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wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/stc.py
|
python
|
StyledTextCtrl.FormatRange
|
(*args, **kwargs)
|
return _stc.StyledTextCtrl_FormatRange(*args, **kwargs)
|
FormatRange(self, bool doDraw, int startPos, int endPos, DC draw, DC target,
Rect renderRect, Rect pageRect) -> int
On Windows, will draw the document into a display context such as a printer.
|
FormatRange(self, bool doDraw, int startPos, int endPos, DC draw, DC target,
Rect renderRect, Rect pageRect) -> int
|
[
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")",
"-",
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def FormatRange(*args, **kwargs):
"""
FormatRange(self, bool doDraw, int startPos, int endPos, DC draw, DC target,
Rect renderRect, Rect pageRect) -> int
On Windows, will draw the document into a display context such as a printer.
"""
return _stc.StyledTextCtrl_FormatRange(*args, **kwargs)
|
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/stc.py#L3504-L3511
|
|
tensorflow/tensorflow
|
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
|
tensorflow/python/ops/variable_scope.py
|
python
|
_VariableStore._get_partitioned_variable
|
(self,
name,
partitioner,
shape=None,
dtype=dtypes.float32,
initializer=None,
regularizer=None,
reuse=None,
trainable=None,
collections=None,
caching_device=None,
validate_shape=True,
use_resource=None,
constraint=None,
synchronization=VariableSynchronization.AUTO,
aggregation=VariableAggregation.NONE)
|
return partitioned_var
|
Gets or creates a sharded variable list with these parameters.
The `partitioner` must be a callable that accepts a fully defined
`TensorShape` and returns a sequence of integers (the `partitions`).
These integers describe how to partition the given sharded `Variable`
along the given dimension. That is, `partitions[1] = 3` means split
the `Variable` into 3 shards along dimension 1. Currently, sharding along
only one axis is supported.
If the list of variables with the given name (prefix) is already stored,
we return the stored variables. Otherwise, we create a new one.
Set `reuse` to `True` when you only want to reuse existing Variables.
Set `reuse` to `False` when you only want to create new Variables.
Set `reuse` to None (the default) or tf.compat.v1.AUTO_REUSE when you want
variables to be created if they don't exist or returned if they do.
If initializer is `None` (the default), the default initializer passed in
the constructor is used. If that one is `None` too, we use a new
`glorot_uniform_initializer`. If initializer is a Tensor, we use
it as a value and derive the shape from the initializer.
If the initializer is a callable, then it will be called for each
shard. Otherwise the initializer should match the shape of the entire
sharded Variable, and it will be sliced accordingly for each shard.
Some useful partitioners are available. See, e.g.,
`variable_axis_size_partitioner` and `min_max_variable_partitioner`.
Args:
name: the name of the new or existing sharded variable.
partitioner: Optional callable that accepts a fully defined `TensorShape`
and `dtype` of the Variable to be created, and returns a list of
partitions for each axis (currently only one axis can be partitioned).
shape: shape of the new or existing sharded variable.
dtype: type of the new or existing sharded variable (defaults to
`DT_FLOAT`).
initializer: initializer for the sharded variable.
regularizer: a (Tensor -> Tensor or None) function; the result of applying
it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
reuse: a Boolean, None, or tf.AUTO_REUSE. Controls reuse or creation of
variables.
trainable: If `True` also add the variable to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see `tf.Variable`).
collections: List of graph collections keys to add the Variable to.
Defaults to `[GraphKeys.GLOBAL_VARIABLES]` (see `tf.Variable`).
caching_device: Optional device string or function describing where the
Variable should be cached for reading. Defaults to the Variable's
device. If not `None`, caches on another device. Typical use is to
cache on the device where the Ops using the Variable reside, to
deduplicate copying through `Switch` and other conditional statements.
validate_shape: If False, allows the variable to be initialized with a
value of unknown shape. If True, the default, the shape of initial_value
must be known.
use_resource: If False, creates a regular Variable. If True, creates an
experimental ResourceVariable which has well-defined semantics. Defaults
to False (will later change to True).
constraint: An optional projection function to be applied to the variable
after being updated by an `Optimizer` (e.g. used to implement norm
constraints or value constraints for layer weights). The function must
take as input the unprojected Tensor representing the value of the
variable and return the Tensor for the projected value (which must have
the same shape). Constraints are not safe to use when doing asynchronous
distributed training.
synchronization: Indicates when a distributed a variable will be
aggregated. Accepted values are constants defined in the class
`tf.VariableSynchronization`. By default the synchronization is set to
`AUTO` and the current `DistributionStrategy` chooses when to
synchronize.
aggregation: Indicates how a distributed variable will be aggregated.
Accepted values are constants defined in the class
`tf.VariableAggregation`.
Returns:
A `PartitionedVariable` object.
Raises:
ValueError: when creating a new variable and shape is not declared,
when reusing a variable and specifying a conflicting shape,
when violating reuse during variable creation, or if an existing
sharded variable exists for the given name but with different sharding.
|
Gets or creates a sharded variable list with these parameters.
|
[
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"a",
"sharded",
"variable",
"list",
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"."
] |
def _get_partitioned_variable(self,
name,
partitioner,
shape=None,
dtype=dtypes.float32,
initializer=None,
regularizer=None,
reuse=None,
trainable=None,
collections=None,
caching_device=None,
validate_shape=True,
use_resource=None,
constraint=None,
synchronization=VariableSynchronization.AUTO,
aggregation=VariableAggregation.NONE):
"""Gets or creates a sharded variable list with these parameters.
The `partitioner` must be a callable that accepts a fully defined
`TensorShape` and returns a sequence of integers (the `partitions`).
These integers describe how to partition the given sharded `Variable`
along the given dimension. That is, `partitions[1] = 3` means split
the `Variable` into 3 shards along dimension 1. Currently, sharding along
only one axis is supported.
If the list of variables with the given name (prefix) is already stored,
we return the stored variables. Otherwise, we create a new one.
Set `reuse` to `True` when you only want to reuse existing Variables.
Set `reuse` to `False` when you only want to create new Variables.
Set `reuse` to None (the default) or tf.compat.v1.AUTO_REUSE when you want
variables to be created if they don't exist or returned if they do.
If initializer is `None` (the default), the default initializer passed in
the constructor is used. If that one is `None` too, we use a new
`glorot_uniform_initializer`. If initializer is a Tensor, we use
it as a value and derive the shape from the initializer.
If the initializer is a callable, then it will be called for each
shard. Otherwise the initializer should match the shape of the entire
sharded Variable, and it will be sliced accordingly for each shard.
Some useful partitioners are available. See, e.g.,
`variable_axis_size_partitioner` and `min_max_variable_partitioner`.
Args:
name: the name of the new or existing sharded variable.
partitioner: Optional callable that accepts a fully defined `TensorShape`
and `dtype` of the Variable to be created, and returns a list of
partitions for each axis (currently only one axis can be partitioned).
shape: shape of the new or existing sharded variable.
dtype: type of the new or existing sharded variable (defaults to
`DT_FLOAT`).
initializer: initializer for the sharded variable.
regularizer: a (Tensor -> Tensor or None) function; the result of applying
it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
reuse: a Boolean, None, or tf.AUTO_REUSE. Controls reuse or creation of
variables.
trainable: If `True` also add the variable to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see `tf.Variable`).
collections: List of graph collections keys to add the Variable to.
Defaults to `[GraphKeys.GLOBAL_VARIABLES]` (see `tf.Variable`).
caching_device: Optional device string or function describing where the
Variable should be cached for reading. Defaults to the Variable's
device. If not `None`, caches on another device. Typical use is to
cache on the device where the Ops using the Variable reside, to
deduplicate copying through `Switch` and other conditional statements.
validate_shape: If False, allows the variable to be initialized with a
value of unknown shape. If True, the default, the shape of initial_value
must be known.
use_resource: If False, creates a regular Variable. If True, creates an
experimental ResourceVariable which has well-defined semantics. Defaults
to False (will later change to True).
constraint: An optional projection function to be applied to the variable
after being updated by an `Optimizer` (e.g. used to implement norm
constraints or value constraints for layer weights). The function must
take as input the unprojected Tensor representing the value of the
variable and return the Tensor for the projected value (which must have
the same shape). Constraints are not safe to use when doing asynchronous
distributed training.
synchronization: Indicates when a distributed a variable will be
aggregated. Accepted values are constants defined in the class
`tf.VariableSynchronization`. By default the synchronization is set to
`AUTO` and the current `DistributionStrategy` chooses when to
synchronize.
aggregation: Indicates how a distributed variable will be aggregated.
Accepted values are constants defined in the class
`tf.VariableAggregation`.
Returns:
A `PartitionedVariable` object.
Raises:
ValueError: when creating a new variable and shape is not declared,
when reusing a variable and specifying a conflicting shape,
when violating reuse during variable creation, or if an existing
sharded variable exists for the given name but with different sharding.
"""
initializing_from_value = initializer is not None and isinstance(
initializer, ops.Tensor)
if name in self._vars:
raise ValueError(
"A partitioner was provided, but an unpartitioned version of the "
"variable was found: %s. Perhaps a variable of the same name was "
"already created without partitioning?" % name)
shape = tensor_shape.as_shape(shape)
if initializing_from_value:
shape = shape.merge_with(initializer.get_shape())
partitions = None
if not reuse or partitioner:
partitions = _call_partitioner(partitioner, shape, dtype)
if name in self._partitioned_vars:
if reuse is False:
raise ValueError(
"Partitioned variable with name %s already exists. Did you mean to "
"set reuse=True or reuse=tf.AUTO_REUSE in VarScope?" % name)
existing_var = self._partitioned_vars[name]
if not shape.is_compatible_with(existing_var.get_shape()):
raise ValueError(
"Trying to reuse partitioned variable %s, but specified shape %s "
"and found shape %s." % (name, shape, existing_var.get_shape()))
if not dtype.is_compatible_with(existing_var.dtype):
raise ValueError(
"Trying to reuse partitioned variable %s, but specified dtype %s "
"and found dtype %s." % (name, dtype.name, existing_var.dtype.name))
# pylint: disable=protected-access
if (partitions is not None and
existing_var._get_partitions() != partitions):
raise ValueError(
"Trying to reuse partitioned variable %s, but specified partitions "
"%s and found partitions %s." %
(name, partitions, existing_var._get_partitions()))
# pylint: enable=protected-access
return existing_var
if reuse is True:
raise ValueError("PartitionedVariable %s does not exist, or was not "
"created with tf.get_variable(). Did you mean to set "
"reuse=False or reuse=tf.AUTO_REUSE in VarScope?" % name)
slice_dim, num_slices = _get_slice_dim_and_num_slices(partitions)
if "%s/part_0" % name in self._vars:
if "%s/part_%d" % (name, num_slices - 1) not in self._vars:
raise ValueError(
"Partitioner returned a different partitioning than what was "
"already found. Partitioner returned %d shards, and shard "
"%s/part_0 was found, but %s/part_%d was not." %
(num_slices, name, name, num_slices - 1))
if "%s/part_%d" % (name, num_slices) in self._vars:
raise ValueError(
"Partitioner returned a different partitioning than what was "
"already found. Partitioner returned %d shards, and shard "
"%s/part_0 was found, but so was the extra shard %s/part_%d." %
(num_slices, name, name, num_slices))
vs = []
for i, (var_offset, var_shape) in enumerate(
_iter_slices(shape.as_list(), num_slices, slice_dim)):
partition_info = _PartitionInfo(
full_shape=shape.as_list(), var_offset=var_offset)
var_full_name = "%s/part_%d" % (name, i)
with ops.name_scope(
var_full_name + "/PartitionedInitializer", skip_on_eager=False):
# Create the tensor to initialize the variable with default value.
if initializer is None:
init, initializing_from_value = self._get_default_initializer(
name=name, shape=shape, dtype=dtype)
if initializing_from_value:
init_shape = None
else:
init_shape = var_shape
elif callable(initializer):
init = initializer
init_shape = var_shape
elif isinstance(initializer, ops.Tensor):
init = array_ops.slice(initializer, var_offset, var_shape)
# Use the dtype of the given tensor.
dtype = init.dtype.base_dtype
init_shape = None
else:
init = ops.convert_to_tensor(initializer, dtype=dtype)
init = array_ops.slice(init, var_offset, var_shape)
init_shape = None
with ops.name_scope(None):
var = self._get_single_variable(
name=var_full_name,
shape=init_shape,
dtype=dtype,
initializer=init,
partition_info=partition_info,
regularizer=regularizer,
reuse=reuse,
trainable=trainable,
collections=collections,
caching_device=caching_device,
validate_shape=validate_shape,
use_resource=use_resource,
constraint=constraint,
synchronization=synchronization,
aggregation=aggregation)
# pylint: disable=protected-access
var._set_save_slice_info(
variables.Variable.SaveSliceInfo(name, shape.as_list(), var_offset,
var_shape))
vs.append(var)
# pylint: enable=protected-access
partitioned_var = variables.PartitionedVariable(
name=name,
shape=shape,
dtype=dtype,
variable_list=vs,
partitions=partitions)
if not context.executing_eagerly() or self._store_eager_variables:
self._partitioned_vars[name] = partitioned_var
return partitioned_var
|
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".",
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"partitions",
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"executing_eagerly",
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":",
"self",
".",
"_partitioned_vars",
"[",
"name",
"]",
"=",
"partitioned_var",
"return",
"partitioned_var"
] |
https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/ops/variable_scope.py#L599-L824
|
|
CRYTEK/CRYENGINE
|
232227c59a220cbbd311576f0fbeba7bb53b2a8c
|
Code/Tools/waf-1.7.13/crywaflib/compile_rules_win_x64_win_x64.py
|
python
|
load_release_win_x64_win_x64_settings
|
(conf)
|
Setup all compiler and linker settings shared over all win_x64_win_x64 configurations for
the 'release' configuration
|
Setup all compiler and linker settings shared over all win_x64_win_x64 configurations for
the 'release' configuration
|
[
"Setup",
"all",
"compiler",
"and",
"linker",
"settings",
"shared",
"over",
"all",
"win_x64_win_x64",
"configurations",
"for",
"the",
"release",
"configuration"
] |
def load_release_win_x64_win_x64_settings(conf):
"""
Setup all compiler and linker settings shared over all win_x64_win_x64 configurations for
the 'release' configuration
"""
v = conf.env
conf.load_win_x64_win_x64_common_settings()
# Load addional shared settings
conf.load_release_cryengine_settings()
conf.load_release_msvc_settings()
conf.load_release_windows_settings()
|
[
"def",
"load_release_win_x64_win_x64_settings",
"(",
"conf",
")",
":",
"v",
"=",
"conf",
".",
"env",
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"load_win_x64_win_x64_common_settings",
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"# Load addional shared settings",
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")",
"conf",
".",
"load_release_msvc_settings",
"(",
")",
"conf",
".",
"load_release_windows_settings",
"(",
")"
] |
https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Code/Tools/waf-1.7.13/crywaflib/compile_rules_win_x64_win_x64.py#L93-L104
|
||
windystrife/UnrealEngine_NVIDIAGameWorks
|
b50e6338a7c5b26374d66306ebc7807541ff815e
|
Engine/Source/ThirdParty/CEF3/pristine/cef_source/tools/cef_parser.py
|
python
|
obj_analysis.is_result_vector_rawptr
|
(self)
|
return self.result_value[0]['result_type'] == 'rawptr'
|
Returns true if this is a RawPtr vector.
|
Returns true if this is a RawPtr vector.
|
[
"Returns",
"true",
"if",
"this",
"is",
"a",
"RawPtr",
"vector",
"."
] |
def is_result_vector_rawptr(self):
""" Returns true if this is a RawPtr vector. """
return self.result_value[0]['result_type'] == 'rawptr'
|
[
"def",
"is_result_vector_rawptr",
"(",
"self",
")",
":",
"return",
"self",
".",
"result_value",
"[",
"0",
"]",
"[",
"'result_type'",
"]",
"==",
"'rawptr'"
] |
https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Source/ThirdParty/CEF3/pristine/cef_source/tools/cef_parser.py#L1913-L1915
|
|
envoyproxy/envoy
|
65541accdafe255e72310b4298d646e091da2d80
|
tools/config_validation/validate_fragment.py
|
python
|
validate_fragment
|
(type_name, fragment, descriptor_path=None)
|
Validate a dictionary representing a JSON/YAML fragment against an Envoy API proto3 type.
Throws Protobuf errors on parsing exceptions, successful validations produce
no result.
Args:
type_name: a string providing the type name, e.g.
envoy.config.bootstrap.v3.Bootstrap.
fragment: a dictionary representing the parsed JSON/YAML configuration
fragment.
|
Validate a dictionary representing a JSON/YAML fragment against an Envoy API proto3 type.
|
[
"Validate",
"a",
"dictionary",
"representing",
"a",
"JSON",
"/",
"YAML",
"fragment",
"against",
"an",
"Envoy",
"API",
"proto3",
"type",
"."
] |
def validate_fragment(type_name, fragment, descriptor_path=None):
"""Validate a dictionary representing a JSON/YAML fragment against an Envoy API proto3 type.
Throws Protobuf errors on parsing exceptions, successful validations produce
no result.
Args:
type_name: a string providing the type name, e.g.
envoy.config.bootstrap.v3.Bootstrap.
fragment: a dictionary representing the parsed JSON/YAML configuration
fragment.
"""
json_fragment = json.dumps(fragment, skipkeys=True)
if not descriptor_path:
r = runfiles.Create()
descriptor_path = r.Rlocation(
'envoy/tools/type_whisperer/all_protos_with_ext_pb_text.pb_text')
file_desc_set = descriptor_pb2.FileDescriptorSet()
text_format.Parse(
pathlib.Path(descriptor_path).read_text(), file_desc_set, allow_unknown_extension=True)
pool = descriptor_pool.DescriptorPool()
for f in file_desc_set.file:
pool.Add(f)
desc = pool.FindMessageTypeByName(type_name)
msg = message_factory.MessageFactory(pool=pool).GetPrototype(desc)()
json_format.Parse(json_fragment, msg, descriptor_pool=pool)
|
[
"def",
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"type_name",
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"fragment",
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"descriptor_path",
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"Parse",
"(",
"json_fragment",
",",
"msg",
",",
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"=",
"pool",
")"
] |
https://github.com/envoyproxy/envoy/blob/65541accdafe255e72310b4298d646e091da2d80/tools/config_validation/validate_fragment.py#L55-L83
|
||
gnina/gnina
|
b9ae032f52fc7a8153987bde09c0efa3620d8bb6
|
caffe/scripts/cpp_lint.py
|
python
|
CheckIncludeLine
|
(filename, clean_lines, linenum, include_state, error)
|
Check rules that are applicable to #include lines.
Strings on #include lines are NOT removed from elided line, to make
certain tasks easier. However, to prevent false positives, checks
applicable to #include lines in CheckLanguage must be put here.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
include_state: An _IncludeState instance in which the headers are inserted.
error: The function to call with any errors found.
|
Check rules that are applicable to #include lines.
|
[
"Check",
"rules",
"that",
"are",
"applicable",
"to",
"#include",
"lines",
"."
] |
def CheckIncludeLine(filename, clean_lines, linenum, include_state, error):
"""Check rules that are applicable to #include lines.
Strings on #include lines are NOT removed from elided line, to make
certain tasks easier. However, to prevent false positives, checks
applicable to #include lines in CheckLanguage must be put here.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
include_state: An _IncludeState instance in which the headers are inserted.
error: The function to call with any errors found.
"""
fileinfo = FileInfo(filename)
line = clean_lines.lines[linenum]
# "include" should use the new style "foo/bar.h" instead of just "bar.h"
if _RE_PATTERN_INCLUDE_NEW_STYLE.search(line):
error(filename, linenum, 'build/include_dir', 4,
'Include the directory when naming .h files')
# we shouldn't include a file more than once. actually, there are a
# handful of instances where doing so is okay, but in general it's
# not.
match = _RE_PATTERN_INCLUDE.search(line)
if match:
include = match.group(2)
is_system = (match.group(1) == '<')
if include in include_state:
error(filename, linenum, 'build/include', 4,
'"%s" already included at %s:%s' %
(include, filename, include_state[include]))
else:
include_state[include] = linenum
# We want to ensure that headers appear in the right order:
# 1) for foo.cc, foo.h (preferred location)
# 2) c system files
# 3) cpp system files
# 4) for foo.cc, foo.h (deprecated location)
# 5) other google headers
#
# We classify each include statement as one of those 5 types
# using a number of techniques. The include_state object keeps
# track of the highest type seen, and complains if we see a
# lower type after that.
error_message = include_state.CheckNextIncludeOrder(
_ClassifyInclude(fileinfo, include, is_system))
if error_message:
error(filename, linenum, 'build/include_order', 4,
'%s. Should be: %s.h, c system, c++ system, other.' %
(error_message, fileinfo.BaseName()))
canonical_include = include_state.CanonicalizeAlphabeticalOrder(include)
if not include_state.IsInAlphabeticalOrder(
clean_lines, linenum, canonical_include):
error(filename, linenum, 'build/include_alpha', 4,
'Include "%s" not in alphabetical order' % include)
include_state.SetLastHeader(canonical_include)
# Look for any of the stream classes that are part of standard C++.
match = _RE_PATTERN_INCLUDE.match(line)
if match:
include = match.group(2)
if Match(r'(f|ind|io|i|o|parse|pf|stdio|str|)?stream$', include):
# Many unit tests use cout, so we exempt them.
if not _IsTestFilename(filename):
error(filename, linenum, 'readability/streams', 3,
'Streams are highly discouraged.')
|
[
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"# 3) cpp system files",
"# 4) for foo.cc, foo.h (deprecated location)",
"# 5) other google headers",
"#",
"# We classify each include statement as one of those 5 types",
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",",
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",",
"3",
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"'Streams are highly discouraged.'",
")"
] |
https://github.com/gnina/gnina/blob/b9ae032f52fc7a8153987bde09c0efa3620d8bb6/caffe/scripts/cpp_lint.py#L3684-L3753
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Code/Tools/AzCodeGenerator/Scripts/az_code_gen/clang_cpp.py
|
python
|
resolve_annotation
|
(annotations, tag, default=None)
|
return default
|
Resolves an annotation in C++ namespace format to its value or None
e.g. AzClass::Serialize::Base -> annotations['AzClass']['Serialize']['Base']
@param annotations The root annotation dict to search through
@param tag The C++ formatted tag (using either :: or . as a separator)
@param default The value to return if no annotation is found (default: None)
@return The resolved annotation value or default
|
Resolves an annotation in C++ namespace format to its value or None
e.g. AzClass::Serialize::Base -> annotations['AzClass']['Serialize']['Base']
|
[
"Resolves",
"an",
"annotation",
"in",
"C",
"++",
"namespace",
"format",
"to",
"its",
"value",
"or",
"None",
"e",
".",
"g",
".",
"AzClass",
"::",
"Serialize",
"::",
"Base",
"-",
">",
"annotations",
"[",
"AzClass",
"]",
"[",
"Serialize",
"]",
"[",
"Base",
"]"
] |
def resolve_annotation(annotations, tag, default=None):
""" Resolves an annotation in C++ namespace format to its value or None
e.g. AzClass::Serialize::Base -> annotations['AzClass']['Serialize']['Base']
@param annotations The root annotation dict to search through
@param tag The C++ formatted tag (using either :: or . as a separator)
@param default The value to return if no annotation is found (default: None)
@return The resolved annotation value or default
"""
tag_parts = re.split(TAG_SPLIT_PATTERN, tag)
try:
namespace = annotations
for part in tag_parts[0:-1]:
namespace = namespace.get(part, {})
return namespace.get(tag_parts[-1], default)
except:
pass
return default
|
[
"def",
"resolve_annotation",
"(",
"annotations",
",",
"tag",
",",
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"=",
"None",
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":",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Code/Tools/AzCodeGenerator/Scripts/az_code_gen/clang_cpp.py#L28-L44
|
|
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/timeseries/python/timeseries/head.py
|
python
|
TimeSeriesRegressionHead._train_ops
|
(self, features)
|
return estimator_lib.EstimatorSpec(
loss=model_outputs.loss,
mode=mode,
train_op=train_op)
|
Add training ops to the graph.
|
Add training ops to the graph.
|
[
"Add",
"training",
"ops",
"to",
"the",
"graph",
"."
] |
def _train_ops(self, features):
"""Add training ops to the graph."""
mode = estimator_lib.ModeKeys.TRAIN
with variable_scope.variable_scope(
"model",
# Use ResourceVariables to avoid race conditions.
use_resource=True):
model_outputs = self.create_loss(features, mode)
train_op = self.optimizer.minimize(
model_outputs.loss,
global_step=training_util.get_global_step())
return estimator_lib.EstimatorSpec(
loss=model_outputs.loss,
mode=mode,
train_op=train_op)
|
[
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https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/timeseries/python/timeseries/head.py#L95-L110
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pkg_resources/__init__.py
|
python
|
fixup_namespace_packages
|
(path_item, parent=None)
|
Ensure that previously-declared namespace packages include path_item
|
Ensure that previously-declared namespace packages include path_item
|
[
"Ensure",
"that",
"previously",
"-",
"declared",
"namespace",
"packages",
"include",
"path_item"
] |
def fixup_namespace_packages(path_item, parent=None):
"""Ensure that previously-declared namespace packages include path_item"""
_imp.acquire_lock()
try:
for package in _namespace_packages.get(parent, ()):
subpath = _handle_ns(package, path_item)
if subpath:
fixup_namespace_packages(subpath, package)
finally:
_imp.release_lock()
|
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"def",
"fixup_namespace_packages",
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"path_item",
",",
"parent",
"=",
"None",
")",
":",
"_imp",
".",
"acquire_lock",
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")",
"try",
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",",
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"(",
"subpath",
",",
"package",
")",
"finally",
":",
"_imp",
".",
"release_lock",
"(",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pkg_resources/__init__.py#L2308-L2317
|
||
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/x86/toolchain/lib/python2.7/distutils/msvccompiler.py
|
python
|
get_build_version
|
()
|
return None
|
Return the version of MSVC that was used to build Python.
For Python 2.3 and up, the version number is included in
sys.version. For earlier versions, assume the compiler is MSVC 6.
|
Return the version of MSVC that was used to build Python.
|
[
"Return",
"the",
"version",
"of",
"MSVC",
"that",
"was",
"used",
"to",
"build",
"Python",
"."
] |
def get_build_version():
"""Return the version of MSVC that was used to build Python.
For Python 2.3 and up, the version number is included in
sys.version. For earlier versions, assume the compiler is MSVC 6.
"""
prefix = "MSC v."
i = string.find(sys.version, prefix)
if i == -1:
return 6
i = i + len(prefix)
s, rest = sys.version[i:].split(" ", 1)
majorVersion = int(s[:-2]) - 6
minorVersion = int(s[2:3]) / 10.0
# I don't think paths are affected by minor version in version 6
if majorVersion == 6:
minorVersion = 0
if majorVersion >= 6:
return majorVersion + minorVersion
# else we don't know what version of the compiler this is
return None
|
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"def",
"get_build_version",
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")",
":",
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"\"MSC v.\"",
"i",
"=",
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">=",
"6",
":",
"return",
"majorVersion",
"+",
"minorVersion",
"# else we don't know what version of the compiler this is",
"return",
"None"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/distutils/msvccompiler.py#L153-L174
|
|
mantidproject/mantid
|
03deeb89254ec4289edb8771e0188c2090a02f32
|
qt/python/mantidqtinterfaces/mantidqtinterfaces/Muon/GUI/Common/fitting_widgets/model_fitting/model_fitting_model.py
|
python
|
ModelFittingModel._extract_x_and_y_from_current_result_table
|
(self)
|
Extracts the X, Y and error values from the currently selected result table and saves them in the context.
|
Extracts the X, Y and error values from the currently selected result table and saves them in the context.
|
[
"Extracts",
"the",
"X",
"Y",
"and",
"error",
"values",
"from",
"the",
"currently",
"selected",
"result",
"table",
"and",
"saves",
"them",
"in",
"the",
"context",
"."
] |
def _extract_x_and_y_from_current_result_table(self) -> None:
"""Extracts the X, Y and error values from the currently selected result table and saves them in the context."""
results_table_name = self.current_result_table_name
if results_table_name is not None and check_if_workspace_exist(results_table_name):
current_results_table = retrieve_ws(results_table_name)
for i, column_name in enumerate(current_results_table.getColumnNames()):
self._save_values_from_table_column(column_name, current_results_table.column(i),
current_results_table.getPlotType(i))
self._populate_empty_parameter_errors(current_results_table.rowCount())
|
[
"def",
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"self",
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"->",
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"self",
".",
"_populate_empty_parameter_errors",
"(",
"current_results_table",
".",
"rowCount",
"(",
")",
")"
] |
https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/python/mantidqtinterfaces/mantidqtinterfaces/Muon/GUI/Common/fitting_widgets/model_fitting/model_fitting_model.py#L128-L138
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/lib/agw/shapedbutton.py
|
python
|
SButton.ConvertWXToPIL
|
(self, bmp)
|
return img
|
Converts a :class:`Image` into a PIL image.
:param `bmp`: an instance of :class:`Image`.
|
Converts a :class:`Image` into a PIL image.
|
[
"Converts",
"a",
":",
"class",
":",
"Image",
"into",
"a",
"PIL",
"image",
"."
] |
def ConvertWXToPIL(self, bmp):
"""
Converts a :class:`Image` into a PIL image.
:param `bmp`: an instance of :class:`Image`.
"""
width = bmp.GetWidth()
height = bmp.GetHeight()
img = Image.fromstring("RGBA", (width, height), bmp.GetData())
return img
|
[
"def",
"ConvertWXToPIL",
"(",
"self",
",",
"bmp",
")",
":",
"width",
"=",
"bmp",
".",
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"(",
")",
"height",
"=",
"bmp",
".",
"GetHeight",
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".",
"fromstring",
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"\"RGBA\"",
",",
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"width",
",",
"height",
")",
",",
"bmp",
".",
"GetData",
"(",
")",
")",
"return",
"img"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/shapedbutton.py#L902-L913
|
|
Tencent/CMONGO
|
c40380caa14e05509f46993aa8b8da966b09b0b5
|
buildscripts/packager-enterprise.py
|
python
|
make_package
|
(distro, build_os, arch, spec, srcdir)
|
return distro.make_pkg(build_os, arch, spec, srcdir)
|
Construct the package for (arch, distro, spec), getting
packaging files from srcdir and any user-specified suffix from
suffixes
|
Construct the package for (arch, distro, spec), getting
packaging files from srcdir and any user-specified suffix from
suffixes
|
[
"Construct",
"the",
"package",
"for",
"(",
"arch",
"distro",
"spec",
")",
"getting",
"packaging",
"files",
"from",
"srcdir",
"and",
"any",
"user",
"-",
"specified",
"suffix",
"from",
"suffixes"
] |
def make_package(distro, build_os, arch, spec, srcdir):
"""Construct the package for (arch, distro, spec), getting
packaging files from srcdir and any user-specified suffix from
suffixes"""
sdir=setupdir(distro, build_os, arch, spec)
packager.ensure_dir(sdir)
# Note that the RPM packages get their man pages from the debian
# directory, so the debian directory is needed in all cases (and
# innocuous in the debianoids' sdirs).
for pkgdir in ["debian", "rpm"]:
print "Copying packaging files from %s to %s" % ("%s/%s" % (srcdir, pkgdir), sdir)
# FIXME: sh-dash-cee is bad. See if tarfile can do this.
packager.sysassert(["sh", "-c", "(cd \"%s\" && git archive %s %s/ ) | (cd \"%s\" && tar xvf -)" % (srcdir, spec.metadata_gitspec(), pkgdir, sdir)])
# Splat the binaries and snmp files under sdir. The "build" stages of the
# packaging infrastructure will move the files to wherever they
# need to go.
unpack_binaries_into(build_os, arch, spec, sdir)
# Remove the mongosniff binary due to libpcap dynamic
# linkage. FIXME: this removal should go away
# eventually.
if os.path.exists(sdir + "bin/mongosniff"):
os.unlink(sdir + "bin/mongosniff")
return distro.make_pkg(build_os, arch, spec, srcdir)
|
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"(",
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] |
https://github.com/Tencent/CMONGO/blob/c40380caa14e05509f46993aa8b8da966b09b0b5/buildscripts/packager-enterprise.py#L210-L233
|
|
miyosuda/TensorFlowAndroidDemo
|
35903e0221aa5f109ea2dbef27f20b52e317f42d
|
jni-build/jni/include/external/bazel_tools/tools/android/incremental_install.py
|
python
|
UploadNativeLibs
|
(adb, native_lib_args, app_dir, full_install)
|
Uploads native libraries to the device.
|
Uploads native libraries to the device.
|
[
"Uploads",
"native",
"libraries",
"to",
"the",
"device",
"."
] |
def UploadNativeLibs(adb, native_lib_args, app_dir, full_install):
"""Uploads native libraries to the device."""
native_libs = ConvertNativeLibs(native_lib_args)
libs = set()
if native_libs:
abi = FindAbi(adb.GetAbi(), native_libs.keys())
if abi:
libs = native_libs[abi]
basename_to_path = {}
install_checksums = {}
for lib in sorted(libs):
install_checksums[os.path.basename(lib)] = Checksum(lib)
basename_to_path[os.path.basename(lib)] = lib
device_manifest = None
if not full_install:
device_manifest = adb.Pull("%s/native/native_manifest" % app_dir)
device_checksums = {}
if device_manifest is None:
# If we couldn't fetch the device manifest or if this is a non-incremental
# install, wipe the slate clean
adb.Delete("%s/native" % app_dir)
else:
# Otherwise, parse the manifest. Note that this branch is also taken if the
# manifest is empty.
for manifest_line in device_manifest.split("\n"):
if manifest_line:
name, checksum = manifest_line.split(" ")
device_checksums[name] = checksum
libs_to_delete = set(device_checksums) - set(install_checksums)
libs_to_upload = set(install_checksums) - set(device_checksums)
common_libs = set(install_checksums).intersection(set(device_checksums))
libs_to_upload.update([l for l in common_libs
if install_checksums[l] != device_checksums[l]])
libs_to_push = [(basename_to_path[lib], "%s/native/%s" % (app_dir, lib))
for lib in libs_to_upload]
if not libs_to_delete and not libs_to_push and device_manifest is not None:
logging.info("Native libs up-to-date")
return
num_files = len(libs_to_delete) + len(libs_to_push)
logging.info("Updating %d native lib%s...",
num_files, "s" if num_files != 1 else "")
adb.Delete("%s/native/native_manifest" % app_dir)
if libs_to_delete:
adb.DeleteMultiple([
"%s/native/%s" % (app_dir, lib) for lib in libs_to_delete])
upload_walltime_start = time.time()
fs = [adb.Push(local, remote) for local, remote in libs_to_push]
done, not_done = futures.wait(fs, return_when=futures.FIRST_EXCEPTION)
upload_walltime = time.time() - upload_walltime_start
logging.debug("Native library upload walltime: %s seconds", upload_walltime)
# If there is anything in not_done, then some adb call failed and we
# can cancel the rest.
if not_done:
for f in not_done:
f.cancel()
# If any adb call resulted in an exception, re-raise it.
for f in done:
f.result()
install_manifest = [
name + " " + checksum for name, checksum in install_checksums.iteritems()]
adb.PushString("\n".join(install_manifest),
"%s/native/native_manifest" % app_dir).result()
|
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"debug",
"(",
"\"Native library upload walltime: %s seconds\"",
",",
"upload_walltime",
")",
"# If there is anything in not_done, then some adb call failed and we",
"# can cancel the rest.",
"if",
"not_done",
":",
"for",
"f",
"in",
"not_done",
":",
"f",
".",
"cancel",
"(",
")",
"# If any adb call resulted in an exception, re-raise it.",
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"f",
"in",
"done",
":",
"f",
".",
"result",
"(",
")",
"install_manifest",
"=",
"[",
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"+",
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",",
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"(",
")",
"]",
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"\"\\n\"",
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"join",
"(",
"install_manifest",
")",
",",
"\"%s/native/native_manifest\"",
"%",
"app_dir",
")",
".",
"result",
"(",
")"
] |
https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/external/bazel_tools/tools/android/incremental_install.py#L504-L579
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/dateutil/tz/tz.py
|
python
|
datetime_ambiguous
|
(dt, tz=None)
|
return not (same_offset and same_dst)
|
Given a datetime and a time zone, determine whether or not a given datetime
is ambiguous (i.e if there are two times differentiated only by their DST
status).
:param dt:
A :class:`datetime.datetime` (whose time zone will be ignored if ``tz``
is provided.)
:param tz:
A :class:`datetime.tzinfo` with support for the ``fold`` attribute. If
``None`` or not provided, the datetime's own time zone will be used.
:return:
Returns a boolean value whether or not the "wall time" is ambiguous in
``tz``.
.. versionadded:: 2.6.0
|
Given a datetime and a time zone, determine whether or not a given datetime
is ambiguous (i.e if there are two times differentiated only by their DST
status).
|
[
"Given",
"a",
"datetime",
"and",
"a",
"time",
"zone",
"determine",
"whether",
"or",
"not",
"a",
"given",
"datetime",
"is",
"ambiguous",
"(",
"i",
".",
"e",
"if",
"there",
"are",
"two",
"times",
"differentiated",
"only",
"by",
"their",
"DST",
"status",
")",
"."
] |
def datetime_ambiguous(dt, tz=None):
"""
Given a datetime and a time zone, determine whether or not a given datetime
is ambiguous (i.e if there are two times differentiated only by their DST
status).
:param dt:
A :class:`datetime.datetime` (whose time zone will be ignored if ``tz``
is provided.)
:param tz:
A :class:`datetime.tzinfo` with support for the ``fold`` attribute. If
``None`` or not provided, the datetime's own time zone will be used.
:return:
Returns a boolean value whether or not the "wall time" is ambiguous in
``tz``.
.. versionadded:: 2.6.0
"""
if tz is None:
if dt.tzinfo is None:
raise ValueError('Datetime is naive and no time zone provided.')
tz = dt.tzinfo
# If a time zone defines its own "is_ambiguous" function, we'll use that.
is_ambiguous_fn = getattr(tz, 'is_ambiguous', None)
if is_ambiguous_fn is not None:
try:
return tz.is_ambiguous(dt)
except Exception:
pass
# If it doesn't come out and tell us it's ambiguous, we'll just check if
# the fold attribute has any effect on this particular date and time.
dt = dt.replace(tzinfo=tz)
wall_0 = enfold(dt, fold=0)
wall_1 = enfold(dt, fold=1)
same_offset = wall_0.utcoffset() == wall_1.utcoffset()
same_dst = wall_0.dst() == wall_1.dst()
return not (same_offset and same_dst)
|
[
"def",
"datetime_ambiguous",
"(",
"dt",
",",
"tz",
"=",
"None",
")",
":",
"if",
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"'Datetime is naive and no time zone provided.'",
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"dst",
"(",
")",
"return",
"not",
"(",
"same_offset",
"and",
"same_dst",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/dateutil/tz/tz.py#L1717-L1760
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/xrc.py
|
python
|
XmlNode.GetParent
|
(*args, **kwargs)
|
return _xrc.XmlNode_GetParent(*args, **kwargs)
|
GetParent(self) -> XmlNode
|
GetParent(self) -> XmlNode
|
[
"GetParent",
"(",
"self",
")",
"-",
">",
"XmlNode"
] |
def GetParent(*args, **kwargs):
"""GetParent(self) -> XmlNode"""
return _xrc.XmlNode_GetParent(*args, **kwargs)
|
[
"def",
"GetParent",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_xrc",
".",
"XmlNode_GetParent",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/xrc.py#L410-L412
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/typing/context.py
|
python
|
CallFrame.add_return_type
|
(self, return_type)
|
Add *return_type* to the list of inferred return-types.
If there are too many, raise `TypingError`.
|
Add *return_type* to the list of inferred return-types.
If there are too many, raise `TypingError`.
|
[
"Add",
"*",
"return_type",
"*",
"to",
"the",
"list",
"of",
"inferred",
"return",
"-",
"types",
".",
"If",
"there",
"are",
"too",
"many",
"raise",
"TypingError",
"."
] |
def add_return_type(self, return_type):
"""Add *return_type* to the list of inferred return-types.
If there are too many, raise `TypingError`.
"""
# The maximum limit is picked arbitrarily.
# Don't think that this needs to be user configurable.
RETTY_LIMIT = 16
self._inferred_retty.add(return_type)
if len(self._inferred_retty) >= RETTY_LIMIT:
m = "Return type of recursive function does not converge"
raise errors.TypingError(m)
|
[
"def",
"add_return_type",
"(",
"self",
",",
"return_type",
")",
":",
"# The maximum limit is picked arbitrarily.",
"# Don't think that this needs to be user configurable.",
"RETTY_LIMIT",
"=",
"16",
"self",
".",
"_inferred_retty",
".",
"add",
"(",
"return_type",
")",
"if",
"len",
"(",
"self",
".",
"_inferred_retty",
")",
">=",
"RETTY_LIMIT",
":",
"m",
"=",
"\"Return type of recursive function does not converge\"",
"raise",
"errors",
".",
"TypingError",
"(",
"m",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/typing/context.py#L118-L128
|
||
weolar/miniblink49
|
1c4678db0594a4abde23d3ebbcc7cd13c3170777
|
third_party/WebKit/Tools/Scripts/webkitpy/style/checkers/cpp.py
|
python
|
_FunctionState.modifiers_and_return_type
|
(self)
|
return SingleLineView(elided, start_modifiers, self.function_name_start_position).single_line.strip()
|
Returns the modifiers and the return type.
|
Returns the modifiers and the return type.
|
[
"Returns",
"the",
"modifiers",
"and",
"the",
"return",
"type",
"."
] |
def modifiers_and_return_type(self):
"""Returns the modifiers and the return type."""
# Go backwards from where the function name is until we encounter one of several things:
# ';' or '{' or '}' or 'private:', etc. or '#' or return Position(0, 0)
elided = self._clean_lines.elided
start_modifiers = _rfind_in_lines(r';|\{|\}|((private|public|protected):)|(#.*)',
elided, self.parameter_start_position, Position(0, 0))
return SingleLineView(elided, start_modifiers, self.function_name_start_position).single_line.strip()
|
[
"def",
"modifiers_and_return_type",
"(",
"self",
")",
":",
"# Go backwards from where the function name is until we encounter one of several things:",
"# ';' or '{' or '}' or 'private:', etc. or '#' or return Position(0, 0)",
"elided",
"=",
"self",
".",
"_clean_lines",
".",
"elided",
"start_modifiers",
"=",
"_rfind_in_lines",
"(",
"r';|\\{|\\}|((private|public|protected):)|(#.*)'",
",",
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",",
"self",
".",
"parameter_start_position",
",",
"Position",
"(",
"0",
",",
"0",
")",
")",
"return",
"SingleLineView",
"(",
"elided",
",",
"start_modifiers",
",",
"self",
".",
"function_name_start_position",
")",
".",
"single_line",
".",
"strip",
"(",
")"
] |
https://github.com/weolar/miniblink49/blob/1c4678db0594a4abde23d3ebbcc7cd13c3170777/third_party/WebKit/Tools/Scripts/webkitpy/style/checkers/cpp.py#L568-L575
|
|
apple/turicreate
|
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
|
deps/src/libxml2-2.9.1/python/libxml2.py
|
python
|
xmlDoc.encodeEntitiesReentrant
|
(self, input)
|
return ret
|
Do a global encoding of a string, replacing the predefined
entities and non ASCII values with their entities and
CharRef counterparts. Contrary to xmlEncodeEntities, this
routine is reentrant, and result must be deallocated.
|
Do a global encoding of a string, replacing the predefined
entities and non ASCII values with their entities and
CharRef counterparts. Contrary to xmlEncodeEntities, this
routine is reentrant, and result must be deallocated.
|
[
"Do",
"a",
"global",
"encoding",
"of",
"a",
"string",
"replacing",
"the",
"predefined",
"entities",
"and",
"non",
"ASCII",
"values",
"with",
"their",
"entities",
"and",
"CharRef",
"counterparts",
".",
"Contrary",
"to",
"xmlEncodeEntities",
"this",
"routine",
"is",
"reentrant",
"and",
"result",
"must",
"be",
"deallocated",
"."
] |
def encodeEntitiesReentrant(self, input):
"""Do a global encoding of a string, replacing the predefined
entities and non ASCII values with their entities and
CharRef counterparts. Contrary to xmlEncodeEntities, this
routine is reentrant, and result must be deallocated. """
ret = libxml2mod.xmlEncodeEntitiesReentrant(self._o, input)
return ret
|
[
"def",
"encodeEntitiesReentrant",
"(",
"self",
",",
"input",
")",
":",
"ret",
"=",
"libxml2mod",
".",
"xmlEncodeEntitiesReentrant",
"(",
"self",
".",
"_o",
",",
"input",
")",
"return",
"ret"
] |
https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/deps/src/libxml2-2.9.1/python/libxml2.py#L4135-L4141
|
|
mindspore-ai/mindspore
|
fb8fd3338605bb34fa5cea054e535a8b1d753fab
|
mindspore/python/mindspore/nn/metrics/loss.py
|
python
|
Loss.eval
|
(self)
|
return self._sum_loss / self._total_num
|
Calculates the average of the loss.
Returns:
numpy.float64. The average of the loss.
Raises:
RuntimeError: If the total number is 0.
|
Calculates the average of the loss.
|
[
"Calculates",
"the",
"average",
"of",
"the",
"loss",
"."
] |
def eval(self):
"""
Calculates the average of the loss.
Returns:
numpy.float64. The average of the loss.
Raises:
RuntimeError: If the total number is 0.
"""
if self._total_num == 0:
raise RuntimeError("The 'Loss' can not be calculated, because the number of samples is 0, please "
"check whether has called update method before calling eval method.")
return self._sum_loss / self._total_num
|
[
"def",
"eval",
"(",
"self",
")",
":",
"if",
"self",
".",
"_total_num",
"==",
"0",
":",
"raise",
"RuntimeError",
"(",
"\"The 'Loss' can not be calculated, because the number of samples is 0, please \"",
"\"check whether has called update method before calling eval method.\"",
")",
"return",
"self",
".",
"_sum_loss",
"/",
"self",
".",
"_total_num"
] |
https://github.com/mindspore-ai/mindspore/blob/fb8fd3338605bb34fa5cea054e535a8b1d753fab/mindspore/python/mindspore/nn/metrics/loss.py#L78-L91
|
|
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/cookielib.py
|
python
|
CookieJar.add_cookie_header
|
(self, request)
|
Add correct Cookie: header to request (urllib2.Request object).
The Cookie2 header is also added unless policy.hide_cookie2 is true.
|
Add correct Cookie: header to request (urllib2.Request object).
|
[
"Add",
"correct",
"Cookie",
":",
"header",
"to",
"request",
"(",
"urllib2",
".",
"Request",
"object",
")",
"."
] |
def add_cookie_header(self, request):
"""Add correct Cookie: header to request (urllib2.Request object).
The Cookie2 header is also added unless policy.hide_cookie2 is true.
"""
_debug("add_cookie_header")
self._cookies_lock.acquire()
try:
self._policy._now = self._now = int(time.time())
cookies = self._cookies_for_request(request)
attrs = self._cookie_attrs(cookies)
if attrs:
if not request.has_header("Cookie"):
request.add_unredirected_header(
"Cookie", "; ".join(attrs))
# if necessary, advertise that we know RFC 2965
if (self._policy.rfc2965 and not self._policy.hide_cookie2 and
not request.has_header("Cookie2")):
for cookie in cookies:
if cookie.version != 1:
request.add_unredirected_header("Cookie2", '$Version="1"')
break
finally:
self._cookies_lock.release()
self.clear_expired_cookies()
|
[
"def",
"add_cookie_header",
"(",
"self",
",",
"request",
")",
":",
"_debug",
"(",
"\"add_cookie_header\"",
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"_cookies_lock",
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"add_unredirected_header",
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"self",
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"_policy",
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"rfc2965",
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"_policy",
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"hide_cookie2",
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".",
"has_header",
"(",
"\"Cookie2\"",
")",
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":",
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"cookie",
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":",
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"version",
"!=",
"1",
":",
"request",
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"add_unredirected_header",
"(",
"\"Cookie2\"",
",",
"'$Version=\"1\"'",
")",
"break",
"finally",
":",
"self",
".",
"_cookies_lock",
".",
"release",
"(",
")",
"self",
".",
"clear_expired_cookies",
"(",
")"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/cookielib.py#L1312-L1343
|
||
benoitsteiner/tensorflow-opencl
|
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
|
tensorflow/python/saved_model/builder_impl.py
|
python
|
SavedModelBuilder.add_meta_graph
|
(self,
tags,
signature_def_map=None,
assets_collection=None,
legacy_init_op=None,
clear_devices=False,
main_op=None)
|
Adds the current meta graph to the SavedModel.
Creates a Saver in the current scope and uses the Saver to export the meta
graph def. Invoking this API requires the `add_meta_graph_and_variables()`
API to have been invoked before.
Args:
tags: The set of tags to annotate the meta graph def with.
signature_def_map: The map of signature defs to be added to the meta graph
def.
assets_collection: Assets collection to be saved with SavedModel. Note
that this collection should be a subset of the assets saved as part of
the first meta graph in the SavedModel.
legacy_init_op: Legacy support for op or group of ops to execute after the
restore op upon a load.
clear_devices: Set to true if the device info on the default graph should
be cleared.
main_op: Op or group of ops to execute when the graph is loaded. Note
that when the main_op is specified it is run after the restore op at
load-time.
Raises:
AssertionError: If the variables for the SavedModel have not been saved
yet, or if the graph already contains one or more legacy init ops.
|
Adds the current meta graph to the SavedModel.
|
[
"Adds",
"the",
"current",
"meta",
"graph",
"to",
"the",
"SavedModel",
"."
] |
def add_meta_graph(self,
tags,
signature_def_map=None,
assets_collection=None,
legacy_init_op=None,
clear_devices=False,
main_op=None):
"""Adds the current meta graph to the SavedModel.
Creates a Saver in the current scope and uses the Saver to export the meta
graph def. Invoking this API requires the `add_meta_graph_and_variables()`
API to have been invoked before.
Args:
tags: The set of tags to annotate the meta graph def with.
signature_def_map: The map of signature defs to be added to the meta graph
def.
assets_collection: Assets collection to be saved with SavedModel. Note
that this collection should be a subset of the assets saved as part of
the first meta graph in the SavedModel.
legacy_init_op: Legacy support for op or group of ops to execute after the
restore op upon a load.
clear_devices: Set to true if the device info on the default graph should
be cleared.
main_op: Op or group of ops to execute when the graph is loaded. Note
that when the main_op is specified it is run after the restore op at
load-time.
Raises:
AssertionError: If the variables for the SavedModel have not been saved
yet, or if the graph already contains one or more legacy init ops.
"""
if not self._has_saved_variables:
raise AssertionError(
"Graph state including variables and assets has not been saved yet. "
"Please invoke `add_meta_graph_and_variables()` first.")
# Validate the signature def map to ensure all included TensorInfos are
# properly populated.
self._validate_signature_def_map(signature_def_map)
# Save asset files and write them to disk, if any.
self._save_and_write_assets(assets_collection)
if main_op is None:
# Add legacy init op to the SavedModel.
self._maybe_add_legacy_init_op(legacy_init_op)
else:
self._add_main_op(main_op)
# Initialize a saver to generate a sharded output for all saveables in the
# current scope.
saver = tf_saver.Saver(
variables._all_saveable_objects(), # pylint: disable=protected-access
sharded=True,
write_version=saver_pb2.SaverDef.V2,
allow_empty=True)
# The graph almost certainly previously contained at least one Saver, and
# possibly several (e.g. one for loading a pretrained embedding, and another
# for the model weights). However, a *new* Saver was just created that
# includes all of the variables. Removing the preexisting ones was the
# motivation for the clear_extraneous_savers option, but it turns out that
# there are edge cases where that option breaks the graph. Until that is
# resolved, we just leave the option set to False for now.
# TODO(soergel): Reinstate clear_extraneous_savers=True when possible.
meta_graph_def = saver.export_meta_graph(clear_devices=clear_devices)
# Tag the meta graph def and add it to the SavedModel.
self._tag_and_add_meta_graph(meta_graph_def, tags, signature_def_map)
|
[
"def",
"add_meta_graph",
"(",
"self",
",",
"tags",
",",
"signature_def_map",
"=",
"None",
",",
"assets_collection",
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"None",
",",
"legacy_init_op",
"=",
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"False",
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"None",
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":",
"if",
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"_has_saved_variables",
":",
"raise",
"AssertionError",
"(",
"\"Graph state including variables and assets has not been saved yet. \"",
"\"Please invoke `add_meta_graph_and_variables()` first.\"",
")",
"# Validate the signature def map to ensure all included TensorInfos are",
"# properly populated.",
"self",
".",
"_validate_signature_def_map",
"(",
"signature_def_map",
")",
"# Save asset files and write them to disk, if any.",
"self",
".",
"_save_and_write_assets",
"(",
"assets_collection",
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"if",
"main_op",
"is",
"None",
":",
"# Add legacy init op to the SavedModel.",
"self",
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"legacy_init_op",
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"else",
":",
"self",
".",
"_add_main_op",
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"main_op",
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"# Initialize a saver to generate a sharded output for all saveables in the",
"# current scope.",
"saver",
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"tf_saver",
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"variables",
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"write_version",
"=",
"saver_pb2",
".",
"SaverDef",
".",
"V2",
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"allow_empty",
"=",
"True",
")",
"# The graph almost certainly previously contained at least one Saver, and",
"# possibly several (e.g. one for loading a pretrained embedding, and another",
"# for the model weights). However, a *new* Saver was just created that",
"# includes all of the variables. Removing the preexisting ones was the",
"# motivation for the clear_extraneous_savers option, but it turns out that",
"# there are edge cases where that option breaks the graph. Until that is",
"# resolved, we just leave the option set to False for now.",
"# TODO(soergel): Reinstate clear_extraneous_savers=True when possible.",
"meta_graph_def",
"=",
"saver",
".",
"export_meta_graph",
"(",
"clear_devices",
"=",
"clear_devices",
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"# Tag the meta graph def and add it to the SavedModel.",
"self",
".",
"_tag_and_add_meta_graph",
"(",
"meta_graph_def",
",",
"tags",
",",
"signature_def_map",
")"
] |
https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/saved_model/builder_impl.py#L236-L305
|
||
ChromiumWebApps/chromium
|
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
|
tools/symsrc/pefile.py
|
python
|
PE.get_string_from_data
|
(self, offset, data)
|
return s
|
Get an ASCII string from within the data.
|
Get an ASCII string from within the data.
|
[
"Get",
"an",
"ASCII",
"string",
"from",
"within",
"the",
"data",
"."
] |
def get_string_from_data(self, offset, data):
"""Get an ASCII string from within the data."""
# OC Patch
b = None
try:
b = data[offset]
except IndexError:
return ''
s = ''
while ord(b):
s += b
offset += 1
try:
b = data[offset]
except IndexError:
break
return s
|
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"def",
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"data",
"[",
"offset",
"]",
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"IndexError",
":",
"break",
"return",
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https://github.com/ChromiumWebApps/chromium/blob/c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7/tools/symsrc/pefile.py#L3027-L3047
|
|
microsoft/checkedc-clang
|
a173fefde5d7877b7750e7ce96dd08cf18baebf2
|
lldb/third_party/Python/module/pexpect-4.6/pexpect/screen.py
|
python
|
screen.cursor_save
|
(self)
|
Save current cursor position.
|
Save current cursor position.
|
[
"Save",
"current",
"cursor",
"position",
"."
] |
def cursor_save (self): # <ESC>[s
'''Save current cursor position.'''
self.cursor_save_attrs()
|
[
"def",
"cursor_save",
"(",
"self",
")",
":",
"# <ESC>[s",
"self",
".",
"cursor_save_attrs",
"(",
")"
] |
https://github.com/microsoft/checkedc-clang/blob/a173fefde5d7877b7750e7ce96dd08cf18baebf2/lldb/third_party/Python/module/pexpect-4.6/pexpect/screen.py#L318-L321
|
||
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/x86/toolchain/lib/python2.7/logging/__init__.py
|
python
|
Logger.log
|
(self, level, msg, *args, **kwargs)
|
Log 'msg % args' with the integer severity 'level'.
To pass exception information, use the keyword argument exc_info with
a true value, e.g.
logger.log(level, "We have a %s", "mysterious problem", exc_info=1)
|
Log 'msg % args' with the integer severity 'level'.
|
[
"Log",
"msg",
"%",
"args",
"with",
"the",
"integer",
"severity",
"level",
"."
] |
def log(self, level, msg, *args, **kwargs):
"""
Log 'msg % args' with the integer severity 'level'.
To pass exception information, use the keyword argument exc_info with
a true value, e.g.
logger.log(level, "We have a %s", "mysterious problem", exc_info=1)
"""
if not isinstance(level, int):
if raiseExceptions:
raise TypeError("level must be an integer")
else:
return
if self.isEnabledFor(level):
self._log(level, msg, args, **kwargs)
|
[
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https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/logging/__init__.py#L1198-L1213
|
||
miyosuda/TensorFlowAndroidDemo
|
35903e0221aa5f109ea2dbef27f20b52e317f42d
|
jni-build/jni/include/tensorflow/python/ops/variable_scope.py
|
python
|
_get_partitioned_variable
|
(name,
shape=None,
dtype=None,
initializer=None,
regularizer=None,
trainable=True,
collections=None,
caching_device=None,
partitioner=None,
validate_shape=True)
|
return scope._get_partitioned_variable(
_get_default_variable_store(), name, shape=shape, dtype=dtype,
initializer=initializer, regularizer=regularizer, trainable=trainable,
collections=collections, caching_device=caching_device,
partitioner=partitioner, validate_shape=validate_shape)
|
Gets or creates a sharded variable list with these parameters.
The `partitioner` must be a callable that accepts a fully defined
`TensorShape` and returns a sequence of integers (the `partitions`).
These integers describe how to partition the given sharded `Variable`
along the given dimension. That is, `partitions[1] = 3` means split
the `Variable` into 3 shards along dimension 1. Currently, sharding along
only one axis is supported.
If the list of variables with the given name (prefix) is already stored,
we return the stored variables. Otherwise, we create a new one.
Set `reuse` to `True` when you only want to reuse existing Variables.
Set `reuse` to `False` when you only want to create new Variables.
If `reuse` is `None` (the default), both new and existing variables are
returned.
If initializer is `None` (the default), the default initializer passed in
the constructor is used. If that one is `None` too, we use a new
`uniform_unit_scaling_initializer`. If initializer is a Tensor, we use
it as a value and derive the shape from the initializer.
If the initializer is a callable, then it will be called for each
shard. Otherwise the initializer should match the shape of the entire
sharded Variable, and it will be sliced accordingly for each shard.
Some useful partitioners are available. See, e.g.,
`variable_axis_size_partitioner` and `min_max_variable_partitioner`.
Args:
name: The name of the new or existing variable.
shape: Shape of the new or existing variable.
dtype: Type of the new or existing variable (defaults to `DT_FLOAT`).
initializer: Initializer for the variable if one is created.
regularizer: A (Tensor -> Tensor or None) function; the result of
applying it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
trainable: If `True` also add the variable to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see tf.Variable).
collections: List of graph collections keys to add the Variable to.
Defaults to `[GraphKeys.VARIABLES]` (see tf.Variable).
caching_device: Optional device string or function describing where the
Variable should be cached for reading. Defaults to the Variable's
device. If not `None`, caches on another device. Typical use is to
cache on the device where the Ops using the Variable reside, to
deduplicate copying through `Switch` and other conditional statements.
partitioner: Optional callable that accepts a fully defined `TensorShape`
and `dtype` of the Variable to be created, and returns a list of
partitions for each axis (currently only one axis can be partitioned).
validate_shape: If False, allows the variable to be initialized with a
value of unknown shape. If True, the default, the shape of initial_value
must be known.
Returns:
A tuple `(shards, partitions)` where `shards` is the list of `Variable`
shards and `partitions` is the output of the partitioner on the input
shape.
Raises:
ValueError: when creating a new variable and shape is not declared,
or when violating reuse during variable creation. Reuse is set inside
`variable_scope`.
|
Gets or creates a sharded variable list with these parameters.
|
[
"Gets",
"or",
"creates",
"a",
"sharded",
"variable",
"list",
"with",
"these",
"parameters",
"."
] |
def _get_partitioned_variable(name,
shape=None,
dtype=None,
initializer=None,
regularizer=None,
trainable=True,
collections=None,
caching_device=None,
partitioner=None,
validate_shape=True):
"""Gets or creates a sharded variable list with these parameters.
The `partitioner` must be a callable that accepts a fully defined
`TensorShape` and returns a sequence of integers (the `partitions`).
These integers describe how to partition the given sharded `Variable`
along the given dimension. That is, `partitions[1] = 3` means split
the `Variable` into 3 shards along dimension 1. Currently, sharding along
only one axis is supported.
If the list of variables with the given name (prefix) is already stored,
we return the stored variables. Otherwise, we create a new one.
Set `reuse` to `True` when you only want to reuse existing Variables.
Set `reuse` to `False` when you only want to create new Variables.
If `reuse` is `None` (the default), both new and existing variables are
returned.
If initializer is `None` (the default), the default initializer passed in
the constructor is used. If that one is `None` too, we use a new
`uniform_unit_scaling_initializer`. If initializer is a Tensor, we use
it as a value and derive the shape from the initializer.
If the initializer is a callable, then it will be called for each
shard. Otherwise the initializer should match the shape of the entire
sharded Variable, and it will be sliced accordingly for each shard.
Some useful partitioners are available. See, e.g.,
`variable_axis_size_partitioner` and `min_max_variable_partitioner`.
Args:
name: The name of the new or existing variable.
shape: Shape of the new or existing variable.
dtype: Type of the new or existing variable (defaults to `DT_FLOAT`).
initializer: Initializer for the variable if one is created.
regularizer: A (Tensor -> Tensor or None) function; the result of
applying it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
trainable: If `True` also add the variable to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see tf.Variable).
collections: List of graph collections keys to add the Variable to.
Defaults to `[GraphKeys.VARIABLES]` (see tf.Variable).
caching_device: Optional device string or function describing where the
Variable should be cached for reading. Defaults to the Variable's
device. If not `None`, caches on another device. Typical use is to
cache on the device where the Ops using the Variable reside, to
deduplicate copying through `Switch` and other conditional statements.
partitioner: Optional callable that accepts a fully defined `TensorShape`
and `dtype` of the Variable to be created, and returns a list of
partitions for each axis (currently only one axis can be partitioned).
validate_shape: If False, allows the variable to be initialized with a
value of unknown shape. If True, the default, the shape of initial_value
must be known.
Returns:
A tuple `(shards, partitions)` where `shards` is the list of `Variable`
shards and `partitions` is the output of the partitioner on the input
shape.
Raises:
ValueError: when creating a new variable and shape is not declared,
or when violating reuse during variable creation. Reuse is set inside
`variable_scope`.
"""
# pylint: disable=protected-access
scope = get_variable_scope()
if scope.custom_getter is not None:
raise ValueError(
"Private access to _get_partitioned_variable is not allowed when "
"a custom getter is set. Current custom getter: %s. "
"It is likely that you're using create_partitioned_variables. "
"If so, consider instead using get_variable with a non-empty "
"partitioner parameter instead." % scope.custom_getter)
return scope._get_partitioned_variable(
_get_default_variable_store(), name, shape=shape, dtype=dtype,
initializer=initializer, regularizer=regularizer, trainable=trainable,
collections=collections, caching_device=caching_device,
partitioner=partitioner, validate_shape=validate_shape)
|
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https://github.com/miyosuda/TensorFlowAndroidDemo/blob/35903e0221aa5f109ea2dbef27f20b52e317f42d/jni-build/jni/include/tensorflow/python/ops/variable_scope.py#L876-L962
|
|
Ewenwan/MVision
|
97b394dfa48cb21c82cd003b1a952745e413a17f
|
vSLAM/矩阵变换python函数.py
|
python
|
is_same_transform
|
(matrix0, matrix1)
|
return numpy.allclose(matrix0, matrix1)
|
Return True if two matrices perform same transformation.
>>> is_same_transform(numpy.identity(4), numpy.identity(4))
True
>>> is_same_transform(numpy.identity(4), random_rotation_matrix())
False
|
Return True if two matrices perform same transformation.
>>> is_same_transform(numpy.identity(4), numpy.identity(4))
True
>>> is_same_transform(numpy.identity(4), random_rotation_matrix())
False
|
[
"Return",
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".",
"identity",
"(",
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")",
"random_rotation_matrix",
"()",
")",
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] |
def is_same_transform(matrix0, matrix1):
"""Return True if two matrices perform same transformation.
>>> is_same_transform(numpy.identity(4), numpy.identity(4))
True
>>> is_same_transform(numpy.identity(4), random_rotation_matrix())
False
"""
matrix0 = numpy.array(matrix0, dtype=numpy.float64, copy=True)
matrix0 /= matrix0[3, 3]
matrix1 = numpy.array(matrix1, dtype=numpy.float64, copy=True)
matrix1 /= matrix1[3, 3]
return numpy.allclose(matrix0, matrix1)
|
[
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https://github.com/Ewenwan/MVision/blob/97b394dfa48cb21c82cd003b1a952745e413a17f/vSLAM/矩阵变换python函数.py#L1540-L1551
|
|
microsoft/checkedc-clang
|
a173fefde5d7877b7750e7ce96dd08cf18baebf2
|
llvm/bindings/python/llvm/object.py
|
python
|
ObjectFile.__init__
|
(self, filename=None, contents=None)
|
Construct an instance from a filename or binary data.
filename must be a path to a file that can be opened with open().
contents can be either a native Python buffer type (like str) or a
llvm.core.MemoryBuffer instance.
|
Construct an instance from a filename or binary data.
|
[
"Construct",
"an",
"instance",
"from",
"a",
"filename",
"or",
"binary",
"data",
"."
] |
def __init__(self, filename=None, contents=None):
"""Construct an instance from a filename or binary data.
filename must be a path to a file that can be opened with open().
contents can be either a native Python buffer type (like str) or a
llvm.core.MemoryBuffer instance.
"""
if contents:
assert isinstance(contents, MemoryBuffer)
if filename is not None:
contents = MemoryBuffer(filename=filename)
if contents is None:
raise Exception('No input found.')
ptr = lib.LLVMCreateObjectFile(contents)
LLVMObject.__init__(self, ptr, disposer=lib.LLVMDisposeObjectFile)
self.take_ownership(contents)
|
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https://github.com/microsoft/checkedc-clang/blob/a173fefde5d7877b7750e7ce96dd08cf18baebf2/llvm/bindings/python/llvm/object.py#L102-L120
|
||
benoitsteiner/tensorflow-opencl
|
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
|
tensorflow/python/framework/errors_impl.py
|
python
|
NotFoundError.__init__
|
(self, node_def, op, message)
|
Creates a `NotFoundError`.
|
Creates a `NotFoundError`.
|
[
"Creates",
"a",
"NotFoundError",
"."
] |
def __init__(self, node_def, op, message):
"""Creates a `NotFoundError`."""
super(NotFoundError, self).__init__(node_def, op, message, NOT_FOUND)
|
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")",
".",
"__init__",
"(",
"node_def",
",",
"op",
",",
"message",
",",
"NOT_FOUND",
")"
] |
https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/framework/errors_impl.py#L237-L239
|
||
Xilinx/Vitis-AI
|
fc74d404563d9951b57245443c73bef389f3657f
|
tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/configure.py
|
python
|
set_tf_nccl_version
|
(environ_cp)
|
Set TF_NCCL_VERSION.
|
Set TF_NCCL_VERSION.
|
[
"Set",
"TF_NCCL_VERSION",
"."
] |
def set_tf_nccl_version(environ_cp):
"""Set TF_NCCL_VERSION."""
if not is_linux():
raise ValueError('Currently NCCL is only supported on Linux platform.')
if 'TF_NCCL_VERSION' in environ_cp:
return
ask_nccl_version = (
'Please specify the locally installed NCCL version you want to use. '
'[Leave empty to use http://github.com/nvidia/nccl]: ')
tf_nccl_version = get_from_env_or_user_or_default(environ_cp,
'TF_NCCL_VERSION',
ask_nccl_version, '')
environ_cp['TF_NCCL_VERSION'] = tf_nccl_version
|
[
"def",
"set_tf_nccl_version",
"(",
"environ_cp",
")",
":",
"if",
"not",
"is_linux",
"(",
")",
":",
"raise",
"ValueError",
"(",
"'Currently NCCL is only supported on Linux platform.'",
")",
"if",
"'TF_NCCL_VERSION'",
"in",
"environ_cp",
":",
"return",
"ask_nccl_version",
"=",
"(",
"'Please specify the locally installed NCCL version you want to use. '",
"'[Leave empty to use http://github.com/nvidia/nccl]: '",
")",
"tf_nccl_version",
"=",
"get_from_env_or_user_or_default",
"(",
"environ_cp",
",",
"'TF_NCCL_VERSION'",
",",
"ask_nccl_version",
",",
"''",
")",
"environ_cp",
"[",
"'TF_NCCL_VERSION'",
"]",
"=",
"tf_nccl_version"
] |
https://github.com/Xilinx/Vitis-AI/blob/fc74d404563d9951b57245443c73bef389f3657f/tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/configure.py#L950-L964
|
||
zju3dv/clean-pvnet
|
5870c509e3cc205e1bb28910a7b1a9a3c8add9a8
|
lib/utils/pysixd/transform.py
|
python
|
translation_from_matrix
|
(matrix)
|
return numpy.array(matrix, copy=False)[:3, 3].copy()
|
Return translation vector from translation matrix.
>>> v0 = numpy.random.random(3) - 0.5
>>> v1 = translation_from_matrix(translation_matrix(v0))
>>> numpy.allclose(v0, v1)
True
|
Return translation vector from translation matrix.
|
[
"Return",
"translation",
"vector",
"from",
"translation",
"matrix",
"."
] |
def translation_from_matrix(matrix):
"""Return translation vector from translation matrix.
>>> v0 = numpy.random.random(3) - 0.5
>>> v1 = translation_from_matrix(translation_matrix(v0))
>>> numpy.allclose(v0, v1)
True
"""
return numpy.array(matrix, copy=False)[:3, 3].copy()
|
[
"def",
"translation_from_matrix",
"(",
"matrix",
")",
":",
"return",
"numpy",
".",
"array",
"(",
"matrix",
",",
"copy",
"=",
"False",
")",
"[",
":",
"3",
",",
"3",
"]",
".",
"copy",
"(",
")"
] |
https://github.com/zju3dv/clean-pvnet/blob/5870c509e3cc205e1bb28910a7b1a9a3c8add9a8/lib/utils/pysixd/transform.py#L235-L244
|
|
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib-tk/ttk.py
|
python
|
_convert_stringval
|
(value)
|
return value
|
Converts a value to, hopefully, a more appropriate Python object.
|
Converts a value to, hopefully, a more appropriate Python object.
|
[
"Converts",
"a",
"value",
"to",
"hopefully",
"a",
"more",
"appropriate",
"Python",
"object",
"."
] |
def _convert_stringval(value):
"""Converts a value to, hopefully, a more appropriate Python object."""
value = unicode(value)
try:
value = int(value)
except (ValueError, TypeError):
pass
return value
|
[
"def",
"_convert_stringval",
"(",
"value",
")",
":",
"value",
"=",
"unicode",
"(",
"value",
")",
"try",
":",
"value",
"=",
"int",
"(",
"value",
")",
"except",
"(",
"ValueError",
",",
"TypeError",
")",
":",
"pass",
"return",
"value"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib-tk/ttk.py#L320-L328
|
|
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/telemetry/telemetry/internal/util/external_modules.py
|
python
|
ImportOptionalModule
|
(module)
|
Tries to import the desired module.
Returns:
The module if successful, None if not.
|
Tries to import the desired module.
|
[
"Tries",
"to",
"import",
"the",
"desired",
"module",
"."
] |
def ImportOptionalModule(module):
"""Tries to import the desired module.
Returns:
The module if successful, None if not."""
try:
return ImportRequiredModule(module)
except ImportError:
return None
|
[
"def",
"ImportOptionalModule",
"(",
"module",
")",
":",
"try",
":",
"return",
"ImportRequiredModule",
"(",
"module",
")",
"except",
"ImportError",
":",
"return",
"None"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/telemetry/telemetry/internal/util/external_modules.py#L48-L56
|
||
CRYTEK/CRYENGINE
|
232227c59a220cbbd311576f0fbeba7bb53b2a8c
|
Editor/Python/windows/Lib/site-packages/pip/_vendor/requests/sessions.py
|
python
|
Session.post
|
(self, url, data=None, json=None, **kwargs)
|
return self.request('POST', url, data=data, json=json, **kwargs)
|
Sends a POST request. Returns :class:`Response` object.
:param url: URL for the new :class:`Request` object.
:param data: (optional) Dictionary, bytes, or file-like object to send in the body of the :class:`Request`.
:param json: (optional) json to send in the body of the :class:`Request`.
:param \*\*kwargs: Optional arguments that ``request`` takes.
|
Sends a POST request. Returns :class:`Response` object.
|
[
"Sends",
"a",
"POST",
"request",
".",
"Returns",
":",
"class",
":",
"Response",
"object",
"."
] |
def post(self, url, data=None, json=None, **kwargs):
"""Sends a POST request. Returns :class:`Response` object.
:param url: URL for the new :class:`Request` object.
:param data: (optional) Dictionary, bytes, or file-like object to send in the body of the :class:`Request`.
:param json: (optional) json to send in the body of the :class:`Request`.
:param \*\*kwargs: Optional arguments that ``request`` takes.
"""
return self.request('POST', url, data=data, json=json, **kwargs)
|
[
"def",
"post",
"(",
"self",
",",
"url",
",",
"data",
"=",
"None",
",",
"json",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"self",
".",
"request",
"(",
"'POST'",
",",
"url",
",",
"data",
"=",
"data",
",",
"json",
"=",
"json",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Editor/Python/windows/Lib/site-packages/pip/_vendor/requests/sessions.py#L499-L508
|
|
openvinotoolkit/openvino
|
dedcbeafa8b84cccdc55ca64b8da516682b381c7
|
cmake/developer_package/cpplint/cpplint.py
|
python
|
CheckSpacingForFunctionCall
|
(filename, clean_lines, linenum, error)
|
Checks for the correctness of various spacing around function calls.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
|
Checks for the correctness of various spacing around function calls.
|
[
"Checks",
"for",
"the",
"correctness",
"of",
"various",
"spacing",
"around",
"function",
"calls",
"."
] |
def CheckSpacingForFunctionCall(filename, clean_lines, linenum, error):
"""Checks for the correctness of various spacing around function calls.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
"""
line = clean_lines.elided[linenum]
# Since function calls often occur inside if/for/while/switch
# expressions - which have their own, more liberal conventions - we
# first see if we should be looking inside such an expression for a
# function call, to which we can apply more strict standards.
fncall = line # if there's no control flow construct, look at whole line
for pattern in (r'\bif\s*\((.*)\)\s*{',
r'\bfor\s*\((.*)\)\s*{',
r'\bwhile\s*\((.*)\)\s*[{;]',
r'\bswitch\s*\((.*)\)\s*{'):
match = Search(pattern, line)
if match:
fncall = match.group(1) # look inside the parens for function calls
break
# Except in if/for/while/switch, there should never be space
# immediately inside parens (eg "f( 3, 4 )"). We make an exception
# for nested parens ( (a+b) + c ). Likewise, there should never be
# a space before a ( when it's a function argument. I assume it's a
# function argument when the char before the whitespace is legal in
# a function name (alnum + _) and we're not starting a macro. Also ignore
# pointers and references to arrays and functions coz they're too tricky:
# we use a very simple way to recognize these:
# " (something)(maybe-something)" or
# " (something)(maybe-something," or
# " (something)[something]"
# Note that we assume the contents of [] to be short enough that
# they'll never need to wrap.
if ( # Ignore control structures.
not Search(r'\b(if|for|while|switch|return|new|delete|catch|sizeof)\b',
fncall) and
# Ignore pointers/references to functions.
not Search(r' \([^)]+\)\([^)]*(\)|,$)', fncall) and
# Ignore pointers/references to arrays.
not Search(r' \([^)]+\)\[[^\]]+\]', fncall)):
if Search(r'\w\s*\(\s(?!\s*\\$)', fncall): # a ( used for a fn call
error(filename, linenum, 'whitespace/parens', 4,
'Extra space after ( in function call')
elif Search(r'\(\s+(?!(\s*\\)|\()', fncall):
error(filename, linenum, 'whitespace/parens', 2,
'Extra space after (')
if (Search(r'\w\s+\(', fncall) and
not Search(r'_{0,2}asm_{0,2}\s+_{0,2}volatile_{0,2}\s+\(', fncall) and
not Search(r'#\s*define|typedef|using\s+\w+\s*=', fncall) and
not Search(r'\w\s+\((\w+::)*\*\w+\)\(', fncall) and
not Search(r'\bcase\s+\(', fncall)):
# TODO(unknown): Space after an operator function seem to be a common
# error, silence those for now by restricting them to highest verbosity.
if Search(r'\boperator_*\b', line):
error(filename, linenum, 'whitespace/parens', 0,
'Extra space before ( in function call')
else:
error(filename, linenum, 'whitespace/parens', 4,
'Extra space before ( in function call')
# If the ) is followed only by a newline or a { + newline, assume it's
# part of a control statement (if/while/etc), and don't complain
if Search(r'[^)]\s+\)\s*[^{\s]', fncall):
# If the closing parenthesis is preceded by only whitespaces,
# try to give a more descriptive error message.
if Search(r'^\s+\)', fncall):
error(filename, linenum, 'whitespace/parens', 2,
'Closing ) should be moved to the previous line')
else:
error(filename, linenum, 'whitespace/parens', 2,
'Extra space before )')
|
[
"def",
"CheckSpacingForFunctionCall",
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"clean_lines",
",",
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",",
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"# function argument when the char before the whitespace is legal in",
"# a function name (alnum + _) and we're not starting a macro. Also ignore",
"# pointers and references to arrays and functions coz they're too tricky:",
"# we use a very simple way to recognize these:",
"# \" (something)(maybe-something)\" or",
"# \" (something)(maybe-something,\" or",
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",",
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",",
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")"
] |
https://github.com/openvinotoolkit/openvino/blob/dedcbeafa8b84cccdc55ca64b8da516682b381c7/cmake/developer_package/cpplint/cpplint.py#L3177-L3251
|
||
pmq20/node-packer
|
12c46c6e44fbc14d9ee645ebd17d5296b324f7e0
|
lts/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/make.py
|
python
|
MakefileWriter.WriteMacBundleResources
|
(self, resources, bundle_deps)
|
Writes Makefile code for 'mac_bundle_resources'.
|
Writes Makefile code for 'mac_bundle_resources'.
|
[
"Writes",
"Makefile",
"code",
"for",
"mac_bundle_resources",
"."
] |
def WriteMacBundleResources(self, resources, bundle_deps):
"""Writes Makefile code for 'mac_bundle_resources'."""
self.WriteLn('### Generated for mac_bundle_resources')
for output, res in gyp.xcode_emulation.GetMacBundleResources(
generator_default_variables['PRODUCT_DIR'], self.xcode_settings,
[Sourceify(self.Absolutify(r)) for r in resources]):
_, ext = os.path.splitext(output)
if ext != '.xcassets':
# Make does not supports '.xcassets' emulation.
self.WriteDoCmd([output], [res], 'mac_tool,,,copy-bundle-resource',
part_of_all=True)
bundle_deps.append(output)
|
[
"def",
"WriteMacBundleResources",
"(",
"self",
",",
"resources",
",",
"bundle_deps",
")",
":",
"self",
".",
"WriteLn",
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",",
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",",
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"=",
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")",
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".",
"append",
"(",
"output",
")"
] |
https://github.com/pmq20/node-packer/blob/12c46c6e44fbc14d9ee645ebd17d5296b324f7e0/lts/deps/npm/node_modules/node-gyp/gyp/pylib/gyp/generator/make.py#L1155-L1167
|
||
potassco/clingo
|
e0c91d8f95cc28de1c480a871f9c97c30de83d40
|
libpyclingo/clingo/backend.py
|
python
|
Observer.begin_step
|
(self)
|
Marks the beginning of a block of directives passed to the solver.
|
Marks the beginning of a block of directives passed to the solver.
|
[
"Marks",
"the",
"beginning",
"of",
"a",
"block",
"of",
"directives",
"passed",
"to",
"the",
"solver",
"."
] |
def begin_step(self) -> None:
'''
Marks the beginning of a block of directives passed to the solver.
'''
|
[
"def",
"begin_step",
"(",
"self",
")",
"->",
"None",
":"
] |
https://github.com/potassco/clingo/blob/e0c91d8f95cc28de1c480a871f9c97c30de83d40/libpyclingo/clingo/backend.py#L97-L100
|
||
facebookresearch/ELF
|
1f790173095cd910976d9f651b80beb872ec5d12
|
vendor/pybind11/tools/clang/cindex.py
|
python
|
Cursor.get_usr
|
(self)
|
return conf.lib.clang_getCursorUSR(self)
|
Return the Unified Symbol Resultion (USR) for the entity referenced
by the given cursor (or None).
A Unified Symbol Resolution (USR) is a string that identifies a
particular entity (function, class, variable, etc.) within a
program. USRs can be compared across translation units to determine,
e.g., when references in one translation refer to an entity defined in
another translation unit.
|
Return the Unified Symbol Resultion (USR) for the entity referenced
by the given cursor (or None).
|
[
"Return",
"the",
"Unified",
"Symbol",
"Resultion",
"(",
"USR",
")",
"for",
"the",
"entity",
"referenced",
"by",
"the",
"given",
"cursor",
"(",
"or",
"None",
")",
"."
] |
def get_usr(self):
"""Return the Unified Symbol Resultion (USR) for the entity referenced
by the given cursor (or None).
A Unified Symbol Resolution (USR) is a string that identifies a
particular entity (function, class, variable, etc.) within a
program. USRs can be compared across translation units to determine,
e.g., when references in one translation refer to an entity defined in
another translation unit."""
return conf.lib.clang_getCursorUSR(self)
|
[
"def",
"get_usr",
"(",
"self",
")",
":",
"return",
"conf",
".",
"lib",
".",
"clang_getCursorUSR",
"(",
"self",
")"
] |
https://github.com/facebookresearch/ELF/blob/1f790173095cd910976d9f651b80beb872ec5d12/vendor/pybind11/tools/clang/cindex.py#L1381-L1390
|
|
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/x86/toolchain/lib/python2.7/imaplib.py
|
python
|
IMAP4.expunge
|
(self)
|
return self._untagged_response(typ, dat, name)
|
Permanently remove deleted items from selected mailbox.
Generates 'EXPUNGE' response for each deleted message.
(typ, [data]) = <instance>.expunge()
'data' is list of 'EXPUNGE'd message numbers in order received.
|
Permanently remove deleted items from selected mailbox.
|
[
"Permanently",
"remove",
"deleted",
"items",
"from",
"selected",
"mailbox",
"."
] |
def expunge(self):
"""Permanently remove deleted items from selected mailbox.
Generates 'EXPUNGE' response for each deleted message.
(typ, [data]) = <instance>.expunge()
'data' is list of 'EXPUNGE'd message numbers in order received.
"""
name = 'EXPUNGE'
typ, dat = self._simple_command(name)
return self._untagged_response(typ, dat, name)
|
[
"def",
"expunge",
"(",
"self",
")",
":",
"name",
"=",
"'EXPUNGE'",
"typ",
",",
"dat",
"=",
"self",
".",
"_simple_command",
"(",
"name",
")",
"return",
"self",
".",
"_untagged_response",
"(",
"typ",
",",
"dat",
",",
"name",
")"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/x86/toolchain/lib/python2.7/imaplib.py#L418-L429
|
|
adobe/chromium
|
cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7
|
tools/site_compare/scrapers/chrome/chrome01970.py
|
python
|
Scrape
|
(urls, outdir, size, pos, timeout=20, **kwargs)
|
return chromebase.Scrape(urls, outdir, size, pos, timeout, kwargs)
|
Invoke a browser, send it to a series of URLs, and save its output.
Args:
urls: list of URLs to scrape
outdir: directory to place output
size: size of browser window to use
pos: position of browser window
timeout: amount of time to wait for page to load
kwargs: miscellaneous keyword args
Returns:
None if succeeded, else an error code
|
Invoke a browser, send it to a series of URLs, and save its output.
|
[
"Invoke",
"a",
"browser",
"send",
"it",
"to",
"a",
"series",
"of",
"URLs",
"and",
"save",
"its",
"output",
"."
] |
def Scrape(urls, outdir, size, pos, timeout=20, **kwargs):
"""Invoke a browser, send it to a series of URLs, and save its output.
Args:
urls: list of URLs to scrape
outdir: directory to place output
size: size of browser window to use
pos: position of browser window
timeout: amount of time to wait for page to load
kwargs: miscellaneous keyword args
Returns:
None if succeeded, else an error code
"""
chromebase.GetChromeRenderPane = GetChromeRenderPane
return chromebase.Scrape(urls, outdir, size, pos, timeout, kwargs)
|
[
"def",
"Scrape",
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"urls",
",",
"outdir",
",",
"size",
",",
"pos",
",",
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"=",
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"GetChromeRenderPane",
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"Scrape",
"(",
"urls",
",",
"outdir",
",",
"size",
",",
"pos",
",",
"timeout",
",",
"kwargs",
")"
] |
https://github.com/adobe/chromium/blob/cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7/tools/site_compare/scrapers/chrome/chrome01970.py#L19-L35
|
|
llvm/llvm-project
|
ffa6262cb4e2a335d26416fad39a581b4f98c5f4
|
lldb/packages/Python/lldbsuite/support/seven.py
|
python
|
bitcast_to_bytes
|
(s)
|
return s if six.PY2 else s.encode("latin1")
|
Take a string and return a string(PY2) or a bytes(PY3) object. The returned
object contains the exact same bytes as the input string. (latin1 <->
unicode transformation is an identity operation for the first 256 code
points).
|
Take a string and return a string(PY2) or a bytes(PY3) object. The returned
object contains the exact same bytes as the input string. (latin1 <->
unicode transformation is an identity operation for the first 256 code
points).
|
[
"Take",
"a",
"string",
"and",
"return",
"a",
"string",
"(",
"PY2",
")",
"or",
"a",
"bytes",
"(",
"PY3",
")",
"object",
".",
"The",
"returned",
"object",
"contains",
"the",
"exact",
"same",
"bytes",
"as",
"the",
"input",
"string",
".",
"(",
"latin1",
"<",
"-",
">",
"unicode",
"transformation",
"is",
"an",
"identity",
"operation",
"for",
"the",
"first",
"256",
"code",
"points",
")",
"."
] |
def bitcast_to_bytes(s):
"""
Take a string and return a string(PY2) or a bytes(PY3) object. The returned
object contains the exact same bytes as the input string. (latin1 <->
unicode transformation is an identity operation for the first 256 code
points).
"""
return s if six.PY2 else s.encode("latin1")
|
[
"def",
"bitcast_to_bytes",
"(",
"s",
")",
":",
"return",
"s",
"if",
"six",
".",
"PY2",
"else",
"s",
".",
"encode",
"(",
"\"latin1\"",
")"
] |
https://github.com/llvm/llvm-project/blob/ffa6262cb4e2a335d26416fad39a581b4f98c5f4/lldb/packages/Python/lldbsuite/support/seven.py#L37-L44
|
|
CRYTEK/CRYENGINE
|
232227c59a220cbbd311576f0fbeba7bb53b2a8c
|
Code/Tools/waf-1.7.13/waflib/Tools/c_preproc.py
|
python
|
reduce_eval
|
(lst)
|
return (NUM, num)
|
Take a list of tokens and output true or false for #if/#elif conditions.
:param lst: a list of tokens
:type lst: list of tuple(token, value)
:return: a token
:rtype: tuple(NUM, int)
|
Take a list of tokens and output true or false for #if/#elif conditions.
|
[
"Take",
"a",
"list",
"of",
"tokens",
"and",
"output",
"true",
"or",
"false",
"for",
"#if",
"/",
"#elif",
"conditions",
"."
] |
def reduce_eval(lst):
"""
Take a list of tokens and output true or false for #if/#elif conditions.
:param lst: a list of tokens
:type lst: list of tuple(token, value)
:return: a token
:rtype: tuple(NUM, int)
"""
num, lst = get_term(lst)
return (NUM, num)
|
[
"def",
"reduce_eval",
"(",
"lst",
")",
":",
"num",
",",
"lst",
"=",
"get_term",
"(",
"lst",
")",
"return",
"(",
"NUM",
",",
"num",
")"
] |
https://github.com/CRYTEK/CRYENGINE/blob/232227c59a220cbbd311576f0fbeba7bb53b2a8c/Code/Tools/waf-1.7.13/waflib/Tools/c_preproc.py#L351-L361
|
|
mantidproject/mantid
|
03deeb89254ec4289edb8771e0188c2090a02f32
|
scripts/Inelastic/Direct/DirectEnergyConversion.py
|
python
|
DirectEnergyConversion._normalize_to_monitor2
|
(self,run,old_name, range_offset=0.0,external_monitor_ws=None)
|
return ('monitor-2',old_name)
|
Helper method implementing normalize_to_monitor_2
|
Helper method implementing normalize_to_monitor_2
|
[
"Helper",
"method",
"implementing",
"normalize_to_monitor_2"
] |
def _normalize_to_monitor2(self,run,old_name, range_offset=0.0,external_monitor_ws=None):
""" Helper method implementing normalize_to_monitor_2 """
# get monitor's workspace
separate_monitors = run.is_monws_separate()
if external_monitor_ws:
separate_monitors = True
mon_ws = external_monitor_ws
else:
mon_ws = run.get_monitors_ws()
if self.__in_white_normalization: # we normalize wb integrals by current separately as they often do not
# have monitors or are in fact wb workspace with some special ei
self.normalise(run,'current',range_offset)
ws = run.get_workspace()
new_name = ws.name()
return ('current',new_name)
else:
if not mon_ws: # no monitors
ws = run.get_workspace()
raise RuntimeError('Normalize by monitor-2:: Workspace {0} for run {1} does not have monitors in it'
.format(ws.name(),run.run_number()))
#
kwargs = {'NormFactorWS':'NormMon2_WS' + mon_ws.name()}
mon_spect = self.prop_man.mon2_norm_spec
mon_index = int(mon_ws.getIndexFromSpectrumNumber(mon_spect))
if separate_monitors:
kwargs['MonitorWorkspace'] = mon_ws
kwargs['MonitorWorkspaceIndex'] = mon_index
else:
kwargs['MonitorSpectrum'] = mon_spect
#Find TOF range, correspondent to incident energy monitor peak
if self._mon2_norm_time_range: # range has been found during ei-calculations
norm_range = self._mon2_norm_time_range
range_min = norm_range[0] + range_offset
range_max = norm_range[1] + range_offset
self._mon2_norm_time_range = None
else:
mon_ws_name = mon_ws.name() #monitor's workspace and detector's workspace are e
if mon_ws_name.find('_shifted') != -1:
# monitor-2 normalization ranges have to be identified before the
# instrument is shifted
raise RuntimeError("""Instrument have been shifted but no time range has been identified.
Monitor-2 normalization can not be performed """)
else:
# instrument and workspace shifted, so TOF will be calculated wrt
# shifted instrument
energy_rage = self.mon2_norm_energy_range
TOF_range = self.get_TOF_for_energies(mon_ws,energy_rage,[mon_spect],None,self._debug_mode)
range_min = TOF_range[0]
range_max = TOF_range[1]
# Normalize to monitor 2
NormaliseToMonitor(InputWorkspace=old_name,OutputWorkspace=old_name,IntegrationRangeMin=range_min,
IntegrationRangeMax=range_max,IncludePartialBins=True,**kwargs)
norm_ws_name = kwargs['NormFactorWS']
norm_mon2ws = mtd[norm_ws_name]
norm_factor = norm_mon2ws.dataY(0)
if len(norm_factor)>1:
raise RuntimeError("Can not normalize by monitor spectra. Normalization range necessary")
AddSampleLog(old_name,LogName='NormalizationFactor',LogText=str(norm_factor[0]),LogType='Number')
if not self._debug_mode:
DeleteWorkspace(norm_ws_name)
return ('monitor-2',old_name)
|
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"[",
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"]",
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"mtd",
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"norm_ws_name",
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"dataY",
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",",
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"[",
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":",
"DeleteWorkspace",
"(",
"norm_ws_name",
")",
"return",
"(",
"'monitor-2'",
",",
"old_name",
")"
] |
https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/scripts/Inelastic/Direct/DirectEnergyConversion.py#L1058-L1126
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/msw/_windows.py
|
python
|
PrintDialogData.SetSelection
|
(*args, **kwargs)
|
return _windows_.PrintDialogData_SetSelection(*args, **kwargs)
|
SetSelection(self, bool flag)
|
SetSelection(self, bool flag)
|
[
"SetSelection",
"(",
"self",
"bool",
"flag",
")"
] |
def SetSelection(*args, **kwargs):
"""SetSelection(self, bool flag)"""
return _windows_.PrintDialogData_SetSelection(*args, **kwargs)
|
[
"def",
"SetSelection",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_windows_",
".",
"PrintDialogData_SetSelection",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/msw/_windows.py#L5110-L5112
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/propgrid.py
|
python
|
PropertyGrid.GetInternalFlags
|
(*args, **kwargs)
|
return _propgrid.PropertyGrid_GetInternalFlags(*args, **kwargs)
|
GetInternalFlags(self) -> long
|
GetInternalFlags(self) -> long
|
[
"GetInternalFlags",
"(",
"self",
")",
"-",
">",
"long"
] |
def GetInternalFlags(*args, **kwargs):
"""GetInternalFlags(self) -> long"""
return _propgrid.PropertyGrid_GetInternalFlags(*args, **kwargs)
|
[
"def",
"GetInternalFlags",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_propgrid",
".",
"PropertyGrid_GetInternalFlags",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/propgrid.py#L2400-L2402
|
|
BVLC/caffe
|
9b891540183ddc834a02b2bd81b31afae71b2153
|
python/caffe/io.py
|
python
|
Transformer.set_raw_scale
|
(self, in_, scale)
|
Set the scale of raw features s.t. the input blob = input * scale.
While Python represents images in [0, 1], certain Caffe models
like CaffeNet and AlexNet represent images in [0, 255] so the raw_scale
of these models must be 255.
Parameters
----------
in_ : which input to assign this scale factor
scale : scale coefficient
|
Set the scale of raw features s.t. the input blob = input * scale.
While Python represents images in [0, 1], certain Caffe models
like CaffeNet and AlexNet represent images in [0, 255] so the raw_scale
of these models must be 255.
|
[
"Set",
"the",
"scale",
"of",
"raw",
"features",
"s",
".",
"t",
".",
"the",
"input",
"blob",
"=",
"input",
"*",
"scale",
".",
"While",
"Python",
"represents",
"images",
"in",
"[",
"0",
"1",
"]",
"certain",
"Caffe",
"models",
"like",
"CaffeNet",
"and",
"AlexNet",
"represent",
"images",
"in",
"[",
"0",
"255",
"]",
"so",
"the",
"raw_scale",
"of",
"these",
"models",
"must",
"be",
"255",
"."
] |
def set_raw_scale(self, in_, scale):
"""
Set the scale of raw features s.t. the input blob = input * scale.
While Python represents images in [0, 1], certain Caffe models
like CaffeNet and AlexNet represent images in [0, 255] so the raw_scale
of these models must be 255.
Parameters
----------
in_ : which input to assign this scale factor
scale : scale coefficient
"""
self.__check_input(in_)
self.raw_scale[in_] = scale
|
[
"def",
"set_raw_scale",
"(",
"self",
",",
"in_",
",",
"scale",
")",
":",
"self",
".",
"__check_input",
"(",
"in_",
")",
"self",
".",
"raw_scale",
"[",
"in_",
"]",
"=",
"scale"
] |
https://github.com/BVLC/caffe/blob/9b891540183ddc834a02b2bd81b31afae71b2153/python/caffe/io.py#L222-L235
|
||
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/pandas/py3/pandas/core/generic.py
|
python
|
NDFrame._repr_data_resource_
|
(self)
|
Not a real Jupyter special repr method, but we use the same
naming convention.
|
Not a real Jupyter special repr method, but we use the same
naming convention.
|
[
"Not",
"a",
"real",
"Jupyter",
"special",
"repr",
"method",
"but",
"we",
"use",
"the",
"same",
"naming",
"convention",
"."
] |
def _repr_data_resource_(self):
"""
Not a real Jupyter special repr method, but we use the same
naming convention.
"""
if config.get_option("display.html.table_schema"):
data = self.head(config.get_option("display.max_rows"))
as_json = data.to_json(orient="table")
as_json = cast(str, as_json)
return json.loads(as_json, object_pairs_hook=collections.OrderedDict)
|
[
"def",
"_repr_data_resource_",
"(",
"self",
")",
":",
"if",
"config",
".",
"get_option",
"(",
"\"display.html.table_schema\"",
")",
":",
"data",
"=",
"self",
".",
"head",
"(",
"config",
".",
"get_option",
"(",
"\"display.max_rows\"",
")",
")",
"as_json",
"=",
"data",
".",
"to_json",
"(",
"orient",
"=",
"\"table\"",
")",
"as_json",
"=",
"cast",
"(",
"str",
",",
"as_json",
")",
"return",
"json",
".",
"loads",
"(",
"as_json",
",",
"object_pairs_hook",
"=",
"collections",
".",
"OrderedDict",
")"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py3/pandas/core/generic.py#L2114-L2124
|
||
PaddlePaddle/Paddle
|
1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c
|
python/paddle/distributed/fleet/base/role_maker.py
|
python
|
PaddleCloudRoleMaker._get_stage_id
|
(self)
|
return self._stage_id
|
return stage id of current heter worker
|
return stage id of current heter worker
|
[
"return",
"stage",
"id",
"of",
"current",
"heter",
"worker"
] |
def _get_stage_id(self):
"""
return stage id of current heter worker
"""
if not self._role_is_generated:
self._generate_role()
return self._stage_id
|
[
"def",
"_get_stage_id",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"_role_is_generated",
":",
"self",
".",
"_generate_role",
"(",
")",
"return",
"self",
".",
"_stage_id"
] |
https://github.com/PaddlePaddle/Paddle/blob/1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c/python/paddle/distributed/fleet/base/role_maker.py#L569-L575
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/gtk/richtext.py
|
python
|
RichTextCtrl.AddParagraph
|
(*args, **kwargs)
|
return _richtext.RichTextCtrl_AddParagraph(*args, **kwargs)
|
AddParagraph(self, String text) -> RichTextRange
Add a new paragraph of text to the end of the buffer
|
AddParagraph(self, String text) -> RichTextRange
|
[
"AddParagraph",
"(",
"self",
"String",
"text",
")",
"-",
">",
"RichTextRange"
] |
def AddParagraph(*args, **kwargs):
"""
AddParagraph(self, String text) -> RichTextRange
Add a new paragraph of text to the end of the buffer
"""
return _richtext.RichTextCtrl_AddParagraph(*args, **kwargs)
|
[
"def",
"AddParagraph",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_richtext",
".",
"RichTextCtrl_AddParagraph",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/gtk/richtext.py#L3687-L3693
|
|
Ifsttar/I-Simpa
|
2283385f4cac769a92e265edabb9c79cb6c42d03
|
currentRelease/SystemScript/graphy/backends/google_chart_api/encoders.py
|
python
|
BaseChartEncoder.Img
|
(self, width, height)
|
return tag % (url, width, height)
|
Get an image tag for our graph.
|
Get an image tag for our graph.
|
[
"Get",
"an",
"image",
"tag",
"for",
"our",
"graph",
"."
] |
def Img(self, width, height):
"""Get an image tag for our graph."""
url = self.Url(width, height, use_html_entities=True)
tag = '<img src="%s" width="%s" height="%s" alt="chart"/>'
return tag % (url, width, height)
|
[
"def",
"Img",
"(",
"self",
",",
"width",
",",
"height",
")",
":",
"url",
"=",
"self",
".",
"Url",
"(",
"width",
",",
"height",
",",
"use_html_entities",
"=",
"True",
")",
"tag",
"=",
"'<img src=\"%s\" width=\"%s\" height=\"%s\" alt=\"chart\"/>'",
"return",
"tag",
"%",
"(",
"url",
",",
"width",
",",
"height",
")"
] |
https://github.com/Ifsttar/I-Simpa/blob/2283385f4cac769a92e265edabb9c79cb6c42d03/currentRelease/SystemScript/graphy/backends/google_chart_api/encoders.py#L67-L71
|
|
tiny-dnn/tiny-dnn
|
c0f576f5cb7b35893f62127cb7aec18f77a3bcc5
|
third_party/gemmlowp/meta/generators/gemm_MxNxK.py
|
python
|
GenerateGemmSwitch3
|
(emitter, output_type, aligned, m_mod, n_mod)
|
Third level of main switch, choose optimized version on depth leftover.
|
Third level of main switch, choose optimized version on depth leftover.
|
[
"Third",
"level",
"of",
"main",
"switch",
"choose",
"optimized",
"version",
"on",
"depth",
"leftover",
"."
] |
def GenerateGemmSwitch3(emitter, output_type, aligned, m_mod, n_mod):
"""Third level of main switch, choose optimized version on depth leftover."""
emitter.EmitSwitch('k % 8')
for leftovers in range(0, 8):
emitter.EmitCase(leftovers)
emitter.PushIndent()
GenerateGemmCall(emitter, output_type, aligned, m_mod, n_mod, leftovers)
emitter.EmitBreak()
emitter.PopIndent()
emitter.EmitSwitchEnd()
|
[
"def",
"GenerateGemmSwitch3",
"(",
"emitter",
",",
"output_type",
",",
"aligned",
",",
"m_mod",
",",
"n_mod",
")",
":",
"emitter",
".",
"EmitSwitch",
"(",
"'k % 8'",
")",
"for",
"leftovers",
"in",
"range",
"(",
"0",
",",
"8",
")",
":",
"emitter",
".",
"EmitCase",
"(",
"leftovers",
")",
"emitter",
".",
"PushIndent",
"(",
")",
"GenerateGemmCall",
"(",
"emitter",
",",
"output_type",
",",
"aligned",
",",
"m_mod",
",",
"n_mod",
",",
"leftovers",
")",
"emitter",
".",
"EmitBreak",
"(",
")",
"emitter",
".",
"PopIndent",
"(",
")",
"emitter",
".",
"EmitSwitchEnd",
"(",
")"
] |
https://github.com/tiny-dnn/tiny-dnn/blob/c0f576f5cb7b35893f62127cb7aec18f77a3bcc5/third_party/gemmlowp/meta/generators/gemm_MxNxK.py#L245-L256
|
||
wlanjie/AndroidFFmpeg
|
7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf
|
tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib2to3/pytree.py
|
python
|
Base.__new__
|
(cls, *args, **kwds)
|
return object.__new__(cls)
|
Constructor that prevents Base from being instantiated.
|
Constructor that prevents Base from being instantiated.
|
[
"Constructor",
"that",
"prevents",
"Base",
"from",
"being",
"instantiated",
"."
] |
def __new__(cls, *args, **kwds):
"""Constructor that prevents Base from being instantiated."""
assert cls is not Base, "Cannot instantiate Base"
return object.__new__(cls)
|
[
"def",
"__new__",
"(",
"cls",
",",
"*",
"args",
",",
"*",
"*",
"kwds",
")",
":",
"assert",
"cls",
"is",
"not",
"Base",
",",
"\"Cannot instantiate Base\"",
"return",
"object",
".",
"__new__",
"(",
"cls",
")"
] |
https://github.com/wlanjie/AndroidFFmpeg/blob/7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf/tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib2to3/pytree.py#L50-L53
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/_windows.py
|
python
|
GenericProgressDialog.Resume
|
(*args, **kwargs)
|
return _windows_.GenericProgressDialog_Resume(*args, **kwargs)
|
Resume(self)
Can be used to continue with the dialog, after the user had chosen to
abort.
|
Resume(self)
|
[
"Resume",
"(",
"self",
")"
] |
def Resume(*args, **kwargs):
"""
Resume(self)
Can be used to continue with the dialog, after the user had chosen to
abort.
"""
return _windows_.GenericProgressDialog_Resume(*args, **kwargs)
|
[
"def",
"Resume",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_windows_",
".",
"GenericProgressDialog_Resume",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_windows.py#L3725-L3732
|
|
trailofbits/llvm-sanitizer-tutorial
|
d29dfeec7f51fbf234fd0080f28f2b30cd0b6e99
|
llvm/projects/compiler-rt/lib/sanitizer_common/scripts/cpplint.py
|
python
|
_NestingState.Update
|
(self, filename, clean_lines, linenum, error)
|
Update nesting state with current line.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
|
Update nesting state with current line.
|
[
"Update",
"nesting",
"state",
"with",
"current",
"line",
"."
] |
def Update(self, filename, clean_lines, linenum, error):
"""Update nesting state with current line.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
error: The function to call with any errors found.
"""
line = clean_lines.elided[linenum]
# Update pp_stack first
self.UpdatePreprocessor(line)
# Count parentheses. This is to avoid adding struct arguments to
# the nesting stack.
if self.stack:
inner_block = self.stack[-1]
depth_change = line.count('(') - line.count(')')
inner_block.open_parentheses += depth_change
# Also check if we are starting or ending an inline assembly block.
if inner_block.inline_asm in (_NO_ASM, _END_ASM):
if (depth_change != 0 and
inner_block.open_parentheses == 1 and
_MATCH_ASM.match(line)):
# Enter assembly block
inner_block.inline_asm = _INSIDE_ASM
else:
# Not entering assembly block. If previous line was _END_ASM,
# we will now shift to _NO_ASM state.
inner_block.inline_asm = _NO_ASM
elif (inner_block.inline_asm == _INSIDE_ASM and
inner_block.open_parentheses == 0):
# Exit assembly block
inner_block.inline_asm = _END_ASM
# Consume namespace declaration at the beginning of the line. Do
# this in a loop so that we catch same line declarations like this:
# namespace proto2 { namespace bridge { class MessageSet; } }
while True:
# Match start of namespace. The "\b\s*" below catches namespace
# declarations even if it weren't followed by a whitespace, this
# is so that we don't confuse our namespace checker. The
# missing spaces will be flagged by CheckSpacing.
namespace_decl_match = Match(r'^\s*namespace\b\s*([:\w]+)?(.*)$', line)
if not namespace_decl_match:
break
new_namespace = _NamespaceInfo(namespace_decl_match.group(1), linenum)
self.stack.append(new_namespace)
line = namespace_decl_match.group(2)
if line.find('{') != -1:
new_namespace.seen_open_brace = True
line = line[line.find('{') + 1:]
# Look for a class declaration in whatever is left of the line
# after parsing namespaces. The regexp accounts for decorated classes
# such as in:
# class LOCKABLE API Object {
# };
#
# Templates with class arguments may confuse the parser, for example:
# template <class T
# class Comparator = less<T>,
# class Vector = vector<T> >
# class HeapQueue {
#
# Because this parser has no nesting state about templates, by the
# time it saw "class Comparator", it may think that it's a new class.
# Nested templates have a similar problem:
# template <
# typename ExportedType,
# typename TupleType,
# template <typename, typename> class ImplTemplate>
#
# To avoid these cases, we ignore classes that are followed by '=' or '>'
class_decl_match = Match(
r'\s*(template\s*<[\w\s<>,:]*>\s*)?'
'(class|struct)\s+([A-Z_]+\s+)*(\w+(?:::\w+)*)'
'(([^=>]|<[^<>]*>)*)$', line)
if (class_decl_match and
(not self.stack or self.stack[-1].open_parentheses == 0)):
self.stack.append(_ClassInfo(
class_decl_match.group(4), class_decl_match.group(2),
clean_lines, linenum))
line = class_decl_match.group(5)
# If we have not yet seen the opening brace for the innermost block,
# run checks here.
if not self.SeenOpenBrace():
self.stack[-1].CheckBegin(filename, clean_lines, linenum, error)
# Update access control if we are inside a class/struct
if self.stack and isinstance(self.stack[-1], _ClassInfo):
access_match = Match(r'\s*(public|private|protected)\s*:', line)
if access_match:
self.stack[-1].access = access_match.group(1)
# Consume braces or semicolons from what's left of the line
while True:
# Match first brace, semicolon, or closed parenthesis.
matched = Match(r'^[^{;)}]*([{;)}])(.*)$', line)
if not matched:
break
token = matched.group(1)
if token == '{':
# If namespace or class hasn't seen a opening brace yet, mark
# namespace/class head as complete. Push a new block onto the
# stack otherwise.
if not self.SeenOpenBrace():
self.stack[-1].seen_open_brace = True
else:
self.stack.append(_BlockInfo(True))
if _MATCH_ASM.match(line):
self.stack[-1].inline_asm = _BLOCK_ASM
elif token == ';' or token == ')':
# If we haven't seen an opening brace yet, but we already saw
# a semicolon, this is probably a forward declaration. Pop
# the stack for these.
#
# Similarly, if we haven't seen an opening brace yet, but we
# already saw a closing parenthesis, then these are probably
# function arguments with extra "class" or "struct" keywords.
# Also pop these stack for these.
if not self.SeenOpenBrace():
self.stack.pop()
else: # token == '}'
# Perform end of block checks and pop the stack.
if self.stack:
self.stack[-1].CheckEnd(filename, clean_lines, linenum, error)
self.stack.pop()
line = matched.group(2)
|
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"if",
"not",
"self",
".",
"SeenOpenBrace",
"(",
")",
":",
"self",
".",
"stack",
"[",
"-",
"1",
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".",
"seen_open_brace",
"=",
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"else",
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"self",
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"stack",
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"append",
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"_BlockInfo",
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"inline_asm",
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"_BLOCK_ASM",
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"token",
"==",
"';'",
"or",
"token",
"==",
"')'",
":",
"# If we haven't seen an opening brace yet, but we already saw",
"# a semicolon, this is probably a forward declaration. Pop",
"# the stack for these.",
"#",
"# Similarly, if we haven't seen an opening brace yet, but we",
"# already saw a closing parenthesis, then these are probably",
"# function arguments with extra \"class\" or \"struct\" keywords.",
"# Also pop these stack for these.",
"if",
"not",
"self",
".",
"SeenOpenBrace",
"(",
")",
":",
"self",
".",
"stack",
".",
"pop",
"(",
")",
"else",
":",
"# token == '}'",
"# Perform end of block checks and pop the stack.",
"if",
"self",
".",
"stack",
":",
"self",
".",
"stack",
"[",
"-",
"1",
"]",
".",
"CheckEnd",
"(",
"filename",
",",
"clean_lines",
",",
"linenum",
",",
"error",
")",
"self",
".",
"stack",
".",
"pop",
"(",
")",
"line",
"=",
"matched",
".",
"group",
"(",
"2",
")"
] |
https://github.com/trailofbits/llvm-sanitizer-tutorial/blob/d29dfeec7f51fbf234fd0080f28f2b30cd0b6e99/llvm/projects/compiler-rt/lib/sanitizer_common/scripts/cpplint.py#L1584-L1718
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/_windows.py
|
python
|
FileDialog.SetDirectory
|
(*args, **kwargs)
|
return _windows_.FileDialog_SetDirectory(*args, **kwargs)
|
SetDirectory(self, String dir)
Sets the default directory.
|
SetDirectory(self, String dir)
|
[
"SetDirectory",
"(",
"self",
"String",
"dir",
")"
] |
def SetDirectory(*args, **kwargs):
"""
SetDirectory(self, String dir)
Sets the default directory.
"""
return _windows_.FileDialog_SetDirectory(*args, **kwargs)
|
[
"def",
"SetDirectory",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_windows_",
".",
"FileDialog_SetDirectory",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_windows.py#L3159-L3165
|
|
H-uru/Plasma
|
c2140ea046e82e9c199e257a7f2e7edb42602871
|
Scripts/Python/plasma/Plasma.py
|
python
|
PtDumpLogs
|
(folder)
|
Dumps all current log files to the specified folder (a sub-folder to the log folder)
|
Dumps all current log files to the specified folder (a sub-folder to the log folder)
|
[
"Dumps",
"all",
"current",
"log",
"files",
"to",
"the",
"specified",
"folder",
"(",
"a",
"sub",
"-",
"folder",
"to",
"the",
"log",
"folder",
")"
] |
def PtDumpLogs(folder):
"""Dumps all current log files to the specified folder (a sub-folder to the log folder)"""
pass
|
[
"def",
"PtDumpLogs",
"(",
"folder",
")",
":",
"pass"
] |
https://github.com/H-uru/Plasma/blob/c2140ea046e82e9c199e257a7f2e7edb42602871/Scripts/Python/plasma/Plasma.py#L230-L232
|
||
neoml-lib/neoml
|
a0d370fba05269a1b2258cef126f77bbd2054a3e
|
NeoML/Python/neoml/Dnn/Conv.py
|
python
|
TimeConv.filter
|
(self)
|
return Blob.Blob(self._internal.get_filter())
|
Gets the filters. The dimensions:
- **BatchLength** is 1
- **BatchWidth** is filter_count
- **Height** is filter_size
- **Width**, **Depth** are 1
- **Channels** is the inputs' **Height** * **Width** * **Depth** * **Channels**
|
Gets the filters. The dimensions:
|
[
"Gets",
"the",
"filters",
".",
"The",
"dimensions",
":"
] |
def filter(self):
"""Gets the filters. The dimensions:
- **BatchLength** is 1
- **BatchWidth** is filter_count
- **Height** is filter_size
- **Width**, **Depth** are 1
- **Channels** is the inputs' **Height** * **Width** * **Depth** * **Channels**
"""
return Blob.Blob(self._internal.get_filter())
|
[
"def",
"filter",
"(",
"self",
")",
":",
"return",
"Blob",
".",
"Blob",
"(",
"self",
".",
"_internal",
".",
"get_filter",
"(",
")",
")"
] |
https://github.com/neoml-lib/neoml/blob/a0d370fba05269a1b2258cef126f77bbd2054a3e/NeoML/Python/neoml/Dnn/Conv.py#L1158-L1167
|
|
sdhash/sdhash
|
b9eff63e4e5867e910f41fd69032bbb1c94a2a5e
|
sdhash-ui/cherrypy/lib/sessions.py
|
python
|
RamSession.acquire_lock
|
(self)
|
Acquire an exclusive lock on the currently-loaded session data.
|
Acquire an exclusive lock on the currently-loaded session data.
|
[
"Acquire",
"an",
"exclusive",
"lock",
"on",
"the",
"currently",
"-",
"loaded",
"session",
"data",
"."
] |
def acquire_lock(self):
"""Acquire an exclusive lock on the currently-loaded session data."""
self.locked = True
self.locks.setdefault(self.id, threading.RLock()).acquire()
|
[
"def",
"acquire_lock",
"(",
"self",
")",
":",
"self",
".",
"locked",
"=",
"True",
"self",
".",
"locks",
".",
"setdefault",
"(",
"self",
".",
"id",
",",
"threading",
".",
"RLock",
"(",
")",
")",
".",
"acquire",
"(",
")"
] |
https://github.com/sdhash/sdhash/blob/b9eff63e4e5867e910f41fd69032bbb1c94a2a5e/sdhash-ui/cherrypy/lib/sessions.py#L367-L370
|
||
benoitsteiner/tensorflow-opencl
|
cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5
|
tensorflow/python/training/basic_session_run_hooks.py
|
python
|
CheckpointSaverHook._save
|
(self, session, step)
|
Saves the latest checkpoint.
|
Saves the latest checkpoint.
|
[
"Saves",
"the",
"latest",
"checkpoint",
"."
] |
def _save(self, session, step):
"""Saves the latest checkpoint."""
logging.info("Saving checkpoints for %d into %s.", step, self._save_path)
for l in self._listeners:
l.before_save(session, step)
self._get_saver().save(session, self._save_path, global_step=step)
self._summary_writer.add_session_log(
SessionLog(
status=SessionLog.CHECKPOINT, checkpoint_path=self._save_path),
step)
for l in self._listeners:
l.after_save(session, step)
|
[
"def",
"_save",
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"self",
",",
"session",
",",
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":",
"logging",
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",",
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"_listeners",
":",
"l",
".",
"after_save",
"(",
"session",
",",
"step",
")"
] |
https://github.com/benoitsteiner/tensorflow-opencl/blob/cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5/tensorflow/python/training/basic_session_run_hooks.py#L461-L475
|
||
moderngl/moderngl
|
32fe79927e02b0fa893b3603d677bdae39771e14
|
moderngl/buffer.py
|
python
|
Buffer.read_into
|
(self, buffer, size=-1, *, offset=0, write_offset=0)
|
return self.mglo.read_into(buffer, size, offset, write_offset)
|
Read the content into a buffer.
Args:
buffer (bytearray): The buffer that will receive the content.
size (int): The size in bytes. Value ``-1`` means all.
Keyword Args:
offset (int): The read offset in bytes.
write_offset (int): The write offset in bytes.
|
Read the content into a buffer.
|
[
"Read",
"the",
"content",
"into",
"a",
"buffer",
"."
] |
def read_into(self, buffer, size=-1, *, offset=0, write_offset=0) -> None:
'''
Read the content into a buffer.
Args:
buffer (bytearray): The buffer that will receive the content.
size (int): The size in bytes. Value ``-1`` means all.
Keyword Args:
offset (int): The read offset in bytes.
write_offset (int): The write offset in bytes.
'''
return self.mglo.read_into(buffer, size, offset, write_offset)
|
[
"def",
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"(",
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",",
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",",
"size",
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"read_into",
"(",
"buffer",
",",
"size",
",",
"offset",
",",
"write_offset",
")"
] |
https://github.com/moderngl/moderngl/blob/32fe79927e02b0fa893b3603d677bdae39771e14/moderngl/buffer.py#L119-L132
|
|
catboost/catboost
|
167f64f237114a4d10b2b4ee42adb4569137debe
|
contrib/python/pandas/py3/pandas/core/dtypes/base.py
|
python
|
ExtensionDtype._is_numeric
|
(self)
|
return False
|
Whether columns with this dtype should be considered numeric.
By default ExtensionDtypes are assumed to be non-numeric.
They'll be excluded from operations that exclude non-numeric
columns, like (groupby) reductions, plotting, etc.
|
Whether columns with this dtype should be considered numeric.
|
[
"Whether",
"columns",
"with",
"this",
"dtype",
"should",
"be",
"considered",
"numeric",
"."
] |
def _is_numeric(self) -> bool:
"""
Whether columns with this dtype should be considered numeric.
By default ExtensionDtypes are assumed to be non-numeric.
They'll be excluded from operations that exclude non-numeric
columns, like (groupby) reductions, plotting, etc.
"""
return False
|
[
"def",
"_is_numeric",
"(",
"self",
")",
"->",
"bool",
":",
"return",
"False"
] |
https://github.com/catboost/catboost/blob/167f64f237114a4d10b2b4ee42adb4569137debe/contrib/python/pandas/py3/pandas/core/dtypes/base.py#L307-L315
|
|
ricardoquesada/Spidermonkey
|
4a75ea2543408bd1b2c515aa95901523eeef7858
|
ipc/ipdl/ipdl/parser.py
|
python
|
p_SpawnsStmtsOpt
|
(p)
|
SpawnsStmtsOpt : SpawnsStmt SpawnsStmtsOpt
| BridgesStmtsOpt
|
SpawnsStmtsOpt : SpawnsStmt SpawnsStmtsOpt
| BridgesStmtsOpt
|
[
"SpawnsStmtsOpt",
":",
"SpawnsStmt",
"SpawnsStmtsOpt",
"|",
"BridgesStmtsOpt"
] |
def p_SpawnsStmtsOpt(p):
"""SpawnsStmtsOpt : SpawnsStmt SpawnsStmtsOpt
| BridgesStmtsOpt"""
if 2 == len(p):
p[0] = p[1]
else:
p[2].spawnsStmts.insert(0, p[1])
p[0] = p[2]
|
[
"def",
"p_SpawnsStmtsOpt",
"(",
"p",
")",
":",
"if",
"2",
"==",
"len",
"(",
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"[",
"1",
"]",
")",
"p",
"[",
"0",
"]",
"=",
"p",
"[",
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"]"
] |
https://github.com/ricardoquesada/Spidermonkey/blob/4a75ea2543408bd1b2c515aa95901523eeef7858/ipc/ipdl/ipdl/parser.py#L370-L377
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/importlib/_bootstrap.py
|
python
|
_requires_builtin
|
(fxn)
|
return _requires_builtin_wrapper
|
Decorator to verify the named module is built-in.
|
Decorator to verify the named module is built-in.
|
[
"Decorator",
"to",
"verify",
"the",
"named",
"module",
"is",
"built",
"-",
"in",
"."
] |
def _requires_builtin(fxn):
"""Decorator to verify the named module is built-in."""
def _requires_builtin_wrapper(self, fullname):
if fullname not in sys.builtin_module_names:
raise ImportError('{!r} is not a built-in module'.format(fullname),
name=fullname)
return fxn(self, fullname)
_wrap(_requires_builtin_wrapper, fxn)
return _requires_builtin_wrapper
|
[
"def",
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"fxn",
")",
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"_requires_builtin_wrapper",
"(",
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",",
"fullname",
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"(",
"_requires_builtin_wrapper",
",",
"fxn",
")",
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/importlib/_bootstrap.py#L230-L238
|
|
mantidproject/mantid
|
03deeb89254ec4289edb8771e0188c2090a02f32
|
qt/python/mantidqt/mantidqt/gui_helper.py
|
python
|
show_interface_help
|
(mantidplot_name, assistant_process, area: str='',
collection_file: str='',
qt_url: str='', external_url: str="")
|
Shows the help page for a custom interface
@param mantidplot_name: used by showCustomInterfaceHelp
@param assistant_process: needs to be started/closed from outside (see example below)
@param collection_file: qth file containing the help in format used by qtassistant. The default is
``mantid._bindir + '../docs/qthelp/MantidProject.qhc'``
@param qt_url: location of the help in the qth file. The default value is
``qthelp://org.sphinx.mantidproject.{mtdversion}/doc/interfaces/{mantidplot_name}.html``.
@param external_url: location of external page to be displayed in the default browser. The default value is
``http://docs.mantidproject.org/nightly/interfaces/framework/{mantidplot_name}.html``
Example using defaults:
#in the __init__ function of the GUI add:
self.assistant_process = QtCore.QProcess(self)
self.mantidplot_name='DGS Planner'
#add a help function in the GUI
def help(self):
show_interface_help(self.mantidplot_name,
self.assistant_process)
#make sure you close the qtassistant when the GUI is closed
def closeEvent(self, event):
self.assistant_process.close()
self.assistant_process.waitForFinished()
event.accept()
|
Shows the help page for a custom interface
@param mantidplot_name: used by showCustomInterfaceHelp
@param assistant_process: needs to be started/closed from outside (see example below)
@param collection_file: qth file containing the help in format used by qtassistant. The default is
``mantid._bindir + '../docs/qthelp/MantidProject.qhc'``
@param qt_url: location of the help in the qth file. The default value is
``qthelp://org.sphinx.mantidproject.{mtdversion}/doc/interfaces/{mantidplot_name}.html``.
@param external_url: location of external page to be displayed in the default browser. The default value is
``http://docs.mantidproject.org/nightly/interfaces/framework/{mantidplot_name}.html``
|
[
"Shows",
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"interface",
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"mantidplot_name",
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"/",
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"nightly",
"/",
"interfaces",
"/",
"framework",
"/",
"{",
"mantidplot_name",
"}",
".",
"html"
] |
def show_interface_help(mantidplot_name, assistant_process, area: str='',
collection_file: str='',
qt_url: str='', external_url: str=""):
''' Shows the help page for a custom interface
@param mantidplot_name: used by showCustomInterfaceHelp
@param assistant_process: needs to be started/closed from outside (see example below)
@param collection_file: qth file containing the help in format used by qtassistant. The default is
``mantid._bindir + '../docs/qthelp/MantidProject.qhc'``
@param qt_url: location of the help in the qth file. The default value is
``qthelp://org.sphinx.mantidproject.{mtdversion}/doc/interfaces/{mantidplot_name}.html``.
@param external_url: location of external page to be displayed in the default browser. The default value is
``http://docs.mantidproject.org/nightly/interfaces/framework/{mantidplot_name}.html``
Example using defaults:
#in the __init__ function of the GUI add:
self.assistant_process = QtCore.QProcess(self)
self.mantidplot_name='DGS Planner'
#add a help function in the GUI
def help(self):
show_interface_help(self.mantidplot_name,
self.assistant_process)
#make sure you close the qtassistant when the GUI is closed
def closeEvent(self, event):
self.assistant_process.close()
self.assistant_process.waitForFinished()
event.accept()
'''
try:
# try using built-in help in mantid
import mantidqt
mantidqt.interfacemanager.InterfaceManager().showCustomInterfaceHelp(mantidplot_name, area)
except: #(ImportError, ModuleNotFoundError) raises the wrong type of error
# built-in help failed, try external qtassistant then give up and launch a browser
# cleanup previous version
assistant_process.close()
assistant_process.waitForFinished()
# where to expect qtassistant
helpapp = QtCore.QLibraryInfo.location(QtCore.QLibraryInfo.BinariesPath) + QtCore.QDir.separator()
helpapp += 'assistant'
collection_file = __get_collection_file(collection_file)
if os.path.isfile(helpapp) and os.path.isfile(collection_file):
# try to find the collection file and launch qtassistant
args = ['-enableRemoteControl',
'-collectionFile', collection_file,
'-showUrl', __to_qthelp_url(mantidplot_name, area, qt_url)]
assistant_process.close()
assistant_process.waitForFinished()
assistant_process.start(helpapp, args)
else:
# give up and upen a URL in default browser
openUrl=QtGui.QDesktopServices.openUrl
sysenv=QtCore.QProcessEnvironment.systemEnvironment()
ldp=sysenv.value('LD_PRELOAD')
if ldp:
del os.environ['LD_PRELOAD']
# create a url to the help in the default location
openUrl(__to_external_url(mantidplot_name, area, external_url))
if ldp:
os.environ['LD_PRELOAD']=ldp
|
[
"def",
"show_interface_help",
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] |
https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/qt/python/mantidqt/mantidqt/gui_helper.py#L83-L150
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_vendor/urllib3/fields.py
|
python
|
RequestField._render_parts
|
(self, header_parts)
|
return u"; ".join(parts)
|
Helper function to format and quote a single header.
Useful for single headers that are composed of multiple items. E.g.,
'Content-Disposition' fields.
:param header_parts:
A sequence of (k, v) tuples or a :class:`dict` of (k, v) to format
as `k1="v1"; k2="v2"; ...`.
|
[] |
def _render_parts(self, header_parts):
"""
Helper function to format and quote a single header.
Useful for single headers that are composed of multiple items. E.g.,
'Content-Disposition' fields.
:param header_parts:
A sequence of (k, v) tuples or a :class:`dict` of (k, v) to format
as `k1="v1"; k2="v2"; ...`.
"""
parts = []
iterable = header_parts
if isinstance(header_parts, dict):
iterable = header_parts.items()
for name, value in iterable:
if value is not None:
parts.append(self._render_part(name, value))
return u"; ".join(parts)
|
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https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_vendor/urllib3/fields.py#L415-L455
|
||
y123456yz/reading-and-annotate-mongodb-3.6
|
93280293672ca7586dc24af18132aa61e4ed7fcf
|
mongo/src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Tool/docbook/__init__.py
|
python
|
DocbookHtmlChunked
|
(env, target, source=None, *args, **kw)
|
return result
|
A pseudo-Builder, providing a Docbook toolchain for chunked HTML output.
|
A pseudo-Builder, providing a Docbook toolchain for chunked HTML output.
|
[
"A",
"pseudo",
"-",
"Builder",
"providing",
"a",
"Docbook",
"toolchain",
"for",
"chunked",
"HTML",
"output",
"."
] |
def DocbookHtmlChunked(env, target, source=None, *args, **kw):
"""
A pseudo-Builder, providing a Docbook toolchain for chunked HTML output.
"""
# Init target/source
if not SCons.Util.is_List(target):
target = [target]
if not source:
source = target
target = ['index.html']
elif not SCons.Util.is_List(source):
source = [source]
# Init XSL stylesheet
__init_xsl_stylesheet(kw, env, '$DOCBOOK_DEFAULT_XSL_HTMLCHUNKED', ['html','chunkfast.xsl'])
# Setup builder
__builder = __select_builder(__lxml_builder, __libxml2_builder, __xsltproc_builder)
# Detect base dir
base_dir = kw.get('base_dir', '')
if base_dir:
__create_output_dir(base_dir)
# Create targets
result = []
r = __builder.__call__(env, __ensure_suffix(str(target[0]), '.html'), source[0], **kw)
env.Depends(r, kw['DOCBOOK_XSL'])
result.extend(r)
# Add supporting files for cleanup
env.Clean(r, glob.glob(os.path.join(base_dir, '*.html')))
return result
|
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",",
"'*.html'",
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")",
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] |
https://github.com/y123456yz/reading-and-annotate-mongodb-3.6/blob/93280293672ca7586dc24af18132aa61e4ed7fcf/mongo/src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Tool/docbook/__init__.py#L557-L589
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_internal/models/selection_prefs.py
|
python
|
SelectionPreferences.__init__
|
(
self,
allow_yanked, # type: bool
allow_all_prereleases=False, # type: bool
format_control=None, # type: Optional[FormatControl]
prefer_binary=False, # type: bool
ignore_requires_python=None, # type: Optional[bool]
)
|
Create a SelectionPreferences object.
:param allow_yanked: Whether files marked as yanked (in the sense
of PEP 592) are permitted to be candidates for install.
:param format_control: A FormatControl object or None. Used to control
the selection of source packages / binary packages when consulting
the index and links.
:param prefer_binary: Whether to prefer an old, but valid, binary
dist over a new source dist.
:param ignore_requires_python: Whether to ignore incompatible
"Requires-Python" values in links. Defaults to False.
|
Create a SelectionPreferences object.
|
[
"Create",
"a",
"SelectionPreferences",
"object",
"."
] |
def __init__(
self,
allow_yanked, # type: bool
allow_all_prereleases=False, # type: bool
format_control=None, # type: Optional[FormatControl]
prefer_binary=False, # type: bool
ignore_requires_python=None, # type: Optional[bool]
):
# type: (...) -> None
"""Create a SelectionPreferences object.
:param allow_yanked: Whether files marked as yanked (in the sense
of PEP 592) are permitted to be candidates for install.
:param format_control: A FormatControl object or None. Used to control
the selection of source packages / binary packages when consulting
the index and links.
:param prefer_binary: Whether to prefer an old, but valid, binary
dist over a new source dist.
:param ignore_requires_python: Whether to ignore incompatible
"Requires-Python" values in links. Defaults to False.
"""
if ignore_requires_python is None:
ignore_requires_python = False
self.allow_yanked = allow_yanked
self.allow_all_prereleases = allow_all_prereleases
self.format_control = format_control
self.prefer_binary = prefer_binary
self.ignore_requires_python = ignore_requires_python
|
[
"def",
"__init__",
"(",
"self",
",",
"allow_yanked",
",",
"# type: bool",
"allow_all_prereleases",
"=",
"False",
",",
"# type: bool",
"format_control",
"=",
"None",
",",
"# type: Optional[FormatControl]",
"prefer_binary",
"=",
"False",
",",
"# type: bool",
"ignore_requires_python",
"=",
"None",
",",
"# type: Optional[bool]",
")",
":",
"# type: (...) -> None",
"if",
"ignore_requires_python",
"is",
"None",
":",
"ignore_requires_python",
"=",
"False",
"self",
".",
"allow_yanked",
"=",
"allow_yanked",
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".",
"allow_all_prereleases",
"=",
"allow_all_prereleases",
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"format_control",
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"self",
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"prefer_binary",
"=",
"prefer_binary",
"self",
".",
"ignore_requires_python",
"=",
"ignore_requires_python"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_internal/models/selection_prefs.py#L43-L99
|
||
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/_controls.py
|
python
|
AnyButton.GetBitmapCurrent
|
(*args, **kwargs)
|
return _controls_.AnyButton_GetBitmapCurrent(*args, **kwargs)
|
GetBitmapCurrent(self) -> Bitmap
|
GetBitmapCurrent(self) -> Bitmap
|
[
"GetBitmapCurrent",
"(",
"self",
")",
"-",
">",
"Bitmap"
] |
def GetBitmapCurrent(*args, **kwargs):
"""GetBitmapCurrent(self) -> Bitmap"""
return _controls_.AnyButton_GetBitmapCurrent(*args, **kwargs)
|
[
"def",
"GetBitmapCurrent",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_controls_",
".",
"AnyButton_GetBitmapCurrent",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/_controls.py#L112-L114
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/lib/agw/thumbnailctrl.py
|
python
|
ThumbnailCtrl.OnComboBox
|
(self, event)
|
Handles the ``wx.EVT_COMBOBOX`` for the folder combobox.
:param `event`: a :class:`CommandEvent` event to be processed.
|
Handles the ``wx.EVT_COMBOBOX`` for the folder combobox.
|
[
"Handles",
"the",
"wx",
".",
"EVT_COMBOBOX",
"for",
"the",
"folder",
"combobox",
"."
] |
def OnComboBox(self, event):
"""
Handles the ``wx.EVT_COMBOBOX`` for the folder combobox.
:param `event`: a :class:`CommandEvent` event to be processed.
"""
dirs = self._combo.GetValue()
if os.path.isdir(opj(dirs)):
self._scrolled.ShowDir(opj(dirs))
event.Skip()
|
[
"def",
"OnComboBox",
"(",
"self",
",",
"event",
")",
":",
"dirs",
"=",
"self",
".",
"_combo",
".",
"GetValue",
"(",
")",
"if",
"os",
".",
"path",
".",
"isdir",
"(",
"opj",
"(",
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")",
")",
":",
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"_scrolled",
".",
"ShowDir",
"(",
"opj",
"(",
"dirs",
")",
")",
"event",
".",
"Skip",
"(",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/lib/agw/thumbnailctrl.py#L1010-L1022
|
||
windystrife/UnrealEngine_NVIDIAGameWorks
|
b50e6338a7c5b26374d66306ebc7807541ff815e
|
Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/HTMLParser.py
|
python
|
HTMLParser.get_starttag_text
|
(self)
|
return self.__starttag_text
|
Return full source of start tag: '<...>'.
|
Return full source of start tag: '<...>'.
|
[
"Return",
"full",
"source",
"of",
"start",
"tag",
":",
"<",
"...",
">",
"."
] |
def get_starttag_text(self):
"""Return full source of start tag: '<...>'."""
return self.__starttag_text
|
[
"def",
"get_starttag_text",
"(",
"self",
")",
":",
"return",
"self",
".",
"__starttag_text"
] |
https://github.com/windystrife/UnrealEngine_NVIDIAGameWorks/blob/b50e6338a7c5b26374d66306ebc7807541ff815e/Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/HTMLParser.py#L125-L127
|
|
gem5/gem5
|
141cc37c2d4b93959d4c249b8f7e6a8b2ef75338
|
src/python/gem5/components/cachehierarchies/classic/no_cache.py
|
python
|
NoCache.__init__
|
(
self, membus: BaseXBar = _get_default_membus.__func__()
)
|
:param membus: The memory bus for this setup. This parameter is
optional and will default toa 64 bit width SystemXBar is not specified.
:type membus: BaseXBar
|
:param membus: The memory bus for this setup. This parameter is
optional and will default toa 64 bit width SystemXBar is not specified.
|
[
":",
"param",
"membus",
":",
"The",
"memory",
"bus",
"for",
"this",
"setup",
".",
"This",
"parameter",
"is",
"optional",
"and",
"will",
"default",
"toa",
"64",
"bit",
"width",
"SystemXBar",
"is",
"not",
"specified",
"."
] |
def __init__(
self, membus: BaseXBar = _get_default_membus.__func__()
) -> None:
"""
:param membus: The memory bus for this setup. This parameter is
optional and will default toa 64 bit width SystemXBar is not specified.
:type membus: BaseXBar
"""
super().__init__()
self.membus = membus
|
[
"def",
"__init__",
"(",
"self",
",",
"membus",
":",
"BaseXBar",
"=",
"_get_default_membus",
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"(",
")",
".",
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"(",
")",
"self",
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"membus",
"=",
"membus"
] |
https://github.com/gem5/gem5/blob/141cc37c2d4b93959d4c249b8f7e6a8b2ef75338/src/python/gem5/components/cachehierarchies/classic/no_cache.py#L76-L86
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/inspect.py
|
python
|
isclass
|
(object)
|
return isinstance(object, type)
|
Return true if the object is a class.
Class objects provide these attributes:
__doc__ documentation string
__module__ name of module in which this class was defined
|
Return true if the object is a class.
|
[
"Return",
"true",
"if",
"the",
"object",
"is",
"a",
"class",
"."
] |
def isclass(object):
"""Return true if the object is a class.
Class objects provide these attributes:
__doc__ documentation string
__module__ name of module in which this class was defined"""
return isinstance(object, type)
|
[
"def",
"isclass",
"(",
"object",
")",
":",
"return",
"isinstance",
"(",
"object",
",",
"type",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/inspect.py#L72-L78
|
|
calamares/calamares
|
9f6f82405b3074af7c99dc26487d2e46e4ece3e5
|
src/modules/bootloader/main.py
|
python
|
run
|
()
|
return None
|
Starts procedure and passes 'fw_type' to other routine.
:return:
|
Starts procedure and passes 'fw_type' to other routine.
|
[
"Starts",
"procedure",
"and",
"passes",
"fw_type",
"to",
"other",
"routine",
"."
] |
def run():
"""
Starts procedure and passes 'fw_type' to other routine.
:return:
"""
fw_type = libcalamares.globalstorage.value("firmwareType")
if (libcalamares.globalstorage.value("bootLoader") is None and fw_type != "efi"):
libcalamares.utils.warning( "Non-EFI system, and no bootloader is set." )
return None
partitions = libcalamares.globalstorage.value("partitions")
if fw_type == "efi":
efi_system_partition = libcalamares.globalstorage.value("efiSystemPartition")
esp_found = [ p for p in partitions if p["mountPoint"] == efi_system_partition ]
if not esp_found:
libcalamares.utils.warning( "EFI system, but nothing mounted on {!s}".format(efi_system_partition) )
return None
try:
prepare_bootloader(fw_type)
except subprocess.CalledProcessError as e:
libcalamares.utils.warning(str(e))
libcalamares.utils.debug("stdout:" + str(e.stdout))
libcalamares.utils.debug("stderr:" + str(e.stderr))
return (_("Bootloader installation error"),
_("The bootloader could not be installed. The installation command <pre>{!s}</pre> returned error code {!s}.")
.format(e.cmd, e.returncode))
return None
|
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"globalstorage",
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".",
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"\"bootLoader\"",
")",
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")",
":",
"libcalamares",
".",
"utils",
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"(",
"\"Non-EFI system, and no bootloader is set.\"",
")",
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"+",
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"(",
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"(",
"\"Bootloader installation error\"",
")",
",",
"_",
"(",
"\"The bootloader could not be installed. The installation command <pre>{!s}</pre> returned error code {!s}.\"",
")",
".",
"format",
"(",
"e",
".",
"cmd",
",",
"e",
".",
"returncode",
")",
")",
"return",
"None"
] |
https://github.com/calamares/calamares/blob/9f6f82405b3074af7c99dc26487d2e46e4ece3e5/src/modules/bootloader/main.py#L753-L784
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_carbon/html.py
|
python
|
HtmlCell.GetLink
|
(*args, **kwargs)
|
return _html.HtmlCell_GetLink(*args, **kwargs)
|
GetLink(self, int x=0, int y=0) -> HtmlLinkInfo
|
GetLink(self, int x=0, int y=0) -> HtmlLinkInfo
|
[
"GetLink",
"(",
"self",
"int",
"x",
"=",
"0",
"int",
"y",
"=",
"0",
")",
"-",
">",
"HtmlLinkInfo"
] |
def GetLink(*args, **kwargs):
"""GetLink(self, int x=0, int y=0) -> HtmlLinkInfo"""
return _html.HtmlCell_GetLink(*args, **kwargs)
|
[
"def",
"GetLink",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_html",
".",
"HtmlCell_GetLink",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_carbon/html.py#L642-L644
|
|
apple/turicreate
|
cce55aa5311300e3ce6af93cb45ba791fd1bdf49
|
src/external/boost/boost_1_68_0/tools/build/src/util/utility.py
|
python
|
get_value
|
(property)
|
return replace_grist (property, '')
|
Gets the value of a property, that is, the part following the grist, if any.
|
Gets the value of a property, that is, the part following the grist, if any.
|
[
"Gets",
"the",
"value",
"of",
"a",
"property",
"that",
"is",
"the",
"part",
"following",
"the",
"grist",
"if",
"any",
"."
] |
def get_value (property):
""" Gets the value of a property, that is, the part following the grist, if any.
"""
assert is_iterable_typed(property, basestring) or isinstance(property, basestring)
return replace_grist (property, '')
|
[
"def",
"get_value",
"(",
"property",
")",
":",
"assert",
"is_iterable_typed",
"(",
"property",
",",
"basestring",
")",
"or",
"isinstance",
"(",
"property",
",",
"basestring",
")",
"return",
"replace_grist",
"(",
"property",
",",
"''",
")"
] |
https://github.com/apple/turicreate/blob/cce55aa5311300e3ce6af93cb45ba791fd1bdf49/src/external/boost/boost_1_68_0/tools/build/src/util/utility.py#L85-L89
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/build/waf-1.7.13/lmbrwaflib/default_settings.py
|
python
|
out_folder_linux64
|
(ctx, section_name, option_name, value)
|
return _get_string_value(ctx, 'Linux x64 Output Folder', value)
|
Configure output folder for linux x64
|
Configure output folder for linux x64
|
[
"Configure",
"output",
"folder",
"for",
"linux",
"x64"
] |
def out_folder_linux64(ctx, section_name, option_name, value):
""" Configure output folder for linux x64 """
if not _is_user_input_allowed(ctx, option_name, value):
return value
# GUI
if not ctx.is_option_true('console_mode'):
return ctx.gui_get_attribute(section_name, option_name, value)
_output_folder_disclaimer(ctx)
return _get_string_value(ctx, 'Linux x64 Output Folder', value)
|
[
"def",
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"ctx",
",",
"section_name",
",",
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",",
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"_is_user_input_allowed",
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"ctx",
",",
"option_name",
",",
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"ctx",
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] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/build/waf-1.7.13/lmbrwaflib/default_settings.py#L298-L308
|
|
ukoethe/vigra
|
093d57d15c8c237adf1704d96daa6393158ce299
|
vigranumpy/lib/arraytypes.py
|
python
|
ScalarImage
|
(obj, dtype=numpy.float32, order=None,
init=True, value=None, axistags=None)
|
return VigraArray(obj, dtype, None, init, value, axistags)
|
Factory function for a :class:`~vigra.VigraArray` representing a single-band image (i.e. an
array with two spatial axes 'x' and 'y' and no channel axis).
Paramters are interpreted as in the VigraArray constructor, but an exception
will be raised if the shape or axistags are unsuitable for a single-band image.
|
Factory function for a :class:`~vigra.VigraArray` representing a single-band image (i.e. an
array with two spatial axes 'x' and 'y' and no channel axis).
Paramters are interpreted as in the VigraArray constructor, but an exception
will be raised if the shape or axistags are unsuitable for a single-band image.
|
[
"Factory",
"function",
"for",
"a",
":",
"class",
":",
"~vigra",
".",
"VigraArray",
"representing",
"a",
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"-",
"band",
"image",
"(",
"i",
".",
"e",
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"an",
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"axes",
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"the",
"VigraArray",
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"be",
"raised",
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"shape",
"or",
"axistags",
"are",
"unsuitable",
"for",
"a",
"single",
"-",
"band",
"image",
"."
] |
def ScalarImage(obj, dtype=numpy.float32, order=None,
init=True, value=None, axistags=None):
'''
Factory function for a :class:`~vigra.VigraArray` representing a single-band image (i.e. an
array with two spatial axes 'x' and 'y' and no channel axis).
Paramters are interpreted as in the VigraArray constructor, but an exception
will be raised if the shape or axistags are unsuitable for a single-band image.
'''
obj, axistags = _adjustInput(obj, order, 2, None, axistags, "vigra.ScalarImage()")
return VigraArray(obj, dtype, None, init, value, axistags)
|
[
"def",
"ScalarImage",
"(",
"obj",
",",
"dtype",
"=",
"numpy",
".",
"float32",
",",
"order",
"=",
"None",
",",
"init",
"=",
"True",
",",
"value",
"=",
"None",
",",
"axistags",
"=",
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"obj",
",",
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",",
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"obj",
",",
"dtype",
",",
"None",
",",
"init",
",",
"value",
",",
"axistags",
")"
] |
https://github.com/ukoethe/vigra/blob/093d57d15c8c237adf1704d96daa6393158ce299/vigranumpy/lib/arraytypes.py#L1803-L1812
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
wx/tools/Editra/plugins/codebrowser/codebrowser/cbrowser.py
|
python
|
CodeBrowserTree.OnTagsReady
|
(self, evt)
|
Processing of tag generation has completed, check results
and update view.
@param evt: EVT_JOB_FINISHED
|
Processing of tag generation has completed, check results
and update view.
@param evt: EVT_JOB_FINISHED
|
[
"Processing",
"of",
"tag",
"generation",
"has",
"completed",
"check",
"results",
"and",
"update",
"view",
".",
"@param",
"evt",
":",
"EVT_JOB_FINISHED"
] |
def OnTagsReady(self, evt):
"""Processing of tag generation has completed, check results
and update view.
@param evt: EVT_JOB_FINISHED
"""
# Make sure that the values that are being returned are the ones for
# the currently active buffer.
if evt.GetId() == self._cjob:
self._lastjob = u''
self.Freeze()
self.UpdateAll(evt.GetValue())
self.Thaw()
# Stop busy indicator
ed_msg.PostMessage(ed_msg.EDMSG_PROGRESS_STATE,
(self._mw.GetId(), 0, 0))
if not self._timer.IsRunning():
self._cpage = None
|
[
"def",
"OnTagsReady",
"(",
"self",
",",
"evt",
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":",
"# Make sure that the values that are being returned are the ones for",
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".",
"IsRunning",
"(",
")",
":",
"self",
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"_cpage",
"=",
"None"
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https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/wx/tools/Editra/plugins/codebrowser/codebrowser/cbrowser.py#L477-L495
|
||
HyeonwooNoh/caffe
|
d9e8494a2832d67b25dee37194c7bcb9d52d0e42
|
scripts/cpp_lint.py
|
python
|
FileInfo.Extension
|
(self)
|
return self.Split()[2]
|
File extension - text following the final period.
|
File extension - text following the final period.
|
[
"File",
"extension",
"-",
"text",
"following",
"the",
"final",
"period",
"."
] |
def Extension(self):
"""File extension - text following the final period."""
return self.Split()[2]
|
[
"def",
"Extension",
"(",
"self",
")",
":",
"return",
"self",
".",
"Split",
"(",
")",
"[",
"2",
"]"
] |
https://github.com/HyeonwooNoh/caffe/blob/d9e8494a2832d67b25dee37194c7bcb9d52d0e42/scripts/cpp_lint.py#L948-L950
|
|
tensorflow/tensorflow
|
419e3a6b650ea4bd1b0cba23c4348f8a69f3272e
|
tensorflow/python/distribute/multi_process_runner.py
|
python
|
MultiProcessRunner._process_watchdog
|
(self)
|
Simulates a cluster management system.
- If auto_restart is True, it restarts processes that exit with a non-zero
exit code. Note that when join() times out it overrides auto_restart to
False.
- If dependence_on_chief is True, it terminates all processes once the chief
exits. If auto_restart is also True, it only terminates all processes if
the chief exit with a zero exit code, otherwise it restarts the chief.
This runs in self._watchdog_thread.
|
Simulates a cluster management system.
|
[
"Simulates",
"a",
"cluster",
"management",
"system",
"."
] |
def _process_watchdog(self):
"""Simulates a cluster management system.
- If auto_restart is True, it restarts processes that exit with a non-zero
exit code. Note that when join() times out it overrides auto_restart to
False.
- If dependence_on_chief is True, it terminates all processes once the chief
exits. If auto_restart is also True, it only terminates all processes if
the chief exit with a zero exit code, otherwise it restarts the chief.
This runs in self._watchdog_thread.
"""
while True:
time.sleep(1)
with self._process_lock:
chief = self._processes.get(('chief', 0), None)
# Terminate the cluster when _dependence_on_chief is True if either:
# - chief has exited with zero exit code.
# - chief has exited with non-zero exit code and self._auto_restart is
# False.
if chief and self._dependence_on_chief and chief.exitcode is not None:
if chief.exitcode == 0 or (not self._auto_restart):
for p in self._processes.values():
# Give other processes a chance to exit on their own.
p.join(timeout=3)
self._terminate_all()
for p in self._processes.values():
p.join()
return
# Auto restart failed processes if self._auto_restart is True.
if self._auto_restart:
has_failure = False
for (task_type, task_id), p in self._processes.items():
if p.exitcode is not None and p.exitcode != 0:
has_failure = True
logging.info('Restarting failed %s-%d', task_type, task_id)
self._start_subprocess_and_reading_thread(task_type, task_id)
if has_failure:
continue
# Exit the thread if all processes have exited at this point.
if all(p.exitcode is not None for p in self._processes.values()):
return
|
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"True",
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",",
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"=",
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"(",
"'Restarting failed %s-%d'",
",",
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",",
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")",
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"(",
"task_type",
",",
"task_id",
")",
"if",
"has_failure",
":",
"continue",
"# Exit the thread if all processes have exited at this point.",
"if",
"all",
"(",
"p",
".",
"exitcode",
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"p",
"in",
"self",
".",
"_processes",
".",
"values",
"(",
")",
")",
":",
"return"
] |
https://github.com/tensorflow/tensorflow/blob/419e3a6b650ea4bd1b0cba23c4348f8a69f3272e/tensorflow/python/distribute/multi_process_runner.py#L515-L558
|
||
miyosuda/TensorFlowAndroidMNIST
|
7b5a4603d2780a8a2834575706e9001977524007
|
jni-build/jni/include/tensorflow/models/rnn/ptb/ptb_word_lm.py
|
python
|
run_epoch
|
(session, m, data, eval_op, verbose=False)
|
return np.exp(costs / iters)
|
Runs the model on the given data.
|
Runs the model on the given data.
|
[
"Runs",
"the",
"model",
"on",
"the",
"given",
"data",
"."
] |
def run_epoch(session, m, data, eval_op, verbose=False):
"""Runs the model on the given data."""
epoch_size = ((len(data) // m.batch_size) - 1) // m.num_steps
start_time = time.time()
costs = 0.0
iters = 0
state = m.initial_state.eval()
for step, (x, y) in enumerate(reader.ptb_iterator(data, m.batch_size,
m.num_steps)):
cost, state, _ = session.run([m.cost, m.final_state, eval_op],
{m.input_data: x,
m.targets: y,
m.initial_state: state})
costs += cost
iters += m.num_steps
if verbose and step % (epoch_size // 10) == 10:
print("%.3f perplexity: %.3f speed: %.0f wps" %
(step * 1.0 / epoch_size, np.exp(costs / iters),
iters * m.batch_size / (time.time() - start_time)))
return np.exp(costs / iters)
|
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",",
"{",
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"x",
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"m",
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"state",
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"cost",
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"m",
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"num_steps",
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"step",
"%",
"(",
"epoch_size",
"//",
"10",
")",
"==",
"10",
":",
"print",
"(",
"\"%.3f perplexity: %.3f speed: %.0f wps\"",
"%",
"(",
"step",
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"/",
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",",
"np",
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"/",
"(",
"time",
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"(",
")",
"-",
"start_time",
")",
")",
")",
"return",
"np",
".",
"exp",
"(",
"costs",
"/",
"iters",
")"
] |
https://github.com/miyosuda/TensorFlowAndroidMNIST/blob/7b5a4603d2780a8a2834575706e9001977524007/jni-build/jni/include/tensorflow/models/rnn/ptb/ptb_word_lm.py#L253-L274
|
|
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/numbers.py
|
python
|
Integral.__rand__
|
(self, other)
|
other & self
|
other & self
|
[
"other",
"&",
"self"
] |
def __rand__(self, other):
"""other & self"""
raise NotImplementedError
|
[
"def",
"__rand__",
"(",
"self",
",",
"other",
")",
":",
"raise",
"NotImplementedError"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/numbers.py#L345-L347
|
||
aws/lumberyard
|
f85344403c1c2e77ec8c75deb2c116e97b713217
|
dev/Tools/Python/3.7.10/windows/Lib/site-packages/botocore/loaders.py
|
python
|
ExtrasProcessor.process
|
(self, original_model, extra_models)
|
Processes data from a list of loaded extras files into a model
:type original_model: dict
:param original_model: The service model to load all the extras into.
:type extra_models: iterable of dict
:param extra_models: A list of loaded extras models.
|
Processes data from a list of loaded extras files into a model
|
[
"Processes",
"data",
"from",
"a",
"list",
"of",
"loaded",
"extras",
"files",
"into",
"a",
"model"
] |
def process(self, original_model, extra_models):
"""Processes data from a list of loaded extras files into a model
:type original_model: dict
:param original_model: The service model to load all the extras into.
:type extra_models: iterable of dict
:param extra_models: A list of loaded extras models.
"""
for extras in extra_models:
self._process(original_model, extras)
|
[
"def",
"process",
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"self",
",",
"original_model",
",",
"extra_models",
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":",
"for",
"extras",
"in",
"extra_models",
":",
"self",
".",
"_process",
"(",
"original_model",
",",
"extras",
")"
] |
https://github.com/aws/lumberyard/blob/f85344403c1c2e77ec8c75deb2c116e97b713217/dev/Tools/Python/3.7.10/windows/Lib/site-packages/botocore/loaders.py#L446-L456
|
||
klzgrad/naiveproxy
|
ed2c513637c77b18721fe428d7ed395b4d284c83
|
src/build/check_gn_headers.py
|
python
|
GetHeadersFromNinja
|
(out_dir, skip_obj, q)
|
Return all the header files from ninja_deps
|
Return all the header files from ninja_deps
|
[
"Return",
"all",
"the",
"header",
"files",
"from",
"ninja_deps"
] |
def GetHeadersFromNinja(out_dir, skip_obj, q):
"""Return all the header files from ninja_deps"""
def NinjaSource():
cmd = [os.path.join(DEPOT_TOOLS_DIR, 'ninja'), '-C', out_dir, '-t', 'deps']
# A negative bufsize means to use the system default, which usually
# means fully buffered.
popen = subprocess.Popen(cmd, stdout=subprocess.PIPE, bufsize=-1)
for line in iter(popen.stdout.readline, ''):
yield line.rstrip()
popen.stdout.close()
return_code = popen.wait()
if return_code:
raise subprocess.CalledProcessError(return_code, cmd)
ans, err = set(), None
try:
ans = ParseNinjaDepsOutput(NinjaSource(), out_dir, skip_obj)
except Exception as e:
err = str(e)
q.put((ans, err))
|
[
"def",
"GetHeadersFromNinja",
"(",
"out_dir",
",",
"skip_obj",
",",
"q",
")",
":",
"def",
"NinjaSource",
"(",
")",
":",
"cmd",
"=",
"[",
"os",
".",
"path",
".",
"join",
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"DEPOT_TOOLS_DIR",
",",
"'ninja'",
")",
",",
"'-C'",
",",
"out_dir",
",",
"'-t'",
",",
"'deps'",
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"# A negative bufsize means to use the system default, which usually",
"# means fully buffered.",
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"Popen",
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"cmd",
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"stdout",
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")",
"q",
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"put",
"(",
"(",
"ans",
",",
"err",
")",
")"
] |
https://github.com/klzgrad/naiveproxy/blob/ed2c513637c77b18721fe428d7ed395b4d284c83/src/build/check_gn_headers.py#L29-L50
|
||
hughperkins/tf-coriander
|
970d3df6c11400ad68405f22b0c42a52374e94ca
|
tensorflow/python/platform/resource_loader.py
|
python
|
get_path_to_datafile
|
(path)
|
return os.path.join(data_files_path, path)
|
Get the path to the specified file in the data dependencies.
The path is relative to tensorflow/
Args:
path: a string resource path relative to tensorflow/
Returns:
The path to the specified file present in the data attribute of py_test
or py_binary.
Raises:
IOError: If the path is not found, or the resource can't be opened.
|
Get the path to the specified file in the data dependencies.
|
[
"Get",
"the",
"path",
"to",
"the",
"specified",
"file",
"in",
"the",
"data",
"dependencies",
"."
] |
def get_path_to_datafile(path):
"""Get the path to the specified file in the data dependencies.
The path is relative to tensorflow/
Args:
path: a string resource path relative to tensorflow/
Returns:
The path to the specified file present in the data attribute of py_test
or py_binary.
Raises:
IOError: If the path is not found, or the resource can't be opened.
"""
data_files_path = os.path.dirname(inspect.getfile(sys._getframe(1)))
return os.path.join(data_files_path, path)
|
[
"def",
"get_path_to_datafile",
"(",
"path",
")",
":",
"data_files_path",
"=",
"os",
".",
"path",
".",
"dirname",
"(",
"inspect",
".",
"getfile",
"(",
"sys",
".",
"_getframe",
"(",
"1",
")",
")",
")",
"return",
"os",
".",
"path",
".",
"join",
"(",
"data_files_path",
",",
"path",
")"
] |
https://github.com/hughperkins/tf-coriander/blob/970d3df6c11400ad68405f22b0c42a52374e94ca/tensorflow/python/platform/resource_loader.py#L65-L81
|
|
cms-sw/cmssw
|
fd9de012d503d3405420bcbeec0ec879baa57cf2
|
Validation/RecoTrack/python/plotting/plotting.py
|
python
|
Plot.addToLegend
|
(self, legend, legendLabels, denomUncertainty)
|
Add histograms to a legend.
Arguments:
legend -- TLegend
legendLabels -- List of strings for the legend labels
|
Add histograms to a legend.
|
[
"Add",
"histograms",
"to",
"a",
"legend",
"."
] |
def addToLegend(self, legend, legendLabels, denomUncertainty):
"""Add histograms to a legend.
Arguments:
legend -- TLegend
legendLabels -- List of strings for the legend labels
"""
first = denomUncertainty
for h, label in zip(self._histograms, legendLabels):
if h is None:
first = False
continue
if first:
self._forLegend = h.Clone()
self._forLegend.SetFillStyle(1001)
self._forLegend.SetFillColor(ROOT.kGray)
entry = legend.AddEntry(self._forLegend, label, "lpf")
first = False
else:
legend.AddEntry(h, label, "LP")
|
[
"def",
"addToLegend",
"(",
"self",
",",
"legend",
",",
"legendLabels",
",",
"denomUncertainty",
")",
":",
"first",
"=",
"denomUncertainty",
"for",
"h",
",",
"label",
"in",
"zip",
"(",
"self",
".",
"_histograms",
",",
"legendLabels",
")",
":",
"if",
"h",
"is",
"None",
":",
"first",
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"_forLegend",
"=",
"h",
".",
"Clone",
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")",
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".",
"_forLegend",
".",
"SetFillStyle",
"(",
"1001",
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".",
"_forLegend",
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"SetFillColor",
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"ROOT",
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"kGray",
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"entry",
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"AddEntry",
"(",
"self",
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"_forLegend",
",",
"label",
",",
"\"lpf\"",
")",
"first",
"=",
"False",
"else",
":",
"legend",
".",
"AddEntry",
"(",
"h",
",",
"label",
",",
"\"LP\"",
")"
] |
https://github.com/cms-sw/cmssw/blob/fd9de012d503d3405420bcbeec0ec879baa57cf2/Validation/RecoTrack/python/plotting/plotting.py#L2230-L2249
|
||
ycm-core/ycmd
|
fc0fb7e5e15176cc5a2a30c80956335988c6b59a
|
ycmd/completers/language_server/language_server_completer.py
|
python
|
WorkspaceEditToFixIt
|
( request_data,
workspace_edit,
text='',
kind = None )
|
return responses.FixIt(
responses.Location( request_data[ 'line_num' ],
request_data[ 'column_num' ],
request_data[ 'filepath' ] ),
chunks,
text,
kind )
|
Converts a LSP workspace edit to a ycmd FixIt suitable for passing to
responses.BuildFixItResponse.
|
Converts a LSP workspace edit to a ycmd FixIt suitable for passing to
responses.BuildFixItResponse.
|
[
"Converts",
"a",
"LSP",
"workspace",
"edit",
"to",
"a",
"ycmd",
"FixIt",
"suitable",
"for",
"passing",
"to",
"responses",
".",
"BuildFixItResponse",
"."
] |
def WorkspaceEditToFixIt( request_data,
workspace_edit,
text='',
kind = None ):
"""Converts a LSP workspace edit to a ycmd FixIt suitable for passing to
responses.BuildFixItResponse."""
if not workspace_edit:
return None
if 'changes' in workspace_edit:
chunks = []
# We sort the filenames to make the response stable. Edits are applied in
# strict sequence within a file, but apply to files in arbitrary order.
# However, it's important for the response to be stable for the tests.
for uri in sorted( workspace_edit[ 'changes' ].keys() ):
chunks.extend( TextEditToChunks( request_data,
uri,
workspace_edit[ 'changes' ][ uri ] ) )
else:
chunks = []
for text_document_edit in workspace_edit[ 'documentChanges' ]:
uri = text_document_edit[ 'textDocument' ][ 'uri' ]
edits = text_document_edit[ 'edits' ]
chunks.extend( TextEditToChunks( request_data, uri, edits ) )
return responses.FixIt(
responses.Location( request_data[ 'line_num' ],
request_data[ 'column_num' ],
request_data[ 'filepath' ] ),
chunks,
text,
kind )
|
[
"def",
"WorkspaceEditToFixIt",
"(",
"request_data",
",",
"workspace_edit",
",",
"text",
"=",
"''",
",",
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"=",
"None",
")",
":",
"if",
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"=",
"[",
"]",
"# We sort the filenames to make the response stable. Edits are applied in",
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"]",
"[",
"'uri'",
"]",
"edits",
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"(",
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"(",
"request_data",
",",
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".",
"FixIt",
"(",
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".",
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"(",
"request_data",
"[",
"'line_num'",
"]",
",",
"request_data",
"[",
"'column_num'",
"]",
",",
"request_data",
"[",
"'filepath'",
"]",
")",
",",
"chunks",
",",
"text",
",",
"kind",
")"
] |
https://github.com/ycm-core/ycmd/blob/fc0fb7e5e15176cc5a2a30c80956335988c6b59a/ycmd/completers/language_server/language_server_completer.py#L3220-L3251
|
|
Ewenwan/MVision
|
97b394dfa48cb21c82cd003b1a952745e413a17f
|
CNN/yolo_v1_tf.py
|
python
|
Yolo._detect_from_image
|
(self, image)
|
return scores, boxes, box_classes
|
Do detection given a cv image
|
Do detection given a cv image
|
[
"Do",
"detection",
"given",
"a",
"cv",
"image"
] |
def _detect_from_image(self, image):
"""Do detection given a cv image"""
img_h, img_w, _ = image.shape#图像长宽
img_resized = cv2.resize(image, (448, 448))#resize到固定尺寸 448*448
img_RGB = cv2.cvtColor(img_resized, cv2.COLOR_BGR2RGB)# 转到 RGB 通道
img_resized_np = np.asarray(img_RGB)#转换成 数组
_images = np.zeros((1, 448, 448, 3), dtype=np.float32)
_images[0] = (img_resized_np / 255.0) * 2.0 - 1.0# 像素值归一化到 0~1 之间
scores, boxes, box_classes = self.sess.run([self.scores, self.boxes, self.box_classes],
feed_dict={self.images: _images, self.width: img_w, self.height: img_h})
return scores, boxes, box_classes
|
[
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",",
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",",
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"}",
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",",
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",",
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] |
https://github.com/Ewenwan/MVision/blob/97b394dfa48cb21c82cd003b1a952745e413a17f/CNN/yolo_v1_tf.py#L200-L210
|
|
eric612/MobileNet-YOLO
|
69b4441cb3ec8d553fbdef788ad033e246f901bd
|
scripts/cpp_lint.py
|
python
|
_NestingState.UpdatePreprocessor
|
(self, line)
|
Update preprocessor stack.
We need to handle preprocessors due to classes like this:
#ifdef SWIG
struct ResultDetailsPageElementExtensionPoint {
#else
struct ResultDetailsPageElementExtensionPoint : public Extension {
#endif
We make the following assumptions (good enough for most files):
- Preprocessor condition evaluates to true from #if up to first
#else/#elif/#endif.
- Preprocessor condition evaluates to false from #else/#elif up
to #endif. We still perform lint checks on these lines, but
these do not affect nesting stack.
Args:
line: current line to check.
|
Update preprocessor stack.
|
[
"Update",
"preprocessor",
"stack",
"."
] |
def UpdatePreprocessor(self, line):
"""Update preprocessor stack.
We need to handle preprocessors due to classes like this:
#ifdef SWIG
struct ResultDetailsPageElementExtensionPoint {
#else
struct ResultDetailsPageElementExtensionPoint : public Extension {
#endif
We make the following assumptions (good enough for most files):
- Preprocessor condition evaluates to true from #if up to first
#else/#elif/#endif.
- Preprocessor condition evaluates to false from #else/#elif up
to #endif. We still perform lint checks on these lines, but
these do not affect nesting stack.
Args:
line: current line to check.
"""
if Match(r'^\s*#\s*(if|ifdef|ifndef)\b', line):
# Beginning of #if block, save the nesting stack here. The saved
# stack will allow us to restore the parsing state in the #else case.
self.pp_stack.append(_PreprocessorInfo(copy.deepcopy(self.stack)))
elif Match(r'^\s*#\s*(else|elif)\b', line):
# Beginning of #else block
if self.pp_stack:
if not self.pp_stack[-1].seen_else:
# This is the first #else or #elif block. Remember the
# whole nesting stack up to this point. This is what we
# keep after the #endif.
self.pp_stack[-1].seen_else = True
self.pp_stack[-1].stack_before_else = copy.deepcopy(self.stack)
# Restore the stack to how it was before the #if
self.stack = copy.deepcopy(self.pp_stack[-1].stack_before_if)
else:
# TODO(unknown): unexpected #else, issue warning?
pass
elif Match(r'^\s*#\s*endif\b', line):
# End of #if or #else blocks.
if self.pp_stack:
# If we saw an #else, we will need to restore the nesting
# stack to its former state before the #else, otherwise we
# will just continue from where we left off.
if self.pp_stack[-1].seen_else:
# Here we can just use a shallow copy since we are the last
# reference to it.
self.stack = self.pp_stack[-1].stack_before_else
# Drop the corresponding #if
self.pp_stack.pop()
else:
# TODO(unknown): unexpected #endif, issue warning?
pass
|
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"pp_stack",
".",
"append",
"(",
"_PreprocessorInfo",
"(",
"copy",
".",
"deepcopy",
"(",
"self",
".",
"stack",
")",
")",
")",
"elif",
"Match",
"(",
"r'^\\s*#\\s*(else|elif)\\b'",
",",
"line",
")",
":",
"# Beginning of #else block",
"if",
"self",
".",
"pp_stack",
":",
"if",
"not",
"self",
".",
"pp_stack",
"[",
"-",
"1",
"]",
".",
"seen_else",
":",
"# This is the first #else or #elif block. Remember the",
"# whole nesting stack up to this point. This is what we",
"# keep after the #endif.",
"self",
".",
"pp_stack",
"[",
"-",
"1",
"]",
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"seen_else",
"=",
"True",
"self",
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"-",
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"]",
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"stack_before_else",
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"deepcopy",
"(",
"self",
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"stack",
")",
"# Restore the stack to how it was before the #if",
"self",
".",
"stack",
"=",
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"deepcopy",
"(",
"self",
".",
"pp_stack",
"[",
"-",
"1",
"]",
".",
"stack_before_if",
")",
"else",
":",
"# TODO(unknown): unexpected #else, issue warning?",
"pass",
"elif",
"Match",
"(",
"r'^\\s*#\\s*endif\\b'",
",",
"line",
")",
":",
"# End of #if or #else blocks.",
"if",
"self",
".",
"pp_stack",
":",
"# If we saw an #else, we will need to restore the nesting",
"# stack to its former state before the #else, otherwise we",
"# will just continue from where we left off.",
"if",
"self",
".",
"pp_stack",
"[",
"-",
"1",
"]",
".",
"seen_else",
":",
"# Here we can just use a shallow copy since we are the last",
"# reference to it.",
"self",
".",
"stack",
"=",
"self",
".",
"pp_stack",
"[",
"-",
"1",
"]",
".",
"stack_before_else",
"# Drop the corresponding #if",
"self",
".",
"pp_stack",
".",
"pop",
"(",
")",
"else",
":",
"# TODO(unknown): unexpected #endif, issue warning?",
"pass"
] |
https://github.com/eric612/MobileNet-YOLO/blob/69b4441cb3ec8d553fbdef788ad033e246f901bd/scripts/cpp_lint.py#L1952-L2006
|
||
perilouswithadollarsign/cstrike15_src
|
f82112a2388b841d72cb62ca48ab1846dfcc11c8
|
thirdparty/protobuf-2.5.0/python/mox.py
|
python
|
MockObject.__setitem__
|
(self, key, value)
|
return self._CreateMockMethod('__setitem__')(key, value)
|
Provide custom logic for mocking classes that support item assignment.
Args:
key: Key to set the value for.
value: Value to set.
Returns:
Expected return value in replay mode. A MockMethod object for the
__setitem__ method that has already been called if not in replay mode.
Raises:
TypeError if the underlying class does not support item assignment.
UnexpectedMethodCallError if the object does not expect the call to
__setitem__.
|
Provide custom logic for mocking classes that support item assignment.
|
[
"Provide",
"custom",
"logic",
"for",
"mocking",
"classes",
"that",
"support",
"item",
"assignment",
"."
] |
def __setitem__(self, key, value):
"""Provide custom logic for mocking classes that support item assignment.
Args:
key: Key to set the value for.
value: Value to set.
Returns:
Expected return value in replay mode. A MockMethod object for the
__setitem__ method that has already been called if not in replay mode.
Raises:
TypeError if the underlying class does not support item assignment.
UnexpectedMethodCallError if the object does not expect the call to
__setitem__.
"""
setitem = self._class_to_mock.__dict__.get('__setitem__', None)
# Verify the class supports item assignment.
if setitem is None:
raise TypeError('object does not support item assignment')
# If we are in replay mode then simply call the mock __setitem__ method.
if self._replay_mode:
return MockMethod('__setitem__', self._expected_calls_queue,
self._replay_mode)(key, value)
# Otherwise, create a mock method __setitem__.
return self._CreateMockMethod('__setitem__')(key, value)
|
[
"def",
"__setitem__",
"(",
"self",
",",
"key",
",",
"value",
")",
":",
"setitem",
"=",
"self",
".",
"_class_to_mock",
".",
"__dict__",
".",
"get",
"(",
"'__setitem__'",
",",
"None",
")",
"# Verify the class supports item assignment.",
"if",
"setitem",
"is",
"None",
":",
"raise",
"TypeError",
"(",
"'object does not support item assignment'",
")",
"# If we are in replay mode then simply call the mock __setitem__ method.",
"if",
"self",
".",
"_replay_mode",
":",
"return",
"MockMethod",
"(",
"'__setitem__'",
",",
"self",
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"_expected_calls_queue",
",",
"self",
".",
"_replay_mode",
")",
"(",
"key",
",",
"value",
")",
"# Otherwise, create a mock method __setitem__.",
"return",
"self",
".",
"_CreateMockMethod",
"(",
"'__setitem__'",
")",
"(",
"key",
",",
"value",
")"
] |
https://github.com/perilouswithadollarsign/cstrike15_src/blob/f82112a2388b841d72cb62ca48ab1846dfcc11c8/thirdparty/protobuf-2.5.0/python/mox.py#L427-L457
|
|
baidu-research/tensorflow-allreduce
|
66d5b855e90b0949e9fa5cca5599fd729a70e874
|
tensorflow/python/debug/wrappers/framework.py
|
python
|
BaseDebugWrapperSession.on_run_start
|
(self, request)
|
Callback invoked on run() calls to the debug-wrapper session.
This is a blocking callback.
The invocation happens after the wrapper's run() call is entered,
after an increment of run call counter.
Args:
request: (`OnRunStartRequest`) callback request object carrying
information about the run call such as the fetches, feed dict, run
options, run metadata, and how many `run()` calls to this wrapper
session have occurred.
Returns:
An instance of `OnRunStartResponse`, carrying information to
1) direct the wrapper session to perform a specified action (e.g., run
with or without debug tensor watching, invoking the stepper.)
2) debug URLs used to watch the tensors.
|
Callback invoked on run() calls to the debug-wrapper session.
|
[
"Callback",
"invoked",
"on",
"run",
"()",
"calls",
"to",
"the",
"debug",
"-",
"wrapper",
"session",
"."
] |
def on_run_start(self, request):
"""Callback invoked on run() calls to the debug-wrapper session.
This is a blocking callback.
The invocation happens after the wrapper's run() call is entered,
after an increment of run call counter.
Args:
request: (`OnRunStartRequest`) callback request object carrying
information about the run call such as the fetches, feed dict, run
options, run metadata, and how many `run()` calls to this wrapper
session have occurred.
Returns:
An instance of `OnRunStartResponse`, carrying information to
1) direct the wrapper session to perform a specified action (e.g., run
with or without debug tensor watching, invoking the stepper.)
2) debug URLs used to watch the tensors.
"""
|
[
"def",
"on_run_start",
"(",
"self",
",",
"request",
")",
":"
] |
https://github.com/baidu-research/tensorflow-allreduce/blob/66d5b855e90b0949e9fa5cca5599fd729a70e874/tensorflow/python/debug/wrappers/framework.py#L638-L656
|
||
BVLC/caffe
|
9b891540183ddc834a02b2bd81b31afae71b2153
|
scripts/cpp_lint.py
|
python
|
ProcessLine
|
(filename, file_extension, clean_lines, line,
include_state, function_state, nesting_state, error,
extra_check_functions=[])
|
Processes a single line in the file.
Args:
filename: Filename of the file that is being processed.
file_extension: The extension (dot not included) of the file.
clean_lines: An array of strings, each representing a line of the file,
with comments stripped.
line: Number of line being processed.
include_state: An _IncludeState instance in which the headers are inserted.
function_state: A _FunctionState instance which counts function lines, etc.
nesting_state: A _NestingState instance which maintains information about
the current stack of nested blocks being parsed.
error: A callable to which errors are reported, which takes 4 arguments:
filename, line number, error level, and message
extra_check_functions: An array of additional check functions that will be
run on each source line. Each function takes 4
arguments: filename, clean_lines, line, error
|
Processes a single line in the file.
|
[
"Processes",
"a",
"single",
"line",
"in",
"the",
"file",
"."
] |
def ProcessLine(filename, file_extension, clean_lines, line,
include_state, function_state, nesting_state, error,
extra_check_functions=[]):
"""Processes a single line in the file.
Args:
filename: Filename of the file that is being processed.
file_extension: The extension (dot not included) of the file.
clean_lines: An array of strings, each representing a line of the file,
with comments stripped.
line: Number of line being processed.
include_state: An _IncludeState instance in which the headers are inserted.
function_state: A _FunctionState instance which counts function lines, etc.
nesting_state: A _NestingState instance which maintains information about
the current stack of nested blocks being parsed.
error: A callable to which errors are reported, which takes 4 arguments:
filename, line number, error level, and message
extra_check_functions: An array of additional check functions that will be
run on each source line. Each function takes 4
arguments: filename, clean_lines, line, error
"""
raw_lines = clean_lines.raw_lines
ParseNolintSuppressions(filename, raw_lines[line], line, error)
nesting_state.Update(filename, clean_lines, line, error)
if nesting_state.stack and nesting_state.stack[-1].inline_asm != _NO_ASM:
return
CheckForFunctionLengths(filename, clean_lines, line, function_state, error)
CheckForMultilineCommentsAndStrings(filename, clean_lines, line, error)
CheckStyle(filename, clean_lines, line, file_extension, nesting_state, error)
CheckLanguage(filename, clean_lines, line, file_extension, include_state,
nesting_state, error)
CheckForNonConstReference(filename, clean_lines, line, nesting_state, error)
CheckForNonStandardConstructs(filename, clean_lines, line,
nesting_state, error)
CheckVlogArguments(filename, clean_lines, line, error)
CheckCaffeAlternatives(filename, clean_lines, line, error)
CheckCaffeDataLayerSetUp(filename, clean_lines, line, error)
CheckCaffeRandom(filename, clean_lines, line, error)
CheckPosixThreading(filename, clean_lines, line, error)
CheckInvalidIncrement(filename, clean_lines, line, error)
CheckMakePairUsesDeduction(filename, clean_lines, line, error)
for check_fn in extra_check_functions:
check_fn(filename, clean_lines, line, error)
|
[
"def",
"ProcessLine",
"(",
"filename",
",",
"file_extension",
",",
"clean_lines",
",",
"line",
",",
"include_state",
",",
"function_state",
",",
"nesting_state",
",",
"error",
",",
"extra_check_functions",
"=",
"[",
"]",
")",
":",
"raw_lines",
"=",
"clean_lines",
".",
"raw_lines",
"ParseNolintSuppressions",
"(",
"filename",
",",
"raw_lines",
"[",
"line",
"]",
",",
"line",
",",
"error",
")",
"nesting_state",
".",
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"filename",
",",
"clean_lines",
",",
"line",
",",
"error",
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"if",
"nesting_state",
".",
"stack",
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".",
"stack",
"[",
"-",
"1",
"]",
".",
"inline_asm",
"!=",
"_NO_ASM",
":",
"return",
"CheckForFunctionLengths",
"(",
"filename",
",",
"clean_lines",
",",
"line",
",",
"function_state",
",",
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")",
"CheckForMultilineCommentsAndStrings",
"(",
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",",
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",",
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"error",
")",
"CheckStyle",
"(",
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",",
"line",
",",
"file_extension",
",",
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",",
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",",
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",",
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",",
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",",
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",",
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",",
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"CheckVlogArguments",
"(",
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",",
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",",
"line",
",",
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")",
"CheckCaffeAlternatives",
"(",
"filename",
",",
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",",
"line",
",",
"error",
")",
"CheckCaffeDataLayerSetUp",
"(",
"filename",
",",
"clean_lines",
",",
"line",
",",
"error",
")",
"CheckCaffeRandom",
"(",
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",",
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",",
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",",
"error",
")",
"CheckPosixThreading",
"(",
"filename",
",",
"clean_lines",
",",
"line",
",",
"error",
")",
"CheckInvalidIncrement",
"(",
"filename",
",",
"clean_lines",
",",
"line",
",",
"error",
")",
"CheckMakePairUsesDeduction",
"(",
"filename",
",",
"clean_lines",
",",
"line",
",",
"error",
")",
"for",
"check_fn",
"in",
"extra_check_functions",
":",
"check_fn",
"(",
"filename",
",",
"clean_lines",
",",
"line",
",",
"error",
")"
] |
https://github.com/BVLC/caffe/blob/9b891540183ddc834a02b2bd81b31afae71b2153/scripts/cpp_lint.py#L4604-L4646
|
||
nnrg/opennero
|
43e12a1bcba6e228639db3886fec1dc47ddc24cb
|
mods/Roomba/module.py
|
python
|
RoombaEnvironment.num_sensors
|
(self)
|
return (len(getMod().marker_map)*4 + constants.N_FIXED_SENSORS)
|
Return total number of sensors
|
Return total number of sensors
|
[
"Return",
"total",
"number",
"of",
"sensors"
] |
def num_sensors(self):
"""
Return total number of sensors
"""
return (len(getMod().marker_map)*4 + constants.N_FIXED_SENSORS)
|
[
"def",
"num_sensors",
"(",
"self",
")",
":",
"return",
"(",
"len",
"(",
"getMod",
"(",
")",
".",
"marker_map",
")",
"*",
"4",
"+",
"constants",
".",
"N_FIXED_SENSORS",
")"
] |
https://github.com/nnrg/opennero/blob/43e12a1bcba6e228639db3886fec1dc47ddc24cb/mods/Roomba/module.py#L304-L308
|
|
weolar/miniblink49
|
1c4678db0594a4abde23d3ebbcc7cd13c3170777
|
third_party/WebKit/Tools/Scripts/webkitpy/style/checkers/cpp.py
|
python
|
_FunctionState.count
|
(self, line_number)
|
Count line in current function body.
|
Count line in current function body.
|
[
"Count",
"line",
"in",
"current",
"function",
"body",
"."
] |
def count(self, line_number):
"""Count line in current function body."""
if self.in_a_function and line_number >= self.body_start_position.row:
self.lines_in_function += 1
|
[
"def",
"count",
"(",
"self",
",",
"line_number",
")",
":",
"if",
"self",
".",
"in_a_function",
"and",
"line_number",
">=",
"self",
".",
"body_start_position",
".",
"row",
":",
"self",
".",
"lines_in_function",
"+=",
"1"
] |
https://github.com/weolar/miniblink49/blob/1c4678db0594a4abde23d3ebbcc7cd13c3170777/third_party/WebKit/Tools/Scripts/webkitpy/style/checkers/cpp.py#L584-L587
|
||
macchina-io/macchina.io
|
ef24ba0e18379c3dd48fb84e6dbf991101cb8db0
|
platform/JS/V8/v8/tools/release/check_clusterfuzz.py
|
python
|
APIRequest
|
(key, **params)
|
return None
|
Send a request to the clusterfuzz api.
Returns a json dict of the response.
|
Send a request to the clusterfuzz api.
|
[
"Send",
"a",
"request",
"to",
"the",
"clusterfuzz",
"api",
"."
] |
def APIRequest(key, **params):
"""Send a request to the clusterfuzz api.
Returns a json dict of the response.
"""
params["api_key"] = key
params = urllib.urlencode(params)
headers = {"Content-type": "application/x-www-form-urlencoded"}
try:
conn = httplib.HTTPSConnection(HOSTNAME)
conn.request("POST", "/_api/", params, headers)
response = conn.getresponse()
# Never leak "data" into public logs.
data = response.read()
except:
raise Exception("ERROR: Connection problem.")
try:
return json.loads(data)
except:
raise Exception("ERROR: Could not read response. Is your key valid?")
return None
|
[
"def",
"APIRequest",
"(",
"key",
",",
"*",
"*",
"params",
")",
":",
"params",
"[",
"\"api_key\"",
"]",
"=",
"key",
"params",
"=",
"urllib",
".",
"urlencode",
"(",
"params",
")",
"headers",
"=",
"{",
"\"Content-type\"",
":",
"\"application/x-www-form-urlencoded\"",
"}",
"try",
":",
"conn",
"=",
"httplib",
".",
"HTTPSConnection",
"(",
"HOSTNAME",
")",
"conn",
".",
"request",
"(",
"\"POST\"",
",",
"\"/_api/\"",
",",
"params",
",",
"headers",
")",
"response",
"=",
"conn",
".",
"getresponse",
"(",
")",
"# Never leak \"data\" into public logs.",
"data",
"=",
"response",
".",
"read",
"(",
")",
"except",
":",
"raise",
"Exception",
"(",
"\"ERROR: Connection problem.\"",
")",
"try",
":",
"return",
"json",
".",
"loads",
"(",
"data",
")",
"except",
":",
"raise",
"Exception",
"(",
"\"ERROR: Could not read response. Is your key valid?\"",
")",
"return",
"None"
] |
https://github.com/macchina-io/macchina.io/blob/ef24ba0e18379c3dd48fb84e6dbf991101cb8db0/platform/JS/V8/v8/tools/release/check_clusterfuzz.py#L159-L186
|
|
google/google-api-cpp-client
|
3df15df632bef43eb320645ac3329d872aabf5ad
|
prepare_dependencies.py
|
python
|
JsonCppPackageInstaller.MaybeTweakAfterUnpackage
|
(self)
|
Creates a CMakeLists.txt to build the package.
|
Creates a CMakeLists.txt to build the package.
|
[
"Creates",
"a",
"CMakeLists",
".",
"txt",
"to",
"build",
"the",
"package",
"."
] |
def MaybeTweakAfterUnpackage(self):
"""Creates a CMakeLists.txt to build the package."""
config = self._config
os.chdir(self._package_path)
if config.force and os.path.exists('CMakeLists.txt'):
os.unlink('CMakeLists.txt')
if os.path.exists('CMakeLists.txt'):
return
if config.build_packages:
allfiles = ''
src_path = os.path.join('src', 'lib_json')
for elem in glob.glob('%s/*.cpp' % src_path):
allfiles = '%s "%s"' % (allfiles, elem)
print '>>> Creating CMakeLists.txt'
with open('CMakeLists.txt', 'w') as f:
f.write('cmake_minimum_required (VERSION 2.6)\n')
f.write('project (JsonCpp)\n')
f.write('INCLUDE_DIRECTORIES(./include src/lib_json)\n')
f.write('add_library(jsoncpp STATIC %s)\n' % allfiles)
|
[
"def",
"MaybeTweakAfterUnpackage",
"(",
"self",
")",
":",
"config",
"=",
"self",
".",
"_config",
"os",
".",
"chdir",
"(",
"self",
".",
"_package_path",
")",
"if",
"config",
".",
"force",
"and",
"os",
".",
"path",
".",
"exists",
"(",
"'CMakeLists.txt'",
")",
":",
"os",
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"unlink",
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":",
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",",
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",",
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",",
"'w'",
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"f",
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"'cmake_minimum_required (VERSION 2.6)\\n'",
")",
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"(",
"'project (JsonCpp)\\n'",
")",
"f",
".",
"write",
"(",
"'INCLUDE_DIRECTORIES(./include src/lib_json)\\n'",
")",
"f",
".",
"write",
"(",
"'add_library(jsoncpp STATIC %s)\\n'",
"%",
"allfiles",
")"
] |
https://github.com/google/google-api-cpp-client/blob/3df15df632bef43eb320645ac3329d872aabf5ad/prepare_dependencies.py#L723-L744
|
||
scribusproject/scribus
|
41ec7c775a060912cf251682a8b1437f753f80f4
|
codegen/cheetah/Cheetah/SettingsManager.py
|
python
|
mergeNestedDictionaries
|
(dict1, dict2, copy=False, deepcopy=False)
|
return dict1
|
Recursively merge the values of dict2 into dict1.
This little function is very handy for selectively overriding settings in a
settings dictionary that has a nested structure.
|
Recursively merge the values of dict2 into dict1.
|
[
"Recursively",
"merge",
"the",
"values",
"of",
"dict2",
"into",
"dict1",
"."
] |
def mergeNestedDictionaries(dict1, dict2, copy=False, deepcopy=False):
"""Recursively merge the values of dict2 into dict1.
This little function is very handy for selectively overriding settings in a
settings dictionary that has a nested structure.
"""
if copy:
dict1 = copyModule.copy(dict1)
elif deepcopy:
dict1 = copyModule.deepcopy(dict1)
for key, val in dict2.iteritems():
if key in dict1 and isinstance(val, dict) and isinstance(dict1[key], dict):
dict1[key] = mergeNestedDictionaries(dict1[key], val)
else:
dict1[key] = val
return dict1
|
[
"def",
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"[",
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",",
"val",
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"else",
":",
"dict1",
"[",
"key",
"]",
"=",
"val",
"return",
"dict1"
] |
https://github.com/scribusproject/scribus/blob/41ec7c775a060912cf251682a8b1437f753f80f4/codegen/cheetah/Cheetah/SettingsManager.py#L19-L36
|
|
hanpfei/chromium-net
|
392cc1fa3a8f92f42e4071ab6e674d8e0482f83f
|
third_party/catapult/third_party/gsutil/third_party/boto/boto/services/servicedef.py
|
python
|
ServiceDef.get_obj
|
(self, name)
|
return obj
|
Returns the AWS object associated with a given option.
The heuristics used are a bit lame. If the option name contains
the word 'bucket' it is assumed to be an S3 bucket, if the name
contains the word 'queue' it is assumed to be an SQS queue and
if it contains the word 'domain' it is assumed to be a SimpleDB
domain. If the option name specified does not exist in the
config file or if the AWS object cannot be retrieved this
returns None.
|
Returns the AWS object associated with a given option.
|
[
"Returns",
"the",
"AWS",
"object",
"associated",
"with",
"a",
"given",
"option",
"."
] |
def get_obj(self, name):
"""
Returns the AWS object associated with a given option.
The heuristics used are a bit lame. If the option name contains
the word 'bucket' it is assumed to be an S3 bucket, if the name
contains the word 'queue' it is assumed to be an SQS queue and
if it contains the word 'domain' it is assumed to be a SimpleDB
domain. If the option name specified does not exist in the
config file or if the AWS object cannot be retrieved this
returns None.
"""
val = self.get(name)
if not val:
return None
if name.find('queue') >= 0:
obj = boto.lookup('sqs', val)
if obj:
obj.set_message_class(ServiceMessage)
elif name.find('bucket') >= 0:
obj = boto.lookup('s3', val)
elif name.find('domain') >= 0:
obj = boto.lookup('sdb', val)
else:
obj = None
return obj
|
[
"def",
"get_obj",
"(",
"self",
",",
"name",
")",
":",
"val",
"=",
"self",
".",
"get",
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"name",
")",
"if",
"not",
"val",
":",
"return",
"None",
"if",
"name",
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"(",
"'queue'",
")",
">=",
"0",
":",
"obj",
"=",
"boto",
".",
"lookup",
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"'sqs'",
",",
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"if",
"obj",
":",
"obj",
".",
"set_message_class",
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"ServiceMessage",
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"'bucket'",
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">=",
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",",
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"'domain'",
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">=",
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"obj",
"=",
"boto",
".",
"lookup",
"(",
"'sdb'",
",",
"val",
")",
"else",
":",
"obj",
"=",
"None",
"return",
"obj"
] |
https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/third_party/gsutil/third_party/boto/boto/services/servicedef.py#L64-L89
|
|
wxWidgets/wxPython-Classic
|
19571e1ae65f1ac445f5491474121998c97a1bf0
|
src/osx_cocoa/_core.py
|
python
|
Window.SetSizeWH
|
(*args, **kwargs)
|
return _core_.Window_SetSizeWH(*args, **kwargs)
|
SetSizeWH(self, int width, int height)
Sets the size of the window in pixels.
|
SetSizeWH(self, int width, int height)
|
[
"SetSizeWH",
"(",
"self",
"int",
"width",
"int",
"height",
")"
] |
def SetSizeWH(*args, **kwargs):
"""
SetSizeWH(self, int width, int height)
Sets the size of the window in pixels.
"""
return _core_.Window_SetSizeWH(*args, **kwargs)
|
[
"def",
"SetSizeWH",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_core_",
".",
"Window_SetSizeWH",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/_core.py#L9365-L9371
|
|
cocos2d/cocos2d-x
|
90f6542cf7fb081335f04e474b880d7ce8c445a1
|
tools/appveyor-scripts/git_retry.py
|
python
|
GitRetry.computeDelay
|
(self, iteration)
|
return (self.delay_factor ** (iteration - 1)) * self.delay
|
Returns: the delay (in seconds) for a given iteration
The first iteration has a delay of '0'.
Args:
iteration: (int) The iteration index (starting with zero as the first
iteration)
|
Returns: the delay (in seconds) for a given iteration
The first iteration has a delay of '0'.
Args:
iteration: (int) The iteration index (starting with zero as the first
iteration)
|
[
"Returns",
":",
"the",
"delay",
"(",
"in",
"seconds",
")",
"for",
"a",
"given",
"iteration",
"The",
"first",
"iteration",
"has",
"a",
"delay",
"of",
"0",
".",
"Args",
":",
"iteration",
":",
"(",
"int",
")",
"The",
"iteration",
"index",
"(",
"starting",
"with",
"zero",
"as",
"the",
"first",
"iteration",
")"
] |
def computeDelay(self, iteration):
"""Returns: the delay (in seconds) for a given iteration
The first iteration has a delay of '0'.
Args:
iteration: (int) The iteration index (starting with zero as the first
iteration)
"""
if (not self.delay) or (iteration == 0):
return 0
if self.delay_factor == 0:
# Linear delay
return iteration * self.delay
# Exponential delay
return (self.delay_factor ** (iteration - 1)) * self.delay
|
[
"def",
"computeDelay",
"(",
"self",
",",
"iteration",
")",
":",
"if",
"(",
"not",
"self",
".",
"delay",
")",
"or",
"(",
"iteration",
"==",
"0",
")",
":",
"return",
"0",
"if",
"self",
".",
"delay_factor",
"==",
"0",
":",
"# Linear delay",
"return",
"iteration",
"*",
"self",
".",
"delay",
"# Exponential delay",
"return",
"(",
"self",
".",
"delay_factor",
"**",
"(",
"iteration",
"-",
"1",
")",
")",
"*",
"self",
".",
"delay"
] |
https://github.com/cocos2d/cocos2d-x/blob/90f6542cf7fb081335f04e474b880d7ce8c445a1/tools/appveyor-scripts/git_retry.py#L89-L102
|
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