
r = e
e = rat
# Check for acceptability of parabola
if ((numpy.abs(p) < numpy.abs(0.5*q*r)) and (p > q*(a - xf)) and
(p < q * (b - xf))):
rat = (p + 0.0) / q
x = xf + rat
step = ' parabolic'
if ((x - a) < tol2) or ((b - x) < tol2):
si = numpy.sign(xm - xf) + ((xm - xf) == 0)
rat = tol1 * si
else: # do a golden section step
golden = 1
if golden: # Do a golden-section step
if xf >= xm:
e = a - xf
else:
e = b - xf
rat = golden_mean*e
step = ' golden'
si = numpy.sign(rat) + (rat == 0)
x = xf + si * numpy.max([numpy.abs(rat), tol1])
fu = func(x, *args)
num += 1
fmin_data = (num, x, fu)
if disp > 2:
print("%5.0f %12.6g %12.6g %s" % (fmin_data + (step,)))
if fu <= fx:
if x >= xf:
a = xf
else:
b = xf
fulc, ffulc = nfc, fnfc
nfc, fnfc = xf, fx
xf, fx = x, fu
else:
if x < xf:
a = x
else:
b = x
if (fu <= fnfc) or (nfc == xf):
fulc, ffulc = nfc, fnfc
nfc, fnfc = x, fu
elif (fu <= ffulc) or (fulc == xf) or (fulc == nfc):
fulc, ffulc = x, fu
xm = 0.5 * (a + b)
tol1 = sqrt_eps * numpy.abs(xf) + xatol / 3.0
tol2 = 2.0 * tol1
if num >= maxfun:
flag = 1
break
fval = fx
if disp > 0:
_endprint(x, flag, fval, maxfun, xatol, disp)
result = OptimizeResult(fun=fval, status=flag, success=(flag == 0),
message={0: 'Solution found.',
1: 'Maximum number of function calls '
'reached.'}.get(flag, ''),
x=xf, nfev=num)
return result | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/ogl/_basic.py | python | Shape.GetEventHandler | (self) | return self._eventHandler | Return the event handler for this shape. | Return the event handler for this shape. | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | build/mac/find_sdk.py | python | parse_version | (version_str) | return map(int, re.findall(r'(\d+)', version_str)) | 10.6' => [10, 6] | 10.6' => [10, 6] | [
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return map(int, re.findall(r'(\d+)', version_str)) | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | build/android/play_services/update.py | python | _CheckLicenseAgreement | (expected_license_path, actual_license_path,
version_number) | return raw_input('> ') in ('Y', 'y') | Checks that the new license is the one already accepted by the user. If it
isn't, it prompts the user to accept it. Returns whether the expected license
has been accepted. | Checks that the new license is the one already accepted by the user. If it
isn't, it prompts the user to accept it. Returns whether the expected license
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'''
Checks that the new license is the one already accepted by the user. If it
isn't, it prompts the user to accept it. Returns whether the expected license
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'''
if utils.FileEquals(expected_license_path, actual_license_path):
return True
with open(expected_license_path) as license_file:
# Uses plain print rather than logging to make sure this is not formatted
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print ('Updating the Google Play services SDK to '
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# The output is buffered when running as part of gclient hooks. We split
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# out.
# Note: text contains *escaped* new lines, so we split by '\\n', not '\n'.
for license_part in license_file.read().split('\\n'):
print license_part
sys.stdout.flush()
# Need to put the prompt on a separate line otherwise the gclient hook buffer
# only prints it after we received an input.
print 'Do you accept the license? [y/n]: '
sys.stdout.flush()
return raw_input('> ') in ('Y', 'y') | [
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tensorflow/deepmath | b5b721f54de1d5d6a02d78f5da5995237f9995f9 | deepmath/premises/model_final_cnn_2x.py | python | Model.conjecture_embedding | (self, conjectures) | return self.make_embedding(conjectures) | Compute the embedding for each of the conjectures. | Compute the embedding for each of the conjectures. | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/fastparquet/core.py | python | read_data_page | (f, helper, header, metadata, skip_nulls=False,
selfmade=False) | return definition_levels, repetition_levels, values[:nval] | Read a data page: definitions, repetitions, values (in order)
Only values are guaranteed to exist, e.g., for a top-level, required
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selfmade=False):
"""Read a data page: definitions, repetitions, values (in order)
Only values are guaranteed to exist, e.g., for a top-level, required
field.
"""
daph = header.data_page_header
raw_bytes = _read_page(f, header, metadata)
io_obj = encoding.Numpy8(np.frombuffer(byte_buffer(raw_bytes),
dtype=np.uint8))
repetition_levels = read_rep(io_obj, daph, helper, metadata)
if skip_nulls and not helper.is_required(metadata.path_in_schema):
num_nulls = 0
definition_levels = None
skip_definition_bytes(io_obj, daph.num_values)
else:
definition_levels, num_nulls = read_def(io_obj, daph, helper, metadata)
nval = daph.num_values - num_nulls
if daph.encoding == parquet_thrift.Encoding.PLAIN:
width = helper.schema_element(metadata.path_in_schema).type_length
values = encoding.read_plain(raw_bytes[io_obj.loc:],
metadata.type,
int(daph.num_values - num_nulls),
width=width)
elif daph.encoding in [parquet_thrift.Encoding.PLAIN_DICTIONARY,
parquet_thrift.Encoding.RLE]:
# bit_width is stored as single byte.
if daph.encoding == parquet_thrift.Encoding.RLE:
bit_width = helper.schema_element(
metadata.path_in_schema).type_length
else:
bit_width = io_obj.read_byte()
if bit_width in [8, 16, 32] and selfmade:
num = (encoding.read_unsigned_var_int(io_obj) >> 1) * 8
values = io_obj.read(num * bit_width // 8).view('int%i' % bit_width)
elif bit_width:
values = encoding.Numpy32(np.empty(daph.num_values-num_nulls+7,
dtype=np.int32))
# length is simply "all data left in this page"
encoding.read_rle_bit_packed_hybrid(
io_obj, bit_width, io_obj.len-io_obj.loc, o=values)
values = values.data[:nval]
else:
values = np.zeros(nval, dtype=np.int8)
else:
raise NotImplementedError('Encoding %s' % daph.encoding)
return definition_levels, repetition_levels, values[:nval] | [
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apple/foundationdb | f7118ad406f44ab7a33970fc8370647ed0085e18 | layers/taskbucket/__init__.py | python | Future.joined_future | (self, tr) | return f | Returns a new unset future which this future is join()ed to. | Returns a new unset future which this future is join()ed to. | [
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self.join(tr, f)
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/share/gdb/python/gdb/command/frame_filters.py | python | _enable_parse_arg | (cmd_name, arg) | return argv | Internal worker function to take an argument from
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cmd_name: Name of the command invoking this function.
args: The argument as a string.
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A tuple containing the dictionary, and the argument, or just
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""" Internal worker function to take an argument from
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Arguments:
cmd_name: Name of the command invoking this function.
args: The argument as a string.
Returns:
A tuple containing the dictionary, and the argument, or just
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"""
argv = gdb.string_to_argv(arg);
argc = len(argv)
if argv[0] == "all" and argc > 1:
raise gdb.GdbError(cmd_name + ": with 'all' " \
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else:
if argv[0] != "all" and argc != 2:
raise gdb.GdbError(cmd_name + " takes exactly two arguments.")
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cyberbotics/webots | af7fa7d68dcf7b4550f1f2e132092b41e83698fc | projects/humans/c3d/controllers/c3d_viewer/c3d.py | python | Param.uint8_array | (self) | return self._as_array('B') | Get the param as an array of 8-bit unsigned integers. | Get the param as an array of 8-bit unsigned integers. | [
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/llvm/examples/Kaleidoscope/MCJIT/cached/genk-timing.py | python | TimingScriptGenerator.writeTimingCall | (self, filename, numFuncs, funcsCalled, totalCalls) | Echo some comments and invoke both versions of toy | Echo some comments and invoke both versions of toy | [
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"""Echo some comments and invoke both versions of toy"""
rootname = filename
if '.' in filename:
rootname = filename[:filename.rfind('.')]
self.shfile.write("echo \"%s: Calls %d of %d functions, %d total\" >> %s\n" % (filename, funcsCalled, numFuncs, totalCalls, self.timeFile))
self.shfile.write("echo \"\" >> %s\n" % self.timeFile)
self.shfile.write("echo \"With MCJIT\" >> %s\n" % self.timeFile)
self.shfile.write("/usr/bin/time -f \"Command %C\\n\\tuser time: %U s\\n\\tsytem time: %S s\\n\\tmax set: %M kb\"")
self.shfile.write(" -o %s -a " % self.timeFile)
self.shfile.write("./toy-mcjit < %s > %s-mcjit.out 2> %s-mcjit.err\n" % (filename, rootname, rootname))
self.shfile.write("echo \"\" >> %s\n" % self.timeFile)
self.shfile.write("echo \"With JIT\" >> %s\n" % self.timeFile)
self.shfile.write("/usr/bin/time -f \"Command %C\\n\\tuser time: %U s\\n\\tsytem time: %S s\\n\\tmax set: %M kb\"")
self.shfile.write(" -o %s -a " % self.timeFile)
self.shfile.write("./toy-jit < %s > %s-jit.out 2> %s-jit.err\n" % (filename, rootname, rootname))
self.shfile.write("echo \"\" >> %s\n" % self.timeFile)
self.shfile.write("echo \"\" >> %s\n" % self.timeFile) | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/klampt/src/robotsim.py | python | RobotModelDriver.getAffineCoeffs | (self) | return _robotsim.RobotModelDriver_getAffineCoeffs(self) | r"""
getAffineCoeffs(RobotModelDriver self)
For "affine" links, returns the scale and offset of the driver value mapped to
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Returns a pair (scale,offset), each of length len(getAffectedLinks()). | r"""
getAffineCoeffs(RobotModelDriver self) | [
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getAffineCoeffs(RobotModelDriver self)
For "affine" links, returns the scale and offset of the driver value mapped to
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Returns a pair (scale,offset), each of length len(getAffectedLinks()).
"""
return _robotsim.RobotModelDriver_getAffineCoeffs(self) | [
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/ast.py | python | walk | (node) | Recursively yield all child nodes of *node*, in no specified order. This is
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Recursively yield all child nodes of *node*, in no specified order. This is
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"""
from collections import deque
todo = deque([node])
while todo:
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todo.extend(iter_child_nodes(node))
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panda3d/panda3d | 833ad89ebad58395d0af0b7ec08538e5e4308265 | direct/src/dist/icon.py | python | Icon.makeICNS | (self, fn) | return True | Writes the images to an Apple ICNS file. Returns True on success. | Writes the images to an Apple ICNS file. Returns True on success. | [
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"success",
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] | def makeICNS(self, fn):
""" Writes the images to an Apple ICNS file. Returns True on success. """
if not isinstance(fn, Filename):
fn = Filename.fromOsSpecific(fn)
fn.setBinary()
icns = open(fn, 'wb')
icns.write(b'icns\0\0\0\0')
icon_types = {16: b'is32', 32: b'il32', 48: b'ih32', 128: b'it32'}
mask_types = {16: b's8mk', 32: b'l8mk', 48: b'h8mk', 128: b't8mk'}
png_types = {256: b'ic08', 512: b'ic09', 1024: b'ic10'}
pngtype = PNMFileTypeRegistry.getGlobalPtr().getTypeFromExtension("png")
for size, image in sorted(self.images.items(), key=lambda item:item[0]):
if size in png_types and pngtype is not None:
stream = StringStream()
image.write(stream, "", pngtype)
pngdata = stream.data
icns.write(png_types[size])
icns.write(struct.pack('>I', len(pngdata)))
icns.write(pngdata)
elif size in icon_types:
# If it has an alpha channel, we write out a mask too.
if image.hasAlpha():
icns.write(mask_types[size])
icns.write(struct.pack('>I', size * size + 8))
for y in range(size):
for x in range(size):
icns.write(struct.pack('<B', int(image.getAlpha(x, y) * 255)))
icns.write(icon_types[size])
icns.write(struct.pack('>I', size * size * 4 + 8))
for y in range(size):
for x in range(size):
r, g, b = image.getXel(x, y)
icns.write(struct.pack('>BBBB', 0, int(r * 255), int(g * 255), int(b * 255)))
length = icns.tell()
icns.seek(4)
icns.write(struct.pack('>I', length))
icns.close()
return True | [
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microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | TPM2_NV_DefineSpace_REQUEST.fromTpm | (buf) | return buf.createObj(TPM2_NV_DefineSpace_REQUEST) | Returns new TPM2_NV_DefineSpace_REQUEST object constructed from its
marshaled representation in the given TpmBuffer buffer | Returns new TPM2_NV_DefineSpace_REQUEST object constructed from its
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""" Returns new TPM2_NV_DefineSpace_REQUEST object constructed from its
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"""
return buf.createObj(TPM2_NV_DefineSpace_REQUEST) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/_pyio.py | python | IOBase.tell | (self) | return self.seek(0, 1) | Return current stream position. | Return current stream position. | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/ops/distributions/multinomial.py | python | Multinomial._maybe_assert_valid_sample | (self, counts) | return control_flow_ops.with_dependencies([
check_ops.assert_equal(
self.total_count, math_ops.reduce_sum(counts, -1),
message="counts must sum to `self.total_count`"),
], counts) | Check counts for proper shape, values, then return tensor version. | Check counts for proper shape, values, then return tensor version. | [
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] | def _maybe_assert_valid_sample(self, counts):
"""Check counts for proper shape, values, then return tensor version."""
if not self.validate_args:
return counts
counts = distribution_util.embed_check_nonnegative_integer_form(counts)
return control_flow_ops.with_dependencies([
check_ops.assert_equal(
self.total_count, math_ops.reduce_sum(counts, -1),
message="counts must sum to `self.total_count`"),
], counts) | [
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | media/webrtc/trunk/build/android/device_status_check.py | python | CheckForMissingDevices | (options, adb_online_devs) | Uses file of previous online devices to detect broken phones.
Args:
options: out_dir parameter of options argument is used as the base
directory to load and update the cache file.
adb_online_devs: A list of serial numbers of the currently visible
and online attached devices. | Uses file of previous online devices to detect broken phones. | [
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] | def CheckForMissingDevices(options, adb_online_devs):
"""Uses file of previous online devices to detect broken phones.
Args:
options: out_dir parameter of options argument is used as the base
directory to load and update the cache file.
adb_online_devs: A list of serial numbers of the currently visible
and online attached devices.
"""
# TODO(navabi): remove this once the bug that causes different number
# of devices to be detected between calls is fixed.
logger = logging.getLogger()
logger.setLevel(logging.INFO)
out_dir = os.path.abspath(options.out_dir)
def ReadDeviceList(file_name):
devices_path = os.path.join(out_dir, file_name)
devices = []
try:
with open(devices_path) as f:
devices = f.read().splitlines()
except IOError:
# Ignore error, file might not exist
pass
return devices
def WriteDeviceList(file_name, device_list):
path = os.path.join(out_dir, file_name)
if not os.path.exists(out_dir):
os.makedirs(out_dir)
with open(path, 'w') as f:
# Write devices currently visible plus devices previously seen.
f.write('\n'.join(set(device_list)))
last_devices_path = os.path.join(out_dir, '.last_devices')
last_devices = ReadDeviceList('.last_devices')
missing_devs = list(set(last_devices) - set(adb_online_devs))
if missing_devs:
from_address = 'buildbot@chromium.org'
to_address = 'chromium-android-device-alerts@google.com'
bot_name = os.environ['BUILDBOT_BUILDERNAME']
slave_name = os.environ['BUILDBOT_SLAVENAME']
num_online_devs = len(adb_online_devs)
subject = 'Devices offline on %s, %s (%d remaining).' % (slave_name,
bot_name,
num_online_devs)
buildbot_report.PrintWarning()
devices_missing_msg = '%d devices not detected.' % len(missing_devs)
buildbot_report.PrintSummaryText(devices_missing_msg)
# TODO(navabi): Debug by printing both output from GetCmdOutput and
# GetAttachedDevices to compare results.
body = '\n'.join(
['Current online devices: %s' % adb_online_devs,
'%s are no longer visible. Were they removed?\n' % missing_devs,
'SHERIFF: See go/chrome_device_monitor',
'Cache file: %s\n\n' % last_devices_path,
'adb devices: %s' % GetCmdOutput(['adb', 'devices']),
'adb devices(GetAttachedDevices): %s' % GetAttachedDevices()])
print body
# Only send email if the first time a particular device goes offline
last_missing = ReadDeviceList('.last_missing')
new_missing_devs = set(missing_devs) - set(last_missing)
if new_missing_devs:
msg_body = '\r\n'.join(
['From: %s' % from_address,
'To: %s' % to_address,
'Subject: %s' % subject,
'', body])
try:
server = smtplib.SMTP('localhost')
server.sendmail(from_address, [to_address], msg_body)
server.quit()
except Exception as e:
print 'Failed to send alert email. Error: %s' % e
else:
new_devs = set(adb_online_devs) - set(last_devices)
if new_devs and os.path.exists(last_devices_path):
buildbot_report.PrintWarning()
buildbot_report.PrintSummaryText(
'%d new devices detected' % len(new_devs))
print ('New devices detected %s. And now back to your '
'regularly scheduled program.' % list(new_devs))
WriteDeviceList('.last_devices', (adb_online_devs + last_devices))
WriteDeviceList('.last_missing', missing_devs) | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | Framework/PythonInterface/plugins/algorithms/Symmetrise.py | python | Symmetrise._calculate_array_points | (self, sample_x, sample_array_len) | Finds the points in the array that match the cut points.
@param sample_x - Sample X axis data
@param sample_array_len - Length of data array for sample data | Finds the points in the array that match the cut points. | [
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] | def _calculate_array_points(self, sample_x, sample_array_len):
"""
Finds the points in the array that match the cut points.
@param sample_x - Sample X axis data
@param sample_array_len - Length of data array for sample data
"""
# Find array index of the first negative XMin
negative_min_diff = sample_x + self._x_min
self._negative_min_index = np.where(negative_min_diff > 0)[0][0]
self._check_bounds(self._negative_min_index, sample_array_len, label='Negative')
# Find array index of the first positive XMin, that is smaller than the required
positive_min_diff = sample_x + sample_x[self._negative_min_index]
self._positive_min_index = np.where(positive_min_diff > 0)[0][0]
self._check_bounds(self._positive_min_index, sample_array_len, label='Positive')
# Find array index of the first positive XMax, that is smaller than the required
self._positive_max_index = np.where(sample_x < self._x_max)[0][-1]
if self._positive_max_index == sample_array_len:
self._positive_max_index -= 1
self._check_bounds(self._positive_max_index, sample_array_len, label='Positive') | [
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rapidsai/cudf | d5b2448fc69f17509304d594f029d0df56984962 | python/cudf/cudf/core/index.py | python | DatetimeIndex.isocalendar | (self) | return cudf.core.tools.datetimes._to_iso_calendar(self) | Returns a DataFrame with the year, week, and day
calculated according to the ISO 8601 standard.
Returns
-------
DataFrame
with columns year, week and day
Examples
--------
>>> gIndex = cudf.DatetimeIndex(["2020-05-31 08:00:00",
... "1999-12-31 18:40:00"])
>>> gIndex.isocalendar()
year week day
2020-05-31 08:00:00 2020 22 7
1999-12-31 18:40:00 1999 52 5 | Returns a DataFrame with the year, week, and day
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"""
Returns a DataFrame with the year, week, and day
calculated according to the ISO 8601 standard.
Returns
-------
DataFrame
with columns year, week and day
Examples
--------
>>> gIndex = cudf.DatetimeIndex(["2020-05-31 08:00:00",
... "1999-12-31 18:40:00"])
>>> gIndex.isocalendar()
year week day
2020-05-31 08:00:00 2020 22 7
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"""
return cudf.core.tools.datetimes._to_iso_calendar(self) | [
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microsoft/ivy | 9f3c7ecc0b2383129fdd0953e10890d98d09a82d | ivy/ivy_logic_parser.py | python | p_terms_terms_term | (p) | terms : terms COMMA term | terms : terms COMMA term | [
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macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/v8/third_party/jinja2/filters.py | python | do_urlencode | (value) | return u'&'.join(unicode_urlencode(k) + '=' +
unicode_urlencode(v, for_qs=True)
for k, v in itemiter) | Escape strings for use in URLs (uses UTF-8 encoding). It accepts both
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"""Escape strings for use in URLs (uses UTF-8 encoding). It accepts both
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.. versionadded:: 2.7
"""
itemiter = None
if isinstance(value, dict):
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/ops/_op_impl/_custom_op/img2col_impl.py | python | height56_width56 | (tik_instance, input_x, res, input_shape, shape_info) | return tik_instance, res | height56_width56 | height56_width56 | [
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] | def height56_width56(tik_instance, input_x, res, input_shape, shape_info):
"""height56_width56"""
if input_shape == ((32, 4, 56, 56, 16), 'float16', (3, 3), (1, 1)):
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tik_instance, res = shape56_2(tik_instance, input_x, res, input_shape, shape_info)
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hakuna-m/wubiuefi | caec1af0a09c78fd5a345180ada1fe45e0c63493 | src/pypack/modulegraph/pkg_resources.py | python | WorkingSet.subscribe | (self, callback) | Invoke `callback` for all distributions (including existing ones) | Invoke `callback` for all distributions (including existing ones) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/ipython/py3/IPython/core/prefilter.py | python | AssignmentChecker.check | (self, line_info) | Check to see if user is assigning to a var for the first time, in
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This allows users to assign to either alias or magic names true python
variables (the magic/alias systems always take second seat to true
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if line_info.the_rest:
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rdkit/rdkit | ede860ae316d12d8568daf5ee800921c3389c84e | rdkit/sping/WX/pidWxDc.py | python | PiddleWxDc._setWXfont | (self, font=None) | return (wx_font) | set/return the current font for the dc
jjk 10/28/99 | set/return the current font for the dc
jjk 10/28/99 | [
"set",
"/",
"return",
"the",
"current",
"font",
"for",
"the",
"dc",
"jjk",
"10",
"/",
"28",
"/",
"99"
] | def _setWXfont(self, font=None):
'''set/return the current font for the dc
jjk 10/28/99'''
wx_font = self._getWXfont(font)
self.dc.SetFont(wx_font)
return (wx_font) | [
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idaholab/moose | 9eeebc65e098b4c30f8205fb41591fd5b61eb6ff | python/MooseDocs/base/Translator.py | python | Translator.renderer | (self) | return self.__renderer | Return the Renderer object. | Return the Renderer object. | [
"Return",
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"."
] | def renderer(self):
"""Return the Renderer object."""
return self.__renderer | [
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":",
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] | https://github.com/idaholab/moose/blob/9eeebc65e098b4c30f8205fb41591fd5b61eb6ff/python/MooseDocs/base/Translator.py#L98-L100 | |
citizenfx/fivem | 88276d40cc7baf8285d02754cc5ae42ec7a8563f | vendor/chromium/mojo/public/tools/bindings/pylib/mojom/generate/translate.py | python | _Union | (module, parsed_union) | return union | Args:
module: {mojom.Module} Module currently being constructed.
parsed_union: {ast.Union} Parsed union.
Returns:
{mojom.Union} AST union. | Args:
module: {mojom.Module} Module currently being constructed.
parsed_union: {ast.Union} Parsed union. | [
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] | def _Union(module, parsed_union):
"""
Args:
module: {mojom.Module} Module currently being constructed.
parsed_union: {ast.Union} Parsed union.
Returns:
{mojom.Union} AST union.
"""
union = mojom.Union(module=module)
union.mojom_name = parsed_union.mojom_name
union.spec = 'x:' + module.mojom_namespace + '.' + union.mojom_name
module.kinds[union.spec] = union
# Stash fields parsed_union here temporarily.
union.fields_data = _ElemsOfType(
parsed_union.body, ast.UnionField, parsed_union.mojom_name)
union.attributes = _AttributeListToDict(parsed_union.attribute_list)
return union | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/pydoc.py | python | TextDoc.section | (self, title, contents) | return self.bold(title) + '\n' + rstrip(self.indent(contents)) + '\n\n' | Format a section with a given heading. | Format a section with a given heading. | [
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"section",
"with",
"a",
"given",
"heading",
"."
] | def section(self, title, contents):
"""Format a section with a given heading."""
return self.bold(title) + '\n' + rstrip(self.indent(contents)) + '\n\n' | [
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] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/pydoc.py#L1048-L1050 | |
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/requests/models.py | python | Response.json | (self, **kwargs) | return complexjson.loads(self.text, **kwargs) | r"""Returns the json-encoded content of a response, if any.
:param \*\*kwargs: Optional arguments that ``json.loads`` takes.
:raises ValueError: If the response body does not contain valid json. | r"""Returns the json-encoded content of a response, if any. | [
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"-",
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] | def json(self, **kwargs):
r"""Returns the json-encoded content of a response, if any.
:param \*\*kwargs: Optional arguments that ``json.loads`` takes.
:raises ValueError: If the response body does not contain valid json.
"""
if not self.encoding and self.content and len(self.content) > 3:
# No encoding set. JSON RFC 4627 section 3 states we should expect
# UTF-8, -16 or -32. Detect which one to use; If the detection or
# decoding fails, fall back to `self.text` (using chardet to make
# a best guess).
encoding = guess_json_utf(self.content)
if encoding is not None:
try:
return complexjson.loads(
self.content.decode(encoding), **kwargs
)
except UnicodeDecodeError:
# Wrong UTF codec detected; usually because it's not UTF-8
# but some other 8-bit codec. This is an RFC violation,
# and the server didn't bother to tell us what codec *was*
# used.
pass
return complexjson.loads(self.text, **kwargs) | [
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tensorflow/minigo | 6d89c202cdceaf449aefc3149ab2110d44f1a6a4 | ml_perf/utils.py | python | wait | (aws) | return results if isinstance(aws, list) else results[0] | Waits for all of the awaitable objects (e.g. coroutines) in aws to finish.
All the awaitable objects are waited for, even if one of them raises an
exception. When one or more awaitable raises an exception, the exception
from the awaitable with the lowest index in the aws list will be reraised.
Args:
aws: a single awaitable, or list awaitables.
Returns:
If aws is a single awaitable, its result.
If aws is a list of awaitables, a list containing the of each awaitable
in the list.
Raises:
Exception: if any of the awaitables raises. | Waits for all of the awaitable objects (e.g. coroutines) in aws to finish. | [
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"."
] | def wait(aws):
"""Waits for all of the awaitable objects (e.g. coroutines) in aws to finish.
All the awaitable objects are waited for, even if one of them raises an
exception. When one or more awaitable raises an exception, the exception
from the awaitable with the lowest index in the aws list will be reraised.
Args:
aws: a single awaitable, or list awaitables.
Returns:
If aws is a single awaitable, its result.
If aws is a list of awaitables, a list containing the of each awaitable
in the list.
Raises:
Exception: if any of the awaitables raises.
"""
aws_list = aws if isinstance(aws, list) else [aws]
results = asyncio.get_event_loop().run_until_complete(asyncio.gather(
*aws_list, return_exceptions=True))
# If any of the cmds failed, re-raise the error.
for result in results:
if isinstance(result, Exception):
raise result
return results if isinstance(aws, list) else results[0] | [
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"gather"... | https://github.com/tensorflow/minigo/blob/6d89c202cdceaf449aefc3149ab2110d44f1a6a4/ml_perf/utils.py#L176-L202 | |
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/codecs.py | python | StreamReader.reset | (self) | Resets the codec buffers used for keeping state.
Note that no stream repositioning should take place.
This method is primarily intended to be able to recover
from decoding errors. | Resets the codec buffers used for keeping state. | [
"Resets",
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"codec",
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"keeping",
"state",
"."
] | def reset(self):
""" Resets the codec buffers used for keeping state.
Note that no stream repositioning should take place.
This method is primarily intended to be able to recover
from decoding errors.
"""
self.bytebuffer = ""
self.charbuffer = u""
self.linebuffer = None | [
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] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/tools/python/src/Lib/codecs.py#L608-L619 | ||
mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Tool/applelink.py | python | _applelib_versioned_lib_suffix | (env, suffix, version) | return suffix | For suffix='.dylib' and version='0.1.2' it returns '.0.1.2.dylib | For suffix='.dylib' and version='0.1.2' it returns '.0.1.2.dylib | [
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"returns",
".",
"0",
".",
"1",
".",
"2",
".",
"dylib"
] | def _applelib_versioned_lib_suffix(env, suffix, version):
"""For suffix='.dylib' and version='0.1.2' it returns '.0.1.2.dylib'"""
Verbose = False
if Verbose:
print("_applelib_versioned_lib_suffix: suffix={!r}".format(suffix))
print("_applelib_versioned_lib_suffix: version={!r}".format(version))
if version not in suffix:
suffix = "." + version + suffix
if Verbose:
print("_applelib_versioned_lib_suffix: return suffix={!r}".format(suffix))
return suffix | [
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simsong/bulk_extractor | 738911df22b7066ca9e1662f4131fb44090a4196 | python/dfxml.py | python | fileobject.savefile | (self,filename=None) | Saves the file. | Saves the file. | [
"Saves",
"the",
"file",
"."
] | def savefile(self,filename=None):
"""Saves the file."""
with open(filename,"wb") as f:
for run in self.byte_runs():
self.imagefile.seek(run.img_offset)
count = run.len
while count>0:
xfer_len = min(count,1024*1024) # transfer up to a megabyte at a time
buf = self.imagefile.read(xfer_len)
if len(buf)==0: break
f.write(buf)
count -= xfer_len | [
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... | https://github.com/simsong/bulk_extractor/blob/738911df22b7066ca9e1662f4131fb44090a4196/python/dfxml.py#L872-L883 | ||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/prompt-toolkit/py3/prompt_toolkit/lexers/base.py | python | Lexer.invalidation_hash | (self) | return id(self) | When this changes, `lex_document` could give a different output.
(Only used for `DynamicLexer`.) | When this changes, `lex_document` could give a different output.
(Only used for `DynamicLexer`.) | [
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"DynamicLexer",
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")"
] | def invalidation_hash(self) -> Hashable:
"""
When this changes, `lex_document` could give a different output.
(Only used for `DynamicLexer`.)
"""
return id(self) | [
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] | https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/prompt-toolkit/py3/prompt_toolkit/lexers/base.py#L33-L38 | |
MegaGlest/megaglest-source | e3af470288a3c9cc179f63b5a1eb414a669e3772 | mk/windoze/symbolstore.py | python | StartProcessFilesWork | (dumper, files, arch_num, arch, vcs_root, after, after_arg) | return dumper.ProcessFilesWork(files, arch_num, arch, vcs_root, after, after_arg) | multiprocessing can't handle methods as Process targets, so we define
a simple wrapper function around the work method. | multiprocessing can't handle methods as Process targets, so we define
a simple wrapper function around the work method. | [
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"."
] | def StartProcessFilesWork(dumper, files, arch_num, arch, vcs_root, after, after_arg):
"""multiprocessing can't handle methods as Process targets, so we define
a simple wrapper function around the work method."""
return dumper.ProcessFilesWork(files, arch_num, arch, vcs_root, after, after_arg) | [
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... | https://github.com/MegaGlest/megaglest-source/blob/e3af470288a3c9cc179f63b5a1eb414a669e3772/mk/windoze/symbolstore.py#L314-L317 |
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